Original Research

The gut-brain axis (GBA) refers to the link between the human brain with its various cognitive and affective functions and the gastrointestinal (GI) system, which includes the enteric nervous system and the diverse microbiome inhabiting the gut lumen. The neurochemical aspects of the GBA have been studied in germ-free mice; these studies demonstrate how absence or derangement of this microbiome can cause significant alterations in levels of serotonin, brain-derived neurotrophic factor, tryptophan, and other neurocompounds.^1,2 These neurotransmitter alterations have demonstrable effects on anxiety, cognition, socialization, and neuronal development in mice.^1,2

Current evidence suggests that the GBA works through a combination of both fast-acting neural and delayed immune-mediated mechanisms in a bidirectional manner with feedback on and from both systems.³ In addition to their direct effects on neural pathways and immune modulation, intestinal microbiota are essential in the production of a vast array of vitamins, cofactors, and nutrients required for optimal health and metabolism.⁴ Existing research on the GBA demonstrates the direct functional impact of the intestinal microbiome on neurologic and psychiatric health.

We will review current knowledge regarding this intriguing relationship. In doing so, we take a closer look at several specific genera and families of intestinal microbiota, review the microbiome’s effects on immune function, and examine the relationship between this microbiome and mental disease, using specific examples such as generalized anxiety disorder (GAD) and major depressive disorder (MDD). We seek to consolidate existing knowledge on the intricacies of the GBA in the hope that it may promote individual health and become a standard component in the treatment of mental illness.

Direct Activation of Neuronal Pathways

Vagal and spinal afferent nerve pathways convey information regarding hormonal, chemical, and mechanical stimuli from the intestines to the brain.³ These afferent neurons have been shown to be responsive to microbial signals and cytokines as well as to gut hormones. This provides the basis for research that presumes that neurobehavioral change may ensue from manipulating the gut microbes emitting these chemical signals to which these afferent neurons respond.³ Using these same pathways, efferent neurons of the parasympathetic and sympathetic nervous systems can modulate the intestinal environment by altering acid and bile secretion, mucous production, and motility. This modulation can directly impact the relative diversity of intestinal flora, and in more extreme states, may result in bacterial overgrowth.⁵ Of particular relevance to mental health (MH) is that the frequency of migrating motor complexes that promote peristalsis can be directly influenced by readily modifiable behaviors such as sleep and food intake, which can cause one bacterial species to dominate in a higher percentage.⁵ This imbalance of gut microbes has been implicated in contributing to somatic conditions, such as irritable bowel syndrome (IBS), which the literature has shown is related to psychiatric conditions such as anxiety. ⁵

The Microbiome and Host Immunity

The GI tract is colonized with commensal microorganisms from dozens of bacterial, archaeal, fungal, and protozoal groups.⁶ This relationship has its most classical immunologic interaction in the toll-like receptors. These receptors are on the lymphoid Peyer patches of the GI tract, which sample microorganisms and develop immunoglobulin (IgA) antibodies to them. Evidence exists that commensal microflora play a critical role in the regulation of host inflammatory response.⁷

The relationship between the microbiome and the immune system remains poorly understood, yet evidence has shown that the use of probiotics may reduce inflammation and its sequelae. Probiotics have been shown to have a beneficial effect on autoimmune diseases, such as Crohn disease and ulcerative colitis, specifically with certain strains of Escherichia coli (E coli) and a proprietary probiotic from VSL pharmaceuticals.^8,9 However, these interventions are not without risk. Fecal microbiota transplants have a risk of transferring unwanted organisms, potentially including COVID-19.¹⁰ Additionally, the use of probiotics is generally discouraged in immunocompromised, chronically ill, and/or hospitalized patients, as these patients may be at greater risk of developing probiotic bacteremia and sepsis.¹¹

Studies have also demonstrated that ingesting probiotics may decrease the expression of pro-inflammatory cytokines.¹¹ In a study comparing patients with ulcerative colitis who were prescribed both sulfasalazine and probiotic supplements vs sulfasalazine alone, patients who took the probiotic supplements were shown to have less colonic inflammation and decreased expression of cytokines such as IL-6, tumor necrosis factor-α (TNF-α), and nuclear factor-κβ.¹²

Gut-Specific Bacterial Phyla

Over the past decade, much attention has been paid toward 2 bacterial phyla that compromise a large proportion of the human gut microbiome: Firmicutes and Bacteroidetes. Intestinal Firmicutes species are predominantly Gram positive and are found as both cocci and bacilli. Well-known classes within the phylum Firmicutes include Bacilli (orders Bacillales and Lactobacillales) and Clostridia. The phylum Bacteroidetes is composed of Gram-negative rods and includes the genus Bacteroides—a substantial component of mammalian gut biomes. The ratio of Firmicutes to Bacteroidetes, also known as the F/B ratio, have shown fascinating patterns in certain psychiatric conditions. This knowledge may be applied to better identify, treat, and manage such patients.

Regarding bacterial phyla and their relationship to mood disorders, interesting patterns have been observed. In one population of patients with anorexia nervosa (AN) lower diversity within classes of Firmicutes bacteria was observed compared with age- and sex-matched controls without AN.¹³ As patients were re-fed and treated in this study, there was a significant corresponding increase in microbiome diversity; however, the level of bacterial diversity in re-fed patients with AN was still far less than that of patients in the control group. In patients with AN with comorbid depression, diversity was noted to be exceptionally reduced. Similarly, patients with AN with a more severe eating disorder psychopathology demonstrated decreased microbial diversity.¹³

The impact of intestinal microbiome diversity and relative bacterial population density in MH conditions such as anxiety, depression, and eating disorders remains an intriguing avenue worth further exploring. Modulating these phenomena may reduce overall dysfunction and serve as a possible treatment modality.

Anxiety and the Microbiome

GAD is characterized by decreased social and occupational functioning. Anxiolytic pharmacotherapy combined with psychotherapy are the current mainstays of GAD treatment. Given the interplay of the gut microbiome and MH, probiotics may prove to be a promising alternative or adjunct treatment option.

The human stress response is enacted largely through the hypothalamus-pituitary-adrenal (HPA) axis. Anxiety and situational fear trigger a stress response that results in increased cortisol being released from the adrenal glands, thereby disrupting typical GI function by modifying the frequency of migrating motor complexes, the electromechanical impulses within the smooth muscle of the stomach and small bowel that allow for propagation of chyme. This, in turn, has downstream consequences on the composition of the intestinal microbiome.¹⁴ Patients with GAD have a lower prevalence of Faecalibacterium, Eubacterium rectale, Lachnospira, Butyricioccus, and Sutterella, all important producers of short-chain fatty acids (SCFA).^15,16 Diminished SCFA production has been linked to intestinal barrier dysfunction, contributing to increases in gut endothelial permeability and facilitating a proinflammatory response with resultant neural feedback loops.^17,18 Indeed, proinflammatory cytokines, namely C-reactive protein (CRP), interleukin 6 (IL-6), and TNF-α were found to be elevated in patients with diagnosed GAD.¹⁹ These proinflammatory cytokines are critical in neurochemical modulation as they inhibit the essential enzyme tetrahydrobiopterin, a cofactor of monoamine synthesis, thereby decreasing the monoamine neurotransmitters serotonin, dopamine, and norepinephrine.²⁰ Decrease in the monoamine neurotransmitters serves as the lynchpin for the monoamine hypothesis of both anxiety and depression and currently guides our choice in pharmacotherapy.²¹

Anxiolytic pharmacotherapy targets the neurochemical consequences of GAD to ameliorate social, functional, and emotional impairment. However, the physiology of the gut-brain feedback loop in GAD is an attractive target for the creation and trialing of probiotics, which can rebalance intestinal flora, reduce inflammation, and allow for increased synthesis of monoamine neurotransmitters. Indeed, Lactobacillus and Bifidobacterium have been shown to possess anxiolytic properties by increasing serotonin and SCFAs while reducing the HPA adrenergic response.²²

Depression and the Microbiome

MDD significantly diminishes quality of life and is the leading cause of disability worldwide, affecting nearly 350 million individuals.²³ Psychotherapy in conjunction with pharmacotherapy aimed at increasing cerebral serotonin availability are the current mainstays of MDD treatment. Yet the brain does not exist in isolation: It has 3 known methods of bidirectional communication with the GI tract via the vagus nerve, immune mediators, and bacterial metabolites.^24,25

The vagus nerve (vagus means wandering in Latin), is the longest nerve of the autonomic nervous system (ANS) and historically has been called the pneumogastric nerve for its parasympathetic innervation of the heart, lungs, and digestive tract. Current research supports that up to 80% of the fibers within the vagus nerve are afferent, relaying signals from the GI tract to the brain.²⁶ Therefore, modulation of vagus nerve signaling may theoretically impact mental health. Indeed, studies have demonstrated clinically significant improvement in patients with treatment-resistant depression who underwent vagal nerve stimulation (VNS).²⁷ Although the mechanism by which it exerts its mood-modulating activity is not well understood, recent human and animal studies indicate that VNS may alter central neurotransmitter levels, having demonstrated the ability to increase serotonin levels.²⁵ Also the vagus nerve possesses the ability to differentiate between pathogenic and nonpathogenic gut microorganisms; beneficial gut flora emit signals within the gut lumen, which in turn, are transmitted through afferent vagus nerve fibers to the brain, effecting both anti-inflammatory and mood-modulating responses.^25,28

Immunomediators involving intestinal microbiota also are known to play a critical role in the pathophysiology of MDD. Depression is closely tied to systemic inflammation; both are hypothesized to have played a role in the evolutionary response to fighting infection and healing wounds.²⁹ With regard to the gut, MDD is associated with increased GI permeability, which allows for microorganisms to leak through the intestinal mucosa into the systemic circulation and stimulate an inflammatory response.¹⁸ Levels of IgM and IgA against enterobacteria lipopolysaccharides (LPS) were found to be markedly greater in patients with MDD vs those of nondepressed controls.³⁰ Current research indicates that IgM and IgA against LPS of translocated bacteria serve to amplify immune pathways seen in the pathophysiology of chronic MDD.^30,31 Further research is indicated to deduce whether bacterial translocation with subsequent immune response induces MDD in susceptible individuals, or whether translocation occurs secondary to the systemic inflammation seen in MDD.

The makeup of the GI microbiome is fundamentally altered in patients with MDD, with a marked reduction in both microorganism diversity and density.³⁰ Patients with MDD have been shown to have increased levels of Alistipes, a bacterium that also is elevated in chronic fatigue syndrome and irritable bowel syndrome (IBS), diagnoses that are associated with MDD.^32-34 Lower counts of Bifidobacterium and Lactobacillus are documented in both MDD and IBS patients as well.³⁵ Decreased Bifidobacterium and Lactobacillus might indicate a causal rather than correlative relationship as these bacterium take the precursor monosodium glutamate to create γ-aminobutyric acid (GABA).³⁶

Psychobiotics and Mental Health

The pathophysiology of the bidirectional communication between the gut and the brain offers an attractive approach for treatment modalities. Currently, the research into probiotic supplementation to treat mental disorders, such as anxiety and depression, is still in its infancy, and treatment guidelines do not support their routine administration. There is great promise in the use of probiotics to ameliorate psychiatric symptomatology, referred to by many in the field as psychobiotics.

One pathophysiology of the stress response seen in anxiety can be traced to the HPA axis and increased cortisol levels, with downstream effects on the microbiome through modification of the migrating motor complexes. Healthy volunteers tasked with taking a trademarked galactooligosaccharide prebiotic daily for 3 weeks had a reduced salivary cortisol awakening response compared with that of a placebo (maltodextrin). The same group demonstrated decreased attentional vigilance to negative information in a dot-probe task compared with attentional vigilance with positive information.³⁷ It is possible that this was due to the decreased stress response secondary to probiotic consumption. In mice models, a probiotic consisting of Lactobacillus helveticus and Bifidobacterium longum (B longum) (bacterium that are decreased in GAD and MDD) demonstrated anxiolytic-like behavior. The same formulation also demonstrated beneficial psychological effects in healthy human volunteers.²² In mice models, Lactobacillus feeding was superior to citalopram in anxiolysis and in cognitive functioning.³⁸

Like GAD, the pathophysiology of the GBA in MDD is an attractive target for psychobiotic therapy. Although current research is not yet sufficient to create general guidelines or recommendations for the routine administration of psychobiotics, it holds significant promise as an effective primary and/or adjunct treatment. In patients with IBS, administration of B longum reduced depression and increased quality of life. This same study demonstrated that probiotic administration was associated with reduced limbic activity in the brain.³⁹ In MDD, the hippocampus demonstrates altered expression of various transcription factors and cellular metabolism.⁴⁰ In a double-blind placebo-controlled trial, Lactobaccillus rhamnosus supplementation in postnatal mothers resulted in less severe depressive symptoms reported.⁴¹ Furthermore, probiotic supplementation consisting of Lactobacillus acidophilus, Lactobacillus casei, and Bifidobacterium bifidum in patients with MDD for 8 weeks had significant decreases in score on the Beck Depression Inventory scale.⁴² Also, a meta-analysis of probiotic administration on depression scales demonstrated appreciably lower scores after administration in both patients with MDD and healthy patients aged 60 years, although these results were found to be correlative.⁴³ However, while promising, another meta-analysis of 10 randomized controlled trials found probiotic supplementation had no significant effect on mood.⁴⁴

The Role of Diet

Although there has been tremendous focus on new and improved therapeutics to address MH conditions, such as depression and anxiety, there also has been renewed interest in the fundamental importance and benefit of a wholesome diet. Recent literature has shown how diet may play a pivotal role in the development and severity of mental illness and holds promise as another potential target for treatment. A 2010 cross-sectional population study of more than 1000 adult women aged 20 to 93 years demonstrated that women with a largely Western dietary pattern (ie, largely composed of processed meats, pizza, chips, hamburgers, white bread, sugar, flavored milk drinks, and beer) were more likely to have dysthymic disorder or major depression, whereas women in this same cohort with a more traditional dietary pattern (ie, composed mainly of vegetables, fruit, lamb, beef, fish, and whole grains) were found to have significantly reduced odds for depression or dysthymic disorder as well as anxiety disorders.⁴⁵

Several other large-scale population studies such as the SUN cohort study, Hordaland Health study, Whitehall II cohort study, and RHEA mother and baby cohort study have demonstrated similar findings: that a more wholesome diet composed mainly of lean meats, vegetables, fruits, and whole grains was associated with significantly reduced risk of depression compared with a largely processed, high fat, and high sugar diet. This trend also has been observed in children and adolescents and is of particular importance when considering that many psychological and psychiatric problems tend to arise in the formative and often turbulent years prior to adulthood.⁴⁶

The causal relationship between diet and MH may be better understood by taking a closer look at a crucial intermediate factor: the gut microbiome. The interplay between diet and intestinal microbiome was well elucidated in a landmark 2010 study by De Filippo and colleagues.⁴⁷ In this study, the microbiota of 14 healthy children from a small village in Burkina Faso (BF) were compared with those of 15 healthy children from an urban area of Florence, Italy (EU). The BF children were reported to consume a traditional rural African diet that is primarily vegetarian, rich in fiber, and low in animal protein and fat, whereas the EU children were noted as consuming a typical Western diet low in fiber but rich in animal protein, fat, sugar, and starch. Comparison revealed that EU children had a higher F/B ratio than their BF counterparts, a metric that has been associated with obesity.⁴⁷ Furthermore, increased exposure to environmental microbes associated with a fiber-rich diet has been postulated to increase the richness of intestinal flora and serve as a protective factor against noninfectious and inflammatory colonic diseases, which are found to be more prevalent in Western nations whose diets lack fiber. BF children were found to have increased microbial diversity and increased abundance of bacteria capable of producing SCFA relative to their EU counterparts, both of which have a positive influence on the gut, systemic inflammation, and MH.⁴⁷

Conclusions

Diet has a powerful impact on the intestinal microbiome, which in turn directly impacts our physical and MH in myriad ways. The well-known benefits of a wholesome, nutritious, and well-varied diet include reduced cardiovascular risk, improved glycemic control, GI regularity, and decreased depression. Along with a balanced diet, patients may achieve further benefit with the addition of probiotics.

With regard to psychiatry in particular, increased awareness of the intimate relationship between the gut and the brain is expected to have profound implications for the field. Given this mounting data, immunology, microbiology, and GI pathophysiology should be included in future discussions regarding MH. Their application will likely improve both somatic and mental well-being. We anticipate that newly discovered probiotics and other psychobiotic formulations will be routinely included in a psychiatrist’s pharmacopeia in the near future. Unfortunately, as is clear from our review of the current literature, we do not yet have specific interventions targeting the intestinal microbiome to recommend for the management of specific psychiatric conditions. However, this should not deter further exploring diet modification and psychobiotic supplementation as a means of impacting the intestinal microbiome in the pursuit of psychiatric symptom relief.

Dietary modification is already a standard component of sound primary care medicine, designed to mitigate risk for cardiovascular disease. This exploration can occur as part of otherwise standard psychiatric care and be used as a form of behavioral activation for the patient. Furthermore, explaining the interconnectedness of the mind, brain, and body along with the rationale for experimentation could further help destigmatize the experience of mental illness.

The gut-brain axis (GBA) refers to the link between the human brain with its various cognitive and affective functions and the gastrointestinal (GI) system, which includes the enteric nervous system and the diverse microbiome inhabiting the gut lumen. The neurochemical aspects of the GBA have been studied in germ-free mice; these studies demonstrate how absence or derangement of this microbiome can cause significant alterations in levels of serotonin, brain-derived neurotrophic factor, tryptophan, and other neurocompounds.^1,2 These neurotransmitter alterations have demonstrable effects on anxiety, cognition, socialization, and neuronal development in mice.^1,2

Current evidence suggests that the GBA works through a combination of both fast-acting neural and delayed immune-mediated mechanisms in a bidirectional manner with feedback on and from both systems.³ In addition to their direct effects on neural pathways and immune modulation, intestinal microbiota are essential in the production of a vast array of vitamins, cofactors, and nutrients required for optimal health and metabolism.⁴ Existing research on the GBA demonstrates the direct functional impact of the intestinal microbiome on neurologic and psychiatric health.

We will review current knowledge regarding this intriguing relationship. In doing so, we take a closer look at several specific genera and families of intestinal microbiota, review the microbiome’s effects on immune function, and examine the relationship between this microbiome and mental disease, using specific examples such as generalized anxiety disorder (GAD) and major depressive disorder (MDD). We seek to consolidate existing knowledge on the intricacies of the GBA in the hope that it may promote individual health and become a standard component in the treatment of mental illness.

Direct Activation of Neuronal Pathways

Vagal and spinal afferent nerve pathways convey information regarding hormonal, chemical, and mechanical stimuli from the intestines to the brain.³ These afferent neurons have been shown to be responsive to microbial signals and cytokines as well as to gut hormones. This provides the basis for research that presumes that neurobehavioral change may ensue from manipulating the gut microbes emitting these chemical signals to which these afferent neurons respond.³ Using these same pathways, efferent neurons of the parasympathetic and sympathetic nervous systems can modulate the intestinal environment by altering acid and bile secretion, mucous production, and motility. This modulation can directly impact the relative diversity of intestinal flora, and in more extreme states, may result in bacterial overgrowth.⁵ Of particular relevance to mental health (MH) is that the frequency of migrating motor complexes that promote peristalsis can be directly influenced by readily modifiable behaviors such as sleep and food intake, which can cause one bacterial species to dominate in a higher percentage.⁵ This imbalance of gut microbes has been implicated in contributing to somatic conditions, such as irritable bowel syndrome (IBS), which the literature has shown is related to psychiatric conditions such as anxiety. ⁵

The Microbiome and Host Immunity

The GI tract is colonized with commensal microorganisms from dozens of bacterial, archaeal, fungal, and protozoal groups.⁶ This relationship has its most classical immunologic interaction in the toll-like receptors. These receptors are on the lymphoid Peyer patches of the GI tract, which sample microorganisms and develop immunoglobulin (IgA) antibodies to them. Evidence exists that commensal microflora play a critical role in the regulation of host inflammatory response.⁷

The relationship between the microbiome and the immune system remains poorly understood, yet evidence has shown that the use of probiotics may reduce inflammation and its sequelae. Probiotics have been shown to have a beneficial effect on autoimmune diseases, such as Crohn disease and ulcerative colitis, specifically with certain strains of Escherichia coli (E coli) and a proprietary probiotic from VSL pharmaceuticals.^8,9 However, these interventions are not without risk. Fecal microbiota transplants have a risk of transferring unwanted organisms, potentially including COVID-19.¹⁰ Additionally, the use of probiotics is generally discouraged in immunocompromised, chronically ill, and/or hospitalized patients, as these patients may be at greater risk of developing probiotic bacteremia and sepsis.¹¹

Studies have also demonstrated that ingesting probiotics may decrease the expression of pro-inflammatory cytokines.¹¹ In a study comparing patients with ulcerative colitis who were prescribed both sulfasalazine and probiotic supplements vs sulfasalazine alone, patients who took the probiotic supplements were shown to have less colonic inflammation and decreased expression of cytokines such as IL-6, tumor necrosis factor-α (TNF-α), and nuclear factor-κβ.¹²

Gut-Specific Bacterial Phyla

Over the past decade, much attention has been paid toward 2 bacterial phyla that compromise a large proportion of the human gut microbiome: Firmicutes and Bacteroidetes. Intestinal Firmicutes species are predominantly Gram positive and are found as both cocci and bacilli. Well-known classes within the phylum Firmicutes include Bacilli (orders Bacillales and Lactobacillales) and Clostridia. The phylum Bacteroidetes is composed of Gram-negative rods and includes the genus Bacteroides—a substantial component of mammalian gut biomes. The ratio of Firmicutes to Bacteroidetes, also known as the F/B ratio, have shown fascinating patterns in certain psychiatric conditions. This knowledge may be applied to better identify, treat, and manage such patients.

Regarding bacterial phyla and their relationship to mood disorders, interesting patterns have been observed. In one population of patients with anorexia nervosa (AN) lower diversity within classes of Firmicutes bacteria was observed compared with age- and sex-matched controls without AN.¹³ As patients were re-fed and treated in this study, there was a significant corresponding increase in microbiome diversity; however, the level of bacterial diversity in re-fed patients with AN was still far less than that of patients in the control group. In patients with AN with comorbid depression, diversity was noted to be exceptionally reduced. Similarly, patients with AN with a more severe eating disorder psychopathology demonstrated decreased microbial diversity.¹³

The impact of intestinal microbiome diversity and relative bacterial population density in MH conditions such as anxiety, depression, and eating disorders remains an intriguing avenue worth further exploring. Modulating these phenomena may reduce overall dysfunction and serve as a possible treatment modality.

Anxiety and the Microbiome

GAD is characterized by decreased social and occupational functioning. Anxiolytic pharmacotherapy combined with psychotherapy are the current mainstays of GAD treatment. Given the interplay of the gut microbiome and MH, probiotics may prove to be a promising alternative or adjunct treatment option.

The human stress response is enacted largely through the hypothalamus-pituitary-adrenal (HPA) axis. Anxiety and situational fear trigger a stress response that results in increased cortisol being released from the adrenal glands, thereby disrupting typical GI function by modifying the frequency of migrating motor complexes, the electromechanical impulses within the smooth muscle of the stomach and small bowel that allow for propagation of chyme. This, in turn, has downstream consequences on the composition of the intestinal microbiome.¹⁴ Patients with GAD have a lower prevalence of Faecalibacterium, Eubacterium rectale, Lachnospira, Butyricioccus, and Sutterella, all important producers of short-chain fatty acids (SCFA).^15,16 Diminished SCFA production has been linked to intestinal barrier dysfunction, contributing to increases in gut endothelial permeability and facilitating a proinflammatory response with resultant neural feedback loops.^17,18 Indeed, proinflammatory cytokines, namely C-reactive protein (CRP), interleukin 6 (IL-6), and TNF-α were found to be elevated in patients with diagnosed GAD.¹⁹ These proinflammatory cytokines are critical in neurochemical modulation as they inhibit the essential enzyme tetrahydrobiopterin, a cofactor of monoamine synthesis, thereby decreasing the monoamine neurotransmitters serotonin, dopamine, and norepinephrine.²⁰ Decrease in the monoamine neurotransmitters serves as the lynchpin for the monoamine hypothesis of both anxiety and depression and currently guides our choice in pharmacotherapy.²¹

Anxiolytic pharmacotherapy targets the neurochemical consequences of GAD to ameliorate social, functional, and emotional impairment. However, the physiology of the gut-brain feedback loop in GAD is an attractive target for the creation and trialing of probiotics, which can rebalance intestinal flora, reduce inflammation, and allow for increased synthesis of monoamine neurotransmitters. Indeed, Lactobacillus and Bifidobacterium have been shown to possess anxiolytic properties by increasing serotonin and SCFAs while reducing the HPA adrenergic response.²²

Depression and the Microbiome

MDD significantly diminishes quality of life and is the leading cause of disability worldwide, affecting nearly 350 million individuals.²³ Psychotherapy in conjunction with pharmacotherapy aimed at increasing cerebral serotonin availability are the current mainstays of MDD treatment. Yet the brain does not exist in isolation: It has 3 known methods of bidirectional communication with the GI tract via the vagus nerve, immune mediators, and bacterial metabolites.^24,25

The vagus nerve (vagus means wandering in Latin), is the longest nerve of the autonomic nervous system (ANS) and historically has been called the pneumogastric nerve for its parasympathetic innervation of the heart, lungs, and digestive tract. Current research supports that up to 80% of the fibers within the vagus nerve are afferent, relaying signals from the GI tract to the brain.²⁶ Therefore, modulation of vagus nerve signaling may theoretically impact mental health. Indeed, studies have demonstrated clinically significant improvement in patients with treatment-resistant depression who underwent vagal nerve stimulation (VNS).²⁷ Although the mechanism by which it exerts its mood-modulating activity is not well understood, recent human and animal studies indicate that VNS may alter central neurotransmitter levels, having demonstrated the ability to increase serotonin levels.²⁵ Also the vagus nerve possesses the ability to differentiate between pathogenic and nonpathogenic gut microorganisms; beneficial gut flora emit signals within the gut lumen, which in turn, are transmitted through afferent vagus nerve fibers to the brain, effecting both anti-inflammatory and mood-modulating responses.^25,28

Immunomediators involving intestinal microbiota also are known to play a critical role in the pathophysiology of MDD. Depression is closely tied to systemic inflammation; both are hypothesized to have played a role in the evolutionary response to fighting infection and healing wounds.²⁹ With regard to the gut, MDD is associated with increased GI permeability, which allows for microorganisms to leak through the intestinal mucosa into the systemic circulation and stimulate an inflammatory response.¹⁸ Levels of IgM and IgA against enterobacteria lipopolysaccharides (LPS) were found to be markedly greater in patients with MDD vs those of nondepressed controls.³⁰ Current research indicates that IgM and IgA against LPS of translocated bacteria serve to amplify immune pathways seen in the pathophysiology of chronic MDD.^30,31 Further research is indicated to deduce whether bacterial translocation with subsequent immune response induces MDD in susceptible individuals, or whether translocation occurs secondary to the systemic inflammation seen in MDD.

The makeup of the GI microbiome is fundamentally altered in patients with MDD, with a marked reduction in both microorganism diversity and density.³⁰ Patients with MDD have been shown to have increased levels of Alistipes, a bacterium that also is elevated in chronic fatigue syndrome and irritable bowel syndrome (IBS), diagnoses that are associated with MDD.^32-34 Lower counts of Bifidobacterium and Lactobacillus are documented in both MDD and IBS patients as well.³⁵ Decreased Bifidobacterium and Lactobacillus might indicate a causal rather than correlative relationship as these bacterium take the precursor monosodium glutamate to create γ-aminobutyric acid (GABA).³⁶

Psychobiotics and Mental Health

The pathophysiology of the bidirectional communication between the gut and the brain offers an attractive approach for treatment modalities. Currently, the research into probiotic supplementation to treat mental disorders, such as anxiety and depression, is still in its infancy, and treatment guidelines do not support their routine administration. There is great promise in the use of probiotics to ameliorate psychiatric symptomatology, referred to by many in the field as psychobiotics.

One pathophysiology of the stress response seen in anxiety can be traced to the HPA axis and increased cortisol levels, with downstream effects on the microbiome through modification of the migrating motor complexes. Healthy volunteers tasked with taking a trademarked galactooligosaccharide prebiotic daily for 3 weeks had a reduced salivary cortisol awakening response compared with that of a placebo (maltodextrin). The same group demonstrated decreased attentional vigilance to negative information in a dot-probe task compared with attentional vigilance with positive information.³⁷ It is possible that this was due to the decreased stress response secondary to probiotic consumption. In mice models, a probiotic consisting of Lactobacillus helveticus and Bifidobacterium longum (B longum) (bacterium that are decreased in GAD and MDD) demonstrated anxiolytic-like behavior. The same formulation also demonstrated beneficial psychological effects in healthy human volunteers.²² In mice models, Lactobacillus feeding was superior to citalopram in anxiolysis and in cognitive functioning.³⁸

Like GAD, the pathophysiology of the GBA in MDD is an attractive target for psychobiotic therapy. Although current research is not yet sufficient to create general guidelines or recommendations for the routine administration of psychobiotics, it holds significant promise as an effective primary and/or adjunct treatment. In patients with IBS, administration of B longum reduced depression and increased quality of life. This same study demonstrated that probiotic administration was associated with reduced limbic activity in the brain.³⁹ In MDD, the hippocampus demonstrates altered expression of various transcription factors and cellular metabolism.⁴⁰ In a double-blind placebo-controlled trial, Lactobaccillus rhamnosus supplementation in postnatal mothers resulted in less severe depressive symptoms reported.⁴¹ Furthermore, probiotic supplementation consisting of Lactobacillus acidophilus, Lactobacillus casei, and Bifidobacterium bifidum in patients with MDD for 8 weeks had significant decreases in score on the Beck Depression Inventory scale.⁴² Also, a meta-analysis of probiotic administration on depression scales demonstrated appreciably lower scores after administration in both patients with MDD and healthy patients aged 60 years, although these results were found to be correlative.⁴³ However, while promising, another meta-analysis of 10 randomized controlled trials found probiotic supplementation had no significant effect on mood.⁴⁴

The Role of Diet

Although there has been tremendous focus on new and improved therapeutics to address MH conditions, such as depression and anxiety, there also has been renewed interest in the fundamental importance and benefit of a wholesome diet. Recent literature has shown how diet may play a pivotal role in the development and severity of mental illness and holds promise as another potential target for treatment. A 2010 cross-sectional population study of more than 1000 adult women aged 20 to 93 years demonstrated that women with a largely Western dietary pattern (ie, largely composed of processed meats, pizza, chips, hamburgers, white bread, sugar, flavored milk drinks, and beer) were more likely to have dysthymic disorder or major depression, whereas women in this same cohort with a more traditional dietary pattern (ie, composed mainly of vegetables, fruit, lamb, beef, fish, and whole grains) were found to have significantly reduced odds for depression or dysthymic disorder as well as anxiety disorders.⁴⁵

Several other large-scale population studies such as the SUN cohort study, Hordaland Health study, Whitehall II cohort study, and RHEA mother and baby cohort study have demonstrated similar findings: that a more wholesome diet composed mainly of lean meats, vegetables, fruits, and whole grains was associated with significantly reduced risk of depression compared with a largely processed, high fat, and high sugar diet. This trend also has been observed in children and adolescents and is of particular importance when considering that many psychological and psychiatric problems tend to arise in the formative and often turbulent years prior to adulthood.⁴⁶

The causal relationship between diet and MH may be better understood by taking a closer look at a crucial intermediate factor: the gut microbiome. The interplay between diet and intestinal microbiome was well elucidated in a landmark 2010 study by De Filippo and colleagues.⁴⁷ In this study, the microbiota of 14 healthy children from a small village in Burkina Faso (BF) were compared with those of 15 healthy children from an urban area of Florence, Italy (EU). The BF children were reported to consume a traditional rural African diet that is primarily vegetarian, rich in fiber, and low in animal protein and fat, whereas the EU children were noted as consuming a typical Western diet low in fiber but rich in animal protein, fat, sugar, and starch. Comparison revealed that EU children had a higher F/B ratio than their BF counterparts, a metric that has been associated with obesity.⁴⁷ Furthermore, increased exposure to environmental microbes associated with a fiber-rich diet has been postulated to increase the richness of intestinal flora and serve as a protective factor against noninfectious and inflammatory colonic diseases, which are found to be more prevalent in Western nations whose diets lack fiber. BF children were found to have increased microbial diversity and increased abundance of bacteria capable of producing SCFA relative to their EU counterparts, both of which have a positive influence on the gut, systemic inflammation, and MH.⁴⁷

Conclusions

Diet has a powerful impact on the intestinal microbiome, which in turn directly impacts our physical and MH in myriad ways. The well-known benefits of a wholesome, nutritious, and well-varied diet include reduced cardiovascular risk, improved glycemic control, GI regularity, and decreased depression. Along with a balanced diet, patients may achieve further benefit with the addition of probiotics.

With regard to psychiatry in particular, increased awareness of the intimate relationship between the gut and the brain is expected to have profound implications for the field. Given this mounting data, immunology, microbiology, and GI pathophysiology should be included in future discussions regarding MH. Their application will likely improve both somatic and mental well-being. We anticipate that newly discovered probiotics and other psychobiotic formulations will be routinely included in a psychiatrist’s pharmacopeia in the near future. Unfortunately, as is clear from our review of the current literature, we do not yet have specific interventions targeting the intestinal microbiome to recommend for the management of specific psychiatric conditions. However, this should not deter further exploring diet modification and psychobiotic supplementation as a means of impacting the intestinal microbiome in the pursuit of psychiatric symptom relief.

Dietary modification is already a standard component of sound primary care medicine, designed to mitigate risk for cardiovascular disease. This exploration can occur as part of otherwise standard psychiatric care and be used as a form of behavioral activation for the patient. Furthermore, explaining the interconnectedness of the mind, brain, and body along with the rationale for experimentation could further help destigmatize the experience of mental illness.

The gut-brain axis (GBA) refers to the link between the human brain with its various cognitive and affective functions and the gastrointestinal (GI) system, which includes the enteric nervous system and the diverse microbiome inhabiting the gut lumen. The neurochemical aspects of the GBA have been studied in germ-free mice; these studies demonstrate how absence or derangement of this microbiome can cause significant alterations in levels of serotonin, brain-derived neurotrophic factor, tryptophan, and other neurocompounds.^1,2 These neurotransmitter alterations have demonstrable effects on anxiety, cognition, socialization, and neuronal development in mice.^1,2

Current evidence suggests that the GBA works through a combination of both fast-acting neural and delayed immune-mediated mechanisms in a bidirectional manner with feedback on and from both systems.³ In addition to their direct effects on neural pathways and immune modulation, intestinal microbiota are essential in the production of a vast array of vitamins, cofactors, and nutrients required for optimal health and metabolism.⁴ Existing research on the GBA demonstrates the direct functional impact of the intestinal microbiome on neurologic and psychiatric health.

We will review current knowledge regarding this intriguing relationship. In doing so, we take a closer look at several specific genera and families of intestinal microbiota, review the microbiome’s effects on immune function, and examine the relationship between this microbiome and mental disease, using specific examples such as generalized anxiety disorder (GAD) and major depressive disorder (MDD). We seek to consolidate existing knowledge on the intricacies of the GBA in the hope that it may promote individual health and become a standard component in the treatment of mental illness.

Direct Activation of Neuronal Pathways

Vagal and spinal afferent nerve pathways convey information regarding hormonal, chemical, and mechanical stimuli from the intestines to the brain.³ These afferent neurons have been shown to be responsive to microbial signals and cytokines as well as to gut hormones. This provides the basis for research that presumes that neurobehavioral change may ensue from manipulating the gut microbes emitting these chemical signals to which these afferent neurons respond.³ Using these same pathways, efferent neurons of the parasympathetic and sympathetic nervous systems can modulate the intestinal environment by altering acid and bile secretion, mucous production, and motility. This modulation can directly impact the relative diversity of intestinal flora, and in more extreme states, may result in bacterial overgrowth.⁵ Of particular relevance to mental health (MH) is that the frequency of migrating motor complexes that promote peristalsis can be directly influenced by readily modifiable behaviors such as sleep and food intake, which can cause one bacterial species to dominate in a higher percentage.⁵ This imbalance of gut microbes has been implicated in contributing to somatic conditions, such as irritable bowel syndrome (IBS), which the literature has shown is related to psychiatric conditions such as anxiety. ⁵

The Microbiome and Host Immunity

The GI tract is colonized with commensal microorganisms from dozens of bacterial, archaeal, fungal, and protozoal groups.⁶ This relationship has its most classical immunologic interaction in the toll-like receptors. These receptors are on the lymphoid Peyer patches of the GI tract, which sample microorganisms and develop immunoglobulin (IgA) antibodies to them. Evidence exists that commensal microflora play a critical role in the regulation of host inflammatory response.⁷

The relationship between the microbiome and the immune system remains poorly understood, yet evidence has shown that the use of probiotics may reduce inflammation and its sequelae. Probiotics have been shown to have a beneficial effect on autoimmune diseases, such as Crohn disease and ulcerative colitis, specifically with certain strains of Escherichia coli (E coli) and a proprietary probiotic from VSL pharmaceuticals.^8,9 However, these interventions are not without risk. Fecal microbiota transplants have a risk of transferring unwanted organisms, potentially including COVID-19.¹⁰ Additionally, the use of probiotics is generally discouraged in immunocompromised, chronically ill, and/or hospitalized patients, as these patients may be at greater risk of developing probiotic bacteremia and sepsis.¹¹

Studies have also demonstrated that ingesting probiotics may decrease the expression of pro-inflammatory cytokines.¹¹ In a study comparing patients with ulcerative colitis who were prescribed both sulfasalazine and probiotic supplements vs sulfasalazine alone, patients who took the probiotic supplements were shown to have less colonic inflammation and decreased expression of cytokines such as IL-6, tumor necrosis factor-α (TNF-α), and nuclear factor-κβ.¹²

Gut-Specific Bacterial Phyla

Over the past decade, much attention has been paid toward 2 bacterial phyla that compromise a large proportion of the human gut microbiome: Firmicutes and Bacteroidetes. Intestinal Firmicutes species are predominantly Gram positive and are found as both cocci and bacilli. Well-known classes within the phylum Firmicutes include Bacilli (orders Bacillales and Lactobacillales) and Clostridia. The phylum Bacteroidetes is composed of Gram-negative rods and includes the genus Bacteroides—a substantial component of mammalian gut biomes. The ratio of Firmicutes to Bacteroidetes, also known as the F/B ratio, have shown fascinating patterns in certain psychiatric conditions. This knowledge may be applied to better identify, treat, and manage such patients.

Regarding bacterial phyla and their relationship to mood disorders, interesting patterns have been observed. In one population of patients with anorexia nervosa (AN) lower diversity within classes of Firmicutes bacteria was observed compared with age- and sex-matched controls without AN.¹³ As patients were re-fed and treated in this study, there was a significant corresponding increase in microbiome diversity; however, the level of bacterial diversity in re-fed patients with AN was still far less than that of patients in the control group. In patients with AN with comorbid depression, diversity was noted to be exceptionally reduced. Similarly, patients with AN with a more severe eating disorder psychopathology demonstrated decreased microbial diversity.¹³

The impact of intestinal microbiome diversity and relative bacterial population density in MH conditions such as anxiety, depression, and eating disorders remains an intriguing avenue worth further exploring. Modulating these phenomena may reduce overall dysfunction and serve as a possible treatment modality.

Anxiety and the Microbiome

GAD is characterized by decreased social and occupational functioning. Anxiolytic pharmacotherapy combined with psychotherapy are the current mainstays of GAD treatment. Given the interplay of the gut microbiome and MH, probiotics may prove to be a promising alternative or adjunct treatment option.

The human stress response is enacted largely through the hypothalamus-pituitary-adrenal (HPA) axis. Anxiety and situational fear trigger a stress response that results in increased cortisol being released from the adrenal glands, thereby disrupting typical GI function by modifying the frequency of migrating motor complexes, the electromechanical impulses within the smooth muscle of the stomach and small bowel that allow for propagation of chyme. This, in turn, has downstream consequences on the composition of the intestinal microbiome.¹⁴ Patients with GAD have a lower prevalence of Faecalibacterium, Eubacterium rectale, Lachnospira, Butyricioccus, and Sutterella, all important producers of short-chain fatty acids (SCFA).^15,16 Diminished SCFA production has been linked to intestinal barrier dysfunction, contributing to increases in gut endothelial permeability and facilitating a proinflammatory response with resultant neural feedback loops.^17,18 Indeed, proinflammatory cytokines, namely C-reactive protein (CRP), interleukin 6 (IL-6), and TNF-α were found to be elevated in patients with diagnosed GAD.¹⁹ These proinflammatory cytokines are critical in neurochemical modulation as they inhibit the essential enzyme tetrahydrobiopterin, a cofactor of monoamine synthesis, thereby decreasing the monoamine neurotransmitters serotonin, dopamine, and norepinephrine.²⁰ Decrease in the monoamine neurotransmitters serves as the lynchpin for the monoamine hypothesis of both anxiety and depression and currently guides our choice in pharmacotherapy.²¹

Anxiolytic pharmacotherapy targets the neurochemical consequences of GAD to ameliorate social, functional, and emotional impairment. However, the physiology of the gut-brain feedback loop in GAD is an attractive target for the creation and trialing of probiotics, which can rebalance intestinal flora, reduce inflammation, and allow for increased synthesis of monoamine neurotransmitters. Indeed, Lactobacillus and Bifidobacterium have been shown to possess anxiolytic properties by increasing serotonin and SCFAs while reducing the HPA adrenergic response.²²

Depression and the Microbiome

MDD significantly diminishes quality of life and is the leading cause of disability worldwide, affecting nearly 350 million individuals.²³ Psychotherapy in conjunction with pharmacotherapy aimed at increasing cerebral serotonin availability are the current mainstays of MDD treatment. Yet the brain does not exist in isolation: It has 3 known methods of bidirectional communication with the GI tract via the vagus nerve, immune mediators, and bacterial metabolites.^24,25

The vagus nerve (vagus means wandering in Latin), is the longest nerve of the autonomic nervous system (ANS) and historically has been called the pneumogastric nerve for its parasympathetic innervation of the heart, lungs, and digestive tract. Current research supports that up to 80% of the fibers within the vagus nerve are afferent, relaying signals from the GI tract to the brain.²⁶ Therefore, modulation of vagus nerve signaling may theoretically impact mental health. Indeed, studies have demonstrated clinically significant improvement in patients with treatment-resistant depression who underwent vagal nerve stimulation (VNS).²⁷ Although the mechanism by which it exerts its mood-modulating activity is not well understood, recent human and animal studies indicate that VNS may alter central neurotransmitter levels, having demonstrated the ability to increase serotonin levels.²⁵ Also the vagus nerve possesses the ability to differentiate between pathogenic and nonpathogenic gut microorganisms; beneficial gut flora emit signals within the gut lumen, which in turn, are transmitted through afferent vagus nerve fibers to the brain, effecting both anti-inflammatory and mood-modulating responses.^25,28

Immunomediators involving intestinal microbiota also are known to play a critical role in the pathophysiology of MDD. Depression is closely tied to systemic inflammation; both are hypothesized to have played a role in the evolutionary response to fighting infection and healing wounds.²⁹ With regard to the gut, MDD is associated with increased GI permeability, which allows for microorganisms to leak through the intestinal mucosa into the systemic circulation and stimulate an inflammatory response.¹⁸ Levels of IgM and IgA against enterobacteria lipopolysaccharides (LPS) were found to be markedly greater in patients with MDD vs those of nondepressed controls.³⁰ Current research indicates that IgM and IgA against LPS of translocated bacteria serve to amplify immune pathways seen in the pathophysiology of chronic MDD.^30,31 Further research is indicated to deduce whether bacterial translocation with subsequent immune response induces MDD in susceptible individuals, or whether translocation occurs secondary to the systemic inflammation seen in MDD.

The makeup of the GI microbiome is fundamentally altered in patients with MDD, with a marked reduction in both microorganism diversity and density.³⁰ Patients with MDD have been shown to have increased levels of Alistipes, a bacterium that also is elevated in chronic fatigue syndrome and irritable bowel syndrome (IBS), diagnoses that are associated with MDD.^32-34 Lower counts of Bifidobacterium and Lactobacillus are documented in both MDD and IBS patients as well.³⁵ Decreased Bifidobacterium and Lactobacillus might indicate a causal rather than correlative relationship as these bacterium take the precursor monosodium glutamate to create γ-aminobutyric acid (GABA).³⁶

Psychobiotics and Mental Health

The pathophysiology of the bidirectional communication between the gut and the brain offers an attractive approach for treatment modalities. Currently, the research into probiotic supplementation to treat mental disorders, such as anxiety and depression, is still in its infancy, and treatment guidelines do not support their routine administration. There is great promise in the use of probiotics to ameliorate psychiatric symptomatology, referred to by many in the field as psychobiotics.

One pathophysiology of the stress response seen in anxiety can be traced to the HPA axis and increased cortisol levels, with downstream effects on the microbiome through modification of the migrating motor complexes. Healthy volunteers tasked with taking a trademarked galactooligosaccharide prebiotic daily for 3 weeks had a reduced salivary cortisol awakening response compared with that of a placebo (maltodextrin). The same group demonstrated decreased attentional vigilance to negative information in a dot-probe task compared with attentional vigilance with positive information.³⁷ It is possible that this was due to the decreased stress response secondary to probiotic consumption. In mice models, a probiotic consisting of Lactobacillus helveticus and Bifidobacterium longum (B longum) (bacterium that are decreased in GAD and MDD) demonstrated anxiolytic-like behavior. The same formulation also demonstrated beneficial psychological effects in healthy human volunteers.²² In mice models, Lactobacillus feeding was superior to citalopram in anxiolysis and in cognitive functioning.³⁸

Like GAD, the pathophysiology of the GBA in MDD is an attractive target for psychobiotic therapy. Although current research is not yet sufficient to create general guidelines or recommendations for the routine administration of psychobiotics, it holds significant promise as an effective primary and/or adjunct treatment. In patients with IBS, administration of B longum reduced depression and increased quality of life. This same study demonstrated that probiotic administration was associated with reduced limbic activity in the brain.³⁹ In MDD, the hippocampus demonstrates altered expression of various transcription factors and cellular metabolism.⁴⁰ In a double-blind placebo-controlled trial, Lactobaccillus rhamnosus supplementation in postnatal mothers resulted in less severe depressive symptoms reported.⁴¹ Furthermore, probiotic supplementation consisting of Lactobacillus acidophilus, Lactobacillus casei, and Bifidobacterium bifidum in patients with MDD for 8 weeks had significant decreases in score on the Beck Depression Inventory scale.⁴² Also, a meta-analysis of probiotic administration on depression scales demonstrated appreciably lower scores after administration in both patients with MDD and healthy patients aged 60 years, although these results were found to be correlative.⁴³ However, while promising, another meta-analysis of 10 randomized controlled trials found probiotic supplementation had no significant effect on mood.⁴⁴

The Role of Diet

Although there has been tremendous focus on new and improved therapeutics to address MH conditions, such as depression and anxiety, there also has been renewed interest in the fundamental importance and benefit of a wholesome diet. Recent literature has shown how diet may play a pivotal role in the development and severity of mental illness and holds promise as another potential target for treatment. A 2010 cross-sectional population study of more than 1000 adult women aged 20 to 93 years demonstrated that women with a largely Western dietary pattern (ie, largely composed of processed meats, pizza, chips, hamburgers, white bread, sugar, flavored milk drinks, and beer) were more likely to have dysthymic disorder or major depression, whereas women in this same cohort with a more traditional dietary pattern (ie, composed mainly of vegetables, fruit, lamb, beef, fish, and whole grains) were found to have significantly reduced odds for depression or dysthymic disorder as well as anxiety disorders.⁴⁵

Several other large-scale population studies such as the SUN cohort study, Hordaland Health study, Whitehall II cohort study, and RHEA mother and baby cohort study have demonstrated similar findings: that a more wholesome diet composed mainly of lean meats, vegetables, fruits, and whole grains was associated with significantly reduced risk of depression compared with a largely processed, high fat, and high sugar diet. This trend also has been observed in children and adolescents and is of particular importance when considering that many psychological and psychiatric problems tend to arise in the formative and often turbulent years prior to adulthood.⁴⁶

The causal relationship between diet and MH may be better understood by taking a closer look at a crucial intermediate factor: the gut microbiome. The interplay between diet and intestinal microbiome was well elucidated in a landmark 2010 study by De Filippo and colleagues.⁴⁷ In this study, the microbiota of 14 healthy children from a small village in Burkina Faso (BF) were compared with those of 15 healthy children from an urban area of Florence, Italy (EU). The BF children were reported to consume a traditional rural African diet that is primarily vegetarian, rich in fiber, and low in animal protein and fat, whereas the EU children were noted as consuming a typical Western diet low in fiber but rich in animal protein, fat, sugar, and starch. Comparison revealed that EU children had a higher F/B ratio than their BF counterparts, a metric that has been associated with obesity.⁴⁷ Furthermore, increased exposure to environmental microbes associated with a fiber-rich diet has been postulated to increase the richness of intestinal flora and serve as a protective factor against noninfectious and inflammatory colonic diseases, which are found to be more prevalent in Western nations whose diets lack fiber. BF children were found to have increased microbial diversity and increased abundance of bacteria capable of producing SCFA relative to their EU counterparts, both of which have a positive influence on the gut, systemic inflammation, and MH.⁴⁷

Conclusions

Diet has a powerful impact on the intestinal microbiome, which in turn directly impacts our physical and MH in myriad ways. The well-known benefits of a wholesome, nutritious, and well-varied diet include reduced cardiovascular risk, improved glycemic control, GI regularity, and decreased depression. Along with a balanced diet, patients may achieve further benefit with the addition of probiotics.

With regard to psychiatry in particular, increased awareness of the intimate relationship between the gut and the brain is expected to have profound implications for the field. Given this mounting data, immunology, microbiology, and GI pathophysiology should be included in future discussions regarding MH. Their application will likely improve both somatic and mental well-being. We anticipate that newly discovered probiotics and other psychobiotic formulations will be routinely included in a psychiatrist’s pharmacopeia in the near future. Unfortunately, as is clear from our review of the current literature, we do not yet have specific interventions targeting the intestinal microbiome to recommend for the management of specific psychiatric conditions. However, this should not deter further exploring diet modification and psychobiotic supplementation as a means of impacting the intestinal microbiome in the pursuit of psychiatric symptom relief.

Dietary modification is already a standard component of sound primary care medicine, designed to mitigate risk for cardiovascular disease. This exploration can occur as part of otherwise standard psychiatric care and be used as a form of behavioral activation for the patient. Furthermore, explaining the interconnectedness of the mind, brain, and body along with the rationale for experimentation could further help destigmatize the experience of mental illness.

The American Medical Association publicly acknowledged in November 2020 that race is a social construct without biological basis, with many other leading medical organizations following suit.¹ Historically, biased science based on observed human physical differences has incorrectly asserted a racial biological hierarchy.^2,3 Today, leading health care organizations recognize that the effects of racist policies in housing, education, employment, and the criminal justice system contribute to health disparities and have a disproportionately negative impact on Black, Indigenous, and People of Color.^3,4 

Racial classification systems are fraught with bias. Trying to classify a complex and nuanced identity such as race into discrete categories does not capture the extensive heterogeneity at the individual level or within the increasingly diverse, multiracial population.⁵ Racial and ethnic categories used in collecting census data and research, as defined by the US Office of Management and Budget, have evolved over time.⁶ These changes in classification are a reflection of changes in the political environment, not changes in scientific knowledge of race and ethnicity.⁶

The Use of Race in Research and Practice

In the United States, racial minorities bear a disproportionate burden of morbidity and mortality across all major disease categories.³ These disparities cannot be explained by genetics.⁴ The Human Genome Project in 2003 confirmed that racial categories have no biologic or genetic basis and that there is more intraracial than interracial genetic variation.³ Nevertheless, significant misapplication of race in medical research and clinical practice remains. Instead of attributing observed differences in health outcomes between racial groups to innate physiological differences between the groups, clinicians and researchers must carefully consider the impact of racism.⁷ This includes considering the complex interactions between socioeconomic, political, and environmental factors, and how they affect health.³

While race is not biologic, the effects of racism can have biologic effects, and advocates appropriately cite the need to collect race as an important category in epidemiological analysis. When race and ethnicity are used as a study variable, bioethicists Kaplan and Bennett recommend that researchers: (1) account for limitations due to imprecision of racial categories; (2) avoid attributing causality when there is an association between race/ethnicity and a health outcome; and (3) refrain from exacerbating racial disparities.⁶

At the bedside, race has become embedded in clinical, seemingly objective, decision-making tools used across medical specialties.⁸ These algorithms often use observational outcomes data and draw conclusions by explicitly or implicitly assuming biological differences among races. By crudely adjusting for race without identifying the root cause for observed racial differences, these tools can further magnify health inequities.⁸ With the increased recognition that race cannot be used as a proxy for genetic ancestry, and that racial and ethnic categories are complex sociopolitical constructs that have changed over time, the practice of race-based medicine is increasingly being criticized.⁸

This article presents a case for the removal of the race coefficient from estimated glomerular filtration rate (eGFR) calculations that exacerbate disparities in kidney health by overestimating kidney function in Black patients.⁸ The main justification for using the race coefficient stems from the disproven assumption that Black people have more muscle mass compared with non-Black people.⁹  The questioning of this racist assertion has led to a national movement to reevaluate the use of race in eGFR calculations.

Racial Disparities in Kidney Disease

According to epidemiological data published by the National Kidney Foundation (NKF) and American Society of Nephrology (ASN), 37 million people in the United States have chronic kidney disease (CKD).¹⁰ Black Americans make up 13% of the US population yet they account for more than 30% of patients with end-stage kidney disease (ESKD) and 35% of those on dialysis.^10,11 There is a 3 times greater risk for progression from early-stage CKD to ESKD in Black Americans when compared to the risk for White Americans.¹¹ Black patients are younger at the time of CKD diagnosis and, once diagnosed, experience a faster progression to ESKD.¹² These disparities are partially attributable to delays in diagnosis, preventative measures, and referrals to nephrology care.¹²  

In a VA medical center study, although Black patients were referred to nephrology care at higher rates than White patients, Black patients had faster progression to CKD stage 5.¹³ An earlier study showed that, at any given eGFR, Black patients have higher levels of albuminuria compared to White patients.¹⁴ While the reasons behind this observation are likely complex and multifactorial, one hypothesis is that Black patients were already at a more advanced stage of kidney disease at the time of referral as a result of the overestimation of eGFR calculations related to the use of a race coefficient.

Additionally, numerous analyses have revealed that Black patients are less likely to be identified as transplant candidates, less likely to be referred for transplant evaluation and, once on the waiting list, wait longer than do White patients.^11,15

Estimated Glomerular Filtration Rate

It is imperative that clinicians have the most accurate measure of GFR to ensure timely diagnosis and appropriate management in patients with CKD. The gold standard for determining renal function requires measuring GFR using an ideal, exogenous, filtration marker such as iothalamate. However, this process is complex and time-consuming, rendering it infeasible in routine care. As a result, we usually estimate GFR using endogenous serum markers such as creatinine and cystatin C. Due to availability and cost, serum creatinine (SCr) is the most widely used marker for estimating kidney function. However, many pitfalls are inherent in its use, including the effects of tubular secretion, extrarenal clearance, and day-to-day variability in creatinine generation related to muscle mass, diet, and activity.¹⁶ The 2 most widely used estimation equations are the Modification of Diet in Renal Disease (MDRD) study equation and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation; both equations incorporate correction factors for age, sex, and race. 

The VA uses MDRD, which was derived and validated in a cohort of 1628 patients that included only 197 Black patients (12%), resulting in an eGFR for Black patients that is 21% higher than is the eGFR for non-Black patients with the same SCr value.⁹ In the VA electronic health record, the race coefficient is incorporated directly into eGFR laboratory calculations based on the race that the veteran self-identified during intake. Because the laboratory reports only a race-adjusted eGFR, there is a lack of transparency as many health care providers and patients are unaware that a race coefficient is used in eGFR calculations at the VA.  

Case for Removing Race Coefficient

When applied to cohorts outside the original study, both the MDRD and CKD-EPI equations have proved to be highly biased, imprecise, and inaccurate when compared to measured GFR (mGFR).^15,17 For any given eGFR, the possible mGFR may span 3 stages of CKD, underscoring the limitations of using such a crude estimate in clinical decision making.¹⁷ 

Current Kidney Estimation Pitfalls

A recent cohort study by Zelnick and colleagues that included 1658 self-identified Black adults showed less bias between mGFR and eGFR without the use of a race coefficient, and a shorter median time to transplant eligibility by 1.9 years.¹⁵ This study provides further evidence that these equations were derived from a biased observational data set that overestimates eGFR in Black patients living with CKD. This overestimation is particularly egregious for frail or malnourished patients with CKD and multiple comorbidities, with many potential harmful clinical consequences.

In addition, multiple international studies in African countries have demonstrated worse performance of eGFR calculations when using the race coefficient than without it. In the Democratic Republic of the Congo, eGFR was calculated for adults using MDRD with and without the race coefficient, as well as CKD-EPI with and without the race coefficient, and then compared to mGFR. Both the MDRD and the CKD-EPI equations overestimated GFR when using the race coefficient, and notably the equations without the race coefficient had better correlation to mGFR.¹⁸ Similar data were also found in studies from South Africa, the Ivory Coast, Brazil, and Europe.^19-22

Clinical Consequences of Race Coefficient Use

The use of a race coefficient in these estimation equations causes adverse clinical outcomes. In early stages of CKD, overestimation of eGFR using the race coefficient can cause an under-recognition of CKD, and can lead to delays in diagnosis and failure to implement measures to slow its progression, such as minimizing drug-related nephrotoxic injury and iatrogenic acute kidney injury. Consequently, a patient with an overestimated eGFR may suffer an accelerated progression to ESKD and premature mortality from cardiovascular disease.²³ 

In advanced CKD stages, eGFR overestimation may result in delayed referral to a nephrologist (recommended at eGFR < 30mL/min/1.73 m²), nutrition counseling, renal replacement therapy education, timely referral for renal replacement therapy access placement, and transplant evaluation (can be listed when eGFR < 20 mL/min/1.73 m²).^16,24,25 

In the Clinical Vignette, it is clear from the information presented that Mr. C’s concerns are well-founded. Table 1 presents the impact on eGFR caused by the race coefficient using the MDRD and CKD-EPI equations. In many VA systems, this overestimation would prevent him from being referred for a kidney transplant at this visit, thereby perpetuating racial health disparities in kidney transplantation. 

Concerns About Removal of Race From eGFR Calculations

Opponents of removing the race coefficient assert that a lower eGFR will preclude some patients from qualifying for medications such as metformin and certain anticoagulants, or that it may result in subtherapeutic dosing of drugs such as antibiotics and chemotherapeutic agents.²⁶ These recommendations are in place for patient safety, so conversely maintaining the race coefficient and overestimating eGFR will expose some patients to medication toxicity. Another fear is that lower eGFRs will have the unintended consequence of limiting the kidney donor pool. However, this can be prevented by following current guidelines to use mGFR in settings where accurate GFR is imperative.¹⁶ Additionally, some nephrologists have expressed concern that diagnosing more patients with advanced stages of CKD will result in inappropriately early initiation of dialysis. Again, this risk can be mitigated by ensuring that nephrologists consider multiple clinical factors and data points, not simply eGFR when deciding to initiate dialysis. Also, an increase in referrals to nephrology may occur when the race coefficient is removed and increased wait times at some VA medical centers could be a concern. An increase in appropriate referrals would show that removing the race coefficient was having its intended effect—more veterans with advanced CKD being seen by nephrologists.

When considering the lack of biological plausibility, inaccuracy, and the clinical harms associated with the use of the race coefficient in eGFR calculations, the benefits of removing the race coefficient from eGFR calculations within the VA far outweigh any potential risks.  

A Call for Equity

The National Conversation on Race and eGFR

To advance health equity, members of the medical community have advocated for the removal of the race coefficient from eGFR calculations for years. Beth Israel Deaconess Medical Center was the first establishment to institute this change in 2017. Since then, many health systems across the country that are affiliated with Veterans Health Administration (VHA) medical centers have removed the race coefficient from eGFR equations (Table 2). Many other hospital systems are contemplating this change. 

In July 2020, the NKF and the ASN established a joint task force dedicated to reassessing the inclusion of race in eGFR calculations. This task force acknowledges that race is a social, not biological, construct.¹² The NKF/ASN task force is now in the second of its 3-phase process. In March 2021, prior to publication of their phase 1 findings, they announced “(1) race modifiers should not be included in equations to estimate kidney function; and (2) current race-based equations should be replaced by a suitable approach that is accurate, inclusive, and standardized in every laboratory in the United States. Any such approach must not differentially introduce bias, inaccuracy, or inequalities.”²⁷

Health Equity in the VHA

In January 2021, President Biden issued an executive order to advance racial equity and support underserved communities through the federal government and its agencies. The VHA is the largest integrated health care system in the United States serving 9 million veterans and is one of the largest federal agencies. As VA clinicians, it is our responsibility to examine the evidence, consider national guidance, and ensure health equity for veterans by practicing unbiased medicine. The evidence and the interim guidance from the NKF-ASN task force clearly indicate that the race coefficient should no longer be used.²⁷ It is imperative that we make these changes immediately knowing that the use of race in kidney function calculators is harming Black veterans. Similar to finding evidence of harm in a treatment group in a clinical trial, it is unethical to wait. Removal of the race coefficient in eGFR calculations will allow VHA clinicians to provide timely and high-quality care to our patients as well as establish the VHA as a national leader in health equity.

VISN 12 Leads the Way

On May 11, 2021, the VA Great Lakes Health Care System, Veterans Integrated Service Network (VISN) 12, leaders responded to this author group’s call to advance health equity and voted to remove the race coefficient from eGFR calculations. Other VISNs should follow, and the VHA should continue to work with national leaders and experts to establish and implement superior tools to ensure the highest quality of kidney health care for all veterans.  

Acknowledgments
The authors would like to thank the medical students across the nation who have been leading the charge on this important issue. The authors are also thankful for the collaboration and support of all members of the Jesse Brown for Black Lives (JB4BL) Task Force. 

The American Medical Association publicly acknowledged in November 2020 that race is a social construct without biological basis, with many other leading medical organizations following suit.¹ Historically, biased science based on observed human physical differences has incorrectly asserted a racial biological hierarchy.^2,3 Today, leading health care organizations recognize that the effects of racist policies in housing, education, employment, and the criminal justice system contribute to health disparities and have a disproportionately negative impact on Black, Indigenous, and People of Color.^3,4 

Racial classification systems are fraught with bias. Trying to classify a complex and nuanced identity such as race into discrete categories does not capture the extensive heterogeneity at the individual level or within the increasingly diverse, multiracial population.⁵ Racial and ethnic categories used in collecting census data and research, as defined by the US Office of Management and Budget, have evolved over time.⁶ These changes in classification are a reflection of changes in the political environment, not changes in scientific knowledge of race and ethnicity.⁶

The Use of Race in Research and Practice

In the United States, racial minorities bear a disproportionate burden of morbidity and mortality across all major disease categories.³ These disparities cannot be explained by genetics.⁴ The Human Genome Project in 2003 confirmed that racial categories have no biologic or genetic basis and that there is more intraracial than interracial genetic variation.³ Nevertheless, significant misapplication of race in medical research and clinical practice remains. Instead of attributing observed differences in health outcomes between racial groups to innate physiological differences between the groups, clinicians and researchers must carefully consider the impact of racism.⁷ This includes considering the complex interactions between socioeconomic, political, and environmental factors, and how they affect health.³

While race is not biologic, the effects of racism can have biologic effects, and advocates appropriately cite the need to collect race as an important category in epidemiological analysis. When race and ethnicity are used as a study variable, bioethicists Kaplan and Bennett recommend that researchers: (1) account for limitations due to imprecision of racial categories; (2) avoid attributing causality when there is an association between race/ethnicity and a health outcome; and (3) refrain from exacerbating racial disparities.⁶

At the bedside, race has become embedded in clinical, seemingly objective, decision-making tools used across medical specialties.⁸ These algorithms often use observational outcomes data and draw conclusions by explicitly or implicitly assuming biological differences among races. By crudely adjusting for race without identifying the root cause for observed racial differences, these tools can further magnify health inequities.⁸ With the increased recognition that race cannot be used as a proxy for genetic ancestry, and that racial and ethnic categories are complex sociopolitical constructs that have changed over time, the practice of race-based medicine is increasingly being criticized.⁸

This article presents a case for the removal of the race coefficient from estimated glomerular filtration rate (eGFR) calculations that exacerbate disparities in kidney health by overestimating kidney function in Black patients.⁸ The main justification for using the race coefficient stems from the disproven assumption that Black people have more muscle mass compared with non-Black people.⁹  The questioning of this racist assertion has led to a national movement to reevaluate the use of race in eGFR calculations.

Racial Disparities in Kidney Disease

According to epidemiological data published by the National Kidney Foundation (NKF) and American Society of Nephrology (ASN), 37 million people in the United States have chronic kidney disease (CKD).¹⁰ Black Americans make up 13% of the US population yet they account for more than 30% of patients with end-stage kidney disease (ESKD) and 35% of those on dialysis.^10,11 There is a 3 times greater risk for progression from early-stage CKD to ESKD in Black Americans when compared to the risk for White Americans.¹¹ Black patients are younger at the time of CKD diagnosis and, once diagnosed, experience a faster progression to ESKD.¹² These disparities are partially attributable to delays in diagnosis, preventative measures, and referrals to nephrology care.¹²  

In a VA medical center study, although Black patients were referred to nephrology care at higher rates than White patients, Black patients had faster progression to CKD stage 5.¹³ An earlier study showed that, at any given eGFR, Black patients have higher levels of albuminuria compared to White patients.¹⁴ While the reasons behind this observation are likely complex and multifactorial, one hypothesis is that Black patients were already at a more advanced stage of kidney disease at the time of referral as a result of the overestimation of eGFR calculations related to the use of a race coefficient.

Additionally, numerous analyses have revealed that Black patients are less likely to be identified as transplant candidates, less likely to be referred for transplant evaluation and, once on the waiting list, wait longer than do White patients.^11,15

Estimated Glomerular Filtration Rate

It is imperative that clinicians have the most accurate measure of GFR to ensure timely diagnosis and appropriate management in patients with CKD. The gold standard for determining renal function requires measuring GFR using an ideal, exogenous, filtration marker such as iothalamate. However, this process is complex and time-consuming, rendering it infeasible in routine care. As a result, we usually estimate GFR using endogenous serum markers such as creatinine and cystatin C. Due to availability and cost, serum creatinine (SCr) is the most widely used marker for estimating kidney function. However, many pitfalls are inherent in its use, including the effects of tubular secretion, extrarenal clearance, and day-to-day variability in creatinine generation related to muscle mass, diet, and activity.¹⁶ The 2 most widely used estimation equations are the Modification of Diet in Renal Disease (MDRD) study equation and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation; both equations incorporate correction factors for age, sex, and race. 

The VA uses MDRD, which was derived and validated in a cohort of 1628 patients that included only 197 Black patients (12%), resulting in an eGFR for Black patients that is 21% higher than is the eGFR for non-Black patients with the same SCr value.⁹ In the VA electronic health record, the race coefficient is incorporated directly into eGFR laboratory calculations based on the race that the veteran self-identified during intake. Because the laboratory reports only a race-adjusted eGFR, there is a lack of transparency as many health care providers and patients are unaware that a race coefficient is used in eGFR calculations at the VA.  

Case for Removing Race Coefficient

When applied to cohorts outside the original study, both the MDRD and CKD-EPI equations have proved to be highly biased, imprecise, and inaccurate when compared to measured GFR (mGFR).^15,17 For any given eGFR, the possible mGFR may span 3 stages of CKD, underscoring the limitations of using such a crude estimate in clinical decision making.¹⁷ 

Current Kidney Estimation Pitfalls

A recent cohort study by Zelnick and colleagues that included 1658 self-identified Black adults showed less bias between mGFR and eGFR without the use of a race coefficient, and a shorter median time to transplant eligibility by 1.9 years.¹⁵ This study provides further evidence that these equations were derived from a biased observational data set that overestimates eGFR in Black patients living with CKD. This overestimation is particularly egregious for frail or malnourished patients with CKD and multiple comorbidities, with many potential harmful clinical consequences.

In addition, multiple international studies in African countries have demonstrated worse performance of eGFR calculations when using the race coefficient than without it. In the Democratic Republic of the Congo, eGFR was calculated for adults using MDRD with and without the race coefficient, as well as CKD-EPI with and without the race coefficient, and then compared to mGFR. Both the MDRD and the CKD-EPI equations overestimated GFR when using the race coefficient, and notably the equations without the race coefficient had better correlation to mGFR.¹⁸ Similar data were also found in studies from South Africa, the Ivory Coast, Brazil, and Europe.^19-22

Clinical Consequences of Race Coefficient Use

The use of a race coefficient in these estimation equations causes adverse clinical outcomes. In early stages of CKD, overestimation of eGFR using the race coefficient can cause an under-recognition of CKD, and can lead to delays in diagnosis and failure to implement measures to slow its progression, such as minimizing drug-related nephrotoxic injury and iatrogenic acute kidney injury. Consequently, a patient with an overestimated eGFR may suffer an accelerated progression to ESKD and premature mortality from cardiovascular disease.²³ 

In advanced CKD stages, eGFR overestimation may result in delayed referral to a nephrologist (recommended at eGFR < 30mL/min/1.73 m²), nutrition counseling, renal replacement therapy education, timely referral for renal replacement therapy access placement, and transplant evaluation (can be listed when eGFR < 20 mL/min/1.73 m²).^16,24,25 

In the Clinical Vignette, it is clear from the information presented that Mr. C’s concerns are well-founded. Table 1 presents the impact on eGFR caused by the race coefficient using the MDRD and CKD-EPI equations. In many VA systems, this overestimation would prevent him from being referred for a kidney transplant at this visit, thereby perpetuating racial health disparities in kidney transplantation. 

Concerns About Removal of Race From eGFR Calculations

Opponents of removing the race coefficient assert that a lower eGFR will preclude some patients from qualifying for medications such as metformin and certain anticoagulants, or that it may result in subtherapeutic dosing of drugs such as antibiotics and chemotherapeutic agents.²⁶ These recommendations are in place for patient safety, so conversely maintaining the race coefficient and overestimating eGFR will expose some patients to medication toxicity. Another fear is that lower eGFRs will have the unintended consequence of limiting the kidney donor pool. However, this can be prevented by following current guidelines to use mGFR in settings where accurate GFR is imperative.¹⁶ Additionally, some nephrologists have expressed concern that diagnosing more patients with advanced stages of CKD will result in inappropriately early initiation of dialysis. Again, this risk can be mitigated by ensuring that nephrologists consider multiple clinical factors and data points, not simply eGFR when deciding to initiate dialysis. Also, an increase in referrals to nephrology may occur when the race coefficient is removed and increased wait times at some VA medical centers could be a concern. An increase in appropriate referrals would show that removing the race coefficient was having its intended effect—more veterans with advanced CKD being seen by nephrologists.

When considering the lack of biological plausibility, inaccuracy, and the clinical harms associated with the use of the race coefficient in eGFR calculations, the benefits of removing the race coefficient from eGFR calculations within the VA far outweigh any potential risks.  

A Call for Equity

The National Conversation on Race and eGFR

To advance health equity, members of the medical community have advocated for the removal of the race coefficient from eGFR calculations for years. Beth Israel Deaconess Medical Center was the first establishment to institute this change in 2017. Since then, many health systems across the country that are affiliated with Veterans Health Administration (VHA) medical centers have removed the race coefficient from eGFR equations (Table 2). Many other hospital systems are contemplating this change. 

In July 2020, the NKF and the ASN established a joint task force dedicated to reassessing the inclusion of race in eGFR calculations. This task force acknowledges that race is a social, not biological, construct.¹² The NKF/ASN task force is now in the second of its 3-phase process. In March 2021, prior to publication of their phase 1 findings, they announced “(1) race modifiers should not be included in equations to estimate kidney function; and (2) current race-based equations should be replaced by a suitable approach that is accurate, inclusive, and standardized in every laboratory in the United States. Any such approach must not differentially introduce bias, inaccuracy, or inequalities.”²⁷

Health Equity in the VHA

In January 2021, President Biden issued an executive order to advance racial equity and support underserved communities through the federal government and its agencies. The VHA is the largest integrated health care system in the United States serving 9 million veterans and is one of the largest federal agencies. As VA clinicians, it is our responsibility to examine the evidence, consider national guidance, and ensure health equity for veterans by practicing unbiased medicine. The evidence and the interim guidance from the NKF-ASN task force clearly indicate that the race coefficient should no longer be used.²⁷ It is imperative that we make these changes immediately knowing that the use of race in kidney function calculators is harming Black veterans. Similar to finding evidence of harm in a treatment group in a clinical trial, it is unethical to wait. Removal of the race coefficient in eGFR calculations will allow VHA clinicians to provide timely and high-quality care to our patients as well as establish the VHA as a national leader in health equity.

VISN 12 Leads the Way

On May 11, 2021, the VA Great Lakes Health Care System, Veterans Integrated Service Network (VISN) 12, leaders responded to this author group’s call to advance health equity and voted to remove the race coefficient from eGFR calculations. Other VISNs should follow, and the VHA should continue to work with national leaders and experts to establish and implement superior tools to ensure the highest quality of kidney health care for all veterans.  

Acknowledgments
The authors would like to thank the medical students across the nation who have been leading the charge on this important issue. The authors are also thankful for the collaboration and support of all members of the Jesse Brown for Black Lives (JB4BL) Task Force. 

The American Medical Association publicly acknowledged in November 2020 that race is a social construct without biological basis, with many other leading medical organizations following suit.¹ Historically, biased science based on observed human physical differences has incorrectly asserted a racial biological hierarchy.^2,3 Today, leading health care organizations recognize that the effects of racist policies in housing, education, employment, and the criminal justice system contribute to health disparities and have a disproportionately negative impact on Black, Indigenous, and People of Color.^3,4 

Racial classification systems are fraught with bias. Trying to classify a complex and nuanced identity such as race into discrete categories does not capture the extensive heterogeneity at the individual level or within the increasingly diverse, multiracial population.⁵ Racial and ethnic categories used in collecting census data and research, as defined by the US Office of Management and Budget, have evolved over time.⁶ These changes in classification are a reflection of changes in the political environment, not changes in scientific knowledge of race and ethnicity.⁶

The Use of Race in Research and Practice

In the United States, racial minorities bear a disproportionate burden of morbidity and mortality across all major disease categories.³ These disparities cannot be explained by genetics.⁴ The Human Genome Project in 2003 confirmed that racial categories have no biologic or genetic basis and that there is more intraracial than interracial genetic variation.³ Nevertheless, significant misapplication of race in medical research and clinical practice remains. Instead of attributing observed differences in health outcomes between racial groups to innate physiological differences between the groups, clinicians and researchers must carefully consider the impact of racism.⁷ This includes considering the complex interactions between socioeconomic, political, and environmental factors, and how they affect health.³

While race is not biologic, the effects of racism can have biologic effects, and advocates appropriately cite the need to collect race as an important category in epidemiological analysis. When race and ethnicity are used as a study variable, bioethicists Kaplan and Bennett recommend that researchers: (1) account for limitations due to imprecision of racial categories; (2) avoid attributing causality when there is an association between race/ethnicity and a health outcome; and (3) refrain from exacerbating racial disparities.⁶

At the bedside, race has become embedded in clinical, seemingly objective, decision-making tools used across medical specialties.⁸ These algorithms often use observational outcomes data and draw conclusions by explicitly or implicitly assuming biological differences among races. By crudely adjusting for race without identifying the root cause for observed racial differences, these tools can further magnify health inequities.⁸ With the increased recognition that race cannot be used as a proxy for genetic ancestry, and that racial and ethnic categories are complex sociopolitical constructs that have changed over time, the practice of race-based medicine is increasingly being criticized.⁸

This article presents a case for the removal of the race coefficient from estimated glomerular filtration rate (eGFR) calculations that exacerbate disparities in kidney health by overestimating kidney function in Black patients.⁸ The main justification for using the race coefficient stems from the disproven assumption that Black people have more muscle mass compared with non-Black people.⁹  The questioning of this racist assertion has led to a national movement to reevaluate the use of race in eGFR calculations.

Racial Disparities in Kidney Disease

According to epidemiological data published by the National Kidney Foundation (NKF) and American Society of Nephrology (ASN), 37 million people in the United States have chronic kidney disease (CKD).¹⁰ Black Americans make up 13% of the US population yet they account for more than 30% of patients with end-stage kidney disease (ESKD) and 35% of those on dialysis.^10,11 There is a 3 times greater risk for progression from early-stage CKD to ESKD in Black Americans when compared to the risk for White Americans.¹¹ Black patients are younger at the time of CKD diagnosis and, once diagnosed, experience a faster progression to ESKD.¹² These disparities are partially attributable to delays in diagnosis, preventative measures, and referrals to nephrology care.¹²  

In a VA medical center study, although Black patients were referred to nephrology care at higher rates than White patients, Black patients had faster progression to CKD stage 5.¹³ An earlier study showed that, at any given eGFR, Black patients have higher levels of albuminuria compared to White patients.¹⁴ While the reasons behind this observation are likely complex and multifactorial, one hypothesis is that Black patients were already at a more advanced stage of kidney disease at the time of referral as a result of the overestimation of eGFR calculations related to the use of a race coefficient.

Additionally, numerous analyses have revealed that Black patients are less likely to be identified as transplant candidates, less likely to be referred for transplant evaluation and, once on the waiting list, wait longer than do White patients.^11,15

Estimated Glomerular Filtration Rate

It is imperative that clinicians have the most accurate measure of GFR to ensure timely diagnosis and appropriate management in patients with CKD. The gold standard for determining renal function requires measuring GFR using an ideal, exogenous, filtration marker such as iothalamate. However, this process is complex and time-consuming, rendering it infeasible in routine care. As a result, we usually estimate GFR using endogenous serum markers such as creatinine and cystatin C. Due to availability and cost, serum creatinine (SCr) is the most widely used marker for estimating kidney function. However, many pitfalls are inherent in its use, including the effects of tubular secretion, extrarenal clearance, and day-to-day variability in creatinine generation related to muscle mass, diet, and activity.¹⁶ The 2 most widely used estimation equations are the Modification of Diet in Renal Disease (MDRD) study equation and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation; both equations incorporate correction factors for age, sex, and race. 

The VA uses MDRD, which was derived and validated in a cohort of 1628 patients that included only 197 Black patients (12%), resulting in an eGFR for Black patients that is 21% higher than is the eGFR for non-Black patients with the same SCr value.⁹ In the VA electronic health record, the race coefficient is incorporated directly into eGFR laboratory calculations based on the race that the veteran self-identified during intake. Because the laboratory reports only a race-adjusted eGFR, there is a lack of transparency as many health care providers and patients are unaware that a race coefficient is used in eGFR calculations at the VA.  

Case for Removing Race Coefficient

When applied to cohorts outside the original study, both the MDRD and CKD-EPI equations have proved to be highly biased, imprecise, and inaccurate when compared to measured GFR (mGFR).^15,17 For any given eGFR, the possible mGFR may span 3 stages of CKD, underscoring the limitations of using such a crude estimate in clinical decision making.¹⁷ 

Current Kidney Estimation Pitfalls

A recent cohort study by Zelnick and colleagues that included 1658 self-identified Black adults showed less bias between mGFR and eGFR without the use of a race coefficient, and a shorter median time to transplant eligibility by 1.9 years.¹⁵ This study provides further evidence that these equations were derived from a biased observational data set that overestimates eGFR in Black patients living with CKD. This overestimation is particularly egregious for frail or malnourished patients with CKD and multiple comorbidities, with many potential harmful clinical consequences.

In addition, multiple international studies in African countries have demonstrated worse performance of eGFR calculations when using the race coefficient than without it. In the Democratic Republic of the Congo, eGFR was calculated for adults using MDRD with and without the race coefficient, as well as CKD-EPI with and without the race coefficient, and then compared to mGFR. Both the MDRD and the CKD-EPI equations overestimated GFR when using the race coefficient, and notably the equations without the race coefficient had better correlation to mGFR.¹⁸ Similar data were also found in studies from South Africa, the Ivory Coast, Brazil, and Europe.^19-22

Clinical Consequences of Race Coefficient Use

The use of a race coefficient in these estimation equations causes adverse clinical outcomes. In early stages of CKD, overestimation of eGFR using the race coefficient can cause an under-recognition of CKD, and can lead to delays in diagnosis and failure to implement measures to slow its progression, such as minimizing drug-related nephrotoxic injury and iatrogenic acute kidney injury. Consequently, a patient with an overestimated eGFR may suffer an accelerated progression to ESKD and premature mortality from cardiovascular disease.²³ 

In advanced CKD stages, eGFR overestimation may result in delayed referral to a nephrologist (recommended at eGFR < 30mL/min/1.73 m²), nutrition counseling, renal replacement therapy education, timely referral for renal replacement therapy access placement, and transplant evaluation (can be listed when eGFR < 20 mL/min/1.73 m²).^16,24,25 

In the Clinical Vignette, it is clear from the information presented that Mr. C’s concerns are well-founded. Table 1 presents the impact on eGFR caused by the race coefficient using the MDRD and CKD-EPI equations. In many VA systems, this overestimation would prevent him from being referred for a kidney transplant at this visit, thereby perpetuating racial health disparities in kidney transplantation. 

Concerns About Removal of Race From eGFR Calculations

Opponents of removing the race coefficient assert that a lower eGFR will preclude some patients from qualifying for medications such as metformin and certain anticoagulants, or that it may result in subtherapeutic dosing of drugs such as antibiotics and chemotherapeutic agents.²⁶ These recommendations are in place for patient safety, so conversely maintaining the race coefficient and overestimating eGFR will expose some patients to medication toxicity. Another fear is that lower eGFRs will have the unintended consequence of limiting the kidney donor pool. However, this can be prevented by following current guidelines to use mGFR in settings where accurate GFR is imperative.¹⁶ Additionally, some nephrologists have expressed concern that diagnosing more patients with advanced stages of CKD will result in inappropriately early initiation of dialysis. Again, this risk can be mitigated by ensuring that nephrologists consider multiple clinical factors and data points, not simply eGFR when deciding to initiate dialysis. Also, an increase in referrals to nephrology may occur when the race coefficient is removed and increased wait times at some VA medical centers could be a concern. An increase in appropriate referrals would show that removing the race coefficient was having its intended effect—more veterans with advanced CKD being seen by nephrologists.

When considering the lack of biological plausibility, inaccuracy, and the clinical harms associated with the use of the race coefficient in eGFR calculations, the benefits of removing the race coefficient from eGFR calculations within the VA far outweigh any potential risks.  

A Call for Equity

The National Conversation on Race and eGFR

To advance health equity, members of the medical community have advocated for the removal of the race coefficient from eGFR calculations for years. Beth Israel Deaconess Medical Center was the first establishment to institute this change in 2017. Since then, many health systems across the country that are affiliated with Veterans Health Administration (VHA) medical centers have removed the race coefficient from eGFR equations (Table 2). Many other hospital systems are contemplating this change. 

In July 2020, the NKF and the ASN established a joint task force dedicated to reassessing the inclusion of race in eGFR calculations. This task force acknowledges that race is a social, not biological, construct.¹² The NKF/ASN task force is now in the second of its 3-phase process. In March 2021, prior to publication of their phase 1 findings, they announced “(1) race modifiers should not be included in equations to estimate kidney function; and (2) current race-based equations should be replaced by a suitable approach that is accurate, inclusive, and standardized in every laboratory in the United States. Any such approach must not differentially introduce bias, inaccuracy, or inequalities.”²⁷

Health Equity in the VHA

In January 2021, President Biden issued an executive order to advance racial equity and support underserved communities through the federal government and its agencies. The VHA is the largest integrated health care system in the United States serving 9 million veterans and is one of the largest federal agencies. As VA clinicians, it is our responsibility to examine the evidence, consider national guidance, and ensure health equity for veterans by practicing unbiased medicine. The evidence and the interim guidance from the NKF-ASN task force clearly indicate that the race coefficient should no longer be used.²⁷ It is imperative that we make these changes immediately knowing that the use of race in kidney function calculators is harming Black veterans. Similar to finding evidence of harm in a treatment group in a clinical trial, it is unethical to wait. Removal of the race coefficient in eGFR calculations will allow VHA clinicians to provide timely and high-quality care to our patients as well as establish the VHA as a national leader in health equity.

VISN 12 Leads the Way

On May 11, 2021, the VA Great Lakes Health Care System, Veterans Integrated Service Network (VISN) 12, leaders responded to this author group’s call to advance health equity and voted to remove the race coefficient from eGFR calculations. Other VISNs should follow, and the VHA should continue to work with national leaders and experts to establish and implement superior tools to ensure the highest quality of kidney health care for all veterans.  

Acknowledgments
The authors would like to thank the medical students across the nation who have been leading the charge on this important issue. The authors are also thankful for the collaboration and support of all members of the Jesse Brown for Black Lives (JB4BL) Task Force. 

From the Department of Internal Medicine, Mount Sinai Health System, Icahn School of Medicine at Mount Sinai, New York, NY (Dr. Gandhi), and the School of Medicine, Seth Gordhandas Sunderdas Medical College, and King Edward Memorial Hospital, Mumbai, India (Drs. Gandhi and Tiwari).

Objective: Calculation of HEART score to (1) stratify patients as low-risk, intermediate-risk, high-risk, and to predict the short-term incidence of major adverse cardiovascular events (MACE), and (2) demonstrate feasibility of HEART score in our local settings.

Design: A prospective cohort study of patients with a chief complaint of chest pain concerning for acute coronary syndrome.

Setting: Participants were recruited from the emergency department (ED) of King Edward Memorial Hospital, a tertiary care academic medical center and a resource-limited setting in Mumbai, India.

Participants: We evaluated 141 patients aged 18 years and older presenting to the ED and stratified them using the HEART score. To assess patients’ progress, a follow-up phone call was made within 6 weeks after presentation to the ED.

Measurements: The primary outcomes were a risk stratification, 6-week occurrence of MACE, and performance of unscheduled revascularization or stress testing. The secondary outcomes were discharge or death.

Results: The 141 participants were stratified into low-risk, intermediate-risk, and high-risk groups: 67 (47.52%), 44 (31.21%), and 30 (21.28%), respectively. The 6-week incidence of MACE in each category was 1.49%, 18.18%, and 90%, respectively. An acute myocardial infarction was diagnosed in 24 patients (17.02%), 15 patients (10.64%) underwent percutaneous coronary intervention (PCI), and 4 patients (2.84%) underwent coronary artery bypass graft (CABG). Overall, 98.5% of low-risk patients and 93.33% of high-risk patients had an uneventful recovery following discharge; therefore, extrapolation based on results demonstrated reduced health care utilization. All the survey respondents found the HEART score to be feasible. The patient characteristics and risk profile of the patients with and without MACE demonstrated that: patients with MACE were older and had a higher proportion of males, hypertension, type 2 diabetes mellitus, smoking, hypercholesterolemia, prior history of PCI/CABG, and history of stroke.

Conclusion: The HEART score seems to be a useful tool for risk stratification and a reliable predictor of outcomes in chest pain patients and can therefore be used for triage.

Keywords: chest pain; emergency department; HEART score; acute coronary syndrome; major adverse cardiac events; myocardial infarction; revascularization.

Cardiovascular diseases (CVDs), especially coronary heart disease (CHD), have epidemic proportions worldwide. Globally, in 2012, CVD led to 17.5 million deaths,^1,2 with more than 75% of them occurring in developing countries. In contrast to developed countries, where mortality from CHD is rapidly declining, it is increasing in developing countries.^1,3 Current estimates from epidemiologic studies from various parts of India indicate the prevalence of CHD in India to be between 7% and 13% in urban populations and 2% and 7% in rural populations.⁴

Premature mortality in terms of years of life lost because of CVD in India increased by 59% over a 20-year span, from 23.2 million in 1990 to 37 million in 2010.⁵ Studies conducted in Mumbai (Mumbai Cohort Study) reported very high CVD mortality rates, approaching 500 per 100 000 for men and 250 per 100 000 for women.^6,7 However, to the best of our knowledge, in the Indian population, there are minimal data on utilization of a triage score, such as the HEART score, in chest pain patients in the emergency department (ED) in a resource-limited setting.

The most common reason for admitting patients to the ED is chest pain.⁸ There are various cardiac and noncardiac etiologies of chest pain presentation. Acute coronary syndrome (ACS) needs to be ruled out first in every patient presenting with chest pain. However, 80% of patients with ACS have no clear diagnostic features on presentation.⁹ The timely diagnosis and treatment of patients with ACS improves their prognosis. Therefore, clinicians tend to start each patient on ACS treatment to reduce the risk, which often leads to increased costs due to unnecessary, time-consuming diagnostic procedures that may place burdens on both the health care system and the patient.¹⁰

Several risk-stratifying tools have been developed in the last few years. Both the GRACE and TIMI risk scores have been designed for risk stratification of patients with proven ACS and not for the chest pain population at the ED.¹¹ Some of these tools are applicable to patients with all types of chest pain presenting to the ED, such as the Manchester Triage System. Other, more selective systems are devoted to the risk stratification of suspected ACS in the ED. One is the HEART score.¹²

The first study on the HEART score—an acronym that stands for History, Electrocardiogram, Age, Risk factors, and Troponin—was done by Backus et al, who proved that the HEART score is an easy, quick, and reliable predictor of outcomes in chest pain patients.¹⁰ The HEART score predicts the short-term incidence of major adverse cardiac events (MACE), which allows clinicians to stratify patients as low-risk, intermediate-risk, and high-risk and to guide their clinical decision-making accordingly. It was developed to provide clinicians with a simple, reliable predictor of cardiac risk on the basis of the lowest score of 0 (very low-risk) up to a score of 10 (very high-risk).

We studied the clinical performance of the HEART score in patients with chest pain, focusing on the efficacy and safety of rapidly identifying patients at risk of MACE. We aimed to determine (1) whether the HEART score is a reliable predictor of outcomes of chest pain patients presenting to the ED; (2) whether the score is feasible in our local settings; and (3) whether it describes the risk profile of patients with and without MACE.

Methods

Setting

Participants were recruited from the ED of King Edward Memorial Hospital, a municipal teaching hospital in Mumbai. The study institute is a tertiary care academic medical center located in Parel, Mumbai, Maharashtra, and is a resource-limited setting serving urban, suburban, and rural populations. Participants requiring urgent attention are first seen by a casualty officer and then referred to the emergency ward. Here, the physician on duty evaluates them and decides on admission to the various wards, like the general ward, medical intensive care unit (ICU), coronary care unit (CCU), etc. The specialist’s opinion may also be obtained before admission. Critically ill patients are initially admitted to the emergency ward and stabilized before being shifted to other areas of the hospital.

Participants

Patients aged 18 years and older presenting with symptoms of acute chest pain or suspected ACS were stratified by priority using the chest pain scoring system—the HEART score. Only patients presenting to the ED were eligible for the study. Informed consent from the patient or next of kin was mandatory for participation in the study.

Patients were determined ineligible for the following reasons: a clear cause for chest pain other than ACS (eg, trauma, diagnosed aortic dissection), persisting or recurrent chest pain caused by rheumatic diseases or cancer (a terminal illness), pregnancy, unable or unwilling to provide informed consent, or incomplete data.

Study design

We conducted a prospective observational study of patients arriving at the tertiary care hospital with a chief complaint of “chest pain” concerning for ACS. All participants provided witnessed written informed consent. Patients were screened over approximately a 3-month period, from July 2019 to October 2019, after acquiring approval from the Institutional Ethics Committee. Any patient who was admitted to the ED due to chest pain, prehospital referrals based on a physician’s suspicions of a heart condition, and previous medical treatment due to ischemic heart disease (IHD) was eligible. All patients were stratified by priority in our ED using the chest pain scoring system—the HEART score—and were followed up by phone within 6 weeks after presenting to the ED, to assess their progress.

We conducted our study to determine the importance of calculating the HEART score in each patient, which will help to correctly place them into low-, intermediate-, and high-risk groups for clinically important, irreversible adverse cardiac events and guide the clinical decision-making. Patients with low risk will avoid costly tests and hospital admissions, thus decreasing the cost of treatment and ensuring timely discharge from the ED. Patients with high risk will be treated immediately, to possibly prevent a life-threatening, ACS-related incident. Thus, the HEART score will serve as a quick and reliable predictor of outcomes in chest pain patients and help clinicians to make accurate diagnostic and therapeutic choices in uncertain situations.

HEART score

The total number of points for History, Electrocardiogram (ECG), Age, Risk factors, and Troponin was noted as the HEART score (Table 1).

For this study, the patient’s history and ECGs were interpreted by internal medicine attending physicians in the ED. The ECG taken in the emergency room was reviewed and classified, and a copy of the admission ECG was added to the file. The recommendation for patients with a HEART score in a particular range was evaluated. Notably, those with a score of 3 or lower led to a recommendation of reassurance and early discharge. Those with a HEART score in the intermediate range (4-6) were admitted to the hospital for further clinical observation and testing, whereas a high HEART score (7-10) led to admission for intensive monitoring and early intervention. In the analysis of HEART score data, we only used those patients having records for all 5 parameters, excluding patients without an ECG or troponin test.

Results

Myocardial infarction (MI) was defined based on Universal Definition of Myocardial Infarction.¹³ Coronary revascularization was defined as angioplasty with or without stent placement or coronary artery bypass surgery.¹⁴ Percutaneous coronary intervention (PCI) was defined as any therapeutic catheter intervention in the coronary arteries. Coronary artery bypass graft (CABG) surgery was defined as any cardiac surgery in which coronary arteries were operated on.

The primary outcomes in this study were the (1) risk stratification of chest pain patients into low-risk, intermediate-risk, and high-risk categories; (2) incidence of a MACE within 6 weeks of initial presentation. MACE consists of acute myocardial infarction (AMI), PCI, CABG, coronary angiography revealing procedurally correctable stenosis managed conservatively, and death due to any cause.

Our secondary outcomes were discharge or death due to any cause within 6 weeks after presentation.

Follow-up

Within 6 weeks after presentation to the ED, a follow-up phone call was placed to assess the patient’s progress. The follow-up focused on the endpoint of MACE, comprising all-cause death, MI, and revascularization. No patient was lost to follow-up.

Statistical analysis

We aimed to find a difference in the 6-week MACE between low-, intermediate-, and high-risk categories of the HEART score. The prevalence of CHD in India is 10%,⁴ and assuming an α of 0.05, we needed a sample of 141 patients from the ED patient population. Continuous variables were presented by mean (SD), and categorical variables as percentages. We used t test and the Mann-Whitney U test for comparison of means for continuous variables, χ² for categorical variables, and Fisher’s exact test for comparison of the categorical variables. Results with P < .05 were considered statistically significant.

We evaluated 141 patients presenting to the ED with chest pain concerning for ACS during the study period, from July 2019 to October 2019. Patients were 57.54 (13.13) years of age. The male to female distribution was 85 to 56. Other patient characteristics are shown in Table 2.

Primary outcomes

The risk stratification of the HEART score in chest pain patients and the incidence of 6-week MACE are outlined in Table 3 and Table 4, respectively.

The distribution of the HEART score’s 5 elements in the groups with or without MACE endpoints is shown in Table 5. Notice the significant differences between the groups. A follow-up phone call was made within 6 weeks after the presentation to the ED to assess the patient’s progress. The 6-week follow-up call data are included in Table 6.

Of 141 patients, 36 patients (25.53%) were diagnosed with MACE within 6 weeks of presentation. An AMI was diagnosed in 24 patients (17.02%). Coronary angiography was performed in 31 of 141 patients (21.99%), 15 patients (10.64%) underwent PCI, and 4 patients (2.84%) underwent CABG. The rest of the patients were treated with medications only.

Myocardial infarction—An AMI was diagnosed in 24 of the 141 patients (17.02%). Twenty-one of those already had positive markers on admission (apparently, these AMI had started before their arrival to the emergency room). One AMI occurred 2 days after admission in a 66-year-old male, and another occurred 10 days after discharge. A further AMI occurred 2 weeks after discharge. All 3 patients belonged to the intermediate-risk group.

Revascularization—Coronary angiography was performed in 31 of 141 patients (21.99%). Revascularization was performed in 19 patients (13.48%), of which 15 were PCIs (10.64%) and 4 were CABGs (2.84%).

Mortality—One patient died from the study population. He was a 72-year-old male who died 14 days after admission. He had a HEART score of 8.

Among the 67 low-risk patients:

• MACE: Coronary angiography was performed in 1 patient (1.49%). Among the 67 patients in the low-risk category, there was no cases of AMI or deaths. The remaining 66 patients (98.51%) had an uneventful recovery following discharge.
• General practitioner (GP) visits/readmissions following discharge: Two of 67 patients (2.99%) had GP visits following discharge, of which 1 was uneventful. The other patient, a 64-year-old male, was readmitted due to a recurrent history of chest pain and underwent coronary angiography.

Among the 44 intermediate-risk patients:

• MACE: Of the 7 of 44 patients (15.91%) who had coronary angiography, 3 patients (6.82%) had AMI, of which 1 occurred 2 days after admission in a 66-year-old male. Two patients had AMI following discharge. There were no deaths. Overall, 42 of 44 patients (95.55%) had an uneventful recovery following discharge.
• GP visits/readmissions following discharge: Three of 44 patients (6.82%) had repeated visits following discharge. One was a GP visit that was uneventful. The remaining 2 patients were diagnosed with AMI and readmitted following discharge. One AMI occurred 10 days after discharge in a patient with a HEART score of 6; another occurred 2 weeks after discharge in a patient with a HEART score of 5.

Among the 30 high-risk patients:

• MACE: Twenty-three of 30 patients (76.67%) underwent coronary angiography. One patient died 5 days after discharge. The patient had a HEART score of 8. Most patients however, had an uneventful recovery following discharge (28, 93.33%).
• GP visits/readmissions following discharge: Five of 30 patients (16.67%) had repeated visits following discharge. Two were uneventful. Two patients had a history of recurrent chest pain that resolved on Sorbitrate. One patient was readmitted 2 weeks following discharge due to a complication: a left ventricular clot was found. The patient had a HEART score of 10.

Secondary outcome—Overall, 140 of 141 patients were discharged. One patient died: a 72-year-old male with a HEART score of 8.

Feasibility—To determine the ease and feasibility of performing a HEART score in chest pain patients presenting to the ED, a survey was distributed to the internal medicine physicians in the ED. In the survey, the Likert scale was used to rate the ease of utilizing the HEART score and whether the physicians found it feasible to use it for risk stratification of their chest pain patients. A total of 12 of 15 respondents (80%) found it “easy” to use. Of the remaining 3 respondents, 2 (13.33%) rated the HEART score “very easy” to use, while 1 (6.66%) considered it “difficult” to work with. None of the respondents said that it was not feasible to perform a HEART score in the ED.

Risk factors for reaching an endpoint:

We compared risk profiles between the patient groups with and without an endpoint. The group of patients with MACE were older and had a higher proportion of males than the group of patients without MACE. Moreover, they also had a higher prevalence of hypertension, type 2 diabetes mellitus, smoking, hypercholesterolemia, prior history of PCI/CABG, and history of stroke. These also showed a significant association with MACE. Obesity was not included in our risk factors as we did not have data collected to measure body mass index. Results are represented in Table 7.

Discussion

Our study described a patient population presenting to an ED with chest pain as their primary complaint. The results of this prospective study confirm that the HEART score is an excellent system to triage chest pain patients. It provides the clinician with a reliable predictor of the outcome (MACE) after the patient’s arrival, based on available clinical data and in a resource-limited setting like ours.

Cardiovascular epidemiology studies indicate that this has become a significant public health problem in India.¹ Several risk scores for ACS have been published in European and American guidelines. However, in the Indian population, minimal data are available on utilization of such a triage score (HEART score) in chest pain patients in the ED in a resource-limited setting, to the best of our knowledge. In India, only 1 such study is reported,¹⁵ at the Sundaram Medical Foundation, a 170-bed community hospital in Chennai. In this study, 13 of 14 patients (92.86%) with a high HEART score had MACE, indicating a sensitivity of 92.86%; in the 44 patients with a low HEART score, 1 patient (2.22%) had MACE, indicating a specificity of 97.78%; and in the 28 patients with a moderate HEART score, 12 patients (42.86%) had MACE.  

In looking for the optimal risk-stratifying system for chest pain patients, we analyzed the HEART score. The first study on the HEART score was done Backus et al, proving that the HEART score is an easy, quick, and reliable predictor of outcomes in chest pain patients.¹⁰ The HEART score had good discriminatory power, too. The C statistic for the HEART score for ACS occurrence shows a value of 0.83. This signifies a good-to-excellent ability to stratify all-cause chest pain patients in the ED for their risk of MACE. The application of the HEART score to our patient population demonstrated that the majority of the patients belonged to the low-risk category, as reported in the first cohort study that applied the HEART score.⁸ The relationship between the HEART score category and occurrence of MACE within 6 weeks showed a curve with 3 different patterns, corresponding to the 3 risk categories defined in the literature.^11,12 The risk stratification of chest pain patients using the 3 categories (0-3, 4-6, 7-10) identified MACE with an incidence similar to the multicenter study of Backus et al,^10,11 but with a greater risk of MACE in the high-risk category (Figure).

Thus, our study confirmed the utility of the HEART score categories to predict the 6-week incidence of MACE. The sensitivity, specificity, and positive and negative predictive values for the established cut-off scores of 4 and 7 are shown in Table 8. The patients in the low-risk category, corresponding to a score < 4, had a very high negative predictive value, thus identifying a small-risk population. The patients in the high-risk category (score ≥ 7) showed a high positive predictive value, allowing the identification of a high-risk population, even in patients with more atypical presentations. Therefore, the HEART score may help clinicians to make accurate management choices by being a strong predictor of both event-free survival and potentially life-threatening cardiac events.^11,12

Our study tested the efficacy of the HEART score pathway in helping clinicians make smart diagnostic and therapeutic choices. It confirmed that the HEART score was accurate in predicting the short-term incidence of MACE, thus stratifying patients according to their risk severity. In our study, 67 of 141 patients (47.52%) had low-risk HEART scores, and we found the 6-week incidence of MACE to be 1.49%. We omitted the diagnostic and treatment evaluation for patients in the low-risk category and moved onto discharge. Overall, 66 of 67 patients (98.51%) in the low-risk category had an uneventful recovery following discharge. Only 2 of 67 these patients (2.99%) of patients had health care utilization following discharge. Therefore, extrapolation based on results demonstrates reduced health care utilization. Previous studies have shown similar results.^9,12,14,16 For instance, in a prospective study conducted in the Netherlands, low-risk patients representing 36.4% of the total were found to have a low MACE rate (1.7%).⁹ These low-risk patients were categorized as appropriate and safe for ED discharge without additional cardiac evaluation or inpatient admission.⁹ Another retrospective study in Portugal,¹² and one in Chennai, India,¹⁵ found the 6-week incidence of MACE to be 2.00% and 2.22%, respectively. The results of the first HEART Pathway Randomized Control Trial¹⁴ showed that the HEART score pathway reduces health care utilization (cardiac testing, hospitalization, and hospital length of stay). The study also showed that these gains occurred without any of the patients that were identified for early discharge, suffering from MACE at 30 days, or secondary increase in cardiac-related hospitalizations. Similar results were obtained by a randomized trial conducted in North Carolina¹⁷ that also demonstrated a reduction in objective cardiac testing, a doubling of the rate of early discharge from the ED, and a reduced length of stay by half a day. Another study using a modified HEART score also demonstrated that when low-risk patients are evaluated with cardiac testing, the likelihood for false positives is high.¹⁶ Hoffman et al also reported that patients randomized to coronary computed tomographic angiography (CCTA) received > 2.5 times more radiation exposure.¹⁶ Thus, low-risk patients may be safely discharged without the need for stress testing or CCTA.

In our study, 30 out of 141 patients (21.28%) had high-risk HEART scores (7-10), and we found the 6-week incidence of MACE to be 90%. Based on the pathway leading to inpatient admission and intensive treatment, 23 of 30 patients (76.67%) patients in our study underwent coronary angiography and further therapeutic treatment. In the high-risk category, 28 of 30 patients (93.33%) patients had an uneventful recovery following discharge. Previous studies have shown similar results. A retrospective study in Portugal showed that 76.9% of the high-risk patients had a 6-week incidence of MACE.¹² In a study in the Netherlands,⁹ 72.7% of high-risk patients had a 6-week incidence of MACE. Therefore, a HEART score of ≥ 7 in patients implies early aggressive treatment, including invasive strategies, when necessary, without noninvasive treatment preceding it.⁸

In terms of intermediate risk, in our study 44 of 141 patients (31.21%) patients had an intermediate-risk HEART score (4-6), and we found the 6-week incidence of MACE to be 18.18%. Based on the pathway, they were kept in the observation ward on admission. In our study, 7 of 44 patients (15.91%) underwent coronary angiography and further treatment; 42 of 44 patients (95.55%) had an uneventful recovery following discharge. In a prospective study in the Netherlands, 46.1% of patients with an intermediate score had a 6-week MACE incidence of 16.6%.¹⁰ Similarly, in another retrospective study in Portugal, the incidence of 6-week MACE in intermediate-risk patients (36.7%) was found to be 15.6%.¹² Therefore, in patients with a HEART score of 4-6 points, immediate discharge is not an option, as this figure indicates a risk of 18.18% for an adverse outcome. These patients should be admitted for clinical observation, treated as an ACS awaiting final diagnosis, and subjected to noninvasive investigations, such as repeated troponin. Using the HEART score as guidance in the treatment of chest pain patients will benefit patients on both sides of the spectrum.^11,12

Our sample presented a male predominance, a wide range of age, and a mean age similar to that of previous studies.^12.16 Some risk factors, we found, can increase significantly the odds of chest pain being of cardiovascular origin, such as male gender, smoking, hypertension, type 2 diabetes mellitus, and hypercholesterolemia. Other studies also reported similar findings.^8,12,16 Risk factors for premature CHD have been quantified in the case-control INTERHEART study.¹ In the INTERHEART study, 8 common risk factors explained > 90% of AMIs in South Asian and Indian patients. The risk factors include dyslipidemia, smoking or tobacco use, known hypertension, known diabetes, abdominal obesity, physical inactivity, low fruit and vegetable intake, and psychosocial stress.¹ Regarding the feasibility of treating physicians using the HEART score in the ED, we observed that, based on the Likert scale, 80% of survey respondents found it easy to use, and 100% found it feasible in the ED.

However, there were certain limitations to our study. It involved a single academic medical center and a small sample size, which limit generalizability of the findings. In addition, troponin levels are not calculated at our institution, as it is a resource-limited setting; therefore, we used a positive and negative as +2 and 0, respectively.

Conclusion

The HEART score provides the clinician with a quick and reliable predictor of outcome of patients with chest pain after arrival to the ED and can be used for triage. For patients with low HEART scores (0-3), short-term MACE can be excluded with greater than 98% certainty. In these patients, one may consider reserved treatment and discharge policies that may also reduce health care utilization. In patients with high HEART scores (7-10), the high risk of MACE (90%) may indicate early aggressive treatment, including invasive strategies, when necessary. Therefore, the HEART score may help clinicians make accurate management choices by being a strong predictor of both event-free survival and potentially life-threatening cardiac events. Age, gender, and cardiovascular risk factors may also be considered in the assessment of patients. This study confirmed the utility of the HEART score categories to predict the 6-week incidence of MACE.

Corresponding author: Smrati Bajpai Tiwari, MD, DNB, FAIMER, Department of Medicine, Seth Gordhandas Sunderdas Medical College and King Edward Memorial Hospital, Acharya Donde Marg, Parel, Mumbai 400 012, Maharashtra, India; [email protected].

Financial disclosures: None.

From the Department of Internal Medicine, Mount Sinai Health System, Icahn School of Medicine at Mount Sinai, New York, NY (Dr. Gandhi), and the School of Medicine, Seth Gordhandas Sunderdas Medical College, and King Edward Memorial Hospital, Mumbai, India (Drs. Gandhi and Tiwari).

Objective: Calculation of HEART score to (1) stratify patients as low-risk, intermediate-risk, high-risk, and to predict the short-term incidence of major adverse cardiovascular events (MACE), and (2) demonstrate feasibility of HEART score in our local settings.

Design: A prospective cohort study of patients with a chief complaint of chest pain concerning for acute coronary syndrome.

Setting: Participants were recruited from the emergency department (ED) of King Edward Memorial Hospital, a tertiary care academic medical center and a resource-limited setting in Mumbai, India.

Participants: We evaluated 141 patients aged 18 years and older presenting to the ED and stratified them using the HEART score. To assess patients’ progress, a follow-up phone call was made within 6 weeks after presentation to the ED.

Measurements: The primary outcomes were a risk stratification, 6-week occurrence of MACE, and performance of unscheduled revascularization or stress testing. The secondary outcomes were discharge or death.

Results: The 141 participants were stratified into low-risk, intermediate-risk, and high-risk groups: 67 (47.52%), 44 (31.21%), and 30 (21.28%), respectively. The 6-week incidence of MACE in each category was 1.49%, 18.18%, and 90%, respectively. An acute myocardial infarction was diagnosed in 24 patients (17.02%), 15 patients (10.64%) underwent percutaneous coronary intervention (PCI), and 4 patients (2.84%) underwent coronary artery bypass graft (CABG). Overall, 98.5% of low-risk patients and 93.33% of high-risk patients had an uneventful recovery following discharge; therefore, extrapolation based on results demonstrated reduced health care utilization. All the survey respondents found the HEART score to be feasible. The patient characteristics and risk profile of the patients with and without MACE demonstrated that: patients with MACE were older and had a higher proportion of males, hypertension, type 2 diabetes mellitus, smoking, hypercholesterolemia, prior history of PCI/CABG, and history of stroke.

Conclusion: The HEART score seems to be a useful tool for risk stratification and a reliable predictor of outcomes in chest pain patients and can therefore be used for triage.

Keywords: chest pain; emergency department; HEART score; acute coronary syndrome; major adverse cardiac events; myocardial infarction; revascularization.

Cardiovascular diseases (CVDs), especially coronary heart disease (CHD), have epidemic proportions worldwide. Globally, in 2012, CVD led to 17.5 million deaths,^1,2 with more than 75% of them occurring in developing countries. In contrast to developed countries, where mortality from CHD is rapidly declining, it is increasing in developing countries.^1,3 Current estimates from epidemiologic studies from various parts of India indicate the prevalence of CHD in India to be between 7% and 13% in urban populations and 2% and 7% in rural populations.⁴

Premature mortality in terms of years of life lost because of CVD in India increased by 59% over a 20-year span, from 23.2 million in 1990 to 37 million in 2010.⁵ Studies conducted in Mumbai (Mumbai Cohort Study) reported very high CVD mortality rates, approaching 500 per 100 000 for men and 250 per 100 000 for women.^6,7 However, to the best of our knowledge, in the Indian population, there are minimal data on utilization of a triage score, such as the HEART score, in chest pain patients in the emergency department (ED) in a resource-limited setting.

The most common reason for admitting patients to the ED is chest pain.⁸ There are various cardiac and noncardiac etiologies of chest pain presentation. Acute coronary syndrome (ACS) needs to be ruled out first in every patient presenting with chest pain. However, 80% of patients with ACS have no clear diagnostic features on presentation.⁹ The timely diagnosis and treatment of patients with ACS improves their prognosis. Therefore, clinicians tend to start each patient on ACS treatment to reduce the risk, which often leads to increased costs due to unnecessary, time-consuming diagnostic procedures that may place burdens on both the health care system and the patient.¹⁰

Several risk-stratifying tools have been developed in the last few years. Both the GRACE and TIMI risk scores have been designed for risk stratification of patients with proven ACS and not for the chest pain population at the ED.¹¹ Some of these tools are applicable to patients with all types of chest pain presenting to the ED, such as the Manchester Triage System. Other, more selective systems are devoted to the risk stratification of suspected ACS in the ED. One is the HEART score.¹²

The first study on the HEART score—an acronym that stands for History, Electrocardiogram, Age, Risk factors, and Troponin—was done by Backus et al, who proved that the HEART score is an easy, quick, and reliable predictor of outcomes in chest pain patients.¹⁰ The HEART score predicts the short-term incidence of major adverse cardiac events (MACE), which allows clinicians to stratify patients as low-risk, intermediate-risk, and high-risk and to guide their clinical decision-making accordingly. It was developed to provide clinicians with a simple, reliable predictor of cardiac risk on the basis of the lowest score of 0 (very low-risk) up to a score of 10 (very high-risk).

We studied the clinical performance of the HEART score in patients with chest pain, focusing on the efficacy and safety of rapidly identifying patients at risk of MACE. We aimed to determine (1) whether the HEART score is a reliable predictor of outcomes of chest pain patients presenting to the ED; (2) whether the score is feasible in our local settings; and (3) whether it describes the risk profile of patients with and without MACE.

Methods

Setting

Participants were recruited from the ED of King Edward Memorial Hospital, a municipal teaching hospital in Mumbai. The study institute is a tertiary care academic medical center located in Parel, Mumbai, Maharashtra, and is a resource-limited setting serving urban, suburban, and rural populations. Participants requiring urgent attention are first seen by a casualty officer and then referred to the emergency ward. Here, the physician on duty evaluates them and decides on admission to the various wards, like the general ward, medical intensive care unit (ICU), coronary care unit (CCU), etc. The specialist’s opinion may also be obtained before admission. Critically ill patients are initially admitted to the emergency ward and stabilized before being shifted to other areas of the hospital.

Participants

Patients aged 18 years and older presenting with symptoms of acute chest pain or suspected ACS were stratified by priority using the chest pain scoring system—the HEART score. Only patients presenting to the ED were eligible for the study. Informed consent from the patient or next of kin was mandatory for participation in the study.

Patients were determined ineligible for the following reasons: a clear cause for chest pain other than ACS (eg, trauma, diagnosed aortic dissection), persisting or recurrent chest pain caused by rheumatic diseases or cancer (a terminal illness), pregnancy, unable or unwilling to provide informed consent, or incomplete data.

Study design

We conducted a prospective observational study of patients arriving at the tertiary care hospital with a chief complaint of “chest pain” concerning for ACS. All participants provided witnessed written informed consent. Patients were screened over approximately a 3-month period, from July 2019 to October 2019, after acquiring approval from the Institutional Ethics Committee. Any patient who was admitted to the ED due to chest pain, prehospital referrals based on a physician’s suspicions of a heart condition, and previous medical treatment due to ischemic heart disease (IHD) was eligible. All patients were stratified by priority in our ED using the chest pain scoring system—the HEART score—and were followed up by phone within 6 weeks after presenting to the ED, to assess their progress.

We conducted our study to determine the importance of calculating the HEART score in each patient, which will help to correctly place them into low-, intermediate-, and high-risk groups for clinically important, irreversible adverse cardiac events and guide the clinical decision-making. Patients with low risk will avoid costly tests and hospital admissions, thus decreasing the cost of treatment and ensuring timely discharge from the ED. Patients with high risk will be treated immediately, to possibly prevent a life-threatening, ACS-related incident. Thus, the HEART score will serve as a quick and reliable predictor of outcomes in chest pain patients and help clinicians to make accurate diagnostic and therapeutic choices in uncertain situations.

HEART score

The total number of points for History, Electrocardiogram (ECG), Age, Risk factors, and Troponin was noted as the HEART score (Table 1).

For this study, the patient’s history and ECGs were interpreted by internal medicine attending physicians in the ED. The ECG taken in the emergency room was reviewed and classified, and a copy of the admission ECG was added to the file. The recommendation for patients with a HEART score in a particular range was evaluated. Notably, those with a score of 3 or lower led to a recommendation of reassurance and early discharge. Those with a HEART score in the intermediate range (4-6) were admitted to the hospital for further clinical observation and testing, whereas a high HEART score (7-10) led to admission for intensive monitoring and early intervention. In the analysis of HEART score data, we only used those patients having records for all 5 parameters, excluding patients without an ECG or troponin test.

Results

Myocardial infarction (MI) was defined based on Universal Definition of Myocardial Infarction.¹³ Coronary revascularization was defined as angioplasty with or without stent placement or coronary artery bypass surgery.¹⁴ Percutaneous coronary intervention (PCI) was defined as any therapeutic catheter intervention in the coronary arteries. Coronary artery bypass graft (CABG) surgery was defined as any cardiac surgery in which coronary arteries were operated on.

The primary outcomes in this study were the (1) risk stratification of chest pain patients into low-risk, intermediate-risk, and high-risk categories; (2) incidence of a MACE within 6 weeks of initial presentation. MACE consists of acute myocardial infarction (AMI), PCI, CABG, coronary angiography revealing procedurally correctable stenosis managed conservatively, and death due to any cause.

Our secondary outcomes were discharge or death due to any cause within 6 weeks after presentation.

Follow-up

Within 6 weeks after presentation to the ED, a follow-up phone call was placed to assess the patient’s progress. The follow-up focused on the endpoint of MACE, comprising all-cause death, MI, and revascularization. No patient was lost to follow-up.

Statistical analysis

We aimed to find a difference in the 6-week MACE between low-, intermediate-, and high-risk categories of the HEART score. The prevalence of CHD in India is 10%,⁴ and assuming an α of 0.05, we needed a sample of 141 patients from the ED patient population. Continuous variables were presented by mean (SD), and categorical variables as percentages. We used t test and the Mann-Whitney U test for comparison of means for continuous variables, χ² for categorical variables, and Fisher’s exact test for comparison of the categorical variables. Results with P < .05 were considered statistically significant.

We evaluated 141 patients presenting to the ED with chest pain concerning for ACS during the study period, from July 2019 to October 2019. Patients were 57.54 (13.13) years of age. The male to female distribution was 85 to 56. Other patient characteristics are shown in Table 2.

Primary outcomes

The risk stratification of the HEART score in chest pain patients and the incidence of 6-week MACE are outlined in Table 3 and Table 4, respectively.

The distribution of the HEART score’s 5 elements in the groups with or without MACE endpoints is shown in Table 5. Notice the significant differences between the groups. A follow-up phone call was made within 6 weeks after the presentation to the ED to assess the patient’s progress. The 6-week follow-up call data are included in Table 6.

Of 141 patients, 36 patients (25.53%) were diagnosed with MACE within 6 weeks of presentation. An AMI was diagnosed in 24 patients (17.02%). Coronary angiography was performed in 31 of 141 patients (21.99%), 15 patients (10.64%) underwent PCI, and 4 patients (2.84%) underwent CABG. The rest of the patients were treated with medications only.

Myocardial infarction—An AMI was diagnosed in 24 of the 141 patients (17.02%). Twenty-one of those already had positive markers on admission (apparently, these AMI had started before their arrival to the emergency room). One AMI occurred 2 days after admission in a 66-year-old male, and another occurred 10 days after discharge. A further AMI occurred 2 weeks after discharge. All 3 patients belonged to the intermediate-risk group.

Revascularization—Coronary angiography was performed in 31 of 141 patients (21.99%). Revascularization was performed in 19 patients (13.48%), of which 15 were PCIs (10.64%) and 4 were CABGs (2.84%).

Mortality—One patient died from the study population. He was a 72-year-old male who died 14 days after admission. He had a HEART score of 8.

Among the 67 low-risk patients:

• MACE: Coronary angiography was performed in 1 patient (1.49%). Among the 67 patients in the low-risk category, there was no cases of AMI or deaths. The remaining 66 patients (98.51%) had an uneventful recovery following discharge.
• General practitioner (GP) visits/readmissions following discharge: Two of 67 patients (2.99%) had GP visits following discharge, of which 1 was uneventful. The other patient, a 64-year-old male, was readmitted due to a recurrent history of chest pain and underwent coronary angiography.

Among the 44 intermediate-risk patients:

• MACE: Of the 7 of 44 patients (15.91%) who had coronary angiography, 3 patients (6.82%) had AMI, of which 1 occurred 2 days after admission in a 66-year-old male. Two patients had AMI following discharge. There were no deaths. Overall, 42 of 44 patients (95.55%) had an uneventful recovery following discharge.
• GP visits/readmissions following discharge: Three of 44 patients (6.82%) had repeated visits following discharge. One was a GP visit that was uneventful. The remaining 2 patients were diagnosed with AMI and readmitted following discharge. One AMI occurred 10 days after discharge in a patient with a HEART score of 6; another occurred 2 weeks after discharge in a patient with a HEART score of 5.

Among the 30 high-risk patients:

• MACE: Twenty-three of 30 patients (76.67%) underwent coronary angiography. One patient died 5 days after discharge. The patient had a HEART score of 8. Most patients however, had an uneventful recovery following discharge (28, 93.33%).
• GP visits/readmissions following discharge: Five of 30 patients (16.67%) had repeated visits following discharge. Two were uneventful. Two patients had a history of recurrent chest pain that resolved on Sorbitrate. One patient was readmitted 2 weeks following discharge due to a complication: a left ventricular clot was found. The patient had a HEART score of 10.

Secondary outcome—Overall, 140 of 141 patients were discharged. One patient died: a 72-year-old male with a HEART score of 8.

Feasibility—To determine the ease and feasibility of performing a HEART score in chest pain patients presenting to the ED, a survey was distributed to the internal medicine physicians in the ED. In the survey, the Likert scale was used to rate the ease of utilizing the HEART score and whether the physicians found it feasible to use it for risk stratification of their chest pain patients. A total of 12 of 15 respondents (80%) found it “easy” to use. Of the remaining 3 respondents, 2 (13.33%) rated the HEART score “very easy” to use, while 1 (6.66%) considered it “difficult” to work with. None of the respondents said that it was not feasible to perform a HEART score in the ED.

Risk factors for reaching an endpoint:

We compared risk profiles between the patient groups with and without an endpoint. The group of patients with MACE were older and had a higher proportion of males than the group of patients without MACE. Moreover, they also had a higher prevalence of hypertension, type 2 diabetes mellitus, smoking, hypercholesterolemia, prior history of PCI/CABG, and history of stroke. These also showed a significant association with MACE. Obesity was not included in our risk factors as we did not have data collected to measure body mass index. Results are represented in Table 7.

Discussion

Our study described a patient population presenting to an ED with chest pain as their primary complaint. The results of this prospective study confirm that the HEART score is an excellent system to triage chest pain patients. It provides the clinician with a reliable predictor of the outcome (MACE) after the patient’s arrival, based on available clinical data and in a resource-limited setting like ours.

Cardiovascular epidemiology studies indicate that this has become a significant public health problem in India.¹ Several risk scores for ACS have been published in European and American guidelines. However, in the Indian population, minimal data are available on utilization of such a triage score (HEART score) in chest pain patients in the ED in a resource-limited setting, to the best of our knowledge. In India, only 1 such study is reported,¹⁵ at the Sundaram Medical Foundation, a 170-bed community hospital in Chennai. In this study, 13 of 14 patients (92.86%) with a high HEART score had MACE, indicating a sensitivity of 92.86%; in the 44 patients with a low HEART score, 1 patient (2.22%) had MACE, indicating a specificity of 97.78%; and in the 28 patients with a moderate HEART score, 12 patients (42.86%) had MACE.  

In looking for the optimal risk-stratifying system for chest pain patients, we analyzed the HEART score. The first study on the HEART score was done Backus et al, proving that the HEART score is an easy, quick, and reliable predictor of outcomes in chest pain patients.¹⁰ The HEART score had good discriminatory power, too. The C statistic for the HEART score for ACS occurrence shows a value of 0.83. This signifies a good-to-excellent ability to stratify all-cause chest pain patients in the ED for their risk of MACE. The application of the HEART score to our patient population demonstrated that the majority of the patients belonged to the low-risk category, as reported in the first cohort study that applied the HEART score.⁸ The relationship between the HEART score category and occurrence of MACE within 6 weeks showed a curve with 3 different patterns, corresponding to the 3 risk categories defined in the literature.^11,12 The risk stratification of chest pain patients using the 3 categories (0-3, 4-6, 7-10) identified MACE with an incidence similar to the multicenter study of Backus et al,^10,11 but with a greater risk of MACE in the high-risk category (Figure).

Thus, our study confirmed the utility of the HEART score categories to predict the 6-week incidence of MACE. The sensitivity, specificity, and positive and negative predictive values for the established cut-off scores of 4 and 7 are shown in Table 8. The patients in the low-risk category, corresponding to a score < 4, had a very high negative predictive value, thus identifying a small-risk population. The patients in the high-risk category (score ≥ 7) showed a high positive predictive value, allowing the identification of a high-risk population, even in patients with more atypical presentations. Therefore, the HEART score may help clinicians to make accurate management choices by being a strong predictor of both event-free survival and potentially life-threatening cardiac events.^11,12

Our study tested the efficacy of the HEART score pathway in helping clinicians make smart diagnostic and therapeutic choices. It confirmed that the HEART score was accurate in predicting the short-term incidence of MACE, thus stratifying patients according to their risk severity. In our study, 67 of 141 patients (47.52%) had low-risk HEART scores, and we found the 6-week incidence of MACE to be 1.49%. We omitted the diagnostic and treatment evaluation for patients in the low-risk category and moved onto discharge. Overall, 66 of 67 patients (98.51%) in the low-risk category had an uneventful recovery following discharge. Only 2 of 67 these patients (2.99%) of patients had health care utilization following discharge. Therefore, extrapolation based on results demonstrates reduced health care utilization. Previous studies have shown similar results.^9,12,14,16 For instance, in a prospective study conducted in the Netherlands, low-risk patients representing 36.4% of the total were found to have a low MACE rate (1.7%).⁹ These low-risk patients were categorized as appropriate and safe for ED discharge without additional cardiac evaluation or inpatient admission.⁹ Another retrospective study in Portugal,¹² and one in Chennai, India,¹⁵ found the 6-week incidence of MACE to be 2.00% and 2.22%, respectively. The results of the first HEART Pathway Randomized Control Trial¹⁴ showed that the HEART score pathway reduces health care utilization (cardiac testing, hospitalization, and hospital length of stay). The study also showed that these gains occurred without any of the patients that were identified for early discharge, suffering from MACE at 30 days, or secondary increase in cardiac-related hospitalizations. Similar results were obtained by a randomized trial conducted in North Carolina¹⁷ that also demonstrated a reduction in objective cardiac testing, a doubling of the rate of early discharge from the ED, and a reduced length of stay by half a day. Another study using a modified HEART score also demonstrated that when low-risk patients are evaluated with cardiac testing, the likelihood for false positives is high.¹⁶ Hoffman et al also reported that patients randomized to coronary computed tomographic angiography (CCTA) received > 2.5 times more radiation exposure.¹⁶ Thus, low-risk patients may be safely discharged without the need for stress testing or CCTA.

In our study, 30 out of 141 patients (21.28%) had high-risk HEART scores (7-10), and we found the 6-week incidence of MACE to be 90%. Based on the pathway leading to inpatient admission and intensive treatment, 23 of 30 patients (76.67%) patients in our study underwent coronary angiography and further therapeutic treatment. In the high-risk category, 28 of 30 patients (93.33%) patients had an uneventful recovery following discharge. Previous studies have shown similar results. A retrospective study in Portugal showed that 76.9% of the high-risk patients had a 6-week incidence of MACE.¹² In a study in the Netherlands,⁹ 72.7% of high-risk patients had a 6-week incidence of MACE. Therefore, a HEART score of ≥ 7 in patients implies early aggressive treatment, including invasive strategies, when necessary, without noninvasive treatment preceding it.⁸

In terms of intermediate risk, in our study 44 of 141 patients (31.21%) patients had an intermediate-risk HEART score (4-6), and we found the 6-week incidence of MACE to be 18.18%. Based on the pathway, they were kept in the observation ward on admission. In our study, 7 of 44 patients (15.91%) underwent coronary angiography and further treatment; 42 of 44 patients (95.55%) had an uneventful recovery following discharge. In a prospective study in the Netherlands, 46.1% of patients with an intermediate score had a 6-week MACE incidence of 16.6%.¹⁰ Similarly, in another retrospective study in Portugal, the incidence of 6-week MACE in intermediate-risk patients (36.7%) was found to be 15.6%.¹² Therefore, in patients with a HEART score of 4-6 points, immediate discharge is not an option, as this figure indicates a risk of 18.18% for an adverse outcome. These patients should be admitted for clinical observation, treated as an ACS awaiting final diagnosis, and subjected to noninvasive investigations, such as repeated troponin. Using the HEART score as guidance in the treatment of chest pain patients will benefit patients on both sides of the spectrum.^11,12

Our sample presented a male predominance, a wide range of age, and a mean age similar to that of previous studies.^12.16 Some risk factors, we found, can increase significantly the odds of chest pain being of cardiovascular origin, such as male gender, smoking, hypertension, type 2 diabetes mellitus, and hypercholesterolemia. Other studies also reported similar findings.^8,12,16 Risk factors for premature CHD have been quantified in the case-control INTERHEART study.¹ In the INTERHEART study, 8 common risk factors explained > 90% of AMIs in South Asian and Indian patients. The risk factors include dyslipidemia, smoking or tobacco use, known hypertension, known diabetes, abdominal obesity, physical inactivity, low fruit and vegetable intake, and psychosocial stress.¹ Regarding the feasibility of treating physicians using the HEART score in the ED, we observed that, based on the Likert scale, 80% of survey respondents found it easy to use, and 100% found it feasible in the ED.

However, there were certain limitations to our study. It involved a single academic medical center and a small sample size, which limit generalizability of the findings. In addition, troponin levels are not calculated at our institution, as it is a resource-limited setting; therefore, we used a positive and negative as +2 and 0, respectively.

Conclusion

The HEART score provides the clinician with a quick and reliable predictor of outcome of patients with chest pain after arrival to the ED and can be used for triage. For patients with low HEART scores (0-3), short-term MACE can be excluded with greater than 98% certainty. In these patients, one may consider reserved treatment and discharge policies that may also reduce health care utilization. In patients with high HEART scores (7-10), the high risk of MACE (90%) may indicate early aggressive treatment, including invasive strategies, when necessary. Therefore, the HEART score may help clinicians make accurate management choices by being a strong predictor of both event-free survival and potentially life-threatening cardiac events. Age, gender, and cardiovascular risk factors may also be considered in the assessment of patients. This study confirmed the utility of the HEART score categories to predict the 6-week incidence of MACE.

Corresponding author: Smrati Bajpai Tiwari, MD, DNB, FAIMER, Department of Medicine, Seth Gordhandas Sunderdas Medical College and King Edward Memorial Hospital, Acharya Donde Marg, Parel, Mumbai 400 012, Maharashtra, India; [email protected].

Financial disclosures: None.

From the Department of Internal Medicine, Mount Sinai Health System, Icahn School of Medicine at Mount Sinai, New York, NY (Dr. Gandhi), and the School of Medicine, Seth Gordhandas Sunderdas Medical College, and King Edward Memorial Hospital, Mumbai, India (Drs. Gandhi and Tiwari).

Objective: Calculation of HEART score to (1) stratify patients as low-risk, intermediate-risk, high-risk, and to predict the short-term incidence of major adverse cardiovascular events (MACE), and (2) demonstrate feasibility of HEART score in our local settings.

Design: A prospective cohort study of patients with a chief complaint of chest pain concerning for acute coronary syndrome.

Setting: Participants were recruited from the emergency department (ED) of King Edward Memorial Hospital, a tertiary care academic medical center and a resource-limited setting in Mumbai, India.

Participants: We evaluated 141 patients aged 18 years and older presenting to the ED and stratified them using the HEART score. To assess patients’ progress, a follow-up phone call was made within 6 weeks after presentation to the ED.

Measurements: The primary outcomes were a risk stratification, 6-week occurrence of MACE, and performance of unscheduled revascularization or stress testing. The secondary outcomes were discharge or death.

Results: The 141 participants were stratified into low-risk, intermediate-risk, and high-risk groups: 67 (47.52%), 44 (31.21%), and 30 (21.28%), respectively. The 6-week incidence of MACE in each category was 1.49%, 18.18%, and 90%, respectively. An acute myocardial infarction was diagnosed in 24 patients (17.02%), 15 patients (10.64%) underwent percutaneous coronary intervention (PCI), and 4 patients (2.84%) underwent coronary artery bypass graft (CABG). Overall, 98.5% of low-risk patients and 93.33% of high-risk patients had an uneventful recovery following discharge; therefore, extrapolation based on results demonstrated reduced health care utilization. All the survey respondents found the HEART score to be feasible. The patient characteristics and risk profile of the patients with and without MACE demonstrated that: patients with MACE were older and had a higher proportion of males, hypertension, type 2 diabetes mellitus, smoking, hypercholesterolemia, prior history of PCI/CABG, and history of stroke.

Conclusion: The HEART score seems to be a useful tool for risk stratification and a reliable predictor of outcomes in chest pain patients and can therefore be used for triage.

Keywords: chest pain; emergency department; HEART score; acute coronary syndrome; major adverse cardiac events; myocardial infarction; revascularization.

Cardiovascular diseases (CVDs), especially coronary heart disease (CHD), have epidemic proportions worldwide. Globally, in 2012, CVD led to 17.5 million deaths,^1,2 with more than 75% of them occurring in developing countries. In contrast to developed countries, where mortality from CHD is rapidly declining, it is increasing in developing countries.^1,3 Current estimates from epidemiologic studies from various parts of India indicate the prevalence of CHD in India to be between 7% and 13% in urban populations and 2% and 7% in rural populations.⁴

Premature mortality in terms of years of life lost because of CVD in India increased by 59% over a 20-year span, from 23.2 million in 1990 to 37 million in 2010.⁵ Studies conducted in Mumbai (Mumbai Cohort Study) reported very high CVD mortality rates, approaching 500 per 100 000 for men and 250 per 100 000 for women.^6,7 However, to the best of our knowledge, in the Indian population, there are minimal data on utilization of a triage score, such as the HEART score, in chest pain patients in the emergency department (ED) in a resource-limited setting.

The most common reason for admitting patients to the ED is chest pain.⁸ There are various cardiac and noncardiac etiologies of chest pain presentation. Acute coronary syndrome (ACS) needs to be ruled out first in every patient presenting with chest pain. However, 80% of patients with ACS have no clear diagnostic features on presentation.⁹ The timely diagnosis and treatment of patients with ACS improves their prognosis. Therefore, clinicians tend to start each patient on ACS treatment to reduce the risk, which often leads to increased costs due to unnecessary, time-consuming diagnostic procedures that may place burdens on both the health care system and the patient.¹⁰

Several risk-stratifying tools have been developed in the last few years. Both the GRACE and TIMI risk scores have been designed for risk stratification of patients with proven ACS and not for the chest pain population at the ED.¹¹ Some of these tools are applicable to patients with all types of chest pain presenting to the ED, such as the Manchester Triage System. Other, more selective systems are devoted to the risk stratification of suspected ACS in the ED. One is the HEART score.¹²

The first study on the HEART score—an acronym that stands for History, Electrocardiogram, Age, Risk factors, and Troponin—was done by Backus et al, who proved that the HEART score is an easy, quick, and reliable predictor of outcomes in chest pain patients.¹⁰ The HEART score predicts the short-term incidence of major adverse cardiac events (MACE), which allows clinicians to stratify patients as low-risk, intermediate-risk, and high-risk and to guide their clinical decision-making accordingly. It was developed to provide clinicians with a simple, reliable predictor of cardiac risk on the basis of the lowest score of 0 (very low-risk) up to a score of 10 (very high-risk).

We studied the clinical performance of the HEART score in patients with chest pain, focusing on the efficacy and safety of rapidly identifying patients at risk of MACE. We aimed to determine (1) whether the HEART score is a reliable predictor of outcomes of chest pain patients presenting to the ED; (2) whether the score is feasible in our local settings; and (3) whether it describes the risk profile of patients with and without MACE.

Methods

Setting

Participants were recruited from the ED of King Edward Memorial Hospital, a municipal teaching hospital in Mumbai. The study institute is a tertiary care academic medical center located in Parel, Mumbai, Maharashtra, and is a resource-limited setting serving urban, suburban, and rural populations. Participants requiring urgent attention are first seen by a casualty officer and then referred to the emergency ward. Here, the physician on duty evaluates them and decides on admission to the various wards, like the general ward, medical intensive care unit (ICU), coronary care unit (CCU), etc. The specialist’s opinion may also be obtained before admission. Critically ill patients are initially admitted to the emergency ward and stabilized before being shifted to other areas of the hospital.

Participants

Patients aged 18 years and older presenting with symptoms of acute chest pain or suspected ACS were stratified by priority using the chest pain scoring system—the HEART score. Only patients presenting to the ED were eligible for the study. Informed consent from the patient or next of kin was mandatory for participation in the study.

Patients were determined ineligible for the following reasons: a clear cause for chest pain other than ACS (eg, trauma, diagnosed aortic dissection), persisting or recurrent chest pain caused by rheumatic diseases or cancer (a terminal illness), pregnancy, unable or unwilling to provide informed consent, or incomplete data.

Study design

We conducted a prospective observational study of patients arriving at the tertiary care hospital with a chief complaint of “chest pain” concerning for ACS. All participants provided witnessed written informed consent. Patients were screened over approximately a 3-month period, from July 2019 to October 2019, after acquiring approval from the Institutional Ethics Committee. Any patient who was admitted to the ED due to chest pain, prehospital referrals based on a physician’s suspicions of a heart condition, and previous medical treatment due to ischemic heart disease (IHD) was eligible. All patients were stratified by priority in our ED using the chest pain scoring system—the HEART score—and were followed up by phone within 6 weeks after presenting to the ED, to assess their progress.

We conducted our study to determine the importance of calculating the HEART score in each patient, which will help to correctly place them into low-, intermediate-, and high-risk groups for clinically important, irreversible adverse cardiac events and guide the clinical decision-making. Patients with low risk will avoid costly tests and hospital admissions, thus decreasing the cost of treatment and ensuring timely discharge from the ED. Patients with high risk will be treated immediately, to possibly prevent a life-threatening, ACS-related incident. Thus, the HEART score will serve as a quick and reliable predictor of outcomes in chest pain patients and help clinicians to make accurate diagnostic and therapeutic choices in uncertain situations.

HEART score

The total number of points for History, Electrocardiogram (ECG), Age, Risk factors, and Troponin was noted as the HEART score (Table 1).

For this study, the patient’s history and ECGs were interpreted by internal medicine attending physicians in the ED. The ECG taken in the emergency room was reviewed and classified, and a copy of the admission ECG was added to the file. The recommendation for patients with a HEART score in a particular range was evaluated. Notably, those with a score of 3 or lower led to a recommendation of reassurance and early discharge. Those with a HEART score in the intermediate range (4-6) were admitted to the hospital for further clinical observation and testing, whereas a high HEART score (7-10) led to admission for intensive monitoring and early intervention. In the analysis of HEART score data, we only used those patients having records for all 5 parameters, excluding patients without an ECG or troponin test.

Results

Myocardial infarction (MI) was defined based on Universal Definition of Myocardial Infarction.¹³ Coronary revascularization was defined as angioplasty with or without stent placement or coronary artery bypass surgery.¹⁴ Percutaneous coronary intervention (PCI) was defined as any therapeutic catheter intervention in the coronary arteries. Coronary artery bypass graft (CABG) surgery was defined as any cardiac surgery in which coronary arteries were operated on.

The primary outcomes in this study were the (1) risk stratification of chest pain patients into low-risk, intermediate-risk, and high-risk categories; (2) incidence of a MACE within 6 weeks of initial presentation. MACE consists of acute myocardial infarction (AMI), PCI, CABG, coronary angiography revealing procedurally correctable stenosis managed conservatively, and death due to any cause.

Our secondary outcomes were discharge or death due to any cause within 6 weeks after presentation.

Follow-up

Within 6 weeks after presentation to the ED, a follow-up phone call was placed to assess the patient’s progress. The follow-up focused on the endpoint of MACE, comprising all-cause death, MI, and revascularization. No patient was lost to follow-up.

Statistical analysis

We aimed to find a difference in the 6-week MACE between low-, intermediate-, and high-risk categories of the HEART score. The prevalence of CHD in India is 10%,⁴ and assuming an α of 0.05, we needed a sample of 141 patients from the ED patient population. Continuous variables were presented by mean (SD), and categorical variables as percentages. We used t test and the Mann-Whitney U test for comparison of means for continuous variables, χ² for categorical variables, and Fisher’s exact test for comparison of the categorical variables. Results with P < .05 were considered statistically significant.

We evaluated 141 patients presenting to the ED with chest pain concerning for ACS during the study period, from July 2019 to October 2019. Patients were 57.54 (13.13) years of age. The male to female distribution was 85 to 56. Other patient characteristics are shown in Table 2.

Primary outcomes

The risk stratification of the HEART score in chest pain patients and the incidence of 6-week MACE are outlined in Table 3 and Table 4, respectively.

The distribution of the HEART score’s 5 elements in the groups with or without MACE endpoints is shown in Table 5. Notice the significant differences between the groups. A follow-up phone call was made within 6 weeks after the presentation to the ED to assess the patient’s progress. The 6-week follow-up call data are included in Table 6.

Of 141 patients, 36 patients (25.53%) were diagnosed with MACE within 6 weeks of presentation. An AMI was diagnosed in 24 patients (17.02%). Coronary angiography was performed in 31 of 141 patients (21.99%), 15 patients (10.64%) underwent PCI, and 4 patients (2.84%) underwent CABG. The rest of the patients were treated with medications only.

Myocardial infarction—An AMI was diagnosed in 24 of the 141 patients (17.02%). Twenty-one of those already had positive markers on admission (apparently, these AMI had started before their arrival to the emergency room). One AMI occurred 2 days after admission in a 66-year-old male, and another occurred 10 days after discharge. A further AMI occurred 2 weeks after discharge. All 3 patients belonged to the intermediate-risk group.

Revascularization—Coronary angiography was performed in 31 of 141 patients (21.99%). Revascularization was performed in 19 patients (13.48%), of which 15 were PCIs (10.64%) and 4 were CABGs (2.84%).

Mortality—One patient died from the study population. He was a 72-year-old male who died 14 days after admission. He had a HEART score of 8.

Among the 67 low-risk patients:

• MACE: Coronary angiography was performed in 1 patient (1.49%). Among the 67 patients in the low-risk category, there was no cases of AMI or deaths. The remaining 66 patients (98.51%) had an uneventful recovery following discharge.
• General practitioner (GP) visits/readmissions following discharge: Two of 67 patients (2.99%) had GP visits following discharge, of which 1 was uneventful. The other patient, a 64-year-old male, was readmitted due to a recurrent history of chest pain and underwent coronary angiography.

Among the 44 intermediate-risk patients:

• MACE: Of the 7 of 44 patients (15.91%) who had coronary angiography, 3 patients (6.82%) had AMI, of which 1 occurred 2 days after admission in a 66-year-old male. Two patients had AMI following discharge. There were no deaths. Overall, 42 of 44 patients (95.55%) had an uneventful recovery following discharge.
• GP visits/readmissions following discharge: Three of 44 patients (6.82%) had repeated visits following discharge. One was a GP visit that was uneventful. The remaining 2 patients were diagnosed with AMI and readmitted following discharge. One AMI occurred 10 days after discharge in a patient with a HEART score of 6; another occurred 2 weeks after discharge in a patient with a HEART score of 5.

Among the 30 high-risk patients:

• MACE: Twenty-three of 30 patients (76.67%) underwent coronary angiography. One patient died 5 days after discharge. The patient had a HEART score of 8. Most patients however, had an uneventful recovery following discharge (28, 93.33%).
• GP visits/readmissions following discharge: Five of 30 patients (16.67%) had repeated visits following discharge. Two were uneventful. Two patients had a history of recurrent chest pain that resolved on Sorbitrate. One patient was readmitted 2 weeks following discharge due to a complication: a left ventricular clot was found. The patient had a HEART score of 10.

Secondary outcome—Overall, 140 of 141 patients were discharged. One patient died: a 72-year-old male with a HEART score of 8.

Feasibility—To determine the ease and feasibility of performing a HEART score in chest pain patients presenting to the ED, a survey was distributed to the internal medicine physicians in the ED. In the survey, the Likert scale was used to rate the ease of utilizing the HEART score and whether the physicians found it feasible to use it for risk stratification of their chest pain patients. A total of 12 of 15 respondents (80%) found it “easy” to use. Of the remaining 3 respondents, 2 (13.33%) rated the HEART score “very easy” to use, while 1 (6.66%) considered it “difficult” to work with. None of the respondents said that it was not feasible to perform a HEART score in the ED.

Risk factors for reaching an endpoint:

We compared risk profiles between the patient groups with and without an endpoint. The group of patients with MACE were older and had a higher proportion of males than the group of patients without MACE. Moreover, they also had a higher prevalence of hypertension, type 2 diabetes mellitus, smoking, hypercholesterolemia, prior history of PCI/CABG, and history of stroke. These also showed a significant association with MACE. Obesity was not included in our risk factors as we did not have data collected to measure body mass index. Results are represented in Table 7.

Discussion

Our study described a patient population presenting to an ED with chest pain as their primary complaint. The results of this prospective study confirm that the HEART score is an excellent system to triage chest pain patients. It provides the clinician with a reliable predictor of the outcome (MACE) after the patient’s arrival, based on available clinical data and in a resource-limited setting like ours.

Cardiovascular epidemiology studies indicate that this has become a significant public health problem in India.¹ Several risk scores for ACS have been published in European and American guidelines. However, in the Indian population, minimal data are available on utilization of such a triage score (HEART score) in chest pain patients in the ED in a resource-limited setting, to the best of our knowledge. In India, only 1 such study is reported,¹⁵ at the Sundaram Medical Foundation, a 170-bed community hospital in Chennai. In this study, 13 of 14 patients (92.86%) with a high HEART score had MACE, indicating a sensitivity of 92.86%; in the 44 patients with a low HEART score, 1 patient (2.22%) had MACE, indicating a specificity of 97.78%; and in the 28 patients with a moderate HEART score, 12 patients (42.86%) had MACE.  

In looking for the optimal risk-stratifying system for chest pain patients, we analyzed the HEART score. The first study on the HEART score was done Backus et al, proving that the HEART score is an easy, quick, and reliable predictor of outcomes in chest pain patients.¹⁰ The HEART score had good discriminatory power, too. The C statistic for the HEART score for ACS occurrence shows a value of 0.83. This signifies a good-to-excellent ability to stratify all-cause chest pain patients in the ED for their risk of MACE. The application of the HEART score to our patient population demonstrated that the majority of the patients belonged to the low-risk category, as reported in the first cohort study that applied the HEART score.⁸ The relationship between the HEART score category and occurrence of MACE within 6 weeks showed a curve with 3 different patterns, corresponding to the 3 risk categories defined in the literature.^11,12 The risk stratification of chest pain patients using the 3 categories (0-3, 4-6, 7-10) identified MACE with an incidence similar to the multicenter study of Backus et al,^10,11 but with a greater risk of MACE in the high-risk category (Figure).

Thus, our study confirmed the utility of the HEART score categories to predict the 6-week incidence of MACE. The sensitivity, specificity, and positive and negative predictive values for the established cut-off scores of 4 and 7 are shown in Table 8. The patients in the low-risk category, corresponding to a score < 4, had a very high negative predictive value, thus identifying a small-risk population. The patients in the high-risk category (score ≥ 7) showed a high positive predictive value, allowing the identification of a high-risk population, even in patients with more atypical presentations. Therefore, the HEART score may help clinicians to make accurate management choices by being a strong predictor of both event-free survival and potentially life-threatening cardiac events.^11,12

Our study tested the efficacy of the HEART score pathway in helping clinicians make smart diagnostic and therapeutic choices. It confirmed that the HEART score was accurate in predicting the short-term incidence of MACE, thus stratifying patients according to their risk severity. In our study, 67 of 141 patients (47.52%) had low-risk HEART scores, and we found the 6-week incidence of MACE to be 1.49%. We omitted the diagnostic and treatment evaluation for patients in the low-risk category and moved onto discharge. Overall, 66 of 67 patients (98.51%) in the low-risk category had an uneventful recovery following discharge. Only 2 of 67 these patients (2.99%) of patients had health care utilization following discharge. Therefore, extrapolation based on results demonstrates reduced health care utilization. Previous studies have shown similar results.^9,12,14,16 For instance, in a prospective study conducted in the Netherlands, low-risk patients representing 36.4% of the total were found to have a low MACE rate (1.7%).⁹ These low-risk patients were categorized as appropriate and safe for ED discharge without additional cardiac evaluation or inpatient admission.⁹ Another retrospective study in Portugal,¹² and one in Chennai, India,¹⁵ found the 6-week incidence of MACE to be 2.00% and 2.22%, respectively. The results of the first HEART Pathway Randomized Control Trial¹⁴ showed that the HEART score pathway reduces health care utilization (cardiac testing, hospitalization, and hospital length of stay). The study also showed that these gains occurred without any of the patients that were identified for early discharge, suffering from MACE at 30 days, or secondary increase in cardiac-related hospitalizations. Similar results were obtained by a randomized trial conducted in North Carolina¹⁷ that also demonstrated a reduction in objective cardiac testing, a doubling of the rate of early discharge from the ED, and a reduced length of stay by half a day. Another study using a modified HEART score also demonstrated that when low-risk patients are evaluated with cardiac testing, the likelihood for false positives is high.¹⁶ Hoffman et al also reported that patients randomized to coronary computed tomographic angiography (CCTA) received > 2.5 times more radiation exposure.¹⁶ Thus, low-risk patients may be safely discharged without the need for stress testing or CCTA.

In our study, 30 out of 141 patients (21.28%) had high-risk HEART scores (7-10), and we found the 6-week incidence of MACE to be 90%. Based on the pathway leading to inpatient admission and intensive treatment, 23 of 30 patients (76.67%) patients in our study underwent coronary angiography and further therapeutic treatment. In the high-risk category, 28 of 30 patients (93.33%) patients had an uneventful recovery following discharge. Previous studies have shown similar results. A retrospective study in Portugal showed that 76.9% of the high-risk patients had a 6-week incidence of MACE.¹² In a study in the Netherlands,⁹ 72.7% of high-risk patients had a 6-week incidence of MACE. Therefore, a HEART score of ≥ 7 in patients implies early aggressive treatment, including invasive strategies, when necessary, without noninvasive treatment preceding it.⁸

In terms of intermediate risk, in our study 44 of 141 patients (31.21%) patients had an intermediate-risk HEART score (4-6), and we found the 6-week incidence of MACE to be 18.18%. Based on the pathway, they were kept in the observation ward on admission. In our study, 7 of 44 patients (15.91%) underwent coronary angiography and further treatment; 42 of 44 patients (95.55%) had an uneventful recovery following discharge. In a prospective study in the Netherlands, 46.1% of patients with an intermediate score had a 6-week MACE incidence of 16.6%.¹⁰ Similarly, in another retrospective study in Portugal, the incidence of 6-week MACE in intermediate-risk patients (36.7%) was found to be 15.6%.¹² Therefore, in patients with a HEART score of 4-6 points, immediate discharge is not an option, as this figure indicates a risk of 18.18% for an adverse outcome. These patients should be admitted for clinical observation, treated as an ACS awaiting final diagnosis, and subjected to noninvasive investigations, such as repeated troponin. Using the HEART score as guidance in the treatment of chest pain patients will benefit patients on both sides of the spectrum.^11,12

Our sample presented a male predominance, a wide range of age, and a mean age similar to that of previous studies.^12.16 Some risk factors, we found, can increase significantly the odds of chest pain being of cardiovascular origin, such as male gender, smoking, hypertension, type 2 diabetes mellitus, and hypercholesterolemia. Other studies also reported similar findings.^8,12,16 Risk factors for premature CHD have been quantified in the case-control INTERHEART study.¹ In the INTERHEART study, 8 common risk factors explained > 90% of AMIs in South Asian and Indian patients. The risk factors include dyslipidemia, smoking or tobacco use, known hypertension, known diabetes, abdominal obesity, physical inactivity, low fruit and vegetable intake, and psychosocial stress.¹ Regarding the feasibility of treating physicians using the HEART score in the ED, we observed that, based on the Likert scale, 80% of survey respondents found it easy to use, and 100% found it feasible in the ED.

However, there were certain limitations to our study. It involved a single academic medical center and a small sample size, which limit generalizability of the findings. In addition, troponin levels are not calculated at our institution, as it is a resource-limited setting; therefore, we used a positive and negative as +2 and 0, respectively.

Conclusion

The HEART score provides the clinician with a quick and reliable predictor of outcome of patients with chest pain after arrival to the ED and can be used for triage. For patients with low HEART scores (0-3), short-term MACE can be excluded with greater than 98% certainty. In these patients, one may consider reserved treatment and discharge policies that may also reduce health care utilization. In patients with high HEART scores (7-10), the high risk of MACE (90%) may indicate early aggressive treatment, including invasive strategies, when necessary. Therefore, the HEART score may help clinicians make accurate management choices by being a strong predictor of both event-free survival and potentially life-threatening cardiac events. Age, gender, and cardiovascular risk factors may also be considered in the assessment of patients. This study confirmed the utility of the HEART score categories to predict the 6-week incidence of MACE.

Corresponding author: Smrati Bajpai Tiwari, MD, DNB, FAIMER, Department of Medicine, Seth Gordhandas Sunderdas Medical College and King Edward Memorial Hospital, Acharya Donde Marg, Parel, Mumbai 400 012, Maharashtra, India; [email protected].

Financial disclosures: None.

Insulin pump technology has been available since the 1970s. Innovation in insulin pumps has had significant impact on the management of diabetes mellitus (DM). In recent years, automated insulin pump technology (AIP) has proven to be a safe and effective way to treat DM. It has been studied mostly in highly organized randomized controlled trials (RCTs) in younger populations with type 1 DM (T1DM).^1-3

One of the challenges in DM care has always been the wide variations in daily plasma glucose concentration that often cause major swings of hyperglycemia and hypoglycemia. Extreme variations in blood glucose have also been linked to adverse outcomes, including poor micro- and macrovascular outcomes.^4,5 AIP technology is a hybrid closed-loop system that attempts to solve this problem by adjusting insulin delivery in response to real-time glucose information from a continuous glucose monitor (CGM). Glucose measurements are sent to the insulin pump in real time, which uses a specialized algorithm to determine whether insulin delivery should be up-titrated, down-titrated, or suspended.⁶

Several studies have shown that AIP technology reduces glucose variability and increases the percentage of time within the optimal glucose range.^1-3,7 Its safety is especially indicated for patients with long-standing DM who often have hypoglycemia unawareness and recurrent episodes of hypoglycemia.⁷ Safety is the major advantage of the hybrid closed-loop system as long duration of DM makes patients particularly prone to emergency department (ED) visits and hospitalizations for severe hypoglycemia.⁸ Recurrent hypoglycemia also is associated with increased cardiovascular mortality in epidemiologic studies.⁹

Safety was the primary endpoint in the pivotal trial in a multicenter clinical study where 124 participants (mean age, 37.8 years; DM duration, 21.7 years; hemoglobin A_1c [HbA_1c], 7.4%) were monitored for 3 months while using a hybrid closed-loop pump, similar to the one used in our study.¹⁰ Remarkably, there were no device-related episodes of severe hypoglycemia or ketoacidosis. There was even a small but significant difference in HbA_1c (7.4% at baseline, 6.9% at 3 months) and of the time in target range measured by CGM from 66.7% at baseline to 72.2% at 3 months). However, the mean age of the population studied was young (mean age, 37.8 years). It is unclear how these results would translate for a population of older patients with T1DM. Moreover, use of AIP systems have not been systematically tested outside of carefully controlled studies, as it would be in middle-aged veterans followed in outpatient US Department of Veterans Affairs (VA) clinics. Such an approach in the context of optimal glucose monitoring combined with use of structured DM education can significantly reduce impaired awareness of hypoglycemia in patients with T1DM of long duration.¹¹

This is the first study to assess the feasibility of AIP technology in a real-world population of older veterans with T1DM in terms of safety and acceptability, because AIP has just recently become available for patient care in the Veterans Health Administration (VHA). This group of patients is of particular interest because they have been largely overlooked in earlier studies. They represent an older population with long-standing DM where hypoglycemia unawareness is often recurrent and incapacitating. In addition, long-standing DM makes optimal glycemic control mandatory to prevent microvascular complications.

Methods

In this retrospective review study,, we examined available data in patients with T1DM at the Malcom Randall VA Medical Center diabetes clinic in Gainesville, Florida, between March and December of 2018 who agreed to use AIP. In this clinic, the AIP system was offered to T1DM patients when the 4-year warranty of a previous insulin pump expired, they had frequent hypoglycemic events, or they were on multiple daily injections and were proficient with carbohydrate counting and adjusting insulin doses and willing to use an insulin pump. Veterans were trained on AIP use by a certified diabetes educator and pump trainer in sessions that lasted 2 to 4 hours depending on previous experience with AIP. Institutional review board approval was obtained at the University of Florida. 

Demographic and clinical data before and after the initiation of AIP were collected, including standard insulin pump/CGM information for the Medtronic 670G and Guardian 3 Sensor AIPs. Several variables were evaluated, including age, gender, year of DM diagnosis, time of initiation of AIP, HbA_1c, download data (percentage sensor wear, time in automated mode and manual mode, time in/above/below range, bolus information, insulin use, average sensor blood glucose, average meter blood glucose, pump settings), weight, body mass index (BMI), glucose meter information, history of hypoglycemia unawareness.

The primary outcome for this study was safety as assessed by percentage of time below target range on glucose sensor (time below target range is defined as < 70 mg/dL). We also addressed the secondary endpoint of efficacy as the percentage of time in-range defined as blood glucose per glucose sensor of 70 mg/dL to 180 mg/dL (efficacy), percentage of glucose sensor wear, and HbA_1c.

Statistics

Comparisons of changes in continuous variables between groups were performed by an analysis of covariance (ANCOVA), adjusting for baseline levels. Fisher exact test (χ²) and unpaired t test were used to compare group differences at baseline for categorical and continuous variables, respectively, while Wilcoxon rank sum test was used for nonnormally distributed values. Changes in continuous measures within the same group were tested by paired t test or Wilcoxon matched-pairs signed rank test when applicable. Analyses were performed using Stata 11.0.

Results

Thirty-seven veterans with T1DM using AIPs in 2018 were evaluated at baseline and at follow up visits (Tables 1 and 2). Time frame for follow-up was approximately 3 months, although there was some variation. Of note, the mean weight and BMI corresponded to mostly lean individuals, consistent with the diagnosis of T1DM.

Time below target range hypoglycemia (sensor glucose < 70 mg/dL) remained low at each follow-up visit (both 1.5%). Percentage of time in automated mode increased from first to second follow-up visit after initiation of AIP (41% vs 53%, P = .06). Percentage of sensor wear numerically increased from first to second follow-up visit (75% vs 85%, P = .39), same as time in range, defined as sensor glucose 70 to 180 mg/dL, from first to second follow-up visit (70% vs 73%, P = .09). Time above range, defined as sensor glucose > 180 mg/dL, demonstrated a strong trend toward decreasing between follow-up appointments (29% to 25%; P = .09). HbA_1c decreased from 7.6% to 7.3% (P = .005).

About half of the patients (18 of 37) reported hypoglycemia unawareness before the initiation of the 670G AIP. On follow-up visit 61% (11 of 18) reported significant improvement in awareness. Of the remaining 18 patients who reported normal awareness before automated mode, 17% (3 of 18) described a new onset unawareness.

Discussion

This study evaluated the safety of adopting a new DM technology in the real world of an outpatient VA clinic. To the best of our knowledge, this is the first study evaluating the use of AIP specifically in a population of middle-aged veterans with longstanding T1DM. After a mean 7 months of follow-up, participants accepted AIP use as evidenced by increased sensor wear over time and experienced improvements in DM measures that indicate successful use (ie, time in automated mode, which represents reduced glycemic variability). These results show success of an AIP approach in a demographically older group of patients.

AIP has been shown to have positive effects on glycemic control such as time in target glucose range (goal ≥ 70%). In our relatively small pilot study, there was trend for an improvement in the time in range from the first to second clinical follow-up visit, suggesting true patient involvement with the use of the device. Studies involving overall younger cohorts have proved that AIP technology is safe and efficacious for outpatient management of T1DM.^7,10,12,13 However, they were all conducted under the safety of a research setting, and trials enrolled a younger population believed to adapt with more ease to this new technology. Tauschmann and colleagues performed a multicenter, parallel randomized controlled trial that compared hybrid closed-loop AIP therapy with sensor-augmented pump therapy in patients with suboptimal T1DM control.¹² Results showed that the hybrid closed-loop system increased the time that the glucose concentration was within the target range (70-180 mg/dL) from 54% in the sensor-augmented pump group to 65% on the closed-loop system (P < .001). A small but significant improvement in HBA_1c (from 8.0 -7.4%) and low rates of hypoglycemia (2.6% of time below 70 mg/dL) were also noted.¹²

A similar benefit was observed in a 2019 landmark study by Brown and colleagues of 168 patients with T1DM at 7 university medical centers who were treated for 6 months with either a closed-loop system (closed-loop group) or a sensor-augmented pump (control group) in a parallel-group, unblinded, randomized trial study.¹³ Mean (SD) time in the target range increased in the closed-loop group from 61% (17) at baseline to 71% (12) during the 6 months. HbA_1c decreased from 7.4 to 7.1% and time ≤ 70 mg/dL was just 1.6%. However, only 13% of patients were aged ≥ 40 years in the study by Tauschmann and colleagues, and mean age was 33 years in the Brown and colleagues study.^12,13 In contrast, the mean (SD) age in our study was 59 (14) years. Our pilot study also showed comparable, or somewhat better results, as mean time in target range was 72%, HbA_1c was 7.3%, and time ≤ 70 mg/dL was just 1.5%.

Limitations

There are some limitations to our study. The small sample size and single-center nature prevent generalization. Also, the veteran population cannot be extrapolated to other populations. For instance, the majority of the patients in this study were male.

Conclusions

We report that an AIP approach for patients with long-standing T1DM is well accepted and engages patients into monitoring their blood sugars and achieving better glycemic control. This was achieved with minimal hypoglycemia in a population where often hypoglycemia unawareness makes DM care a challenge. Future studies within the VHA are needed to fully assess the long-term benefits and cost-effectiveness of this technology in veterans.

Insulin pump technology has been available since the 1970s. Innovation in insulin pumps has had significant impact on the management of diabetes mellitus (DM). In recent years, automated insulin pump technology (AIP) has proven to be a safe and effective way to treat DM. It has been studied mostly in highly organized randomized controlled trials (RCTs) in younger populations with type 1 DM (T1DM).^1-3

One of the challenges in DM care has always been the wide variations in daily plasma glucose concentration that often cause major swings of hyperglycemia and hypoglycemia. Extreme variations in blood glucose have also been linked to adverse outcomes, including poor micro- and macrovascular outcomes.^4,5 AIP technology is a hybrid closed-loop system that attempts to solve this problem by adjusting insulin delivery in response to real-time glucose information from a continuous glucose monitor (CGM). Glucose measurements are sent to the insulin pump in real time, which uses a specialized algorithm to determine whether insulin delivery should be up-titrated, down-titrated, or suspended.⁶

Several studies have shown that AIP technology reduces glucose variability and increases the percentage of time within the optimal glucose range.^1-3,7 Its safety is especially indicated for patients with long-standing DM who often have hypoglycemia unawareness and recurrent episodes of hypoglycemia.⁷ Safety is the major advantage of the hybrid closed-loop system as long duration of DM makes patients particularly prone to emergency department (ED) visits and hospitalizations for severe hypoglycemia.⁸ Recurrent hypoglycemia also is associated with increased cardiovascular mortality in epidemiologic studies.⁹

Safety was the primary endpoint in the pivotal trial in a multicenter clinical study where 124 participants (mean age, 37.8 years; DM duration, 21.7 years; hemoglobin A_1c [HbA_1c], 7.4%) were monitored for 3 months while using a hybrid closed-loop pump, similar to the one used in our study.¹⁰ Remarkably, there were no device-related episodes of severe hypoglycemia or ketoacidosis. There was even a small but significant difference in HbA_1c (7.4% at baseline, 6.9% at 3 months) and of the time in target range measured by CGM from 66.7% at baseline to 72.2% at 3 months). However, the mean age of the population studied was young (mean age, 37.8 years). It is unclear how these results would translate for a population of older patients with T1DM. Moreover, use of AIP systems have not been systematically tested outside of carefully controlled studies, as it would be in middle-aged veterans followed in outpatient US Department of Veterans Affairs (VA) clinics. Such an approach in the context of optimal glucose monitoring combined with use of structured DM education can significantly reduce impaired awareness of hypoglycemia in patients with T1DM of long duration.¹¹

This is the first study to assess the feasibility of AIP technology in a real-world population of older veterans with T1DM in terms of safety and acceptability, because AIP has just recently become available for patient care in the Veterans Health Administration (VHA). This group of patients is of particular interest because they have been largely overlooked in earlier studies. They represent an older population with long-standing DM where hypoglycemia unawareness is often recurrent and incapacitating. In addition, long-standing DM makes optimal glycemic control mandatory to prevent microvascular complications.

Methods

In this retrospective review study,, we examined available data in patients with T1DM at the Malcom Randall VA Medical Center diabetes clinic in Gainesville, Florida, between March and December of 2018 who agreed to use AIP. In this clinic, the AIP system was offered to T1DM patients when the 4-year warranty of a previous insulin pump expired, they had frequent hypoglycemic events, or they were on multiple daily injections and were proficient with carbohydrate counting and adjusting insulin doses and willing to use an insulin pump. Veterans were trained on AIP use by a certified diabetes educator and pump trainer in sessions that lasted 2 to 4 hours depending on previous experience with AIP. Institutional review board approval was obtained at the University of Florida. 

Demographic and clinical data before and after the initiation of AIP were collected, including standard insulin pump/CGM information for the Medtronic 670G and Guardian 3 Sensor AIPs. Several variables were evaluated, including age, gender, year of DM diagnosis, time of initiation of AIP, HbA_1c, download data (percentage sensor wear, time in automated mode and manual mode, time in/above/below range, bolus information, insulin use, average sensor blood glucose, average meter blood glucose, pump settings), weight, body mass index (BMI), glucose meter information, history of hypoglycemia unawareness.

The primary outcome for this study was safety as assessed by percentage of time below target range on glucose sensor (time below target range is defined as < 70 mg/dL). We also addressed the secondary endpoint of efficacy as the percentage of time in-range defined as blood glucose per glucose sensor of 70 mg/dL to 180 mg/dL (efficacy), percentage of glucose sensor wear, and HbA_1c.

Statistics

Comparisons of changes in continuous variables between groups were performed by an analysis of covariance (ANCOVA), adjusting for baseline levels. Fisher exact test (χ²) and unpaired t test were used to compare group differences at baseline for categorical and continuous variables, respectively, while Wilcoxon rank sum test was used for nonnormally distributed values. Changes in continuous measures within the same group were tested by paired t test or Wilcoxon matched-pairs signed rank test when applicable. Analyses were performed using Stata 11.0.

Results

Thirty-seven veterans with T1DM using AIPs in 2018 were evaluated at baseline and at follow up visits (Tables 1 and 2). Time frame for follow-up was approximately 3 months, although there was some variation. Of note, the mean weight and BMI corresponded to mostly lean individuals, consistent with the diagnosis of T1DM.

Time below target range hypoglycemia (sensor glucose < 70 mg/dL) remained low at each follow-up visit (both 1.5%). Percentage of time in automated mode increased from first to second follow-up visit after initiation of AIP (41% vs 53%, P = .06). Percentage of sensor wear numerically increased from first to second follow-up visit (75% vs 85%, P = .39), same as time in range, defined as sensor glucose 70 to 180 mg/dL, from first to second follow-up visit (70% vs 73%, P = .09). Time above range, defined as sensor glucose > 180 mg/dL, demonstrated a strong trend toward decreasing between follow-up appointments (29% to 25%; P = .09). HbA_1c decreased from 7.6% to 7.3% (P = .005).

About half of the patients (18 of 37) reported hypoglycemia unawareness before the initiation of the 670G AIP. On follow-up visit 61% (11 of 18) reported significant improvement in awareness. Of the remaining 18 patients who reported normal awareness before automated mode, 17% (3 of 18) described a new onset unawareness.

Discussion

This study evaluated the safety of adopting a new DM technology in the real world of an outpatient VA clinic. To the best of our knowledge, this is the first study evaluating the use of AIP specifically in a population of middle-aged veterans with longstanding T1DM. After a mean 7 months of follow-up, participants accepted AIP use as evidenced by increased sensor wear over time and experienced improvements in DM measures that indicate successful use (ie, time in automated mode, which represents reduced glycemic variability). These results show success of an AIP approach in a demographically older group of patients.

AIP has been shown to have positive effects on glycemic control such as time in target glucose range (goal ≥ 70%). In our relatively small pilot study, there was trend for an improvement in the time in range from the first to second clinical follow-up visit, suggesting true patient involvement with the use of the device. Studies involving overall younger cohorts have proved that AIP technology is safe and efficacious for outpatient management of T1DM.^7,10,12,13 However, they were all conducted under the safety of a research setting, and trials enrolled a younger population believed to adapt with more ease to this new technology. Tauschmann and colleagues performed a multicenter, parallel randomized controlled trial that compared hybrid closed-loop AIP therapy with sensor-augmented pump therapy in patients with suboptimal T1DM control.¹² Results showed that the hybrid closed-loop system increased the time that the glucose concentration was within the target range (70-180 mg/dL) from 54% in the sensor-augmented pump group to 65% on the closed-loop system (P < .001). A small but significant improvement in HBA_1c (from 8.0 -7.4%) and low rates of hypoglycemia (2.6% of time below 70 mg/dL) were also noted.¹²

A similar benefit was observed in a 2019 landmark study by Brown and colleagues of 168 patients with T1DM at 7 university medical centers who were treated for 6 months with either a closed-loop system (closed-loop group) or a sensor-augmented pump (control group) in a parallel-group, unblinded, randomized trial study.¹³ Mean (SD) time in the target range increased in the closed-loop group from 61% (17) at baseline to 71% (12) during the 6 months. HbA_1c decreased from 7.4 to 7.1% and time ≤ 70 mg/dL was just 1.6%. However, only 13% of patients were aged ≥ 40 years in the study by Tauschmann and colleagues, and mean age was 33 years in the Brown and colleagues study.^12,13 In contrast, the mean (SD) age in our study was 59 (14) years. Our pilot study also showed comparable, or somewhat better results, as mean time in target range was 72%, HbA_1c was 7.3%, and time ≤ 70 mg/dL was just 1.5%.

Limitations

There are some limitations to our study. The small sample size and single-center nature prevent generalization. Also, the veteran population cannot be extrapolated to other populations. For instance, the majority of the patients in this study were male.

Conclusions

We report that an AIP approach for patients with long-standing T1DM is well accepted and engages patients into monitoring their blood sugars and achieving better glycemic control. This was achieved with minimal hypoglycemia in a population where often hypoglycemia unawareness makes DM care a challenge. Future studies within the VHA are needed to fully assess the long-term benefits and cost-effectiveness of this technology in veterans.

Insulin pump technology has been available since the 1970s. Innovation in insulin pumps has had significant impact on the management of diabetes mellitus (DM). In recent years, automated insulin pump technology (AIP) has proven to be a safe and effective way to treat DM. It has been studied mostly in highly organized randomized controlled trials (RCTs) in younger populations with type 1 DM (T1DM).^1-3

One of the challenges in DM care has always been the wide variations in daily plasma glucose concentration that often cause major swings of hyperglycemia and hypoglycemia. Extreme variations in blood glucose have also been linked to adverse outcomes, including poor micro- and macrovascular outcomes.^4,5 AIP technology is a hybrid closed-loop system that attempts to solve this problem by adjusting insulin delivery in response to real-time glucose information from a continuous glucose monitor (CGM). Glucose measurements are sent to the insulin pump in real time, which uses a specialized algorithm to determine whether insulin delivery should be up-titrated, down-titrated, or suspended.⁶

Several studies have shown that AIP technology reduces glucose variability and increases the percentage of time within the optimal glucose range.^1-3,7 Its safety is especially indicated for patients with long-standing DM who often have hypoglycemia unawareness and recurrent episodes of hypoglycemia.⁷ Safety is the major advantage of the hybrid closed-loop system as long duration of DM makes patients particularly prone to emergency department (ED) visits and hospitalizations for severe hypoglycemia.⁸ Recurrent hypoglycemia also is associated with increased cardiovascular mortality in epidemiologic studies.⁹

Safety was the primary endpoint in the pivotal trial in a multicenter clinical study where 124 participants (mean age, 37.8 years; DM duration, 21.7 years; hemoglobin A_1c [HbA_1c], 7.4%) were monitored for 3 months while using a hybrid closed-loop pump, similar to the one used in our study.¹⁰ Remarkably, there were no device-related episodes of severe hypoglycemia or ketoacidosis. There was even a small but significant difference in HbA_1c (7.4% at baseline, 6.9% at 3 months) and of the time in target range measured by CGM from 66.7% at baseline to 72.2% at 3 months). However, the mean age of the population studied was young (mean age, 37.8 years). It is unclear how these results would translate for a population of older patients with T1DM. Moreover, use of AIP systems have not been systematically tested outside of carefully controlled studies, as it would be in middle-aged veterans followed in outpatient US Department of Veterans Affairs (VA) clinics. Such an approach in the context of optimal glucose monitoring combined with use of structured DM education can significantly reduce impaired awareness of hypoglycemia in patients with T1DM of long duration.¹¹

This is the first study to assess the feasibility of AIP technology in a real-world population of older veterans with T1DM in terms of safety and acceptability, because AIP has just recently become available for patient care in the Veterans Health Administration (VHA). This group of patients is of particular interest because they have been largely overlooked in earlier studies. They represent an older population with long-standing DM where hypoglycemia unawareness is often recurrent and incapacitating. In addition, long-standing DM makes optimal glycemic control mandatory to prevent microvascular complications.

Methods

In this retrospective review study,, we examined available data in patients with T1DM at the Malcom Randall VA Medical Center diabetes clinic in Gainesville, Florida, between March and December of 2018 who agreed to use AIP. In this clinic, the AIP system was offered to T1DM patients when the 4-year warranty of a previous insulin pump expired, they had frequent hypoglycemic events, or they were on multiple daily injections and were proficient with carbohydrate counting and adjusting insulin doses and willing to use an insulin pump. Veterans were trained on AIP use by a certified diabetes educator and pump trainer in sessions that lasted 2 to 4 hours depending on previous experience with AIP. Institutional review board approval was obtained at the University of Florida. 

Demographic and clinical data before and after the initiation of AIP were collected, including standard insulin pump/CGM information for the Medtronic 670G and Guardian 3 Sensor AIPs. Several variables were evaluated, including age, gender, year of DM diagnosis, time of initiation of AIP, HbA_1c, download data (percentage sensor wear, time in automated mode and manual mode, time in/above/below range, bolus information, insulin use, average sensor blood glucose, average meter blood glucose, pump settings), weight, body mass index (BMI), glucose meter information, history of hypoglycemia unawareness.

The primary outcome for this study was safety as assessed by percentage of time below target range on glucose sensor (time below target range is defined as < 70 mg/dL). We also addressed the secondary endpoint of efficacy as the percentage of time in-range defined as blood glucose per glucose sensor of 70 mg/dL to 180 mg/dL (efficacy), percentage of glucose sensor wear, and HbA_1c.

Statistics

Comparisons of changes in continuous variables between groups were performed by an analysis of covariance (ANCOVA), adjusting for baseline levels. Fisher exact test (χ²) and unpaired t test were used to compare group differences at baseline for categorical and continuous variables, respectively, while Wilcoxon rank sum test was used for nonnormally distributed values. Changes in continuous measures within the same group were tested by paired t test or Wilcoxon matched-pairs signed rank test when applicable. Analyses were performed using Stata 11.0.

Results

Thirty-seven veterans with T1DM using AIPs in 2018 were evaluated at baseline and at follow up visits (Tables 1 and 2). Time frame for follow-up was approximately 3 months, although there was some variation. Of note, the mean weight and BMI corresponded to mostly lean individuals, consistent with the diagnosis of T1DM.

Time below target range hypoglycemia (sensor glucose < 70 mg/dL) remained low at each follow-up visit (both 1.5%). Percentage of time in automated mode increased from first to second follow-up visit after initiation of AIP (41% vs 53%, P = .06). Percentage of sensor wear numerically increased from first to second follow-up visit (75% vs 85%, P = .39), same as time in range, defined as sensor glucose 70 to 180 mg/dL, from first to second follow-up visit (70% vs 73%, P = .09). Time above range, defined as sensor glucose > 180 mg/dL, demonstrated a strong trend toward decreasing between follow-up appointments (29% to 25%; P = .09). HbA_1c decreased from 7.6% to 7.3% (P = .005).

About half of the patients (18 of 37) reported hypoglycemia unawareness before the initiation of the 670G AIP. On follow-up visit 61% (11 of 18) reported significant improvement in awareness. Of the remaining 18 patients who reported normal awareness before automated mode, 17% (3 of 18) described a new onset unawareness.

Discussion

This study evaluated the safety of adopting a new DM technology in the real world of an outpatient VA clinic. To the best of our knowledge, this is the first study evaluating the use of AIP specifically in a population of middle-aged veterans with longstanding T1DM. After a mean 7 months of follow-up, participants accepted AIP use as evidenced by increased sensor wear over time and experienced improvements in DM measures that indicate successful use (ie, time in automated mode, which represents reduced glycemic variability). These results show success of an AIP approach in a demographically older group of patients.

AIP has been shown to have positive effects on glycemic control such as time in target glucose range (goal ≥ 70%). In our relatively small pilot study, there was trend for an improvement in the time in range from the first to second clinical follow-up visit, suggesting true patient involvement with the use of the device. Studies involving overall younger cohorts have proved that AIP technology is safe and efficacious for outpatient management of T1DM.^7,10,12,13 However, they were all conducted under the safety of a research setting, and trials enrolled a younger population believed to adapt with more ease to this new technology. Tauschmann and colleagues performed a multicenter, parallel randomized controlled trial that compared hybrid closed-loop AIP therapy with sensor-augmented pump therapy in patients with suboptimal T1DM control.¹² Results showed that the hybrid closed-loop system increased the time that the glucose concentration was within the target range (70-180 mg/dL) from 54% in the sensor-augmented pump group to 65% on the closed-loop system (P < .001). A small but significant improvement in HBA_1c (from 8.0 -7.4%) and low rates of hypoglycemia (2.6% of time below 70 mg/dL) were also noted.¹²

A similar benefit was observed in a 2019 landmark study by Brown and colleagues of 168 patients with T1DM at 7 university medical centers who were treated for 6 months with either a closed-loop system (closed-loop group) or a sensor-augmented pump (control group) in a parallel-group, unblinded, randomized trial study.¹³ Mean (SD) time in the target range increased in the closed-loop group from 61% (17) at baseline to 71% (12) during the 6 months. HbA_1c decreased from 7.4 to 7.1% and time ≤ 70 mg/dL was just 1.6%. However, only 13% of patients were aged ≥ 40 years in the study by Tauschmann and colleagues, and mean age was 33 years in the Brown and colleagues study.^12,13 In contrast, the mean (SD) age in our study was 59 (14) years. Our pilot study also showed comparable, or somewhat better results, as mean time in target range was 72%, HbA_1c was 7.3%, and time ≤ 70 mg/dL was just 1.5%.

Limitations

There are some limitations to our study. The small sample size and single-center nature prevent generalization. Also, the veteran population cannot be extrapolated to other populations. For instance, the majority of the patients in this study were male.

Conclusions

We report that an AIP approach for patients with long-standing T1DM is well accepted and engages patients into monitoring their blood sugars and achieving better glycemic control. This was achieved with minimal hypoglycemia in a population where often hypoglycemia unawareness makes DM care a challenge. Future studies within the VHA are needed to fully assess the long-term benefits and cost-effectiveness of this technology in veterans.

From the Department of Pharmaceutical and Health Economics, University of Southern California, Los Angeles, CA, (Drs. Sangha and McCombs), Department of Pediatrics, Keck School of Medicine, and Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, (Dr. Steinberg), and Leonard Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, CA (Dr. McCombs).

Objective: The recommended treatment for children and adolescents under 18 years of age who have a positive test for group A Streptococcus (GAS) are antibiotics using the “test and treat” strategy to detect and treat GAS for pediatric pharyngitis. This study used paid claims data to document the extent to which real-world treatment patterns are consistent with these recommendations. We document the factors correlated with testing and treatment, then examine the effects of receiving a GAS test and being treated with an antibiotic impact the likelihood of a revisit for an acute respiratory tract infection within 28 days.

Methods: This retrospective cohort study used Optum Insight Clinformatics data for medical and pharmacy claims from 2011-2013 to identify episodes of care for children and adolescents with pharyngitis around their index visit (± 6 months). The sample population included children and adolescents under 18 years of age with a diagnosis of pharyngitis. Multivariable logistic regression analyses were used to document factors associated with receipt of GAS test and antibiotic treatment. Next, we used logistic regression models to estimate the impact of test and treat recommendation on revisit risk.

Results: There were 24 685 treatment episodes for children and adolescents diagnosed with pharyngitis. Nearly 47% of these episodes included a GAS test and 48% of tested patients were prescribed an antibiotic prescription. Failing to perform a GAS test increased the risk of a revisit within 28 days by 44%. The use of antibiotics by tested and untested patients had no impact on revisit risk.

Conclusion: While the judicious use of antibiotics is important in managing pharyngitis infections and managing complications, the use of rapid diagnostic tools was found to be the determining factor in reducing revisits for pediatric patients with pharyngitis.

Keywords: pediatrics; pharyngitis; respiratory infections; acute infections; diagnostic tests; group A Streptococcus; antibiotics; revisits.

Acute pharyngitis is a common acute respiratory tract infection (ARTI) in children. Group A β-hemolytic streptococci (GABHS) is the most common bacterial etiology for pediatric pharyngitis, accounting for 15% to 30% of cases.¹

Beyond clinical assessment, laboratory diagnostic testing generally plays a limited role in guiding appropriate antibiotic prescribing for patients with an ARTI.^2,3 Most diagnostic tests require 2 or 3 days to result, incur additional costs, and may delay treatment.⁴ While these tests do not provide clear and timely guidance on which specific antibiotic is appropriate for ARTI patients, this is not the case for patients with pharyngitis.^5,6,7 A rapid diagnostic test exists to identify pharyngitis patients with GABHS which accounts for 1 in 4 children with acute sore throat.^1,4,6 Both the American Academy of Pediatrics and the Infectious Diseases Society of America recommend antibiotic treatment for children and adolescents under 18 years of age who have a positive test for group A Streptococcus (GAS).^8,9 This “test and treat” protocol has been consistently included in the Healthcare Effectiveness Data and Information Set (HEDIS) standards over time for pediatric pharyngitis patients aged 3 to 18 years before dispensing an antibiotic.¹⁰

Sinusitis, pneumonia, and acute otitis media are considered ARTIs where antibiotic treatment is justified. Therefore, pharyngitis of unclear etiology seen with these comorbid infections may not always undergo GAS testing but move directly to the patient being prescribed antibiotics. This analysis enumerates ARTI-related comorbidities present together with the initial coded pharyngitis diagnosis to evaluate their impact on the provider’s decision to test and treat, and on revisit risk.

Antibiotic treatment for GAS patients is likely to eradicate the acute GABHS infection within 10 days. Penicillin and amoxicillin are commonly recommended because of their narrow spectrum of activity, few adverse effects, established efficacy, and modest cost. Alternative antibiotics for patients with penicillin allergy, or with polymicrobial infection seen on culture results, include a first-generation cephalosporin, clindamycin, clarithromycin (Biaxin), or azithromycin (Zithromax).^1,8,11 However, while compliance with these HEDIS guidelines has been evaluated, the outcome effects of following the HEDIS “test and treat” recommendations for children with pharyngitis have not been adequately evaluated.

These outcome evaluations have increasing importance as the latest HEDIS survey has shown testing rates in commercial Preferred Provider Organizations (PPO) falling from 86.4% in 2018 to 75.9% in 2019, the lowest rate of testing since 2009, with similar reductions under 80% for Health Maintenance Organizations (HMO).¹⁰ While health plans may execute cost-benefit analyses and algorithms to forge best practices for GAS testing in children and adolescents presenting with symptoms of pharyngitis, it is important to regard the wasteful resource utilization and additional cost of revisits that may offset any gains accrued by more focused GAS testing outside the existing clinical guidelines and HEDIS measures. This may be of particular importance in documenting infection and sparing antibiotic therapy in toddlers and younger.

The objective of this study was to investigate the correlation between testing and antibiotic use on the likelihood of a revisit for an acute respiratory tract infection within 28 days. To achieve this objective, this investigation consists of 3 sequential analyses. First, we document the factors associated with the decision to test the patient for a GABHS infection using the GAS test. Next, we document the factors associated with the decision to use an antibiotic to treat the patient as a function of having tested the patient. Finally, we investigate the impact of the testing and treatment decisions on the likelihood of a revisit within 28 days.

Methods

Study design

This was a retrospective cohort study of episodes of treatment for pediatric patients with pharyngitis. Episodes were identified using data derived from the Optum Insight Clinformatics claims database provided to the University of Southern California to facilitate the training of graduate students. These data cover commercially insured patients with both medical and pharmacy benefits. Data were retrieved from the 3-year period spanning 2011-2013. An episode of care was identified based on date of the first (index) outpatient visit for a pharyngitis diagnosis (International Classification of Diseases, Ninth Revision [ICD-9]: 462, 463, 034.0). Outpatient visits were defined by visit setting: ambulatory clinics, physician offices, emergency rooms, and urgent care facilities. Each pharyngitis treatment episode was then screened for at least a 6-month enrollment in a health insurance plan prior and subsequent to the index visit using Optum enrollment data. Finally, eligible treatment episodes were restricted to children and adolescents under 18 years of age, who had an index outpatient visit for a primary diagnosis of acute pharyngitis.

A diagnostic profile was created for each episode using the diagnoses recorded for the index visit. Up to 3 diagnoses may be recorded for any outpatient visit and the first recorded diagnosis was assumed to be the primary diagnosis for that episode. Any secondary diagnoses recorded on the index visit were used to define comorbidities present at the index visit. ARTI-related comorbidities included: acute otitis media (AOM), bronchitis, sinusitis, pneumonia, and upper respiratory infection (URI). Other comorbid medical diagnoses were documented using diagnostic data from the pre-index period. Dichotomous variables for the following categories were created: mental disorders, nervous system disorders, respiratory symptoms, fever, injury and poisoning, other, or no diseases.

Prior visits for other respiratory infections in the previous 90 days were also identified for patients based on their index visit for pharyngitis. Similarly, any subsequent visits, within 28 days of the index visit, were also recorded to measure the health outcome for analysis. Practice settings include physician offices and federally qualified health centers, state and local health clinics, outpatient hospitals facilities, emergency departments, and other outpatient settings such as walk-in retail health clinic or ambulatory centers. Providers include primary care physicians (family practice, pediatricians, internal medicine), specialty care physicians (emergency medicine, preventive medicine), nonphysician providers (nurse practitioners, physician assistants) and other providers (urgent care, acute outpatient care, ambulatory care centers). Seasons of the year were determined based on the index date of the episode to account for possible seasonality in pharyngitis treatment. Lastly, a previous visits variable was created to identify whether the child had nonpharyngitis ARTI visits in the 3 months prior to the index visit.

Demographic variables were created based on enrollment and the socioeconomic data available in the Optum socioeconomic status file. These variables include patient age, race, sex, household income, geographic location, practice setting type, provider specialty, and type of insurance. An estimate of patient household income was based on algorithms using census block groups. Income categories were informed by the federal guidelines for a family of 4. A low-income family was defined as earning less than $50 000; a middle-income family earned between $50 000 and $75 000, and a high-income family earned $75 000 and above.¹² Patient insurance type was categorized as HMO, Exclusive Provider Organization (EPO), Point of Service (POS), and PPO. Race was identified as White, Black, Hispanic, and Asian. Patient location was defined according to national census regions.

Outcomes

GAS test

The HEDIS measures for pharyngitis recommend using the GAS test to identify the bacterial etiology of the pharyngitis infection. Patients who received the test were identified based on Current Procedural Terminology (CPT) codes 87070-71, 87081, 87430, 87650-52, and 87880.¹⁰

The pharmacy administrative claims dataset was used to identify study patients who filled a prescription for an antibiotic during their pharyngitis treatment episode. Optum pharmacy data identify the medications received, specifies the date of prescription filling, National Drug Codes, and American Hospital Formulary Service (AHFS) Classification System codes for each medication. We used the AHFS Pharmacologic-Therapeutic classification of antibiotics to create dichotomous variables documenting the antibacterial used by each patient.¹³ These are categorized under antibacterial including penicillins, cephalosporins (first, second, third, fourth generation cephalosporins), macrolides (first generation and others), tetracyclines, sulfonamides, fluoroquinolones (ciprofloxacin, levofloxacin, moxifloxacin), cephamycin, carbapenems, and β-lactam antibiotics (amoxicillin, amoxicillin/clavulanate, cephalexin, cefuroxime, cefdinir).

Revisits to physician or other provider

Revisits within 28 days were used as the measure of patient outcomes related to testing and filling of an antibiotic prescription for acute pharyngitis. Revisits may also be due to a patient returning for a follow-up, alternative treatment, worsening pharyngitis, or for another ARTI. An ARTI-related revisit also increases total resources used to treat pediatric pharyngitis patients.

Statistical analysis

Logistic regression was used for all 3 analyses conducted in this study. First, we determined the patient and treating physician characteristics that impact the decision to use GAS testing for pharyngitis. Second, we identified those factors that impact the decision to use antibiotic prescriptions among children who were diagnosed with pharyngitis adding in the dichotomous variable indicating if the patient had received a GAS test. Third, we used a logit regression analysis to document if receiving a GAS test and/or an antibiotic impacted the likelihood of a revisit by comparing revisit risk. To estimate the effect of testing and/or antibiotic use, we divided patients into 4 groups based on whether the patient received a GAS test and/or an antibiotic prescription. This specification of the analysis of revisits as an outcome focuses on adherence to HEDIS “test and treat” guidelines¹⁰:

1. Patients who were not tested yet filled an antibiotic prescription. This decision was likely based on the clinician’s judgment of the patient’s signs and symptoms, and confirmational testing not performed.
2. Patients who were not tested and did not fill an antibiotic prescription. Apparently, in the clinician’s judgment the patient’s signs and symptoms were such that the infection did not warrant treatment and the clinical presentation did not necessitate the GAS test to confirm the recorded diagnosis of pharyngitis.
3. Patients who were tested and received antibiotic prescription, likely because the test was positive for GABHS.
4. Patients who were tested and did not receive antibiotic prescription.

We tested for statistically significant differences in baseline characteristics across these 4 patient groups using t tests for continuous variables and χ² tests for categorical variables. Odds ratios (OR) and CI were computed for the influential variables included the regression analyses.

We conducted a sensitivity analysis using a model specification which included the dichotomous variables for testing and for treatment, and the interaction term between these variables to assess if treatment effects varied in tested and untested patients. We also estimated this model of revisit risk using revisits within 7 days as the outcome variable.

All analyses were completed using STATA/IC 13 (StataCorp, College Station, TX).

Results

There were 24 685 treatment episodes for children diagnosed with pharyngitis. Nearly 47% of these episodes included GAS testing and 47% of the tested patients filled an antibiotic prescription. Similarly, 53% of patients were not tested and 49% of untested patients filled an antibiotic prescription. As a result, the 4 groups identified for analysis were evenly distributed: untested and no prescription (26.9%), untested and prescription (26.3%), tested and prescription (21.9%), and tested and no prescription (24.9%) (Figure).

Table 1 presents the descriptive statistics for these 4 patient groups. Note first that the rate of revisits within 28 days is under 5% across all groups. Second, the 2 tested groups have a lower revisit rate than the untested groups: the tested and treated have a revisit rate of 3.3%, and the tested and untreated have a revisit rate of 2.4%, while both the untested groups have a revisit rate of nearly 5%. These small absolute differences in revisit rates across groups were statistically significant.

Factors associated with receiving GAS test

Several factors were found to impact the decision to test (Table 2). Only 9.7% of children were reported to have any ARTI coinfection. As expected, these comorbidities resulted in a significantly lower likelihood of receiving the GAS test: AOM, bronchitis, sinusitis, pneumonia, and URI as comorbid infections had a 48%, 41%, 37%, 63%, and 13% lower likelihood of receiving the GAS test, respectively, than those with no comorbidities. Similarly, children with fever and respiratory symptoms were 35% and 45% less likely to receiving the GAS test, respectively. This is consistent with our expectation that comorbid ARTI infections will lead many providers to forgo testing.

Provider type and patient age also plays a role in receipt of the GAS test. Relative to outpatient facility providers, primary care physicians were 24% more likely and specialty physicians were 38% less likely of employing the GAS test. The child’s age played a significant role in receipt of the GAS test. Children aged 1 to 5 years and 5 to 12 years were 15% and 14% more likely to receive the test compared to children older than 12 years.

Pharyngitis patients have disproportionately higher odds of receiving a GAS test in most regions of the country compared to the Pacific region. For instance, children in the Mid-Atlantic region have 51% higher odds of receiving a GAS test while children in New England have 80% higher odds of receiving the same test.

Black children have 11% lower odds of receiving the GAS test compared to White children. Both middle-income and high-income children have 12% and 32% higher odds of receiving the test compared to low-income children. Compared to office-based visits, children visiting a clinic were twice as likely to receive a GAS test while those seen in the emergency room have 43% lower odds of receiving a GAS test. Hospital outpatient departments, which account for less than 1% of all visits, rarely used a GAS test which could be a statistical artifact due to small sample size. Lastly, insurance and season of the year had no significant impact of receipt of a GAS test.

Factors associated with receiving antibiotic prescription

Surprisingly, receiving the GAS test has a small but insignificant impact on the likelihood that the patient will receive an antibiotic prescription (Table 3) (Adjusted OR = 1.055, P = .07). After controlling for receipt of a GAS test, children with AOM and sinusitis comorbidities have an increased likelihood of being prescribed an antibiotic. Children with URI have a lower likelihood of being prescribed an antibiotic. Additionally, relative to primary care physicians, children visiting nonphysician providers for pharyngitis were more likely to be prescribed an antibiotic.

Children under 12 years of age were more likely to use an antibiotic compared to children 12 years and older. Geographically, there is some evidence of regional variation in antibiotic use as well. Children in the south Atlantic, west-south central, and southeast central regions had a significantly lower odds of being prescribed an antibiotic respectively than pharyngitis patients in the Pacific region. Black children had a 10% lower likelihood of being prescribed an antibiotic compared to White children, possibly related to their lower rate of GAS testing. Compared to office-based visits, children visiting a clinic were less likely to use an antibiotic. Household income, insurance type, and season had no significant impact on revisit risk.

Effects of GAS test and antibiotic prescriptions on likelihood of revisits

The multivariate analysis of the risk of a revisit within 28 days is presented in Table 4. Children with pharyngitis who tested and did not receive an antibiotic serve as the reference comparison group for this analysis to illustrate the impact of using the GAS test and treatment with an antibiotic. The results in Table 4 are quite clear: patients who receive the GAS test were significantly less likely to have a revisit within 28 days. Moreover, within the group of patients who were tested, those not receiving an antibiotic, presumedly because their GAS test was negative, experienced the lowest risk of a revisit. This result is consistent with the data in Table 1. Moreover, using an antibiotic had no impact on the likelihood of a revisit in patients not receiving the GAS test. This result is also consistent with Table 1.

Other results from the analysis of revisit risk may be of interest to clinicians. Pharyngitis patients with a prior episode of treatment within 90 days for an acute respiratory tract infection were more than 7 times more likely to experience a revisit within 28 days of the pharyngitis diagnosis than patients without a history of recent ARTI infections. Age is also a risk factor in likelihood of initiating a revisit. Children under 1 year and children aged 1 to 5 years were more likely to have a revisit than children aged more than 12 years. Compared to White children, Black children were 25% (P = .04) less likely to have a revisit. The care setting also has a significant impact on revisit risk. Children visiting outpatient hospital and other care settings had a significantly higher revisit risk than those visiting a physician’s office. Lastly, household income, geographic region, season, medical comorbidities, gender, and insurance type have no significant impact on revisit risk.

Sensitivity analysis

The results from the analysis of 7-day and 28-day revisit risk are summarized in Table 5. These results indicate that patients who were tested had a more significant decrease in revisit risk at 7 days (72%) than was evident at 28 days (47% reduction). Receiving an antibiotic, with or without the test, had no impact on revisit risk.

Discussion

Published data on revisits for pharyngitis are lacking with the concentration of prior research focused more on systemic complications of undertreated GABHS disease or on identifying carrier status. Our study results suggest that GAS testing is the most important factor in reducing revisit risk. Being prescribed an antibiotic, on its own, does not have a significant impact on the risk of a revisit. However, once the GAS test is used, the decision not to use an antibiotic was correlated with the lowest revisit rate, likely because the source of the pharyngitis infection was viral and more likely to resolve without a revisit. Prior studies have reported variable rates of testing among children with pharyngitis prescribed an antibiotic, ranging from 23% to 91%,^14,15 with testing important toward more appropriate antibiotic use.¹⁶ More recently, among more than 67 000 patients aged 3 to 21 years presenting with sore throat and receiving a GAS test, 32.6% were positive.¹⁷

Our analysis found that more than 46% of pediatric pharyngitis patients were given the rapid GAS test. While this testing rate is substantially lower than HEDIS recommendations and lower than testing rates achieved by several health maintenance organizations,¹⁰ it is similar to the 53% of children receiving such testing in a recent National Ambulatory Medical Care Survey.¹⁸ Furthermore, we found that when antibiotics are prescribed following a GAS test, the revisit risk is not significantly reduced, possibly because antibiotics lower revisit risk when informed by diagnostic testing tools that determine the infectious organism. This is supported by a similar population analysis in which we observed reduced revisit rates in children with AOM managed with antibiotics within 3 days of index diagnosis.¹⁹

Several other factors also affect the likelihood of a child receiving the GAS test. Children aged 1 to 12 years were significantly more likely to receive the GAS test than children over the age of 12. This included children in the 1 to 5 years old bracket who had a 15% higher likelihood of undergoing a GAS test, despite children less than 3 years of age as not recommended targets for GAS testing.²⁰ As expected, children with reported ARTI-associated comorbidities were also less likely to receive a GAS test. Additionally, specialty care physicians were less inclined to implement the GAS test, possibly because of diagnostic confidence without testing or referral after GAS was ruled out. Black and low-income children had statistically lower odds of receiving the test, even after controlling for other factors, and yet were less likely to consume a revisit. As the overall data suggested more revisits in those not tested, further study is needed to examine if race or income discrepancies are equity based. Finally, children in the Pacific region, compared to the rest of the nation, were the least likely to receive a GAS test and yet there were no significant differences in revisit rates by region. Regional differences in antibiotic use were also observed in our study, as has been seen by others.²¹

After statistically controlling for having received the diagnostic GAS test and filled a prescription for an antibiotic, there are multitude of factors that independently affect the revisit risk, the most important of which if which was a history of an ARTI infection in the prior 90 days. While prior visit history had no impact on the likelihood of being tested or filling an antibiotic, patients with prior visits were more than 7 times more likely to consume a revisit. This was not reflected in nor related to comorbid ARTIs as these patients did not have statistically higher revisits than those with pharyngitis as the sole-coded diagnosis. Moreover, speculation for bacterial etiology of primary or superinfection based on a recent history of ARTI accounting for revisits seems unlikely as it did not yield greater antibiotic use in that group. Further analysis is required to determine the clinical and behavioral factors that promote for prior ARTI history as a major factor in revisit risk after an index visit for pharyngitis.

Children aged between 1 and 5 years, though 15% more likely to be tested than those aged 12 through 17 years, were also 39% more likely to initiate a revisit compared to older children when statistically controlling for other covariates. This perhaps suggests longer illness, wrong diagnosis, delay in appropriate treatment, or more caution by parents and providers in this age group. Justification for testing children less than 3 years of age who are outside of the HEDIS suggested age group, when clinical judgement does not point to another infection source, can result in positivity rates between 22% and 30% as previously observed.^22,23 Patients visiting nonphysician providers and outpatient facility providers were less likely to have a revisit than those visiting primary and specialty care physicians, though slightly higher propensity for antibiotic prescriptions was seen for nonphysician providers. Pediatricians have been noted to be less likely to prescribe antibiotics without GAS testing than nonpediatric providers, and more guidelines-compliant in prescribing.²⁴

Recommendations to not test children under 3 years of age are based on the lack of acute rheumatic fever and other complications in this age group together with more frequent viral syndromes. Selectivity in applying clinical criteria to testing can be attempted to separate bacterial from viral illness. Postnasal drainage/rhinorrhea, hoarse voice, and cough have been used successfully to identify those with viral illness and less need for testing, with greater certainty of low risk for GABHS in those over 11 years of age without tonsillar exudates, cervical adenopathy, or fever.¹⁷ However, the marginal benefits of those who have all 3 features of viral illness versus none in identifying GAS positivity was 23.3% vs 37.6% - helpful, but certainly not diminishing the need for testing. These constitutional findings of viral URI also do not exclude the GAS carrier state that features these symptoms.²⁵ Others have reinforced the doubt of pharyngeal exudates as the premier diagnostic finding for test-positive GAS.²⁶

This study had several limitations. The Optum claims dataset only contains ICD-9 codes for diagnoses. It does not include data on infection severity and clinical findings related to symptoms, thus empiric treatment warranted based in clinical severity is not assessed. Antibiotics are commonly available as generics and very inexpensive. Patients may fill and pay for these prescriptions directly, in which case, a claim for payment may not be filed with Optum. This could result in an undercount of treated patients in our study.

There is no corresponding problem of missing medical claims for GAS testing which were obtained from the CPT codes within the Optum claims data set. However, we elected not to verify the test results due to these data being missing for 75% of the study population. Nevertheless, this study’s focus was less about justifying antibiotic treatment, but dealt with the outcomes generated by testing and treatment. Toward that end, we used CPT codes to identify a revisit, and while those can at times be affected by financial reimbursement incentives, differences related to revisits in the 4 patient groups should not be subject to bias.

Conclusion

This study used data from real world practices to document the patterns of GAS testing and antibiotic use in pediatric pharyngitis patients. Revisit rates were under 5% for all patient groups and the use of rapid diagnostic tools were found to be the determining factor in further reducing the risk of revisits. This supports the need for compliance with the HEDIS quality metric for pharyngitis to the recommended levels of rapid testing which have been falling in recent years. Use of more accurate antigen and newer molecular detection testing methods may help further delineate important factors in determining pediatric pharyngitis treatment and need for revisits.²⁷

Corresponding author: Jeffrey McCombs, MD, University of Southern California School of Pharmacy, Department of Pharmaceutical and Health Economics, Leonard D. Schaeffer Center for Health Policy & Economics, 635 Downey Way, Verna & Peter Dauterive Hall 310, Los Angeles, CA 90089-3333; [email protected].

Financial disclosures: None.

From the Department of Pharmaceutical and Health Economics, University of Southern California, Los Angeles, CA, (Drs. Sangha and McCombs), Department of Pediatrics, Keck School of Medicine, and Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, (Dr. Steinberg), and Leonard Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, CA (Dr. McCombs).

Objective: The recommended treatment for children and adolescents under 18 years of age who have a positive test for group A Streptococcus (GAS) are antibiotics using the “test and treat” strategy to detect and treat GAS for pediatric pharyngitis. This study used paid claims data to document the extent to which real-world treatment patterns are consistent with these recommendations. We document the factors correlated with testing and treatment, then examine the effects of receiving a GAS test and being treated with an antibiotic impact the likelihood of a revisit for an acute respiratory tract infection within 28 days.

Methods: This retrospective cohort study used Optum Insight Clinformatics data for medical and pharmacy claims from 2011-2013 to identify episodes of care for children and adolescents with pharyngitis around their index visit (± 6 months). The sample population included children and adolescents under 18 years of age with a diagnosis of pharyngitis. Multivariable logistic regression analyses were used to document factors associated with receipt of GAS test and antibiotic treatment. Next, we used logistic regression models to estimate the impact of test and treat recommendation on revisit risk.

Results: There were 24 685 treatment episodes for children and adolescents diagnosed with pharyngitis. Nearly 47% of these episodes included a GAS test and 48% of tested patients were prescribed an antibiotic prescription. Failing to perform a GAS test increased the risk of a revisit within 28 days by 44%. The use of antibiotics by tested and untested patients had no impact on revisit risk.

Conclusion: While the judicious use of antibiotics is important in managing pharyngitis infections and managing complications, the use of rapid diagnostic tools was found to be the determining factor in reducing revisits for pediatric patients with pharyngitis.

Keywords: pediatrics; pharyngitis; respiratory infections; acute infections; diagnostic tests; group A Streptococcus; antibiotics; revisits.

Acute pharyngitis is a common acute respiratory tract infection (ARTI) in children. Group A β-hemolytic streptococci (GABHS) is the most common bacterial etiology for pediatric pharyngitis, accounting for 15% to 30% of cases.¹

Beyond clinical assessment, laboratory diagnostic testing generally plays a limited role in guiding appropriate antibiotic prescribing for patients with an ARTI.^2,3 Most diagnostic tests require 2 or 3 days to result, incur additional costs, and may delay treatment.⁴ While these tests do not provide clear and timely guidance on which specific antibiotic is appropriate for ARTI patients, this is not the case for patients with pharyngitis.^5,6,7 A rapid diagnostic test exists to identify pharyngitis patients with GABHS which accounts for 1 in 4 children with acute sore throat.^1,4,6 Both the American Academy of Pediatrics and the Infectious Diseases Society of America recommend antibiotic treatment for children and adolescents under 18 years of age who have a positive test for group A Streptococcus (GAS).^8,9 This “test and treat” protocol has been consistently included in the Healthcare Effectiveness Data and Information Set (HEDIS) standards over time for pediatric pharyngitis patients aged 3 to 18 years before dispensing an antibiotic.¹⁰

Sinusitis, pneumonia, and acute otitis media are considered ARTIs where antibiotic treatment is justified. Therefore, pharyngitis of unclear etiology seen with these comorbid infections may not always undergo GAS testing but move directly to the patient being prescribed antibiotics. This analysis enumerates ARTI-related comorbidities present together with the initial coded pharyngitis diagnosis to evaluate their impact on the provider’s decision to test and treat, and on revisit risk.

Antibiotic treatment for GAS patients is likely to eradicate the acute GABHS infection within 10 days. Penicillin and amoxicillin are commonly recommended because of their narrow spectrum of activity, few adverse effects, established efficacy, and modest cost. Alternative antibiotics for patients with penicillin allergy, or with polymicrobial infection seen on culture results, include a first-generation cephalosporin, clindamycin, clarithromycin (Biaxin), or azithromycin (Zithromax).^1,8,11 However, while compliance with these HEDIS guidelines has been evaluated, the outcome effects of following the HEDIS “test and treat” recommendations for children with pharyngitis have not been adequately evaluated.

These outcome evaluations have increasing importance as the latest HEDIS survey has shown testing rates in commercial Preferred Provider Organizations (PPO) falling from 86.4% in 2018 to 75.9% in 2019, the lowest rate of testing since 2009, with similar reductions under 80% for Health Maintenance Organizations (HMO).¹⁰ While health plans may execute cost-benefit analyses and algorithms to forge best practices for GAS testing in children and adolescents presenting with symptoms of pharyngitis, it is important to regard the wasteful resource utilization and additional cost of revisits that may offset any gains accrued by more focused GAS testing outside the existing clinical guidelines and HEDIS measures. This may be of particular importance in documenting infection and sparing antibiotic therapy in toddlers and younger.

The objective of this study was to investigate the correlation between testing and antibiotic use on the likelihood of a revisit for an acute respiratory tract infection within 28 days. To achieve this objective, this investigation consists of 3 sequential analyses. First, we document the factors associated with the decision to test the patient for a GABHS infection using the GAS test. Next, we document the factors associated with the decision to use an antibiotic to treat the patient as a function of having tested the patient. Finally, we investigate the impact of the testing and treatment decisions on the likelihood of a revisit within 28 days.

Methods

Study design

This was a retrospective cohort study of episodes of treatment for pediatric patients with pharyngitis. Episodes were identified using data derived from the Optum Insight Clinformatics claims database provided to the University of Southern California to facilitate the training of graduate students. These data cover commercially insured patients with both medical and pharmacy benefits. Data were retrieved from the 3-year period spanning 2011-2013. An episode of care was identified based on date of the first (index) outpatient visit for a pharyngitis diagnosis (International Classification of Diseases, Ninth Revision [ICD-9]: 462, 463, 034.0). Outpatient visits were defined by visit setting: ambulatory clinics, physician offices, emergency rooms, and urgent care facilities. Each pharyngitis treatment episode was then screened for at least a 6-month enrollment in a health insurance plan prior and subsequent to the index visit using Optum enrollment data. Finally, eligible treatment episodes were restricted to children and adolescents under 18 years of age, who had an index outpatient visit for a primary diagnosis of acute pharyngitis.

A diagnostic profile was created for each episode using the diagnoses recorded for the index visit. Up to 3 diagnoses may be recorded for any outpatient visit and the first recorded diagnosis was assumed to be the primary diagnosis for that episode. Any secondary diagnoses recorded on the index visit were used to define comorbidities present at the index visit. ARTI-related comorbidities included: acute otitis media (AOM), bronchitis, sinusitis, pneumonia, and upper respiratory infection (URI). Other comorbid medical diagnoses were documented using diagnostic data from the pre-index period. Dichotomous variables for the following categories were created: mental disorders, nervous system disorders, respiratory symptoms, fever, injury and poisoning, other, or no diseases.

Prior visits for other respiratory infections in the previous 90 days were also identified for patients based on their index visit for pharyngitis. Similarly, any subsequent visits, within 28 days of the index visit, were also recorded to measure the health outcome for analysis. Practice settings include physician offices and federally qualified health centers, state and local health clinics, outpatient hospitals facilities, emergency departments, and other outpatient settings such as walk-in retail health clinic or ambulatory centers. Providers include primary care physicians (family practice, pediatricians, internal medicine), specialty care physicians (emergency medicine, preventive medicine), nonphysician providers (nurse practitioners, physician assistants) and other providers (urgent care, acute outpatient care, ambulatory care centers). Seasons of the year were determined based on the index date of the episode to account for possible seasonality in pharyngitis treatment. Lastly, a previous visits variable was created to identify whether the child had nonpharyngitis ARTI visits in the 3 months prior to the index visit.

Demographic variables were created based on enrollment and the socioeconomic data available in the Optum socioeconomic status file. These variables include patient age, race, sex, household income, geographic location, practice setting type, provider specialty, and type of insurance. An estimate of patient household income was based on algorithms using census block groups. Income categories were informed by the federal guidelines for a family of 4. A low-income family was defined as earning less than $50 000; a middle-income family earned between $50 000 and $75 000, and a high-income family earned $75 000 and above.¹² Patient insurance type was categorized as HMO, Exclusive Provider Organization (EPO), Point of Service (POS), and PPO. Race was identified as White, Black, Hispanic, and Asian. Patient location was defined according to national census regions.

Outcomes

GAS test

The HEDIS measures for pharyngitis recommend using the GAS test to identify the bacterial etiology of the pharyngitis infection. Patients who received the test were identified based on Current Procedural Terminology (CPT) codes 87070-71, 87081, 87430, 87650-52, and 87880.¹⁰

The pharmacy administrative claims dataset was used to identify study patients who filled a prescription for an antibiotic during their pharyngitis treatment episode. Optum pharmacy data identify the medications received, specifies the date of prescription filling, National Drug Codes, and American Hospital Formulary Service (AHFS) Classification System codes for each medication. We used the AHFS Pharmacologic-Therapeutic classification of antibiotics to create dichotomous variables documenting the antibacterial used by each patient.¹³ These are categorized under antibacterial including penicillins, cephalosporins (first, second, third, fourth generation cephalosporins), macrolides (first generation and others), tetracyclines, sulfonamides, fluoroquinolones (ciprofloxacin, levofloxacin, moxifloxacin), cephamycin, carbapenems, and β-lactam antibiotics (amoxicillin, amoxicillin/clavulanate, cephalexin, cefuroxime, cefdinir).

Revisits to physician or other provider

Revisits within 28 days were used as the measure of patient outcomes related to testing and filling of an antibiotic prescription for acute pharyngitis. Revisits may also be due to a patient returning for a follow-up, alternative treatment, worsening pharyngitis, or for another ARTI. An ARTI-related revisit also increases total resources used to treat pediatric pharyngitis patients.

Statistical analysis

Logistic regression was used for all 3 analyses conducted in this study. First, we determined the patient and treating physician characteristics that impact the decision to use GAS testing for pharyngitis. Second, we identified those factors that impact the decision to use antibiotic prescriptions among children who were diagnosed with pharyngitis adding in the dichotomous variable indicating if the patient had received a GAS test. Third, we used a logit regression analysis to document if receiving a GAS test and/or an antibiotic impacted the likelihood of a revisit by comparing revisit risk. To estimate the effect of testing and/or antibiotic use, we divided patients into 4 groups based on whether the patient received a GAS test and/or an antibiotic prescription. This specification of the analysis of revisits as an outcome focuses on adherence to HEDIS “test and treat” guidelines¹⁰:

1. Patients who were not tested yet filled an antibiotic prescription. This decision was likely based on the clinician’s judgment of the patient’s signs and symptoms, and confirmational testing not performed.
2. Patients who were not tested and did not fill an antibiotic prescription. Apparently, in the clinician’s judgment the patient’s signs and symptoms were such that the infection did not warrant treatment and the clinical presentation did not necessitate the GAS test to confirm the recorded diagnosis of pharyngitis.
3. Patients who were tested and received antibiotic prescription, likely because the test was positive for GABHS.
4. Patients who were tested and did not receive antibiotic prescription.

We tested for statistically significant differences in baseline characteristics across these 4 patient groups using t tests for continuous variables and χ² tests for categorical variables. Odds ratios (OR) and CI were computed for the influential variables included the regression analyses.

We conducted a sensitivity analysis using a model specification which included the dichotomous variables for testing and for treatment, and the interaction term between these variables to assess if treatment effects varied in tested and untested patients. We also estimated this model of revisit risk using revisits within 7 days as the outcome variable.

All analyses were completed using STATA/IC 13 (StataCorp, College Station, TX).

Results

There were 24 685 treatment episodes for children diagnosed with pharyngitis. Nearly 47% of these episodes included GAS testing and 47% of the tested patients filled an antibiotic prescription. Similarly, 53% of patients were not tested and 49% of untested patients filled an antibiotic prescription. As a result, the 4 groups identified for analysis were evenly distributed: untested and no prescription (26.9%), untested and prescription (26.3%), tested and prescription (21.9%), and tested and no prescription (24.9%) (Figure).

Table 1 presents the descriptive statistics for these 4 patient groups. Note first that the rate of revisits within 28 days is under 5% across all groups. Second, the 2 tested groups have a lower revisit rate than the untested groups: the tested and treated have a revisit rate of 3.3%, and the tested and untreated have a revisit rate of 2.4%, while both the untested groups have a revisit rate of nearly 5%. These small absolute differences in revisit rates across groups were statistically significant.

Factors associated with receiving GAS test

Several factors were found to impact the decision to test (Table 2). Only 9.7% of children were reported to have any ARTI coinfection. As expected, these comorbidities resulted in a significantly lower likelihood of receiving the GAS test: AOM, bronchitis, sinusitis, pneumonia, and URI as comorbid infections had a 48%, 41%, 37%, 63%, and 13% lower likelihood of receiving the GAS test, respectively, than those with no comorbidities. Similarly, children with fever and respiratory symptoms were 35% and 45% less likely to receiving the GAS test, respectively. This is consistent with our expectation that comorbid ARTI infections will lead many providers to forgo testing.

Provider type and patient age also plays a role in receipt of the GAS test. Relative to outpatient facility providers, primary care physicians were 24% more likely and specialty physicians were 38% less likely of employing the GAS test. The child’s age played a significant role in receipt of the GAS test. Children aged 1 to 5 years and 5 to 12 years were 15% and 14% more likely to receive the test compared to children older than 12 years.

Pharyngitis patients have disproportionately higher odds of receiving a GAS test in most regions of the country compared to the Pacific region. For instance, children in the Mid-Atlantic region have 51% higher odds of receiving a GAS test while children in New England have 80% higher odds of receiving the same test.

Black children have 11% lower odds of receiving the GAS test compared to White children. Both middle-income and high-income children have 12% and 32% higher odds of receiving the test compared to low-income children. Compared to office-based visits, children visiting a clinic were twice as likely to receive a GAS test while those seen in the emergency room have 43% lower odds of receiving a GAS test. Hospital outpatient departments, which account for less than 1% of all visits, rarely used a GAS test which could be a statistical artifact due to small sample size. Lastly, insurance and season of the year had no significant impact of receipt of a GAS test.

Factors associated with receiving antibiotic prescription

Surprisingly, receiving the GAS test has a small but insignificant impact on the likelihood that the patient will receive an antibiotic prescription (Table 3) (Adjusted OR = 1.055, P = .07). After controlling for receipt of a GAS test, children with AOM and sinusitis comorbidities have an increased likelihood of being prescribed an antibiotic. Children with URI have a lower likelihood of being prescribed an antibiotic. Additionally, relative to primary care physicians, children visiting nonphysician providers for pharyngitis were more likely to be prescribed an antibiotic.

Children under 12 years of age were more likely to use an antibiotic compared to children 12 years and older. Geographically, there is some evidence of regional variation in antibiotic use as well. Children in the south Atlantic, west-south central, and southeast central regions had a significantly lower odds of being prescribed an antibiotic respectively than pharyngitis patients in the Pacific region. Black children had a 10% lower likelihood of being prescribed an antibiotic compared to White children, possibly related to their lower rate of GAS testing. Compared to office-based visits, children visiting a clinic were less likely to use an antibiotic. Household income, insurance type, and season had no significant impact on revisit risk.

Effects of GAS test and antibiotic prescriptions on likelihood of revisits

The multivariate analysis of the risk of a revisit within 28 days is presented in Table 4. Children with pharyngitis who tested and did not receive an antibiotic serve as the reference comparison group for this analysis to illustrate the impact of using the GAS test and treatment with an antibiotic. The results in Table 4 are quite clear: patients who receive the GAS test were significantly less likely to have a revisit within 28 days. Moreover, within the group of patients who were tested, those not receiving an antibiotic, presumedly because their GAS test was negative, experienced the lowest risk of a revisit. This result is consistent with the data in Table 1. Moreover, using an antibiotic had no impact on the likelihood of a revisit in patients not receiving the GAS test. This result is also consistent with Table 1.

Other results from the analysis of revisit risk may be of interest to clinicians. Pharyngitis patients with a prior episode of treatment within 90 days for an acute respiratory tract infection were more than 7 times more likely to experience a revisit within 28 days of the pharyngitis diagnosis than patients without a history of recent ARTI infections. Age is also a risk factor in likelihood of initiating a revisit. Children under 1 year and children aged 1 to 5 years were more likely to have a revisit than children aged more than 12 years. Compared to White children, Black children were 25% (P = .04) less likely to have a revisit. The care setting also has a significant impact on revisit risk. Children visiting outpatient hospital and other care settings had a significantly higher revisit risk than those visiting a physician’s office. Lastly, household income, geographic region, season, medical comorbidities, gender, and insurance type have no significant impact on revisit risk.

Sensitivity analysis

The results from the analysis of 7-day and 28-day revisit risk are summarized in Table 5. These results indicate that patients who were tested had a more significant decrease in revisit risk at 7 days (72%) than was evident at 28 days (47% reduction). Receiving an antibiotic, with or without the test, had no impact on revisit risk.

Discussion

Published data on revisits for pharyngitis are lacking with the concentration of prior research focused more on systemic complications of undertreated GABHS disease or on identifying carrier status. Our study results suggest that GAS testing is the most important factor in reducing revisit risk. Being prescribed an antibiotic, on its own, does not have a significant impact on the risk of a revisit. However, once the GAS test is used, the decision not to use an antibiotic was correlated with the lowest revisit rate, likely because the source of the pharyngitis infection was viral and more likely to resolve without a revisit. Prior studies have reported variable rates of testing among children with pharyngitis prescribed an antibiotic, ranging from 23% to 91%,^14,15 with testing important toward more appropriate antibiotic use.¹⁶ More recently, among more than 67 000 patients aged 3 to 21 years presenting with sore throat and receiving a GAS test, 32.6% were positive.¹⁷

Our analysis found that more than 46% of pediatric pharyngitis patients were given the rapid GAS test. While this testing rate is substantially lower than HEDIS recommendations and lower than testing rates achieved by several health maintenance organizations,¹⁰ it is similar to the 53% of children receiving such testing in a recent National Ambulatory Medical Care Survey.¹⁸ Furthermore, we found that when antibiotics are prescribed following a GAS test, the revisit risk is not significantly reduced, possibly because antibiotics lower revisit risk when informed by diagnostic testing tools that determine the infectious organism. This is supported by a similar population analysis in which we observed reduced revisit rates in children with AOM managed with antibiotics within 3 days of index diagnosis.¹⁹

Several other factors also affect the likelihood of a child receiving the GAS test. Children aged 1 to 12 years were significantly more likely to receive the GAS test than children over the age of 12. This included children in the 1 to 5 years old bracket who had a 15% higher likelihood of undergoing a GAS test, despite children less than 3 years of age as not recommended targets for GAS testing.²⁰ As expected, children with reported ARTI-associated comorbidities were also less likely to receive a GAS test. Additionally, specialty care physicians were less inclined to implement the GAS test, possibly because of diagnostic confidence without testing or referral after GAS was ruled out. Black and low-income children had statistically lower odds of receiving the test, even after controlling for other factors, and yet were less likely to consume a revisit. As the overall data suggested more revisits in those not tested, further study is needed to examine if race or income discrepancies are equity based. Finally, children in the Pacific region, compared to the rest of the nation, were the least likely to receive a GAS test and yet there were no significant differences in revisit rates by region. Regional differences in antibiotic use were also observed in our study, as has been seen by others.²¹

After statistically controlling for having received the diagnostic GAS test and filled a prescription for an antibiotic, there are multitude of factors that independently affect the revisit risk, the most important of which if which was a history of an ARTI infection in the prior 90 days. While prior visit history had no impact on the likelihood of being tested or filling an antibiotic, patients with prior visits were more than 7 times more likely to consume a revisit. This was not reflected in nor related to comorbid ARTIs as these patients did not have statistically higher revisits than those with pharyngitis as the sole-coded diagnosis. Moreover, speculation for bacterial etiology of primary or superinfection based on a recent history of ARTI accounting for revisits seems unlikely as it did not yield greater antibiotic use in that group. Further analysis is required to determine the clinical and behavioral factors that promote for prior ARTI history as a major factor in revisit risk after an index visit for pharyngitis.

Children aged between 1 and 5 years, though 15% more likely to be tested than those aged 12 through 17 years, were also 39% more likely to initiate a revisit compared to older children when statistically controlling for other covariates. This perhaps suggests longer illness, wrong diagnosis, delay in appropriate treatment, or more caution by parents and providers in this age group. Justification for testing children less than 3 years of age who are outside of the HEDIS suggested age group, when clinical judgement does not point to another infection source, can result in positivity rates between 22% and 30% as previously observed.^22,23 Patients visiting nonphysician providers and outpatient facility providers were less likely to have a revisit than those visiting primary and specialty care physicians, though slightly higher propensity for antibiotic prescriptions was seen for nonphysician providers. Pediatricians have been noted to be less likely to prescribe antibiotics without GAS testing than nonpediatric providers, and more guidelines-compliant in prescribing.²⁴

Recommendations to not test children under 3 years of age are based on the lack of acute rheumatic fever and other complications in this age group together with more frequent viral syndromes. Selectivity in applying clinical criteria to testing can be attempted to separate bacterial from viral illness. Postnasal drainage/rhinorrhea, hoarse voice, and cough have been used successfully to identify those with viral illness and less need for testing, with greater certainty of low risk for GABHS in those over 11 years of age without tonsillar exudates, cervical adenopathy, or fever.¹⁷ However, the marginal benefits of those who have all 3 features of viral illness versus none in identifying GAS positivity was 23.3% vs 37.6% - helpful, but certainly not diminishing the need for testing. These constitutional findings of viral URI also do not exclude the GAS carrier state that features these symptoms.²⁵ Others have reinforced the doubt of pharyngeal exudates as the premier diagnostic finding for test-positive GAS.²⁶

This study had several limitations. The Optum claims dataset only contains ICD-9 codes for diagnoses. It does not include data on infection severity and clinical findings related to symptoms, thus empiric treatment warranted based in clinical severity is not assessed. Antibiotics are commonly available as generics and very inexpensive. Patients may fill and pay for these prescriptions directly, in which case, a claim for payment may not be filed with Optum. This could result in an undercount of treated patients in our study.

There is no corresponding problem of missing medical claims for GAS testing which were obtained from the CPT codes within the Optum claims data set. However, we elected not to verify the test results due to these data being missing for 75% of the study population. Nevertheless, this study’s focus was less about justifying antibiotic treatment, but dealt with the outcomes generated by testing and treatment. Toward that end, we used CPT codes to identify a revisit, and while those can at times be affected by financial reimbursement incentives, differences related to revisits in the 4 patient groups should not be subject to bias.

Conclusion

This study used data from real world practices to document the patterns of GAS testing and antibiotic use in pediatric pharyngitis patients. Revisit rates were under 5% for all patient groups and the use of rapid diagnostic tools were found to be the determining factor in further reducing the risk of revisits. This supports the need for compliance with the HEDIS quality metric for pharyngitis to the recommended levels of rapid testing which have been falling in recent years. Use of more accurate antigen and newer molecular detection testing methods may help further delineate important factors in determining pediatric pharyngitis treatment and need for revisits.²⁷

Corresponding author: Jeffrey McCombs, MD, University of Southern California School of Pharmacy, Department of Pharmaceutical and Health Economics, Leonard D. Schaeffer Center for Health Policy & Economics, 635 Downey Way, Verna & Peter Dauterive Hall 310, Los Angeles, CA 90089-3333; [email protected].

Financial disclosures: None.

From the Department of Pharmaceutical and Health Economics, University of Southern California, Los Angeles, CA, (Drs. Sangha and McCombs), Department of Pediatrics, Keck School of Medicine, and Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, (Dr. Steinberg), and Leonard Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, CA (Dr. McCombs).

Objective: The recommended treatment for children and adolescents under 18 years of age who have a positive test for group A Streptococcus (GAS) are antibiotics using the “test and treat” strategy to detect and treat GAS for pediatric pharyngitis. This study used paid claims data to document the extent to which real-world treatment patterns are consistent with these recommendations. We document the factors correlated with testing and treatment, then examine the effects of receiving a GAS test and being treated with an antibiotic impact the likelihood of a revisit for an acute respiratory tract infection within 28 days.

Methods: This retrospective cohort study used Optum Insight Clinformatics data for medical and pharmacy claims from 2011-2013 to identify episodes of care for children and adolescents with pharyngitis around their index visit (± 6 months). The sample population included children and adolescents under 18 years of age with a diagnosis of pharyngitis. Multivariable logistic regression analyses were used to document factors associated with receipt of GAS test and antibiotic treatment. Next, we used logistic regression models to estimate the impact of test and treat recommendation on revisit risk.

Results: There were 24 685 treatment episodes for children and adolescents diagnosed with pharyngitis. Nearly 47% of these episodes included a GAS test and 48% of tested patients were prescribed an antibiotic prescription. Failing to perform a GAS test increased the risk of a revisit within 28 days by 44%. The use of antibiotics by tested and untested patients had no impact on revisit risk.

Conclusion: While the judicious use of antibiotics is important in managing pharyngitis infections and managing complications, the use of rapid diagnostic tools was found to be the determining factor in reducing revisits for pediatric patients with pharyngitis.

Keywords: pediatrics; pharyngitis; respiratory infections; acute infections; diagnostic tests; group A Streptococcus; antibiotics; revisits.

Acute pharyngitis is a common acute respiratory tract infection (ARTI) in children. Group A β-hemolytic streptococci (GABHS) is the most common bacterial etiology for pediatric pharyngitis, accounting for 15% to 30% of cases.¹

Beyond clinical assessment, laboratory diagnostic testing generally plays a limited role in guiding appropriate antibiotic prescribing for patients with an ARTI.^2,3 Most diagnostic tests require 2 or 3 days to result, incur additional costs, and may delay treatment.⁴ While these tests do not provide clear and timely guidance on which specific antibiotic is appropriate for ARTI patients, this is not the case for patients with pharyngitis.^5,6,7 A rapid diagnostic test exists to identify pharyngitis patients with GABHS which accounts for 1 in 4 children with acute sore throat.^1,4,6 Both the American Academy of Pediatrics and the Infectious Diseases Society of America recommend antibiotic treatment for children and adolescents under 18 years of age who have a positive test for group A Streptococcus (GAS).^8,9 This “test and treat” protocol has been consistently included in the Healthcare Effectiveness Data and Information Set (HEDIS) standards over time for pediatric pharyngitis patients aged 3 to 18 years before dispensing an antibiotic.¹⁰

Sinusitis, pneumonia, and acute otitis media are considered ARTIs where antibiotic treatment is justified. Therefore, pharyngitis of unclear etiology seen with these comorbid infections may not always undergo GAS testing but move directly to the patient being prescribed antibiotics. This analysis enumerates ARTI-related comorbidities present together with the initial coded pharyngitis diagnosis to evaluate their impact on the provider’s decision to test and treat, and on revisit risk.

Antibiotic treatment for GAS patients is likely to eradicate the acute GABHS infection within 10 days. Penicillin and amoxicillin are commonly recommended because of their narrow spectrum of activity, few adverse effects, established efficacy, and modest cost. Alternative antibiotics for patients with penicillin allergy, or with polymicrobial infection seen on culture results, include a first-generation cephalosporin, clindamycin, clarithromycin (Biaxin), or azithromycin (Zithromax).^1,8,11 However, while compliance with these HEDIS guidelines has been evaluated, the outcome effects of following the HEDIS “test and treat” recommendations for children with pharyngitis have not been adequately evaluated.

These outcome evaluations have increasing importance as the latest HEDIS survey has shown testing rates in commercial Preferred Provider Organizations (PPO) falling from 86.4% in 2018 to 75.9% in 2019, the lowest rate of testing since 2009, with similar reductions under 80% for Health Maintenance Organizations (HMO).¹⁰ While health plans may execute cost-benefit analyses and algorithms to forge best practices for GAS testing in children and adolescents presenting with symptoms of pharyngitis, it is important to regard the wasteful resource utilization and additional cost of revisits that may offset any gains accrued by more focused GAS testing outside the existing clinical guidelines and HEDIS measures. This may be of particular importance in documenting infection and sparing antibiotic therapy in toddlers and younger.

The objective of this study was to investigate the correlation between testing and antibiotic use on the likelihood of a revisit for an acute respiratory tract infection within 28 days. To achieve this objective, this investigation consists of 3 sequential analyses. First, we document the factors associated with the decision to test the patient for a GABHS infection using the GAS test. Next, we document the factors associated with the decision to use an antibiotic to treat the patient as a function of having tested the patient. Finally, we investigate the impact of the testing and treatment decisions on the likelihood of a revisit within 28 days.

Methods

Study design

This was a retrospective cohort study of episodes of treatment for pediatric patients with pharyngitis. Episodes were identified using data derived from the Optum Insight Clinformatics claims database provided to the University of Southern California to facilitate the training of graduate students. These data cover commercially insured patients with both medical and pharmacy benefits. Data were retrieved from the 3-year period spanning 2011-2013. An episode of care was identified based on date of the first (index) outpatient visit for a pharyngitis diagnosis (International Classification of Diseases, Ninth Revision [ICD-9]: 462, 463, 034.0). Outpatient visits were defined by visit setting: ambulatory clinics, physician offices, emergency rooms, and urgent care facilities. Each pharyngitis treatment episode was then screened for at least a 6-month enrollment in a health insurance plan prior and subsequent to the index visit using Optum enrollment data. Finally, eligible treatment episodes were restricted to children and adolescents under 18 years of age, who had an index outpatient visit for a primary diagnosis of acute pharyngitis.

A diagnostic profile was created for each episode using the diagnoses recorded for the index visit. Up to 3 diagnoses may be recorded for any outpatient visit and the first recorded diagnosis was assumed to be the primary diagnosis for that episode. Any secondary diagnoses recorded on the index visit were used to define comorbidities present at the index visit. ARTI-related comorbidities included: acute otitis media (AOM), bronchitis, sinusitis, pneumonia, and upper respiratory infection (URI). Other comorbid medical diagnoses were documented using diagnostic data from the pre-index period. Dichotomous variables for the following categories were created: mental disorders, nervous system disorders, respiratory symptoms, fever, injury and poisoning, other, or no diseases.

Prior visits for other respiratory infections in the previous 90 days were also identified for patients based on their index visit for pharyngitis. Similarly, any subsequent visits, within 28 days of the index visit, were also recorded to measure the health outcome for analysis. Practice settings include physician offices and federally qualified health centers, state and local health clinics, outpatient hospitals facilities, emergency departments, and other outpatient settings such as walk-in retail health clinic or ambulatory centers. Providers include primary care physicians (family practice, pediatricians, internal medicine), specialty care physicians (emergency medicine, preventive medicine), nonphysician providers (nurse practitioners, physician assistants) and other providers (urgent care, acute outpatient care, ambulatory care centers). Seasons of the year were determined based on the index date of the episode to account for possible seasonality in pharyngitis treatment. Lastly, a previous visits variable was created to identify whether the child had nonpharyngitis ARTI visits in the 3 months prior to the index visit.

Demographic variables were created based on enrollment and the socioeconomic data available in the Optum socioeconomic status file. These variables include patient age, race, sex, household income, geographic location, practice setting type, provider specialty, and type of insurance. An estimate of patient household income was based on algorithms using census block groups. Income categories were informed by the federal guidelines for a family of 4. A low-income family was defined as earning less than $50 000; a middle-income family earned between $50 000 and $75 000, and a high-income family earned $75 000 and above.¹² Patient insurance type was categorized as HMO, Exclusive Provider Organization (EPO), Point of Service (POS), and PPO. Race was identified as White, Black, Hispanic, and Asian. Patient location was defined according to national census regions.

Outcomes

GAS test

The HEDIS measures for pharyngitis recommend using the GAS test to identify the bacterial etiology of the pharyngitis infection. Patients who received the test were identified based on Current Procedural Terminology (CPT) codes 87070-71, 87081, 87430, 87650-52, and 87880.¹⁰

The pharmacy administrative claims dataset was used to identify study patients who filled a prescription for an antibiotic during their pharyngitis treatment episode. Optum pharmacy data identify the medications received, specifies the date of prescription filling, National Drug Codes, and American Hospital Formulary Service (AHFS) Classification System codes for each medication. We used the AHFS Pharmacologic-Therapeutic classification of antibiotics to create dichotomous variables documenting the antibacterial used by each patient.¹³ These are categorized under antibacterial including penicillins, cephalosporins (first, second, third, fourth generation cephalosporins), macrolides (first generation and others), tetracyclines, sulfonamides, fluoroquinolones (ciprofloxacin, levofloxacin, moxifloxacin), cephamycin, carbapenems, and β-lactam antibiotics (amoxicillin, amoxicillin/clavulanate, cephalexin, cefuroxime, cefdinir).

Revisits to physician or other provider

Revisits within 28 days were used as the measure of patient outcomes related to testing and filling of an antibiotic prescription for acute pharyngitis. Revisits may also be due to a patient returning for a follow-up, alternative treatment, worsening pharyngitis, or for another ARTI. An ARTI-related revisit also increases total resources used to treat pediatric pharyngitis patients.

Statistical analysis

Logistic regression was used for all 3 analyses conducted in this study. First, we determined the patient and treating physician characteristics that impact the decision to use GAS testing for pharyngitis. Second, we identified those factors that impact the decision to use antibiotic prescriptions among children who were diagnosed with pharyngitis adding in the dichotomous variable indicating if the patient had received a GAS test. Third, we used a logit regression analysis to document if receiving a GAS test and/or an antibiotic impacted the likelihood of a revisit by comparing revisit risk. To estimate the effect of testing and/or antibiotic use, we divided patients into 4 groups based on whether the patient received a GAS test and/or an antibiotic prescription. This specification of the analysis of revisits as an outcome focuses on adherence to HEDIS “test and treat” guidelines¹⁰:

1. Patients who were not tested yet filled an antibiotic prescription. This decision was likely based on the clinician’s judgment of the patient’s signs and symptoms, and confirmational testing not performed.
2. Patients who were not tested and did not fill an antibiotic prescription. Apparently, in the clinician’s judgment the patient’s signs and symptoms were such that the infection did not warrant treatment and the clinical presentation did not necessitate the GAS test to confirm the recorded diagnosis of pharyngitis.
3. Patients who were tested and received antibiotic prescription, likely because the test was positive for GABHS.
4. Patients who were tested and did not receive antibiotic prescription.

We tested for statistically significant differences in baseline characteristics across these 4 patient groups using t tests for continuous variables and χ² tests for categorical variables. Odds ratios (OR) and CI were computed for the influential variables included the regression analyses.

We conducted a sensitivity analysis using a model specification which included the dichotomous variables for testing and for treatment, and the interaction term between these variables to assess if treatment effects varied in tested and untested patients. We also estimated this model of revisit risk using revisits within 7 days as the outcome variable.

All analyses were completed using STATA/IC 13 (StataCorp, College Station, TX).

Results

There were 24 685 treatment episodes for children diagnosed with pharyngitis. Nearly 47% of these episodes included GAS testing and 47% of the tested patients filled an antibiotic prescription. Similarly, 53% of patients were not tested and 49% of untested patients filled an antibiotic prescription. As a result, the 4 groups identified for analysis were evenly distributed: untested and no prescription (26.9%), untested and prescription (26.3%), tested and prescription (21.9%), and tested and no prescription (24.9%) (Figure).

Table 1 presents the descriptive statistics for these 4 patient groups. Note first that the rate of revisits within 28 days is under 5% across all groups. Second, the 2 tested groups have a lower revisit rate than the untested groups: the tested and treated have a revisit rate of 3.3%, and the tested and untreated have a revisit rate of 2.4%, while both the untested groups have a revisit rate of nearly 5%. These small absolute differences in revisit rates across groups were statistically significant.

Factors associated with receiving GAS test

Several factors were found to impact the decision to test (Table 2). Only 9.7% of children were reported to have any ARTI coinfection. As expected, these comorbidities resulted in a significantly lower likelihood of receiving the GAS test: AOM, bronchitis, sinusitis, pneumonia, and URI as comorbid infections had a 48%, 41%, 37%, 63%, and 13% lower likelihood of receiving the GAS test, respectively, than those with no comorbidities. Similarly, children with fever and respiratory symptoms were 35% and 45% less likely to receiving the GAS test, respectively. This is consistent with our expectation that comorbid ARTI infections will lead many providers to forgo testing.

Provider type and patient age also plays a role in receipt of the GAS test. Relative to outpatient facility providers, primary care physicians were 24% more likely and specialty physicians were 38% less likely of employing the GAS test. The child’s age played a significant role in receipt of the GAS test. Children aged 1 to 5 years and 5 to 12 years were 15% and 14% more likely to receive the test compared to children older than 12 years.

Pharyngitis patients have disproportionately higher odds of receiving a GAS test in most regions of the country compared to the Pacific region. For instance, children in the Mid-Atlantic region have 51% higher odds of receiving a GAS test while children in New England have 80% higher odds of receiving the same test.

Black children have 11% lower odds of receiving the GAS test compared to White children. Both middle-income and high-income children have 12% and 32% higher odds of receiving the test compared to low-income children. Compared to office-based visits, children visiting a clinic were twice as likely to receive a GAS test while those seen in the emergency room have 43% lower odds of receiving a GAS test. Hospital outpatient departments, which account for less than 1% of all visits, rarely used a GAS test which could be a statistical artifact due to small sample size. Lastly, insurance and season of the year had no significant impact of receipt of a GAS test.

Factors associated with receiving antibiotic prescription

Surprisingly, receiving the GAS test has a small but insignificant impact on the likelihood that the patient will receive an antibiotic prescription (Table 3) (Adjusted OR = 1.055, P = .07). After controlling for receipt of a GAS test, children with AOM and sinusitis comorbidities have an increased likelihood of being prescribed an antibiotic. Children with URI have a lower likelihood of being prescribed an antibiotic. Additionally, relative to primary care physicians, children visiting nonphysician providers for pharyngitis were more likely to be prescribed an antibiotic.

Children under 12 years of age were more likely to use an antibiotic compared to children 12 years and older. Geographically, there is some evidence of regional variation in antibiotic use as well. Children in the south Atlantic, west-south central, and southeast central regions had a significantly lower odds of being prescribed an antibiotic respectively than pharyngitis patients in the Pacific region. Black children had a 10% lower likelihood of being prescribed an antibiotic compared to White children, possibly related to their lower rate of GAS testing. Compared to office-based visits, children visiting a clinic were less likely to use an antibiotic. Household income, insurance type, and season had no significant impact on revisit risk.

Effects of GAS test and antibiotic prescriptions on likelihood of revisits

The multivariate analysis of the risk of a revisit within 28 days is presented in Table 4. Children with pharyngitis who tested and did not receive an antibiotic serve as the reference comparison group for this analysis to illustrate the impact of using the GAS test and treatment with an antibiotic. The results in Table 4 are quite clear: patients who receive the GAS test were significantly less likely to have a revisit within 28 days. Moreover, within the group of patients who were tested, those not receiving an antibiotic, presumedly because their GAS test was negative, experienced the lowest risk of a revisit. This result is consistent with the data in Table 1. Moreover, using an antibiotic had no impact on the likelihood of a revisit in patients not receiving the GAS test. This result is also consistent with Table 1.

Other results from the analysis of revisit risk may be of interest to clinicians. Pharyngitis patients with a prior episode of treatment within 90 days for an acute respiratory tract infection were more than 7 times more likely to experience a revisit within 28 days of the pharyngitis diagnosis than patients without a history of recent ARTI infections. Age is also a risk factor in likelihood of initiating a revisit. Children under 1 year and children aged 1 to 5 years were more likely to have a revisit than children aged more than 12 years. Compared to White children, Black children were 25% (P = .04) less likely to have a revisit. The care setting also has a significant impact on revisit risk. Children visiting outpatient hospital and other care settings had a significantly higher revisit risk than those visiting a physician’s office. Lastly, household income, geographic region, season, medical comorbidities, gender, and insurance type have no significant impact on revisit risk.

Sensitivity analysis

The results from the analysis of 7-day and 28-day revisit risk are summarized in Table 5. These results indicate that patients who were tested had a more significant decrease in revisit risk at 7 days (72%) than was evident at 28 days (47% reduction). Receiving an antibiotic, with or without the test, had no impact on revisit risk.

Discussion

Published data on revisits for pharyngitis are lacking with the concentration of prior research focused more on systemic complications of undertreated GABHS disease or on identifying carrier status. Our study results suggest that GAS testing is the most important factor in reducing revisit risk. Being prescribed an antibiotic, on its own, does not have a significant impact on the risk of a revisit. However, once the GAS test is used, the decision not to use an antibiotic was correlated with the lowest revisit rate, likely because the source of the pharyngitis infection was viral and more likely to resolve without a revisit. Prior studies have reported variable rates of testing among children with pharyngitis prescribed an antibiotic, ranging from 23% to 91%,^14,15 with testing important toward more appropriate antibiotic use.¹⁶ More recently, among more than 67 000 patients aged 3 to 21 years presenting with sore throat and receiving a GAS test, 32.6% were positive.¹⁷

Our analysis found that more than 46% of pediatric pharyngitis patients were given the rapid GAS test. While this testing rate is substantially lower than HEDIS recommendations and lower than testing rates achieved by several health maintenance organizations,¹⁰ it is similar to the 53% of children receiving such testing in a recent National Ambulatory Medical Care Survey.¹⁸ Furthermore, we found that when antibiotics are prescribed following a GAS test, the revisit risk is not significantly reduced, possibly because antibiotics lower revisit risk when informed by diagnostic testing tools that determine the infectious organism. This is supported by a similar population analysis in which we observed reduced revisit rates in children with AOM managed with antibiotics within 3 days of index diagnosis.¹⁹

Several other factors also affect the likelihood of a child receiving the GAS test. Children aged 1 to 12 years were significantly more likely to receive the GAS test than children over the age of 12. This included children in the 1 to 5 years old bracket who had a 15% higher likelihood of undergoing a GAS test, despite children less than 3 years of age as not recommended targets for GAS testing.²⁰ As expected, children with reported ARTI-associated comorbidities were also less likely to receive a GAS test. Additionally, specialty care physicians were less inclined to implement the GAS test, possibly because of diagnostic confidence without testing or referral after GAS was ruled out. Black and low-income children had statistically lower odds of receiving the test, even after controlling for other factors, and yet were less likely to consume a revisit. As the overall data suggested more revisits in those not tested, further study is needed to examine if race or income discrepancies are equity based. Finally, children in the Pacific region, compared to the rest of the nation, were the least likely to receive a GAS test and yet there were no significant differences in revisit rates by region. Regional differences in antibiotic use were also observed in our study, as has been seen by others.²¹

After statistically controlling for having received the diagnostic GAS test and filled a prescription for an antibiotic, there are multitude of factors that independently affect the revisit risk, the most important of which if which was a history of an ARTI infection in the prior 90 days. While prior visit history had no impact on the likelihood of being tested or filling an antibiotic, patients with prior visits were more than 7 times more likely to consume a revisit. This was not reflected in nor related to comorbid ARTIs as these patients did not have statistically higher revisits than those with pharyngitis as the sole-coded diagnosis. Moreover, speculation for bacterial etiology of primary or superinfection based on a recent history of ARTI accounting for revisits seems unlikely as it did not yield greater antibiotic use in that group. Further analysis is required to determine the clinical and behavioral factors that promote for prior ARTI history as a major factor in revisit risk after an index visit for pharyngitis.

Children aged between 1 and 5 years, though 15% more likely to be tested than those aged 12 through 17 years, were also 39% more likely to initiate a revisit compared to older children when statistically controlling for other covariates. This perhaps suggests longer illness, wrong diagnosis, delay in appropriate treatment, or more caution by parents and providers in this age group. Justification for testing children less than 3 years of age who are outside of the HEDIS suggested age group, when clinical judgement does not point to another infection source, can result in positivity rates between 22% and 30% as previously observed.^22,23 Patients visiting nonphysician providers and outpatient facility providers were less likely to have a revisit than those visiting primary and specialty care physicians, though slightly higher propensity for antibiotic prescriptions was seen for nonphysician providers. Pediatricians have been noted to be less likely to prescribe antibiotics without GAS testing than nonpediatric providers, and more guidelines-compliant in prescribing.²⁴

Recommendations to not test children under 3 years of age are based on the lack of acute rheumatic fever and other complications in this age group together with more frequent viral syndromes. Selectivity in applying clinical criteria to testing can be attempted to separate bacterial from viral illness. Postnasal drainage/rhinorrhea, hoarse voice, and cough have been used successfully to identify those with viral illness and less need for testing, with greater certainty of low risk for GABHS in those over 11 years of age without tonsillar exudates, cervical adenopathy, or fever.¹⁷ However, the marginal benefits of those who have all 3 features of viral illness versus none in identifying GAS positivity was 23.3% vs 37.6% - helpful, but certainly not diminishing the need for testing. These constitutional findings of viral URI also do not exclude the GAS carrier state that features these symptoms.²⁵ Others have reinforced the doubt of pharyngeal exudates as the premier diagnostic finding for test-positive GAS.²⁶

This study had several limitations. The Optum claims dataset only contains ICD-9 codes for diagnoses. It does not include data on infection severity and clinical findings related to symptoms, thus empiric treatment warranted based in clinical severity is not assessed. Antibiotics are commonly available as generics and very inexpensive. Patients may fill and pay for these prescriptions directly, in which case, a claim for payment may not be filed with Optum. This could result in an undercount of treated patients in our study.

There is no corresponding problem of missing medical claims for GAS testing which were obtained from the CPT codes within the Optum claims data set. However, we elected not to verify the test results due to these data being missing for 75% of the study population. Nevertheless, this study’s focus was less about justifying antibiotic treatment, but dealt with the outcomes generated by testing and treatment. Toward that end, we used CPT codes to identify a revisit, and while those can at times be affected by financial reimbursement incentives, differences related to revisits in the 4 patient groups should not be subject to bias.

Conclusion

This study used data from real world practices to document the patterns of GAS testing and antibiotic use in pediatric pharyngitis patients. Revisit rates were under 5% for all patient groups and the use of rapid diagnostic tools were found to be the determining factor in further reducing the risk of revisits. This supports the need for compliance with the HEDIS quality metric for pharyngitis to the recommended levels of rapid testing which have been falling in recent years. Use of more accurate antigen and newer molecular detection testing methods may help further delineate important factors in determining pediatric pharyngitis treatment and need for revisits.²⁷

Corresponding author: Jeffrey McCombs, MD, University of Southern California School of Pharmacy, Department of Pharmaceutical and Health Economics, Leonard D. Schaeffer Center for Health Policy & Economics, 635 Downey Way, Verna & Peter Dauterive Hall 310, Los Angeles, CA 90089-3333; [email protected].

Financial disclosures: None.

From the Department of Anesthesiology, Thomas Jefferson University and Hospitals, Sidney Kimmel Medical College, Philadelphia, PA, and Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA.

Objective: Retrospective study examining hospital cost information of patients requiring endotracheal intubation with video laryngoscopy. Provide a practical cost assessment on use of the McGRATH and GlideScope video laryngoscopes (VLs).

Methods: This study examined 52 hospital locations within a single, large university hospital, with most of those locations being hospital operating rooms. A total of 34 600 endotracheal intubations performed over 24 months, of which 11 345 were video laryngoscopies. Electronic medical records containing demographic data and information related to endotracheal intubation procedures, with monthly breakdowns between GlideScope and McGRATH intubations, were reviewed. Cost information calculated for equipment, blades, batteries, repairs, and subsequent analysis performed to determine cost differences between those 2 instruments during the COVID-19 period.

Results: A total of 5501 video laryngoscopy procedures were performed using the McGRATH VL and 5305 were performed using the GlideScope VL. Costs over 24 months were $181 093 lower (55.5%) for McGRATH compared to GlideScope. The mean (SD) monthly costs for GlideScope blades were $3837 ($1050) and $3236 ($538) for years 1 and 2, respectively, vs $1652 ($663) and $2933 ($585) for McGRATH blades (P < .001). Most total cost differences were attributed to equipment and blade purchases, which were $202 595 (65.0%) higher for GlideScope. During the COVID-19 period, the use of the McGRATH increased to 61% of all video laryngoscopy cases, compared to 37% for GlideScope (P < .001). Blade cost difference for the COVID-19 period was $128 higher for the McGRATH even though 293 more intubations were performed with that device.

Conclusions: Use of the McGRATH resulted in a cost savings of 55% compared to the GlideScope, and its use was highest during the COVID-19 period, which may be explained by its more portable and practical features.

Keywords: video laryngoscope; McGRATH; GlideScope; endotracheal intubation; hospital costs; COVID-19.

Hospitals have come to rely on video laryngoscopes (VLs) for tracheal intubation as necessary tools for better visualization of airways. Modern video laryngoscopy developed in the 2000s¹ as a progression from direct laryngoscopy, which began in 1852 when Horace Green used a bent tongue spatula and sunlight to examine a child.² VLs have seen many improvements and adaptations of their own, resulting in many different styles and types circulating around hospitals. The GlideScope (Verathon Inc, Bothell, WA) and the McGRATH (Medtronic, Minneapolis, MN) are examples of such instruments, which are now widely used in the US and are the 2 VLs of choice at our institution.

A few studies have compared VLs to direct laryngoscopes. In their systematic review, Lewis et al have shown the numerous benefits of using a VL over a direct laryngoscope. Some general conclusions were that the use of video laryngoscopy reduced the number of failed intubations, decreased laryngeal trauma, and provided improved visualizations.³ Other studies have compared the different types of VLs, including the McGRATH and the GlideScope, examining factors such as intubation time and display quality of the image. Two studies found that medical students were equally successful at using both the McGRATH and the GlideScope,^4,5 while another study found that care providers using the GlideScope had quicker intubation times.⁶ Lastly, Savoldelli et al concluded that more providers preferred the McGRATH, which provided better laryngeal views,⁷ while their subsequent study showed more favorable learning curves of the Airtraq compared to the McGRATH and other VLs.⁸

Although there have been no reported differences in safety and effectiveness of the McGRATH and GlideScope devices, cost data on the use of these 2 popular laryngoscopes are lacking. Such information is important considering the increasing costs of medical technologies and the significant financial losses experienced by health care systems due to the COVID-19 crisis. The purpose of this retrospective cohort study was to compare the cost efficiency of the McGRATH MAC and GlideScope Core VLs at a large academic center.

Methods

This retrospective study was performed under exemption from the Thomas Jefferson University Institutional Review Board. The primary data sources consisted of hospital electronic patient records (EPIC) and cost information from the device manufacturers and hospital staff. The electronic patient data were provided by the EPIC Enterprise Analytics Business Intelligence group at Thomas Jefferson University Hospital (Center City Campus, Philadelphia, PA), while device costs were obtained from Verathon, Medtronic, and departmental staff responsible for purchasing equipment. Monthly data were obtained over a 24-month period (June 2018 through May 2020) when the McGRATH VL was placed into use in the department of anesthesiology. The 2 types of VLs were made available for use in a total of 52 locations, with the majority being hospital operating rooms.

The following variables were recorded: number of endotracheal intubations performed each month with breakdown between video laryngoscopy and flexible bronchoscopy airways, frequency of use for each type of laryngoscope, blades used, and equipment costs for use of each laryngoscope. Hospital cost estimates for both the McGRATH and GlideScope laryngoscopes included batteries, handles, blades, and the devices themselves. Cost data were also collected on frequency of device failure, maintenance, and replacement of parts and lost equipment.

Analysis

De-identified electronic medical records consisted of nominal and quantitative variables, with demographic data and information related to the endotracheal intubation procedure. All data were in chronological order and sorted by date after which coding was applied, to identify device type and allocate pertinent cost information. Descriptive statistics were reported as mean (SD) and sum for costs; frequency tables were generated for intubation procedures according to device type and time periods. Data were analyzed using the χ² test, the student t test, and the Wilcoxon Mann-Whitney U test, with a P value set at .05 for statistical significance. SPSS version 26 and GraphPad Prism version 6 were used for all statistical analyses.

A total of 34 600 endotracheal intubations were performed over the 24-month study period, and 11 345 (32.8%) were video laryngoscopy procedures. Out of all video laryngoscopy procedures, 5501 (48.5%) were performed using the McGRATH VL and 5305 (46.8%) were conducted using the GlideScope VL. The difference of 539 (4.8%) cases accounts for flexible bronchoscopy procedures and endotracheal intubations using other video laryngoscopy equipment. The mean (SD) monthly number of video laryngoscopy procedures for the 24 months was 221 (54) and 229 (89) for the GlideScope and McGRATH devices, respectively. Monthly endotracheal intubation distributions over 24 months trended upward for the McGRATH VL and downward for the GlideScope, but there was no statistically significant (P = .71) difference in overall use between the 2 instruments (Figure 1).

To examine the observed usage trends between the 2 VL during the first and last 12 months, a univariate ANOVA was conducted with the 2 time periods entered as predictors in the model. Video laryngoscopy intubations were performed (P = .001) more frequently with the GlideScope during the first 12 months; however, use of the McGRATH VL increased (P < .001) during the following 12 months compared to GlideScope. The GlideScope accounted for 54% of all VL intubations during the first 12 months, with the McGRATH accounting for 58% of all video laryngoscopy procedures for months 12 to 24. Additionally, the increase in video laryngoscopy procedures with the McGRATH during the last 3 months of the study period was despite an overall reduction in surgical volume due to the COVID-19 crisis, defined for this study as March 1, 2020, to May 31, 2020 (Figure 1). There was a statistically significant (P < .001) difference in the case distribution between use of the McGRATH and GlideScope VL for that period. The anesthesia personnel’s use of the McGRATH VL increased to 61% of all video laryngoscopy cases, compared to 37% for the GlideScope (Figure 2).

The total costs calculated for equipment, blades, and repairs are presented in Table 1 and yearly total costs are shown in Figure 3. Overall costs were $181 093 lower (55.5%) for the McGRATH VL compared to the GlideScope over the 24-month period. The mean (SD) monthly costs for GlideScope VL blades were $3837 ($1050) and $3236 ($538) for years 1 and 2, respectively, vs $1652 ($663) and $2933 ($585) for the McGRATH VL blades. Most of the total cost differences were attributed to equipment and blade purchases, which were $202 595 (65.0%) higher for the GlideScope compared to the McGRATH VL. The monthly blade costs alone were higher (P < .001) for the GlideScope over the 2-year period; however, the McGRATH VL required use of disposable stylets at a cost of $10 177 for all endotracheal intubations, compared to $700 for the GlideScope device.

An analysis was performed to determine whether costs differed between those 2 instruments during the COVID-19 period. There was a statistically significant (P < .001) difference in the case distribution between use of the McGRATH and GlideScope VLs during that period. The calculated blade cost difference for the COVID period was $128 higher for the McGRATH even though 293 more intubations were performed with that device (Table 2).

Discussion

We attempted to provide useful cost estimates by presenting pricing data reflecting the approximate cost that most large institutional anesthesia practices would incur for using those 2 specific devices and related peripherals. The main findings of our analysis showed that use of the McGRATH MAC VL resulted in a 55% cost savings compared to the GlideScope, with a similar number of cases performed with each device over the 24-month study period. We believe this represents a substantial savings to the department and institution, which has prompted internal review on the use of video laryngoscopy equipment. None of the McGRATH units failed; however, the GlideScope required 3 baton replacements.

Of note, use of the McGRATH MAC increased during the COVID-19 period, which may be explained by the fact that the operators found it to be a more portable device. Several physicians in the department commented that its smaller size made the McGRATH MAC more practical during the time when a plexiglass box was being used around the patient’s head to shield the intubator from aerosolized viral particles.

Although this study demonstrated the cost-saving value of the McGRATH over the GlideScope, a suggested next step would be to examine resource utilization related to video laryngoscopy use. The more dynamic tracking of the use of these devices should facilitate the assessment of existing related resources and decision making, to optimize the benefits of this initiative. We would anticipate reduced use of anesthesia personnel, such as technicians to assist with the management of this device which could be significant. As new respiratory viruses are appearing each year, video laryngoscopy will continue to gain increasing use in operating rooms and acute care locations. The adding of protective barriers between patients and providers calls for use of the most practical and effective VL devices, to protect personnel who are at high risk of contamination from airway secretions and aerosolized particles.^9,10

The COVID-19 pandemic has demonstrated the value of anesthesiology in regards to analyzing and finding solutions to effectively manage infected patients or those suspected of infection in the perioperative environment. Inexpensive products are often avoided because cheaper devices are associated with being of lower quality. However, the association with cost and quality—and the assumption that a higher price is positively correlated with higher quality—is overall inconsistent in the medical literature.¹¹ A more effective or higher quality treatment does not necessarily cost more and may actually end up costing less,¹² as was the case in this study. We have been able to directly cut departmental expenses by using a more efficient and cost-effective device for intubations, without compromising safety and efficacy. Future studies should determine whether this significant reduction in costs from video laryngoscopy intubations with the McGRATH VL will be sustained across anesthesiology departments in the Jefferson Health Enterprise Hospitals, or other health systems, as well as its impact on workflow and personnel resources.

This analysis was restricted to one of the campuses of the Jefferson Health Enterprise. However, this is the largest anesthesia practice, encompassing several locations, which should reflect the general practice patterns across other anesthesiology departments in this large institution. The costs for the devices and peripherals may vary across anesthesia practices depending on volume and contracts negotiated with the suppliers. It was not possible to estimate this variability, which could change the total costs by a few percentage points. We recognize that there may be other costs associated with securing the McGRATH VL to prevent loss from theft or misplacement, which were not included in the study. Lastly, the inability to obtain randomized samples for the 2 groups treated with each device opens up the possibility of selection bias. There were, however, multiple intubators who were free to select 1 of the devices for endotracheal intubation, which may have reduced the effect of selection bias.

Conclusion

This study demonstrated that over a 24-month period use of the McGRATH MAC VL resulted in a cost reduction of around 55% compared to using the GlideScope for endotracheal intubation procedures performed at a major academic center. Over the first 3 months of the COVID-19 crisis, which our study included, use of the McGRATH VL increased while GlideScope use decreased. This was most likely related to the portability and smaller size of the McGRATH, which better facilitated intubations of COVID-19 patients.

Acknowledgements: The authors thank Craig Smith, Senior Anesthesia Technician, for his assistance with the cost information and excellent record-keeping related to the use of video laryngoscopes.

Corresponding author: Marc C. Torjman, PhD, Professor, Department of Anesthesiology, Sidney Kimmel Medical College at Thomas Jefferson University, 111 South 11th St, Suite G-8290, Philadelphia, PA 19107; [email protected].

Financial disclosures: Dr. Thaler has served as a consultant for Medtronic since September 2020. He has participated in 2 webinars on the routine use of video laryngoscopy.

Funding: This study was supported by the Department of Anesthesiology at Thomas Jefferson University.

From the Department of Anesthesiology, Thomas Jefferson University and Hospitals, Sidney Kimmel Medical College, Philadelphia, PA, and Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA.

Objective: Retrospective study examining hospital cost information of patients requiring endotracheal intubation with video laryngoscopy. Provide a practical cost assessment on use of the McGRATH and GlideScope video laryngoscopes (VLs).

Methods: This study examined 52 hospital locations within a single, large university hospital, with most of those locations being hospital operating rooms. A total of 34 600 endotracheal intubations performed over 24 months, of which 11 345 were video laryngoscopies. Electronic medical records containing demographic data and information related to endotracheal intubation procedures, with monthly breakdowns between GlideScope and McGRATH intubations, were reviewed. Cost information calculated for equipment, blades, batteries, repairs, and subsequent analysis performed to determine cost differences between those 2 instruments during the COVID-19 period.

Results: A total of 5501 video laryngoscopy procedures were performed using the McGRATH VL and 5305 were performed using the GlideScope VL. Costs over 24 months were $181 093 lower (55.5%) for McGRATH compared to GlideScope. The mean (SD) monthly costs for GlideScope blades were $3837 ($1050) and $3236 ($538) for years 1 and 2, respectively, vs $1652 ($663) and $2933 ($585) for McGRATH blades (P < .001). Most total cost differences were attributed to equipment and blade purchases, which were $202 595 (65.0%) higher for GlideScope. During the COVID-19 period, the use of the McGRATH increased to 61% of all video laryngoscopy cases, compared to 37% for GlideScope (P < .001). Blade cost difference for the COVID-19 period was $128 higher for the McGRATH even though 293 more intubations were performed with that device.

Conclusions: Use of the McGRATH resulted in a cost savings of 55% compared to the GlideScope, and its use was highest during the COVID-19 period, which may be explained by its more portable and practical features.

Keywords: video laryngoscope; McGRATH; GlideScope; endotracheal intubation; hospital costs; COVID-19.

Hospitals have come to rely on video laryngoscopes (VLs) for tracheal intubation as necessary tools for better visualization of airways. Modern video laryngoscopy developed in the 2000s¹ as a progression from direct laryngoscopy, which began in 1852 when Horace Green used a bent tongue spatula and sunlight to examine a child.² VLs have seen many improvements and adaptations of their own, resulting in many different styles and types circulating around hospitals. The GlideScope (Verathon Inc, Bothell, WA) and the McGRATH (Medtronic, Minneapolis, MN) are examples of such instruments, which are now widely used in the US and are the 2 VLs of choice at our institution.

A few studies have compared VLs to direct laryngoscopes. In their systematic review, Lewis et al have shown the numerous benefits of using a VL over a direct laryngoscope. Some general conclusions were that the use of video laryngoscopy reduced the number of failed intubations, decreased laryngeal trauma, and provided improved visualizations.³ Other studies have compared the different types of VLs, including the McGRATH and the GlideScope, examining factors such as intubation time and display quality of the image. Two studies found that medical students were equally successful at using both the McGRATH and the GlideScope,^4,5 while another study found that care providers using the GlideScope had quicker intubation times.⁶ Lastly, Savoldelli et al concluded that more providers preferred the McGRATH, which provided better laryngeal views,⁷ while their subsequent study showed more favorable learning curves of the Airtraq compared to the McGRATH and other VLs.⁸

Although there have been no reported differences in safety and effectiveness of the McGRATH and GlideScope devices, cost data on the use of these 2 popular laryngoscopes are lacking. Such information is important considering the increasing costs of medical technologies and the significant financial losses experienced by health care systems due to the COVID-19 crisis. The purpose of this retrospective cohort study was to compare the cost efficiency of the McGRATH MAC and GlideScope Core VLs at a large academic center.

Methods

This retrospective study was performed under exemption from the Thomas Jefferson University Institutional Review Board. The primary data sources consisted of hospital electronic patient records (EPIC) and cost information from the device manufacturers and hospital staff. The electronic patient data were provided by the EPIC Enterprise Analytics Business Intelligence group at Thomas Jefferson University Hospital (Center City Campus, Philadelphia, PA), while device costs were obtained from Verathon, Medtronic, and departmental staff responsible for purchasing equipment. Monthly data were obtained over a 24-month period (June 2018 through May 2020) when the McGRATH VL was placed into use in the department of anesthesiology. The 2 types of VLs were made available for use in a total of 52 locations, with the majority being hospital operating rooms.

The following variables were recorded: number of endotracheal intubations performed each month with breakdown between video laryngoscopy and flexible bronchoscopy airways, frequency of use for each type of laryngoscope, blades used, and equipment costs for use of each laryngoscope. Hospital cost estimates for both the McGRATH and GlideScope laryngoscopes included batteries, handles, blades, and the devices themselves. Cost data were also collected on frequency of device failure, maintenance, and replacement of parts and lost equipment.

Analysis

De-identified electronic medical records consisted of nominal and quantitative variables, with demographic data and information related to the endotracheal intubation procedure. All data were in chronological order and sorted by date after which coding was applied, to identify device type and allocate pertinent cost information. Descriptive statistics were reported as mean (SD) and sum for costs; frequency tables were generated for intubation procedures according to device type and time periods. Data were analyzed using the χ² test, the student t test, and the Wilcoxon Mann-Whitney U test, with a P value set at .05 for statistical significance. SPSS version 26 and GraphPad Prism version 6 were used for all statistical analyses.

A total of 34 600 endotracheal intubations were performed over the 24-month study period, and 11 345 (32.8%) were video laryngoscopy procedures. Out of all video laryngoscopy procedures, 5501 (48.5%) were performed using the McGRATH VL and 5305 (46.8%) were conducted using the GlideScope VL. The difference of 539 (4.8%) cases accounts for flexible bronchoscopy procedures and endotracheal intubations using other video laryngoscopy equipment. The mean (SD) monthly number of video laryngoscopy procedures for the 24 months was 221 (54) and 229 (89) for the GlideScope and McGRATH devices, respectively. Monthly endotracheal intubation distributions over 24 months trended upward for the McGRATH VL and downward for the GlideScope, but there was no statistically significant (P = .71) difference in overall use between the 2 instruments (Figure 1).

To examine the observed usage trends between the 2 VL during the first and last 12 months, a univariate ANOVA was conducted with the 2 time periods entered as predictors in the model. Video laryngoscopy intubations were performed (P = .001) more frequently with the GlideScope during the first 12 months; however, use of the McGRATH VL increased (P < .001) during the following 12 months compared to GlideScope. The GlideScope accounted for 54% of all VL intubations during the first 12 months, with the McGRATH accounting for 58% of all video laryngoscopy procedures for months 12 to 24. Additionally, the increase in video laryngoscopy procedures with the McGRATH during the last 3 months of the study period was despite an overall reduction in surgical volume due to the COVID-19 crisis, defined for this study as March 1, 2020, to May 31, 2020 (Figure 1). There was a statistically significant (P < .001) difference in the case distribution between use of the McGRATH and GlideScope VL for that period. The anesthesia personnel’s use of the McGRATH VL increased to 61% of all video laryngoscopy cases, compared to 37% for the GlideScope (Figure 2).

The total costs calculated for equipment, blades, and repairs are presented in Table 1 and yearly total costs are shown in Figure 3. Overall costs were $181 093 lower (55.5%) for the McGRATH VL compared to the GlideScope over the 24-month period. The mean (SD) monthly costs for GlideScope VL blades were $3837 ($1050) and $3236 ($538) for years 1 and 2, respectively, vs $1652 ($663) and $2933 ($585) for the McGRATH VL blades. Most of the total cost differences were attributed to equipment and blade purchases, which were $202 595 (65.0%) higher for the GlideScope compared to the McGRATH VL. The monthly blade costs alone were higher (P < .001) for the GlideScope over the 2-year period; however, the McGRATH VL required use of disposable stylets at a cost of $10 177 for all endotracheal intubations, compared to $700 for the GlideScope device.

An analysis was performed to determine whether costs differed between those 2 instruments during the COVID-19 period. There was a statistically significant (P < .001) difference in the case distribution between use of the McGRATH and GlideScope VLs during that period. The calculated blade cost difference for the COVID period was $128 higher for the McGRATH even though 293 more intubations were performed with that device (Table 2).

Discussion

We attempted to provide useful cost estimates by presenting pricing data reflecting the approximate cost that most large institutional anesthesia practices would incur for using those 2 specific devices and related peripherals. The main findings of our analysis showed that use of the McGRATH MAC VL resulted in a 55% cost savings compared to the GlideScope, with a similar number of cases performed with each device over the 24-month study period. We believe this represents a substantial savings to the department and institution, which has prompted internal review on the use of video laryngoscopy equipment. None of the McGRATH units failed; however, the GlideScope required 3 baton replacements.

Of note, use of the McGRATH MAC increased during the COVID-19 period, which may be explained by the fact that the operators found it to be a more portable device. Several physicians in the department commented that its smaller size made the McGRATH MAC more practical during the time when a plexiglass box was being used around the patient’s head to shield the intubator from aerosolized viral particles.

Although this study demonstrated the cost-saving value of the McGRATH over the GlideScope, a suggested next step would be to examine resource utilization related to video laryngoscopy use. The more dynamic tracking of the use of these devices should facilitate the assessment of existing related resources and decision making, to optimize the benefits of this initiative. We would anticipate reduced use of anesthesia personnel, such as technicians to assist with the management of this device which could be significant. As new respiratory viruses are appearing each year, video laryngoscopy will continue to gain increasing use in operating rooms and acute care locations. The adding of protective barriers between patients and providers calls for use of the most practical and effective VL devices, to protect personnel who are at high risk of contamination from airway secretions and aerosolized particles.^9,10

The COVID-19 pandemic has demonstrated the value of anesthesiology in regards to analyzing and finding solutions to effectively manage infected patients or those suspected of infection in the perioperative environment. Inexpensive products are often avoided because cheaper devices are associated with being of lower quality. However, the association with cost and quality—and the assumption that a higher price is positively correlated with higher quality—is overall inconsistent in the medical literature.¹¹ A more effective or higher quality treatment does not necessarily cost more and may actually end up costing less,¹² as was the case in this study. We have been able to directly cut departmental expenses by using a more efficient and cost-effective device for intubations, without compromising safety and efficacy. Future studies should determine whether this significant reduction in costs from video laryngoscopy intubations with the McGRATH VL will be sustained across anesthesiology departments in the Jefferson Health Enterprise Hospitals, or other health systems, as well as its impact on workflow and personnel resources.

This analysis was restricted to one of the campuses of the Jefferson Health Enterprise. However, this is the largest anesthesia practice, encompassing several locations, which should reflect the general practice patterns across other anesthesiology departments in this large institution. The costs for the devices and peripherals may vary across anesthesia practices depending on volume and contracts negotiated with the suppliers. It was not possible to estimate this variability, which could change the total costs by a few percentage points. We recognize that there may be other costs associated with securing the McGRATH VL to prevent loss from theft or misplacement, which were not included in the study. Lastly, the inability to obtain randomized samples for the 2 groups treated with each device opens up the possibility of selection bias. There were, however, multiple intubators who were free to select 1 of the devices for endotracheal intubation, which may have reduced the effect of selection bias.

Conclusion

This study demonstrated that over a 24-month period use of the McGRATH MAC VL resulted in a cost reduction of around 55% compared to using the GlideScope for endotracheal intubation procedures performed at a major academic center. Over the first 3 months of the COVID-19 crisis, which our study included, use of the McGRATH VL increased while GlideScope use decreased. This was most likely related to the portability and smaller size of the McGRATH, which better facilitated intubations of COVID-19 patients.

Acknowledgements: The authors thank Craig Smith, Senior Anesthesia Technician, for his assistance with the cost information and excellent record-keeping related to the use of video laryngoscopes.

Corresponding author: Marc C. Torjman, PhD, Professor, Department of Anesthesiology, Sidney Kimmel Medical College at Thomas Jefferson University, 111 South 11th St, Suite G-8290, Philadelphia, PA 19107; [email protected].

Financial disclosures: Dr. Thaler has served as a consultant for Medtronic since September 2020. He has participated in 2 webinars on the routine use of video laryngoscopy.

Funding: This study was supported by the Department of Anesthesiology at Thomas Jefferson University.

From the Department of Anesthesiology, Thomas Jefferson University and Hospitals, Sidney Kimmel Medical College, Philadelphia, PA, and Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA.

Objective: Retrospective study examining hospital cost information of patients requiring endotracheal intubation with video laryngoscopy. Provide a practical cost assessment on use of the McGRATH and GlideScope video laryngoscopes (VLs).

Methods: This study examined 52 hospital locations within a single, large university hospital, with most of those locations being hospital operating rooms. A total of 34 600 endotracheal intubations performed over 24 months, of which 11 345 were video laryngoscopies. Electronic medical records containing demographic data and information related to endotracheal intubation procedures, with monthly breakdowns between GlideScope and McGRATH intubations, were reviewed. Cost information calculated for equipment, blades, batteries, repairs, and subsequent analysis performed to determine cost differences between those 2 instruments during the COVID-19 period.

Results: A total of 5501 video laryngoscopy procedures were performed using the McGRATH VL and 5305 were performed using the GlideScope VL. Costs over 24 months were $181 093 lower (55.5%) for McGRATH compared to GlideScope. The mean (SD) monthly costs for GlideScope blades were $3837 ($1050) and $3236 ($538) for years 1 and 2, respectively, vs $1652 ($663) and $2933 ($585) for McGRATH blades (P < .001). Most total cost differences were attributed to equipment and blade purchases, which were $202 595 (65.0%) higher for GlideScope. During the COVID-19 period, the use of the McGRATH increased to 61% of all video laryngoscopy cases, compared to 37% for GlideScope (P < .001). Blade cost difference for the COVID-19 period was $128 higher for the McGRATH even though 293 more intubations were performed with that device.

Conclusions: Use of the McGRATH resulted in a cost savings of 55% compared to the GlideScope, and its use was highest during the COVID-19 period, which may be explained by its more portable and practical features.

Keywords: video laryngoscope; McGRATH; GlideScope; endotracheal intubation; hospital costs; COVID-19.

Hospitals have come to rely on video laryngoscopes (VLs) for tracheal intubation as necessary tools for better visualization of airways. Modern video laryngoscopy developed in the 2000s¹ as a progression from direct laryngoscopy, which began in 1852 when Horace Green used a bent tongue spatula and sunlight to examine a child.² VLs have seen many improvements and adaptations of their own, resulting in many different styles and types circulating around hospitals. The GlideScope (Verathon Inc, Bothell, WA) and the McGRATH (Medtronic, Minneapolis, MN) are examples of such instruments, which are now widely used in the US and are the 2 VLs of choice at our institution.

A few studies have compared VLs to direct laryngoscopes. In their systematic review, Lewis et al have shown the numerous benefits of using a VL over a direct laryngoscope. Some general conclusions were that the use of video laryngoscopy reduced the number of failed intubations, decreased laryngeal trauma, and provided improved visualizations.³ Other studies have compared the different types of VLs, including the McGRATH and the GlideScope, examining factors such as intubation time and display quality of the image. Two studies found that medical students were equally successful at using both the McGRATH and the GlideScope,^4,5 while another study found that care providers using the GlideScope had quicker intubation times.⁶ Lastly, Savoldelli et al concluded that more providers preferred the McGRATH, which provided better laryngeal views,⁷ while their subsequent study showed more favorable learning curves of the Airtraq compared to the McGRATH and other VLs.⁸

Although there have been no reported differences in safety and effectiveness of the McGRATH and GlideScope devices, cost data on the use of these 2 popular laryngoscopes are lacking. Such information is important considering the increasing costs of medical technologies and the significant financial losses experienced by health care systems due to the COVID-19 crisis. The purpose of this retrospective cohort study was to compare the cost efficiency of the McGRATH MAC and GlideScope Core VLs at a large academic center.

Methods

This retrospective study was performed under exemption from the Thomas Jefferson University Institutional Review Board. The primary data sources consisted of hospital electronic patient records (EPIC) and cost information from the device manufacturers and hospital staff. The electronic patient data were provided by the EPIC Enterprise Analytics Business Intelligence group at Thomas Jefferson University Hospital (Center City Campus, Philadelphia, PA), while device costs were obtained from Verathon, Medtronic, and departmental staff responsible for purchasing equipment. Monthly data were obtained over a 24-month period (June 2018 through May 2020) when the McGRATH VL was placed into use in the department of anesthesiology. The 2 types of VLs were made available for use in a total of 52 locations, with the majority being hospital operating rooms.

The following variables were recorded: number of endotracheal intubations performed each month with breakdown between video laryngoscopy and flexible bronchoscopy airways, frequency of use for each type of laryngoscope, blades used, and equipment costs for use of each laryngoscope. Hospital cost estimates for both the McGRATH and GlideScope laryngoscopes included batteries, handles, blades, and the devices themselves. Cost data were also collected on frequency of device failure, maintenance, and replacement of parts and lost equipment.

Analysis

De-identified electronic medical records consisted of nominal and quantitative variables, with demographic data and information related to the endotracheal intubation procedure. All data were in chronological order and sorted by date after which coding was applied, to identify device type and allocate pertinent cost information. Descriptive statistics were reported as mean (SD) and sum for costs; frequency tables were generated for intubation procedures according to device type and time periods. Data were analyzed using the χ² test, the student t test, and the Wilcoxon Mann-Whitney U test, with a P value set at .05 for statistical significance. SPSS version 26 and GraphPad Prism version 6 were used for all statistical analyses.

A total of 34 600 endotracheal intubations were performed over the 24-month study period, and 11 345 (32.8%) were video laryngoscopy procedures. Out of all video laryngoscopy procedures, 5501 (48.5%) were performed using the McGRATH VL and 5305 (46.8%) were conducted using the GlideScope VL. The difference of 539 (4.8%) cases accounts for flexible bronchoscopy procedures and endotracheal intubations using other video laryngoscopy equipment. The mean (SD) monthly number of video laryngoscopy procedures for the 24 months was 221 (54) and 229 (89) for the GlideScope and McGRATH devices, respectively. Monthly endotracheal intubation distributions over 24 months trended upward for the McGRATH VL and downward for the GlideScope, but there was no statistically significant (P = .71) difference in overall use between the 2 instruments (Figure 1).

To examine the observed usage trends between the 2 VL during the first and last 12 months, a univariate ANOVA was conducted with the 2 time periods entered as predictors in the model. Video laryngoscopy intubations were performed (P = .001) more frequently with the GlideScope during the first 12 months; however, use of the McGRATH VL increased (P < .001) during the following 12 months compared to GlideScope. The GlideScope accounted for 54% of all VL intubations during the first 12 months, with the McGRATH accounting for 58% of all video laryngoscopy procedures for months 12 to 24. Additionally, the increase in video laryngoscopy procedures with the McGRATH during the last 3 months of the study period was despite an overall reduction in surgical volume due to the COVID-19 crisis, defined for this study as March 1, 2020, to May 31, 2020 (Figure 1). There was a statistically significant (P < .001) difference in the case distribution between use of the McGRATH and GlideScope VL for that period. The anesthesia personnel’s use of the McGRATH VL increased to 61% of all video laryngoscopy cases, compared to 37% for the GlideScope (Figure 2).

The total costs calculated for equipment, blades, and repairs are presented in Table 1 and yearly total costs are shown in Figure 3. Overall costs were $181 093 lower (55.5%) for the McGRATH VL compared to the GlideScope over the 24-month period. The mean (SD) monthly costs for GlideScope VL blades were $3837 ($1050) and $3236 ($538) for years 1 and 2, respectively, vs $1652 ($663) and $2933 ($585) for the McGRATH VL blades. Most of the total cost differences were attributed to equipment and blade purchases, which were $202 595 (65.0%) higher for the GlideScope compared to the McGRATH VL. The monthly blade costs alone were higher (P < .001) for the GlideScope over the 2-year period; however, the McGRATH VL required use of disposable stylets at a cost of $10 177 for all endotracheal intubations, compared to $700 for the GlideScope device.

An analysis was performed to determine whether costs differed between those 2 instruments during the COVID-19 period. There was a statistically significant (P < .001) difference in the case distribution between use of the McGRATH and GlideScope VLs during that period. The calculated blade cost difference for the COVID period was $128 higher for the McGRATH even though 293 more intubations were performed with that device (Table 2).

Discussion

We attempted to provide useful cost estimates by presenting pricing data reflecting the approximate cost that most large institutional anesthesia practices would incur for using those 2 specific devices and related peripherals. The main findings of our analysis showed that use of the McGRATH MAC VL resulted in a 55% cost savings compared to the GlideScope, with a similar number of cases performed with each device over the 24-month study period. We believe this represents a substantial savings to the department and institution, which has prompted internal review on the use of video laryngoscopy equipment. None of the McGRATH units failed; however, the GlideScope required 3 baton replacements.

Of note, use of the McGRATH MAC increased during the COVID-19 period, which may be explained by the fact that the operators found it to be a more portable device. Several physicians in the department commented that its smaller size made the McGRATH MAC more practical during the time when a plexiglass box was being used around the patient’s head to shield the intubator from aerosolized viral particles.

Although this study demonstrated the cost-saving value of the McGRATH over the GlideScope, a suggested next step would be to examine resource utilization related to video laryngoscopy use. The more dynamic tracking of the use of these devices should facilitate the assessment of existing related resources and decision making, to optimize the benefits of this initiative. We would anticipate reduced use of anesthesia personnel, such as technicians to assist with the management of this device which could be significant. As new respiratory viruses are appearing each year, video laryngoscopy will continue to gain increasing use in operating rooms and acute care locations. The adding of protective barriers between patients and providers calls for use of the most practical and effective VL devices, to protect personnel who are at high risk of contamination from airway secretions and aerosolized particles.^9,10

The COVID-19 pandemic has demonstrated the value of anesthesiology in regards to analyzing and finding solutions to effectively manage infected patients or those suspected of infection in the perioperative environment. Inexpensive products are often avoided because cheaper devices are associated with being of lower quality. However, the association with cost and quality—and the assumption that a higher price is positively correlated with higher quality—is overall inconsistent in the medical literature.¹¹ A more effective or higher quality treatment does not necessarily cost more and may actually end up costing less,¹² as was the case in this study. We have been able to directly cut departmental expenses by using a more efficient and cost-effective device for intubations, without compromising safety and efficacy. Future studies should determine whether this significant reduction in costs from video laryngoscopy intubations with the McGRATH VL will be sustained across anesthesiology departments in the Jefferson Health Enterprise Hospitals, or other health systems, as well as its impact on workflow and personnel resources.

This analysis was restricted to one of the campuses of the Jefferson Health Enterprise. However, this is the largest anesthesia practice, encompassing several locations, which should reflect the general practice patterns across other anesthesiology departments in this large institution. The costs for the devices and peripherals may vary across anesthesia practices depending on volume and contracts negotiated with the suppliers. It was not possible to estimate this variability, which could change the total costs by a few percentage points. We recognize that there may be other costs associated with securing the McGRATH VL to prevent loss from theft or misplacement, which were not included in the study. Lastly, the inability to obtain randomized samples for the 2 groups treated with each device opens up the possibility of selection bias. There were, however, multiple intubators who were free to select 1 of the devices for endotracheal intubation, which may have reduced the effect of selection bias.

Conclusion

This study demonstrated that over a 24-month period use of the McGRATH MAC VL resulted in a cost reduction of around 55% compared to using the GlideScope for endotracheal intubation procedures performed at a major academic center. Over the first 3 months of the COVID-19 crisis, which our study included, use of the McGRATH VL increased while GlideScope use decreased. This was most likely related to the portability and smaller size of the McGRATH, which better facilitated intubations of COVID-19 patients.

Acknowledgements: The authors thank Craig Smith, Senior Anesthesia Technician, for his assistance with the cost information and excellent record-keeping related to the use of video laryngoscopes.

Corresponding author: Marc C. Torjman, PhD, Professor, Department of Anesthesiology, Sidney Kimmel Medical College at Thomas Jefferson University, 111 South 11th St, Suite G-8290, Philadelphia, PA 19107; [email protected].

Financial disclosures: Dr. Thaler has served as a consultant for Medtronic since September 2020. He has participated in 2 webinars on the routine use of video laryngoscopy.

Funding: This study was supported by the Department of Anesthesiology at Thomas Jefferson University.

Identifying safe, effective, and affordable evidence-based dermatologic treatments for older adults can be challenging because of age-related changes in the skin, comorbidities, polypharmacy, mobility issues, and cognitive changes. Phototherapy has been shown to be an effective nonpharmacologic treatment option for multiple challenging dermatologic conditions^1-8; however, few studies have specifically examined its effectiveness in older adults. The challenge for older patients with psoriasis and dermatitis is that the conditions can be difficult to control and often require multiple treatment modalities.^9,10 Patients with psoriasis also have a higher risk for diabetes, dyslipidemia, and cardiovascular disease compared to other older patients,^11,12 which poses treatment challenges and makes nonpharmacologic treatments even more appealing.

Recent studies show that phototherapy can help decrease the use of dermatologic medications. Foerster and colleagues² found that adults with psoriasis who were treated with phototherapy significantly decreased their use of topical steroids (24.5% fewer patients required steroid creams and 31.1% fewer patients required psoriasis-specific topicals)(P<.01) while their use of non–psoriasis-specific medications did not change. Click and colleagues¹³ identified a decrease in medication costs, health care utilization, and risk for immunosuppression in patients treated with phototherapy when compared to those treated with biologics and apremilast. Methotrexate is a common dermatologic medication that is highly associated with increased risks in elderly patients because of impaired immune system function and the presence of comorbidities (eg, kidney disease, obesity, diabetes, fatty liver),¹⁴ which increase in prevalence with age. Combining phototherapy with methotrexate can substantially decrease the amount of methotrexate needed to achieve disease control,¹⁵ thereby decreasing the methotrexate-associated risks. Findings from these studies suggest that a safe, effective, cost-effective, and well-tolerated nonpharmacologic alternative, such as phototherapy, is highly desirable and should be optimized. Unfortunately, most studies that report the effectiveness of phototherapy are in younger populations.

This retrospective study aimed to (1) identify the most common dermatologic conditions treated with phototherapy in older adults, (2) examine the effectiveness and safety of phototherapy in older adults, and (3) compare the outcomes with 2 similar studies in the United Kingdom¹⁶ and Turkey.¹⁷

Methods

Design, Setting, Sample, and Statistical Analysis
The institutional review boards of Kaiser Permanente Washington Health Research Institute, Seattle, and the University of Washington, Seattle, approved this study. It was conducted in a large US multispecialty health care system (Group Health, Seattle, Washington [now Kaiser Permanente Washington]) serving approximately 600,000 patients, using billing records to identify all patients treated with phototherapy between January 1, 2015, and December 31, 2015, all who received narrowband UVB (NB-UVB) phototherapy. All adults 65 years and older who received phototherapy treatment during the 12-month study period were included. Patients were included regardless of comorbidities and other dermatologic treatments to maintain as much uniformity as possible between the present study and 2 prior studies examining phototherapy in older adult populations in the United Kingdom¹⁶ and Turkey.¹⁷ Demographic and clinical factors were presented using frequencies (percentages) or means and medians as appropriate. Comparisons of dermatologic conditions and clearance levels used a Fisher exact test. The number of phototherapy treatments to clearance and total number of treatments were compared between groups of patients using independent sample t tests.

Phototherapy Protocol
All patients received treatments administered by specially trained phototherapy nurses using a Daavlin UV Series (The Daavlin Company) or an Ultralite unit (Ultralite Enterprises, Inc), both with 48 lamps. All phototherapy nurses had been previously trained to provide treatments based on standardized protocols (Table 1) and to determine the patient’s level of disease clearance using a high to low clearance scale (Table 2). Daavlin’s treatment protocols were built into the software that accompanied the units and were developed based on the American Academy of Dermatology guidelines. The starting dose for an individual patient was determined based on the estimated minimal erythema dose for each phototype. If the patient was using photosensitizing medications, then the protocol guided the nurse to start the patient at a lower dose appropriate for their phototype. Patients with vitiligo were treated with the same starting and escalation doses as patients with Fitzpatrick phototype I because of the assumption that their vitiliginous skin had an increased risk for photosensitivity. A more recent review of the evidence has indicated that this assumption was overly conservative,¹⁸ and Kaiser Permanente Washington’s vitiligo protocol has been adjusted.

Results

Patients
Billing records identified 229 total patients who received phototherapy in 2015, of whom 52 (22.7%) were at least 65 years old. The median age was 70 years (range, 65–91 years). Twenty-nine (56%) were men and 35 (67%) had previously received phototherapy treatments.

Dermatologic Conditions Treated With Phototherapy
Our primary aim was to identify the most common dermatologic conditions treated with phototherapy in older adults. Psoriasis and dermatitis were the most common conditions treated in the sample (50% [26/52] and 21% [11/52], respectively), with mycosis fungoides being the third most common (10% [5/52]) and vitiligo tied with prurigo nodularis as fourth most common (6% [3/52])(Figure 1).

Effectiveness and Safety of Phototherapy
Our secondary aim was to examine the effectiveness and safety of phototherapy in older adults. Phototherapy was effective in this population, with 50 of 52 patients (96%) achieving a high or medium level of clearance. The degree of clearance for each of the dermatologic conditions is shown in Figure 2. Psoriasis and dermatitis achieved high clearance rates in 81% (21/26) and 82% (9/11) of patients, respectively. Overall, conditions did not have significant differences in clearances rates (Fisher exact test, P=.10). On average, it took patients 33 treatments to achieve medium or high rates of clearance. Psoriasis cleared more quickly, with an average of 30.4 treatments vs 36.1 treatments for other conditions, but the difference was not significant (t test, P=.26). Patients received an average of 98 total phototherapy treatments; the median number of treatments was 81 due to many being on maintenance therapy over several months. There was no relationship between a history of treatment with phototherapy and the total number of treatments needed to achieve clearance (t test, P=.40), but interestingly, those who had a history of phototherapy took approximately 5 more treatments to achieve clearance. The present study found that a slightly larger number of men were being treated for psoriasis (15 men vs 11 women), but there was no significant difference in response rate based on gender.

Comment

Our study found that 94% of patients with psoriasis achieved clearance with an average of 30.4 treatments, which is comparable to the reported 91% response rate with an average of 30 treatments in the United Kingdom.¹⁶ The other similar study in Turkey¹⁷ reported 73.7% of psoriasis patients achieved a 75% or more improvement from baseline with an average of 42 treatments, which may reflect underlying differences in regional skin type. Of note, the scatter chart (Figure 3) shows that several patients in the present study’s analysis are listed as not clear, but many of those patients had low treatment numbers below the mean time to clearance. Thus, the present study’s response rate may have been underestimated.

In the general population, studies show that psoriasis treated with standardized phototherapy protocols typically clears with an average of 20.6 treatments.²¹ The levels of clearance were similar in our study’s older population, but more treatments were required to achieve those results, with an average of 10 more treatments needed (an additional 3.3 weeks). Similar results were found in this sample for dermatitis and mycosis fungoides, indicating comparable clearance rates and levels but a need for more treatments to achieve similar results compared to the general population.

Additionally, in the current study more patients experienced grade 1 (mild) erythema (46%) and grade 2 erythema (25%) at some point in their treatment compared with the United Kingdom¹⁶ (1.89%) and Turkey¹⁷ (35%) studies, though these side effects did not impact the clearance rate. Interestingly, the current study’s scatter chart (Figure 3) illustrates that this side effect did not seem to increase with aging in this population. If anything, the erythema response was more prevalent in the median or younger patients in the sample. Erythema may have been due to the frequent use of photosensitizing medications in older adults in the United States, some of which typically get discontinued in patients 75 years and older (eg, statins). Other potential causes might include the use of phototype vs minimal erythema dose–driven protocols, the standard utilization of protocols originally designed for psoriasis vs other condition-specific protocols, missed treatments leading to increased sensitivity, or possibly shielding mishaps (eg, not wearing a prescribed face shield). Given the number of potential causes and the possibility of overlapping factors, careful analysis is important. With NB-UVB phototherapy, near-erythemogenic doses are optimal to achieve effective treatments, but this delicate balance may be more problematic for older adults. Future studies are needed to fully determine the factors at play for this population. In the interim, it is important for phototherapy-trained nurses to consider this risk carefully in the older population. They must follow the prescribed protocols that guide them to query patients about their responses to the prior treatment (eg, erythema, tenderness, itching), photosensitizing medications, missed treatments, and placement of shielding, and then adjust the treatment dosing accordingly.

Limitations
This study had several limitations. Although clinical outcomes were recorded prospectively, the analysis was retrospective, unblinded, and not placebo controlled. It was conducted in a single organization (Group Health [now Kaiser Permanente Washington]) but did analyze data from 4 medical centers in different cities with diverse demographics and a variety of nursing staff providing the treatments. Although the vitiligo treatment protocol likely slowed the response rate for those patients with vitiligo, the numbers were small (ie, only 3 of 52 patients), so the researchers chose to include them in the current study. The sample population was relatively small, but when these data are evaluated alongside the studies in the United Kingdom¹⁶ and Turkey,¹⁷ they show a consistent picture illustrating the effectiveness and safety of phototherapy in the older population. Further epidemiologic studies could be helpful to further describe the usefulness of this modality compared with other treatments for a variety of dermatoses in this age group. Supplementary analysis specifically examining the relationship between the number and type of photosensitizing medications, frequency of erythema, and time to clearance also could be useful.

Conclusion

Older adults with a variety of dermatoses respond well to phototherapy and should have the opportunity to use it, particularly considering the potential for increased complications and costs from other treatment modalities, such as commonly used immunosuppressive pharmaceuticals. However, the current study and the comparison studies indicate that it is important to carefully consider the slower clearance rates and the potential risk for increased erythema in this population and adjust patient education and treatment dosing accordingly.

Unfortunately, many dermatology centers do not offer phototherapy because of infrastructure limitations such as space and specially trained nursing staff. Increasing accessibility of phototherapy for older adults through home treatments may be an alternative, given its effectiveness in the general population.^22,23 In addition, home phototherapy may be worth pursuing for the older population considering the challenges they may face with transportation to the clinic setting and their increased risk for serious illness if exposed to infections such as COVID-19. The COVID-19 pandemic has brought to light the need for reliable, safe, and effective treatments that can be utilized in the safety of patients’ homes and should therefore be considered as an option for older adults. Issues such as mobility and cognitive decline could pose some complicating factors, but with the help of a well-trained family member or caregiver, home phototherapy could be a viable option that improves accessibility for older patients. Future research opportunities include further examination of the slower but ultimately equivalent response to phototherapy in the older population, the influence of photosensitizing medications on phototherapy effects, and the impact of phototherapy on utilization of immunosuppressive pharmaceuticals in older adults.

Identifying safe, effective, and affordable evidence-based dermatologic treatments for older adults can be challenging because of age-related changes in the skin, comorbidities, polypharmacy, mobility issues, and cognitive changes. Phototherapy has been shown to be an effective nonpharmacologic treatment option for multiple challenging dermatologic conditions^1-8; however, few studies have specifically examined its effectiveness in older adults. The challenge for older patients with psoriasis and dermatitis is that the conditions can be difficult to control and often require multiple treatment modalities.^9,10 Patients with psoriasis also have a higher risk for diabetes, dyslipidemia, and cardiovascular disease compared to other older patients,^11,12 which poses treatment challenges and makes nonpharmacologic treatments even more appealing.

Recent studies show that phototherapy can help decrease the use of dermatologic medications. Foerster and colleagues² found that adults with psoriasis who were treated with phototherapy significantly decreased their use of topical steroids (24.5% fewer patients required steroid creams and 31.1% fewer patients required psoriasis-specific topicals)(P<.01) while their use of non–psoriasis-specific medications did not change. Click and colleagues¹³ identified a decrease in medication costs, health care utilization, and risk for immunosuppression in patients treated with phototherapy when compared to those treated with biologics and apremilast. Methotrexate is a common dermatologic medication that is highly associated with increased risks in elderly patients because of impaired immune system function and the presence of comorbidities (eg, kidney disease, obesity, diabetes, fatty liver),¹⁴ which increase in prevalence with age. Combining phototherapy with methotrexate can substantially decrease the amount of methotrexate needed to achieve disease control,¹⁵ thereby decreasing the methotrexate-associated risks. Findings from these studies suggest that a safe, effective, cost-effective, and well-tolerated nonpharmacologic alternative, such as phototherapy, is highly desirable and should be optimized. Unfortunately, most studies that report the effectiveness of phototherapy are in younger populations.

This retrospective study aimed to (1) identify the most common dermatologic conditions treated with phototherapy in older adults, (2) examine the effectiveness and safety of phototherapy in older adults, and (3) compare the outcomes with 2 similar studies in the United Kingdom¹⁶ and Turkey.¹⁷

Methods

Design, Setting, Sample, and Statistical Analysis
The institutional review boards of Kaiser Permanente Washington Health Research Institute, Seattle, and the University of Washington, Seattle, approved this study. It was conducted in a large US multispecialty health care system (Group Health, Seattle, Washington [now Kaiser Permanente Washington]) serving approximately 600,000 patients, using billing records to identify all patients treated with phototherapy between January 1, 2015, and December 31, 2015, all who received narrowband UVB (NB-UVB) phototherapy. All adults 65 years and older who received phototherapy treatment during the 12-month study period were included. Patients were included regardless of comorbidities and other dermatologic treatments to maintain as much uniformity as possible between the present study and 2 prior studies examining phototherapy in older adult populations in the United Kingdom¹⁶ and Turkey.¹⁷ Demographic and clinical factors were presented using frequencies (percentages) or means and medians as appropriate. Comparisons of dermatologic conditions and clearance levels used a Fisher exact test. The number of phototherapy treatments to clearance and total number of treatments were compared between groups of patients using independent sample t tests.

Phototherapy Protocol
All patients received treatments administered by specially trained phototherapy nurses using a Daavlin UV Series (The Daavlin Company) or an Ultralite unit (Ultralite Enterprises, Inc), both with 48 lamps. All phototherapy nurses had been previously trained to provide treatments based on standardized protocols (Table 1) and to determine the patient’s level of disease clearance using a high to low clearance scale (Table 2). Daavlin’s treatment protocols were built into the software that accompanied the units and were developed based on the American Academy of Dermatology guidelines. The starting dose for an individual patient was determined based on the estimated minimal erythema dose for each phototype. If the patient was using photosensitizing medications, then the protocol guided the nurse to start the patient at a lower dose appropriate for their phototype. Patients with vitiligo were treated with the same starting and escalation doses as patients with Fitzpatrick phototype I because of the assumption that their vitiliginous skin had an increased risk for photosensitivity. A more recent review of the evidence has indicated that this assumption was overly conservative,¹⁸ and Kaiser Permanente Washington’s vitiligo protocol has been adjusted.

Results

Patients
Billing records identified 229 total patients who received phototherapy in 2015, of whom 52 (22.7%) were at least 65 years old. The median age was 70 years (range, 65–91 years). Twenty-nine (56%) were men and 35 (67%) had previously received phototherapy treatments.

Dermatologic Conditions Treated With Phototherapy
Our primary aim was to identify the most common dermatologic conditions treated with phototherapy in older adults. Psoriasis and dermatitis were the most common conditions treated in the sample (50% [26/52] and 21% [11/52], respectively), with mycosis fungoides being the third most common (10% [5/52]) and vitiligo tied with prurigo nodularis as fourth most common (6% [3/52])(Figure 1).

Effectiveness and Safety of Phototherapy
Our secondary aim was to examine the effectiveness and safety of phototherapy in older adults. Phototherapy was effective in this population, with 50 of 52 patients (96%) achieving a high or medium level of clearance. The degree of clearance for each of the dermatologic conditions is shown in Figure 2. Psoriasis and dermatitis achieved high clearance rates in 81% (21/26) and 82% (9/11) of patients, respectively. Overall, conditions did not have significant differences in clearances rates (Fisher exact test, P=.10). On average, it took patients 33 treatments to achieve medium or high rates of clearance. Psoriasis cleared more quickly, with an average of 30.4 treatments vs 36.1 treatments for other conditions, but the difference was not significant (t test, P=.26). Patients received an average of 98 total phototherapy treatments; the median number of treatments was 81 due to many being on maintenance therapy over several months. There was no relationship between a history of treatment with phototherapy and the total number of treatments needed to achieve clearance (t test, P=.40), but interestingly, those who had a history of phototherapy took approximately 5 more treatments to achieve clearance. The present study found that a slightly larger number of men were being treated for psoriasis (15 men vs 11 women), but there was no significant difference in response rate based on gender.

Comment

Our study found that 94% of patients with psoriasis achieved clearance with an average of 30.4 treatments, which is comparable to the reported 91% response rate with an average of 30 treatments in the United Kingdom.¹⁶ The other similar study in Turkey¹⁷ reported 73.7% of psoriasis patients achieved a 75% or more improvement from baseline with an average of 42 treatments, which may reflect underlying differences in regional skin type. Of note, the scatter chart (Figure 3) shows that several patients in the present study’s analysis are listed as not clear, but many of those patients had low treatment numbers below the mean time to clearance. Thus, the present study’s response rate may have been underestimated.

In the general population, studies show that psoriasis treated with standardized phototherapy protocols typically clears with an average of 20.6 treatments.²¹ The levels of clearance were similar in our study’s older population, but more treatments were required to achieve those results, with an average of 10 more treatments needed (an additional 3.3 weeks). Similar results were found in this sample for dermatitis and mycosis fungoides, indicating comparable clearance rates and levels but a need for more treatments to achieve similar results compared to the general population.

Additionally, in the current study more patients experienced grade 1 (mild) erythema (46%) and grade 2 erythema (25%) at some point in their treatment compared with the United Kingdom¹⁶ (1.89%) and Turkey¹⁷ (35%) studies, though these side effects did not impact the clearance rate. Interestingly, the current study’s scatter chart (Figure 3) illustrates that this side effect did not seem to increase with aging in this population. If anything, the erythema response was more prevalent in the median or younger patients in the sample. Erythema may have been due to the frequent use of photosensitizing medications in older adults in the United States, some of which typically get discontinued in patients 75 years and older (eg, statins). Other potential causes might include the use of phototype vs minimal erythema dose–driven protocols, the standard utilization of protocols originally designed for psoriasis vs other condition-specific protocols, missed treatments leading to increased sensitivity, or possibly shielding mishaps (eg, not wearing a prescribed face shield). Given the number of potential causes and the possibility of overlapping factors, careful analysis is important. With NB-UVB phototherapy, near-erythemogenic doses are optimal to achieve effective treatments, but this delicate balance may be more problematic for older adults. Future studies are needed to fully determine the factors at play for this population. In the interim, it is important for phototherapy-trained nurses to consider this risk carefully in the older population. They must follow the prescribed protocols that guide them to query patients about their responses to the prior treatment (eg, erythema, tenderness, itching), photosensitizing medications, missed treatments, and placement of shielding, and then adjust the treatment dosing accordingly.

Limitations
This study had several limitations. Although clinical outcomes were recorded prospectively, the analysis was retrospective, unblinded, and not placebo controlled. It was conducted in a single organization (Group Health [now Kaiser Permanente Washington]) but did analyze data from 4 medical centers in different cities with diverse demographics and a variety of nursing staff providing the treatments. Although the vitiligo treatment protocol likely slowed the response rate for those patients with vitiligo, the numbers were small (ie, only 3 of 52 patients), so the researchers chose to include them in the current study. The sample population was relatively small, but when these data are evaluated alongside the studies in the United Kingdom¹⁶ and Turkey,¹⁷ they show a consistent picture illustrating the effectiveness and safety of phototherapy in the older population. Further epidemiologic studies could be helpful to further describe the usefulness of this modality compared with other treatments for a variety of dermatoses in this age group. Supplementary analysis specifically examining the relationship between the number and type of photosensitizing medications, frequency of erythema, and time to clearance also could be useful.

Conclusion

Older adults with a variety of dermatoses respond well to phototherapy and should have the opportunity to use it, particularly considering the potential for increased complications and costs from other treatment modalities, such as commonly used immunosuppressive pharmaceuticals. However, the current study and the comparison studies indicate that it is important to carefully consider the slower clearance rates and the potential risk for increased erythema in this population and adjust patient education and treatment dosing accordingly.

Unfortunately, many dermatology centers do not offer phototherapy because of infrastructure limitations such as space and specially trained nursing staff. Increasing accessibility of phototherapy for older adults through home treatments may be an alternative, given its effectiveness in the general population.^22,23 In addition, home phototherapy may be worth pursuing for the older population considering the challenges they may face with transportation to the clinic setting and their increased risk for serious illness if exposed to infections such as COVID-19. The COVID-19 pandemic has brought to light the need for reliable, safe, and effective treatments that can be utilized in the safety of patients’ homes and should therefore be considered as an option for older adults. Issues such as mobility and cognitive decline could pose some complicating factors, but with the help of a well-trained family member or caregiver, home phototherapy could be a viable option that improves accessibility for older patients. Future research opportunities include further examination of the slower but ultimately equivalent response to phototherapy in the older population, the influence of photosensitizing medications on phototherapy effects, and the impact of phototherapy on utilization of immunosuppressive pharmaceuticals in older adults.

Identifying safe, effective, and affordable evidence-based dermatologic treatments for older adults can be challenging because of age-related changes in the skin, comorbidities, polypharmacy, mobility issues, and cognitive changes. Phototherapy has been shown to be an effective nonpharmacologic treatment option for multiple challenging dermatologic conditions^1-8; however, few studies have specifically examined its effectiveness in older adults. The challenge for older patients with psoriasis and dermatitis is that the conditions can be difficult to control and often require multiple treatment modalities.^9,10 Patients with psoriasis also have a higher risk for diabetes, dyslipidemia, and cardiovascular disease compared to other older patients,^11,12 which poses treatment challenges and makes nonpharmacologic treatments even more appealing.

Recent studies show that phototherapy can help decrease the use of dermatologic medications. Foerster and colleagues² found that adults with psoriasis who were treated with phototherapy significantly decreased their use of topical steroids (24.5% fewer patients required steroid creams and 31.1% fewer patients required psoriasis-specific topicals)(P<.01) while their use of non–psoriasis-specific medications did not change. Click and colleagues¹³ identified a decrease in medication costs, health care utilization, and risk for immunosuppression in patients treated with phototherapy when compared to those treated with biologics and apremilast. Methotrexate is a common dermatologic medication that is highly associated with increased risks in elderly patients because of impaired immune system function and the presence of comorbidities (eg, kidney disease, obesity, diabetes, fatty liver),¹⁴ which increase in prevalence with age. Combining phototherapy with methotrexate can substantially decrease the amount of methotrexate needed to achieve disease control,¹⁵ thereby decreasing the methotrexate-associated risks. Findings from these studies suggest that a safe, effective, cost-effective, and well-tolerated nonpharmacologic alternative, such as phototherapy, is highly desirable and should be optimized. Unfortunately, most studies that report the effectiveness of phototherapy are in younger populations.

This retrospective study aimed to (1) identify the most common dermatologic conditions treated with phototherapy in older adults, (2) examine the effectiveness and safety of phototherapy in older adults, and (3) compare the outcomes with 2 similar studies in the United Kingdom¹⁶ and Turkey.¹⁷

Methods

Design, Setting, Sample, and Statistical Analysis
The institutional review boards of Kaiser Permanente Washington Health Research Institute, Seattle, and the University of Washington, Seattle, approved this study. It was conducted in a large US multispecialty health care system (Group Health, Seattle, Washington [now Kaiser Permanente Washington]) serving approximately 600,000 patients, using billing records to identify all patients treated with phototherapy between January 1, 2015, and December 31, 2015, all who received narrowband UVB (NB-UVB) phototherapy. All adults 65 years and older who received phototherapy treatment during the 12-month study period were included. Patients were included regardless of comorbidities and other dermatologic treatments to maintain as much uniformity as possible between the present study and 2 prior studies examining phototherapy in older adult populations in the United Kingdom¹⁶ and Turkey.¹⁷ Demographic and clinical factors were presented using frequencies (percentages) or means and medians as appropriate. Comparisons of dermatologic conditions and clearance levels used a Fisher exact test. The number of phototherapy treatments to clearance and total number of treatments were compared between groups of patients using independent sample t tests.

Phototherapy Protocol
All patients received treatments administered by specially trained phototherapy nurses using a Daavlin UV Series (The Daavlin Company) or an Ultralite unit (Ultralite Enterprises, Inc), both with 48 lamps. All phototherapy nurses had been previously trained to provide treatments based on standardized protocols (Table 1) and to determine the patient’s level of disease clearance using a high to low clearance scale (Table 2). Daavlin’s treatment protocols were built into the software that accompanied the units and were developed based on the American Academy of Dermatology guidelines. The starting dose for an individual patient was determined based on the estimated minimal erythema dose for each phototype. If the patient was using photosensitizing medications, then the protocol guided the nurse to start the patient at a lower dose appropriate for their phototype. Patients with vitiligo were treated with the same starting and escalation doses as patients with Fitzpatrick phototype I because of the assumption that their vitiliginous skin had an increased risk for photosensitivity. A more recent review of the evidence has indicated that this assumption was overly conservative,¹⁸ and Kaiser Permanente Washington’s vitiligo protocol has been adjusted.

Results

Patients
Billing records identified 229 total patients who received phototherapy in 2015, of whom 52 (22.7%) were at least 65 years old. The median age was 70 years (range, 65–91 years). Twenty-nine (56%) were men and 35 (67%) had previously received phototherapy treatments.

Dermatologic Conditions Treated With Phototherapy
Our primary aim was to identify the most common dermatologic conditions treated with phototherapy in older adults. Psoriasis and dermatitis were the most common conditions treated in the sample (50% [26/52] and 21% [11/52], respectively), with mycosis fungoides being the third most common (10% [5/52]) and vitiligo tied with prurigo nodularis as fourth most common (6% [3/52])(Figure 1).

Effectiveness and Safety of Phototherapy
Our secondary aim was to examine the effectiveness and safety of phototherapy in older adults. Phototherapy was effective in this population, with 50 of 52 patients (96%) achieving a high or medium level of clearance. The degree of clearance for each of the dermatologic conditions is shown in Figure 2. Psoriasis and dermatitis achieved high clearance rates in 81% (21/26) and 82% (9/11) of patients, respectively. Overall, conditions did not have significant differences in clearances rates (Fisher exact test, P=.10). On average, it took patients 33 treatments to achieve medium or high rates of clearance. Psoriasis cleared more quickly, with an average of 30.4 treatments vs 36.1 treatments for other conditions, but the difference was not significant (t test, P=.26). Patients received an average of 98 total phototherapy treatments; the median number of treatments was 81 due to many being on maintenance therapy over several months. There was no relationship between a history of treatment with phototherapy and the total number of treatments needed to achieve clearance (t test, P=.40), but interestingly, those who had a history of phototherapy took approximately 5 more treatments to achieve clearance. The present study found that a slightly larger number of men were being treated for psoriasis (15 men vs 11 women), but there was no significant difference in response rate based on gender.

Comment

Our study found that 94% of patients with psoriasis achieved clearance with an average of 30.4 treatments, which is comparable to the reported 91% response rate with an average of 30 treatments in the United Kingdom.¹⁶ The other similar study in Turkey¹⁷ reported 73.7% of psoriasis patients achieved a 75% or more improvement from baseline with an average of 42 treatments, which may reflect underlying differences in regional skin type. Of note, the scatter chart (Figure 3) shows that several patients in the present study’s analysis are listed as not clear, but many of those patients had low treatment numbers below the mean time to clearance. Thus, the present study’s response rate may have been underestimated.

In the general population, studies show that psoriasis treated with standardized phototherapy protocols typically clears with an average of 20.6 treatments.²¹ The levels of clearance were similar in our study’s older population, but more treatments were required to achieve those results, with an average of 10 more treatments needed (an additional 3.3 weeks). Similar results were found in this sample for dermatitis and mycosis fungoides, indicating comparable clearance rates and levels but a need for more treatments to achieve similar results compared to the general population.

Additionally, in the current study more patients experienced grade 1 (mild) erythema (46%) and grade 2 erythema (25%) at some point in their treatment compared with the United Kingdom¹⁶ (1.89%) and Turkey¹⁷ (35%) studies, though these side effects did not impact the clearance rate. Interestingly, the current study’s scatter chart (Figure 3) illustrates that this side effect did not seem to increase with aging in this population. If anything, the erythema response was more prevalent in the median or younger patients in the sample. Erythema may have been due to the frequent use of photosensitizing medications in older adults in the United States, some of which typically get discontinued in patients 75 years and older (eg, statins). Other potential causes might include the use of phototype vs minimal erythema dose–driven protocols, the standard utilization of protocols originally designed for psoriasis vs other condition-specific protocols, missed treatments leading to increased sensitivity, or possibly shielding mishaps (eg, not wearing a prescribed face shield). Given the number of potential causes and the possibility of overlapping factors, careful analysis is important. With NB-UVB phototherapy, near-erythemogenic doses are optimal to achieve effective treatments, but this delicate balance may be more problematic for older adults. Future studies are needed to fully determine the factors at play for this population. In the interim, it is important for phototherapy-trained nurses to consider this risk carefully in the older population. They must follow the prescribed protocols that guide them to query patients about their responses to the prior treatment (eg, erythema, tenderness, itching), photosensitizing medications, missed treatments, and placement of shielding, and then adjust the treatment dosing accordingly.

Limitations
This study had several limitations. Although clinical outcomes were recorded prospectively, the analysis was retrospective, unblinded, and not placebo controlled. It was conducted in a single organization (Group Health [now Kaiser Permanente Washington]) but did analyze data from 4 medical centers in different cities with diverse demographics and a variety of nursing staff providing the treatments. Although the vitiligo treatment protocol likely slowed the response rate for those patients with vitiligo, the numbers were small (ie, only 3 of 52 patients), so the researchers chose to include them in the current study. The sample population was relatively small, but when these data are evaluated alongside the studies in the United Kingdom¹⁶ and Turkey,¹⁷ they show a consistent picture illustrating the effectiveness and safety of phototherapy in the older population. Further epidemiologic studies could be helpful to further describe the usefulness of this modality compared with other treatments for a variety of dermatoses in this age group. Supplementary analysis specifically examining the relationship between the number and type of photosensitizing medications, frequency of erythema, and time to clearance also could be useful.

Conclusion

Older adults with a variety of dermatoses respond well to phototherapy and should have the opportunity to use it, particularly considering the potential for increased complications and costs from other treatment modalities, such as commonly used immunosuppressive pharmaceuticals. However, the current study and the comparison studies indicate that it is important to carefully consider the slower clearance rates and the potential risk for increased erythema in this population and adjust patient education and treatment dosing accordingly.

Unfortunately, many dermatology centers do not offer phototherapy because of infrastructure limitations such as space and specially trained nursing staff. Increasing accessibility of phototherapy for older adults through home treatments may be an alternative, given its effectiveness in the general population.^22,23 In addition, home phototherapy may be worth pursuing for the older population considering the challenges they may face with transportation to the clinic setting and their increased risk for serious illness if exposed to infections such as COVID-19. The COVID-19 pandemic has brought to light the need for reliable, safe, and effective treatments that can be utilized in the safety of patients’ homes and should therefore be considered as an option for older adults. Issues such as mobility and cognitive decline could pose some complicating factors, but with the help of a well-trained family member or caregiver, home phototherapy could be a viable option that improves accessibility for older patients. Future research opportunities include further examination of the slower but ultimately equivalent response to phototherapy in the older population, the influence of photosensitizing medications on phototherapy effects, and the impact of phototherapy on utilization of immunosuppressive pharmaceuticals in older adults.

Acute illnesses requiring hospitalization serve as a sentinel event, with many older adults requiring assistance with activities of daily living (ADLs) upon discharge.^1-3 Older adults who are frail experience even higher rates of hospital-associated disability, and rates of recovery to baseline functional status have varied.^4,5 Loss of independence in ADLs has been associated with nursing home (NH) utilization, caregiver burden, and mortality.⁶

To date, studies have characterized functional trajectories before and after hospitalization in older persons for broad medical conditions, noting persistence of disability and incomplete recovery to baseline functional status.⁷ Prior evaluations have also noted the long-term disabling impact of critical conditions such as acute myocardial infarction, stroke, and sepsis,^8,9 but a knowledge gap exists regarding the subsequent functional disability, recovery, and incident NH admission among older persons who are hospitalized for ambulatory care sensitive conditions (ACSCs). Often considered potentially preventable with optimal ambulatory care,^10,11 ACSCs represent acute, chronic, and vaccine-preventable conditions, including urinary tract infection, congestive heart failure, diabetes mellitus, and pneumonia. Investigating the aforementioned patient-centered measures post hospitalization could provide valuable supporting evidence for the continued recognition of ACSC-related hospitalizations in national quality payment programs set forth by the Centers for Medicare & Medicaid Services (CMS).¹² Demonstrating adverse outcomes after ACSC-related hospitalizations may help support interventions that target potentially preventable ACSC-related hospitalizations, such as home-based care or telehealth, with the goal of improving functional outcomes and reducing NH admission in older persons.

To address these gaps, we evaluated ACSC-related hospitalizations among participants of the Precipitating Events Project (PEP), a 19-year longitudinal study of community-living persons who were initially nondisabled in their basic functional activities. In the 6 months following an ACSC-related hospitalization, our objectives were to describe: (1) the 6-month course of postdischarge functional disability, (2) the cumulative monthly probability of functional recovery, and (3) the cumulative monthly probability of incident NH admission.

Study Population

Participants were drawn from the PEP study, an ongoing, prospective, longitudinal study of 754 community-dwelling persons aged 70 years or older.¹³ Potential participants were members of a large health plan in greater New Haven, Connecticut, and were enrolled from March 1998 through October 1999. As previously described,¹⁴ persons were oversampled if they were physically frail, as denoted by a timed score >10 seconds on the rapid gait test. Exclusion criteria included significant cognitive impairment with no available proxy, life expectancy less than 12 months, plans to leave the area, and inability to speak English. Participants were initially required to be nondisabled in four basic activities of daily living (bathing, dressing, walking across a room, and transferring from a chair). Eligibility was determined during a screening telephone interview and was confirmed during an in-home assessment. Of the eligible members, 75.2% agreed to participate in the project, and persons who declined to participate did not significantly differ in age or sex from those who were enrolled. The Yale Human Investigation Committee approved the study protocol, and all participants provided verbal informed consent.

Data Collection

From 1998 to 2017, comprehensive home-based assessments were completed by trained research nurses at baseline and at 18-month intervals over 234 months (except at 126 months), and telephone interviews were completed monthly through June 2018, to obtain information on disability over time. For participants who had significant cognitive impairment or who were unavailable, we interviewed a proxy informant using a rigorous protocol with demonstrated reliability and validity.¹⁴ All incident NH admissions, including both short- and long-term stays, were identified using the CMS Skilled Nursing Facility claims file and Long Term Care Minimum Data Set. Deaths were ascertained by review of obituaries and/or from a proxy informant, with a completion rate of 100%. A total of 688 participants (91.2%) had died after a median follow-up of 108 months, while 43 participants (5.7%) dropped out of the study after a median follow-up of 27 months. Among all participants, data were otherwise available for 99.2% of 85,531 monthly telephone interviews.

Assembly of Analytic Sample

PEP participants were considered for inclusion in the analytic sample if they had a hospitalization with an ACSC as the primary diagnosis on linked Medicare claims data. The complete list of ACSCs was defined using specifications from the Agency for Healthcare Research and Quality,¹⁵ and was assembled using the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) classification prior to October 1, 2015, and ICD Tenth Revision, Clinical Modification (ICD-10-CM) classification after October 1, 2015 (Appendix Table 1). Examples of ACSCs include congestive heart failure, dehydration, urinary tract infection, and angina without procedure. As performed previously,^16,17 two ACSCs (low birthweight; asthma in younger adults 18-39 years) were not included in this analysis because they were not based on full adult populations.

ACSC-related hospitalizations were included through December 2017. Participants could contribute more than one ACSC-related hospitalization over the course of the study based on the following criteria: (1) participant did not have a prior non-ACSC-related hospitalization within an 18-month interval; (2) participant did not have a prior ACSC-related hospitalization or treat-and-release emergency department (ED) visit within an 18-month interval (to ensure independence of observations if the participant was still recovering from the prior event and because some of the characteristics within Table 1 are susceptible to change in the setting of an intervening event and, hence, would not accurately reflect the status of the participant prior to ACSC-related hospitalization); (3) participant was not admitted from a NH; (4) participant did not have an in-hospital intensive care unit (ICU) stay (because persons with critical illness are a distinct population with frequent disability and prolonged recovery, as previously described¹⁸), in-hospital death, or death before first follow-up interview (because our aim was to evaluate disability and recovery after the hospitalization⁷).

Assembly of the primary analytic sample is depicted in the Appendix Figure. Of the 814 patients who were identified with ACSC-related hospitalizations, 107 had a prior non-ACSC-related hospitalization and 275 had a prior ACSC-related hospitalization or a treat-and-release ED visit within an 18-month interval. Of the remaining 432 ACSC-related hospitalizations, 181 were excluded: 114 patients were admitted from a NH, 38 had an in-hospital ICU stay, 3 died in the hospital, 11 died before their first follow-up interview, and 15 had withdrawn from the study. The primary analytic sample included the remaining 251 ACSC-related hospitalizations, contributed by 196 participants. Specifically, nine participants contributed three ACSC-related hospitalizations each, 37 participants contributed two hospitalizations each, and the remaining 150 participants contributed one hospitalization each. During the 6-month follow-up period, 40 participants contributing ACSC-related hospitalizations died after a median (interquartile range [IQR]) of 4 (2-5) months, and 1 person refused continued participation.

Comprehensive Assessments

During the comprehensive in-home assessments, data were obtained on demographic characteristics. Age was measured in years at the time of the ACSC-related hospitalization. In addition, we describe factors from the comprehensive assessment immediately prior to the ACSC-related hospitalization, grouped into two additional domains related to disability¹⁹: health-related and cognitive-psychosocial. The health-related factors included nine self-reported, physician-diagnosed chronic conditions and frailty. The cognitive-psychosocial factors included social support, cognitive impairment, and depressive symptoms.

Assessment of Disability

Complete details about the assessment of disability have been previously described.^13,14,19,20 Briefly, disability was assessed during the monthly telephone interviews, and included four basic activities (bathing, dressing, walking across a room, and transferring from a chair), five instrumental activities (shopping, housework, meal preparation, taking medications, and managing finances), and three mobility activities (walking a quarter mile, climbing a flight of stairs, and lifting or carrying 10 lb). Participants were asked, “At the present time, do you need help from another person to [complete the task]?” Disability was operationalized as the need for personal assistance or an inability to perform the task. Participants were also asked about a fourth mobility activity, “Have you driven a car during the past month?” Those who responded no were classified as being disabled in driving.¹⁹

The number of disabilities overall and for each functional domain (basic, instrumental, and mobility) was summed. Possible disability scores ranged from 0 to 13, with a score of 0 indicating complete independence in all of the items, and a score of 13 indicating complete dependence. Worse postdischarge disability was defined as a total disability score (0-13) at the first telephone interview after an ACSC-related hospitalization that was greater than the total disability score from the telephone interview immediately preceding hospitalization.

Outcome Measures

The primary outcome was the number of disabilities in all 13 basic, instrumental, and mobility activities in each of the 6 months following discharge from an ACSC-related hospitalization. To determine whether our findings were consistent across the three functional domains, we also evaluated the number of disabilities in the four basic, five instrumental, and four mobility activities separately. As secondary outcomes, we evaluated: (1) the cumulative probability of recovery within the 6-month follow-up time frame after an ACSC-related hospitalization, with “recovery” defined as return to the participant’s pre-ACSC-related hospitalization total disability score, and (2) the cumulative probability of incident NH admission within the 6 months after an ACSC-related hospitalization. Aligned with CMS and prior literature,^21,22 we defined a short-term NH stay as ≤100 days and a long-term NH stay as >100 days.

Statistical Analysis

Pre-ACSC-related hospitalization characteristics were summarized by means (SDs) and frequencies with proportions. We determined the mean number of disabilities in each of the 6 months following hospital discharge, with the prehospitalization value included as a reference point. We also determined the mean (SD) number of disabilities for the three subscales of disability (basic activities of daily living [BADLs], instrumental activities of daily living [IADLs], and mobility activities). We calculated the cumulative probability of recovery within 6 months of hospital discharge. Finally, we determined the cumulative probability of incident NH admission during the 6 months after hospital discharge.

To test the robustness of our main results, we conducted a sensitivity analysis assessing disability scores of the 150 participants that contributed only one ACSC-related hospitalization. All analyses were performed using Stata, version 16.0, statistical software (StataCorp).

Table 1 shows the characteristics of the 251 ACSC-related hospitalizations immediately prior to hospitalization. Participants’ mean (SD) age was 85.1 (6.0) years, and the mean total disability score was 5.4. The majority were female, non-Hispanic White, frail, and lived alone. As shown in Appendix Table 2, the three most common reasons for ACSC-related hospitalizations were congestive heart failure (n = 69), bacterial pneumonia (n = 53), and dehydration (n = 44).

The Figure shows the disability scores during the 6-month follow-up period for total, basic, instrumental, and mobility activities, in panels A, B, C, and D, respectively. The exact values are provided in Appendix Table 3. After hospitalization, disability scores for total, basic, instrumental, and mobility activities peaked at month 1 and tended to improve modestly over the next 5 months, but remained greater, on average, than pre-hospitalization scores. Of the 40 participants who died within the 6-month follow-up period, 36 (90%) had worse disability scores in their last month of life than in the month prior to their ACSC-related hospitalization.

Table 2 shows the cumulative probability of functional recovery after ACSC-related hospitalizations. Recovery was incomplete, with only 70% (95% CI, 64%-76%) of hospitalizations achieving a return to the pre-hospitalization total disability score within 6 months of hospitalization.

Table 3 shows the cumulative probability of incident NH admission after an ACSC-related hospitalization. Of the 251 ACSC-related hospitalizations, incident NH admission was experienced by 38% (95% CI, 32%-44%) within 1 month and 50% (95% CI, 43%-56%) within 6 months of discharge. Short-term NH stays accounted for 90 (75.6%) of the 119 incident NH admissions within the 6 months after ACSC-related hospitalizations. Sensitivity analyses yielded comparable disability scores, shown in Appendix Table 4.

In this longitudinal study of community-living older persons, we evaluated functional disability, recovery, and incident NH admission within 6 months of hospitalization for an ACSC. Our study has three major findings. First, disability scores for total, basic, instrumental, and mobility activities at months 1 to 6 of follow-up were greater on average than pre-hospitalization scores. Second, functional recovery was not achieved by 3 of 10 participants after an ACSC-related hospitalization. Third, half of them experienced an incident NH admission within 6 months of discharge from an ACSC-related hospitalization, although about three-quarters of these were short-term stays. Our findings provide evidence that older persons experience clinically meaningful adverse patient-reported outcomes after ACSC-related hospitalizations.

Prior research involving ACSCs has focused largely on rates of hospitalization as a measure of access to primary care and the associated factors predictive of ACSC-related hospitalizations,^23-26 and has not addressed subsequent patient-reported outcomes. The findings in this analysis highlight that older persons experience worsening disability immediately after an ACSC-related hospitalization, which persists for prolonged periods and often results in incomplete recovery. Prior research has assessed pre-hospitalization functional status through retrospective recall approaches,² included only older adults discharged with incident disability,³ and examined functional status after all-cause medical illness hospitalizations.⁵ Our prospective analysis extends the literature by reliably capturing pre-hospital disability scores and uniquely assessing the cohort of older persons hospitalized with ACSCs.

Our work is relevant to the continued evaluation of ACSC-related hospitalizations in national quality measurement and payment initiatives among Medicare beneficiaries. In prior evaluations of ACSC-related quality measures, stakeholders have criticized the measures for limited validity due to a lack of evidence linking each utilization outcome to other patient-centered outcomes.^10,27 Our work addresses this gap by demonstrating that ACSC-related hospitalizations are linked to persistent disability, incomplete functional recovery, and incident NH admissions. Given the large body of evidence demonstrating the priority older persons place on these patient-reported outcomes,^28,29 our work should reassure policymakers seeking to transform quality measurement programs into a more patient-oriented enterprise.

Our findings have several clinical practice, research, and policy implications. First, more-effective clinical strategies to minimize the level of care required for acute exacerbations of ACSC-related illnesses may include: (1) substituting home-based care³⁰ and telehealth interventions³¹ for traditional inpatient hospitalization, (2) making in-ED resources (ie, case management services, geriatric-focused advanced practice providers) more accessible for older persons with ACSC-related illnesses, thereby enhancing care transitions and follow-up to avoid potential current and subsequent hospitalizations, and (3) ensuring adequate ambulatory care access to all older persons, as prior work has shown variation in ACSC hospital admission rates dependent on population factors such as high-poverty neighborhoods,¹⁶ insurance status,^16,32 and race/ethnicity.³³

Clinical strategies have been narrow and not holistic for ACSCs; for example, many institutions have focused on pneumonia vaccinations to reduce hospitalizations, but our work supports the need to further evaluate the impact of preventing ACSC-related hospitalizations and their associated disabling consequences. For patients admitted to the hospital, clinical strategies, such as in-hospital or post-hospital mobility and activity programs, have been shown to be protective against hospital-associated disability.^34,35 Furthermore, hospital discharge planning could include preparing older persons for anticipated functional disabilities, associated recoveries, and NH admission after ACSC-related hospitalizations. Risk factors contributing to post-hospitalization functional disability and recovery have been identified,^19,20,36 but future work is needed to: (1) identify target populations (including those most likely to worsen) so that interventions can be offered earlier in the course of care to those who would benefit most, and (2) identify and learn from those who are resilient and have recovered, to better understand factors contributing to their success.

Our study has several strengths. First, the study is unique due to its longitudinal design, with monthly assessments of functional status. Since functional status was assessed prospectively before the ACSC-related hospitalization, we also have avoided any potential concern for recall bias that may be present if assessed after the hospitalization. Additionally, through the use of Medicare claims and the Minimum Data Set, the ascertainment of hospitalizations and NH admissions was likely complete for the studied population.

However, the study has limitations. First, functional measures were based on self-reports rather than objective measurements. Nevertheless, the self-report function is often used to guide coverage determinations in the Medicare program, as it has been shown to be associated with poor health outcomes.³⁷ Second, we are unable to comment on the rate of functional decline or NH admission when an older person was not hospitalized in relation to an ACSC. Future analyses may benefit from using a control group (eg, older adults without an ACSC hospitalization or older adults with a non-ACSC hospitalization). Third, we used strict exclusion criteria to identify a population of older adults without recent hospitalizations to determine the isolated impact of ACSC hospitalization on disability, incident NH admission, and functional recovery. Considering this potential selection bias, our findings are likely conservative estimates of the patient-centered outcomes evaluated. Fourth, participants were not asked about feeding and toileting. However, the incidence of disability in these ADLs is low among nondisabled, community-living older persons, and it is highly uncommon for disability to develop in these ADLs without concurrent disability in the ADLs within this analysis.^14,38

Finally, because our study participants were members of a single health plan in a small urban area and included nondisabled older persons living in the community, our findings may not be generalizable to geriatric patients in other settings. Nonetheless, the demographics of our cohort reflect those of older persons in New Haven County, Connecticut, which are similar to the demographics of the US population, with the exception of race and ethnicity. In addition, the generalizability of our results are strengthened by the study’s high participation rate and minimal attrition.

Within 6 months of ACSC-related hospitalizations, community-living older persons exhibited greater total disability scores than those immediately preceding hospitalization. In the same time frame, 3 of 10 older persons did not achieve functional recovery, and half experienced incident NH admission. These results provide evidence regarding the continued recognition of ACSC-related hospitalizations in federal quality measurement and payment programs and suggests the need for preventive and comprehensive interventions to meaningfully improve longitudinal outcomes.

We thank Denise Shepard, BSN, MBA, Andrea Benjamin, BSN, Barbara Foster, and Amy Shelton, MPH, for assistance with data collection; Geraldine Hawthorne, BS, for assistance with data entry and management; Peter Charpentier, MPH, for design and development of the study database and participant tracking system; and Joanne McGloin, MDiv, MBA, for leadership and advice as the Project Director. Each of these persons were paid employees of Yale School of Medicine during the conduct of this study.

Acute illnesses requiring hospitalization serve as a sentinel event, with many older adults requiring assistance with activities of daily living (ADLs) upon discharge.^1-3 Older adults who are frail experience even higher rates of hospital-associated disability, and rates of recovery to baseline functional status have varied.^4,5 Loss of independence in ADLs has been associated with nursing home (NH) utilization, caregiver burden, and mortality.⁶

To date, studies have characterized functional trajectories before and after hospitalization in older persons for broad medical conditions, noting persistence of disability and incomplete recovery to baseline functional status.⁷ Prior evaluations have also noted the long-term disabling impact of critical conditions such as acute myocardial infarction, stroke, and sepsis,^8,9 but a knowledge gap exists regarding the subsequent functional disability, recovery, and incident NH admission among older persons who are hospitalized for ambulatory care sensitive conditions (ACSCs). Often considered potentially preventable with optimal ambulatory care,^10,11 ACSCs represent acute, chronic, and vaccine-preventable conditions, including urinary tract infection, congestive heart failure, diabetes mellitus, and pneumonia. Investigating the aforementioned patient-centered measures post hospitalization could provide valuable supporting evidence for the continued recognition of ACSC-related hospitalizations in national quality payment programs set forth by the Centers for Medicare & Medicaid Services (CMS).¹² Demonstrating adverse outcomes after ACSC-related hospitalizations may help support interventions that target potentially preventable ACSC-related hospitalizations, such as home-based care or telehealth, with the goal of improving functional outcomes and reducing NH admission in older persons.

To address these gaps, we evaluated ACSC-related hospitalizations among participants of the Precipitating Events Project (PEP), a 19-year longitudinal study of community-living persons who were initially nondisabled in their basic functional activities. In the 6 months following an ACSC-related hospitalization, our objectives were to describe: (1) the 6-month course of postdischarge functional disability, (2) the cumulative monthly probability of functional recovery, and (3) the cumulative monthly probability of incident NH admission.

Study Population

Participants were drawn from the PEP study, an ongoing, prospective, longitudinal study of 754 community-dwelling persons aged 70 years or older.¹³ Potential participants were members of a large health plan in greater New Haven, Connecticut, and were enrolled from March 1998 through October 1999. As previously described,¹⁴ persons were oversampled if they were physically frail, as denoted by a timed score >10 seconds on the rapid gait test. Exclusion criteria included significant cognitive impairment with no available proxy, life expectancy less than 12 months, plans to leave the area, and inability to speak English. Participants were initially required to be nondisabled in four basic activities of daily living (bathing, dressing, walking across a room, and transferring from a chair). Eligibility was determined during a screening telephone interview and was confirmed during an in-home assessment. Of the eligible members, 75.2% agreed to participate in the project, and persons who declined to participate did not significantly differ in age or sex from those who were enrolled. The Yale Human Investigation Committee approved the study protocol, and all participants provided verbal informed consent.

Data Collection

From 1998 to 2017, comprehensive home-based assessments were completed by trained research nurses at baseline and at 18-month intervals over 234 months (except at 126 months), and telephone interviews were completed monthly through June 2018, to obtain information on disability over time. For participants who had significant cognitive impairment or who were unavailable, we interviewed a proxy informant using a rigorous protocol with demonstrated reliability and validity.¹⁴ All incident NH admissions, including both short- and long-term stays, were identified using the CMS Skilled Nursing Facility claims file and Long Term Care Minimum Data Set. Deaths were ascertained by review of obituaries and/or from a proxy informant, with a completion rate of 100%. A total of 688 participants (91.2%) had died after a median follow-up of 108 months, while 43 participants (5.7%) dropped out of the study after a median follow-up of 27 months. Among all participants, data were otherwise available for 99.2% of 85,531 monthly telephone interviews.

Assembly of Analytic Sample

PEP participants were considered for inclusion in the analytic sample if they had a hospitalization with an ACSC as the primary diagnosis on linked Medicare claims data. The complete list of ACSCs was defined using specifications from the Agency for Healthcare Research and Quality,¹⁵ and was assembled using the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) classification prior to October 1, 2015, and ICD Tenth Revision, Clinical Modification (ICD-10-CM) classification after October 1, 2015 (Appendix Table 1). Examples of ACSCs include congestive heart failure, dehydration, urinary tract infection, and angina without procedure. As performed previously,^16,17 two ACSCs (low birthweight; asthma in younger adults 18-39 years) were not included in this analysis because they were not based on full adult populations.

ACSC-related hospitalizations were included through December 2017. Participants could contribute more than one ACSC-related hospitalization over the course of the study based on the following criteria: (1) participant did not have a prior non-ACSC-related hospitalization within an 18-month interval; (2) participant did not have a prior ACSC-related hospitalization or treat-and-release emergency department (ED) visit within an 18-month interval (to ensure independence of observations if the participant was still recovering from the prior event and because some of the characteristics within Table 1 are susceptible to change in the setting of an intervening event and, hence, would not accurately reflect the status of the participant prior to ACSC-related hospitalization); (3) participant was not admitted from a NH; (4) participant did not have an in-hospital intensive care unit (ICU) stay (because persons with critical illness are a distinct population with frequent disability and prolonged recovery, as previously described¹⁸), in-hospital death, or death before first follow-up interview (because our aim was to evaluate disability and recovery after the hospitalization⁷).

Assembly of the primary analytic sample is depicted in the Appendix Figure. Of the 814 patients who were identified with ACSC-related hospitalizations, 107 had a prior non-ACSC-related hospitalization and 275 had a prior ACSC-related hospitalization or a treat-and-release ED visit within an 18-month interval. Of the remaining 432 ACSC-related hospitalizations, 181 were excluded: 114 patients were admitted from a NH, 38 had an in-hospital ICU stay, 3 died in the hospital, 11 died before their first follow-up interview, and 15 had withdrawn from the study. The primary analytic sample included the remaining 251 ACSC-related hospitalizations, contributed by 196 participants. Specifically, nine participants contributed three ACSC-related hospitalizations each, 37 participants contributed two hospitalizations each, and the remaining 150 participants contributed one hospitalization each. During the 6-month follow-up period, 40 participants contributing ACSC-related hospitalizations died after a median (interquartile range [IQR]) of 4 (2-5) months, and 1 person refused continued participation.

Comprehensive Assessments

During the comprehensive in-home assessments, data were obtained on demographic characteristics. Age was measured in years at the time of the ACSC-related hospitalization. In addition, we describe factors from the comprehensive assessment immediately prior to the ACSC-related hospitalization, grouped into two additional domains related to disability¹⁹: health-related and cognitive-psychosocial. The health-related factors included nine self-reported, physician-diagnosed chronic conditions and frailty. The cognitive-psychosocial factors included social support, cognitive impairment, and depressive symptoms.

Assessment of Disability

Complete details about the assessment of disability have been previously described.^13,14,19,20 Briefly, disability was assessed during the monthly telephone interviews, and included four basic activities (bathing, dressing, walking across a room, and transferring from a chair), five instrumental activities (shopping, housework, meal preparation, taking medications, and managing finances), and three mobility activities (walking a quarter mile, climbing a flight of stairs, and lifting or carrying 10 lb). Participants were asked, “At the present time, do you need help from another person to [complete the task]?” Disability was operationalized as the need for personal assistance or an inability to perform the task. Participants were also asked about a fourth mobility activity, “Have you driven a car during the past month?” Those who responded no were classified as being disabled in driving.¹⁹

The number of disabilities overall and for each functional domain (basic, instrumental, and mobility) was summed. Possible disability scores ranged from 0 to 13, with a score of 0 indicating complete independence in all of the items, and a score of 13 indicating complete dependence. Worse postdischarge disability was defined as a total disability score (0-13) at the first telephone interview after an ACSC-related hospitalization that was greater than the total disability score from the telephone interview immediately preceding hospitalization.

Outcome Measures

The primary outcome was the number of disabilities in all 13 basic, instrumental, and mobility activities in each of the 6 months following discharge from an ACSC-related hospitalization. To determine whether our findings were consistent across the three functional domains, we also evaluated the number of disabilities in the four basic, five instrumental, and four mobility activities separately. As secondary outcomes, we evaluated: (1) the cumulative probability of recovery within the 6-month follow-up time frame after an ACSC-related hospitalization, with “recovery” defined as return to the participant’s pre-ACSC-related hospitalization total disability score, and (2) the cumulative probability of incident NH admission within the 6 months after an ACSC-related hospitalization. Aligned with CMS and prior literature,^21,22 we defined a short-term NH stay as ≤100 days and a long-term NH stay as >100 days.

Statistical Analysis

Pre-ACSC-related hospitalization characteristics were summarized by means (SDs) and frequencies with proportions. We determined the mean number of disabilities in each of the 6 months following hospital discharge, with the prehospitalization value included as a reference point. We also determined the mean (SD) number of disabilities for the three subscales of disability (basic activities of daily living [BADLs], instrumental activities of daily living [IADLs], and mobility activities). We calculated the cumulative probability of recovery within 6 months of hospital discharge. Finally, we determined the cumulative probability of incident NH admission during the 6 months after hospital discharge.

To test the robustness of our main results, we conducted a sensitivity analysis assessing disability scores of the 150 participants that contributed only one ACSC-related hospitalization. All analyses were performed using Stata, version 16.0, statistical software (StataCorp).

Table 1 shows the characteristics of the 251 ACSC-related hospitalizations immediately prior to hospitalization. Participants’ mean (SD) age was 85.1 (6.0) years, and the mean total disability score was 5.4. The majority were female, non-Hispanic White, frail, and lived alone. As shown in Appendix Table 2, the three most common reasons for ACSC-related hospitalizations were congestive heart failure (n = 69), bacterial pneumonia (n = 53), and dehydration (n = 44).

The Figure shows the disability scores during the 6-month follow-up period for total, basic, instrumental, and mobility activities, in panels A, B, C, and D, respectively. The exact values are provided in Appendix Table 3. After hospitalization, disability scores for total, basic, instrumental, and mobility activities peaked at month 1 and tended to improve modestly over the next 5 months, but remained greater, on average, than pre-hospitalization scores. Of the 40 participants who died within the 6-month follow-up period, 36 (90%) had worse disability scores in their last month of life than in the month prior to their ACSC-related hospitalization.

Table 2 shows the cumulative probability of functional recovery after ACSC-related hospitalizations. Recovery was incomplete, with only 70% (95% CI, 64%-76%) of hospitalizations achieving a return to the pre-hospitalization total disability score within 6 months of hospitalization.

Table 3 shows the cumulative probability of incident NH admission after an ACSC-related hospitalization. Of the 251 ACSC-related hospitalizations, incident NH admission was experienced by 38% (95% CI, 32%-44%) within 1 month and 50% (95% CI, 43%-56%) within 6 months of discharge. Short-term NH stays accounted for 90 (75.6%) of the 119 incident NH admissions within the 6 months after ACSC-related hospitalizations. Sensitivity analyses yielded comparable disability scores, shown in Appendix Table 4.

In this longitudinal study of community-living older persons, we evaluated functional disability, recovery, and incident NH admission within 6 months of hospitalization for an ACSC. Our study has three major findings. First, disability scores for total, basic, instrumental, and mobility activities at months 1 to 6 of follow-up were greater on average than pre-hospitalization scores. Second, functional recovery was not achieved by 3 of 10 participants after an ACSC-related hospitalization. Third, half of them experienced an incident NH admission within 6 months of discharge from an ACSC-related hospitalization, although about three-quarters of these were short-term stays. Our findings provide evidence that older persons experience clinically meaningful adverse patient-reported outcomes after ACSC-related hospitalizations.

Prior research involving ACSCs has focused largely on rates of hospitalization as a measure of access to primary care and the associated factors predictive of ACSC-related hospitalizations,^23-26 and has not addressed subsequent patient-reported outcomes. The findings in this analysis highlight that older persons experience worsening disability immediately after an ACSC-related hospitalization, which persists for prolonged periods and often results in incomplete recovery. Prior research has assessed pre-hospitalization functional status through retrospective recall approaches,² included only older adults discharged with incident disability,³ and examined functional status after all-cause medical illness hospitalizations.⁵ Our prospective analysis extends the literature by reliably capturing pre-hospital disability scores and uniquely assessing the cohort of older persons hospitalized with ACSCs.

Our work is relevant to the continued evaluation of ACSC-related hospitalizations in national quality measurement and payment initiatives among Medicare beneficiaries. In prior evaluations of ACSC-related quality measures, stakeholders have criticized the measures for limited validity due to a lack of evidence linking each utilization outcome to other patient-centered outcomes.^10,27 Our work addresses this gap by demonstrating that ACSC-related hospitalizations are linked to persistent disability, incomplete functional recovery, and incident NH admissions. Given the large body of evidence demonstrating the priority older persons place on these patient-reported outcomes,^28,29 our work should reassure policymakers seeking to transform quality measurement programs into a more patient-oriented enterprise.

Our findings have several clinical practice, research, and policy implications. First, more-effective clinical strategies to minimize the level of care required for acute exacerbations of ACSC-related illnesses may include: (1) substituting home-based care³⁰ and telehealth interventions³¹ for traditional inpatient hospitalization, (2) making in-ED resources (ie, case management services, geriatric-focused advanced practice providers) more accessible for older persons with ACSC-related illnesses, thereby enhancing care transitions and follow-up to avoid potential current and subsequent hospitalizations, and (3) ensuring adequate ambulatory care access to all older persons, as prior work has shown variation in ACSC hospital admission rates dependent on population factors such as high-poverty neighborhoods,¹⁶ insurance status,^16,32 and race/ethnicity.³³

Clinical strategies have been narrow and not holistic for ACSCs; for example, many institutions have focused on pneumonia vaccinations to reduce hospitalizations, but our work supports the need to further evaluate the impact of preventing ACSC-related hospitalizations and their associated disabling consequences. For patients admitted to the hospital, clinical strategies, such as in-hospital or post-hospital mobility and activity programs, have been shown to be protective against hospital-associated disability.^34,35 Furthermore, hospital discharge planning could include preparing older persons for anticipated functional disabilities, associated recoveries, and NH admission after ACSC-related hospitalizations. Risk factors contributing to post-hospitalization functional disability and recovery have been identified,^19,20,36 but future work is needed to: (1) identify target populations (including those most likely to worsen) so that interventions can be offered earlier in the course of care to those who would benefit most, and (2) identify and learn from those who are resilient and have recovered, to better understand factors contributing to their success.

Our study has several strengths. First, the study is unique due to its longitudinal design, with monthly assessments of functional status. Since functional status was assessed prospectively before the ACSC-related hospitalization, we also have avoided any potential concern for recall bias that may be present if assessed after the hospitalization. Additionally, through the use of Medicare claims and the Minimum Data Set, the ascertainment of hospitalizations and NH admissions was likely complete for the studied population.

However, the study has limitations. First, functional measures were based on self-reports rather than objective measurements. Nevertheless, the self-report function is often used to guide coverage determinations in the Medicare program, as it has been shown to be associated with poor health outcomes.³⁷ Second, we are unable to comment on the rate of functional decline or NH admission when an older person was not hospitalized in relation to an ACSC. Future analyses may benefit from using a control group (eg, older adults without an ACSC hospitalization or older adults with a non-ACSC hospitalization). Third, we used strict exclusion criteria to identify a population of older adults without recent hospitalizations to determine the isolated impact of ACSC hospitalization on disability, incident NH admission, and functional recovery. Considering this potential selection bias, our findings are likely conservative estimates of the patient-centered outcomes evaluated. Fourth, participants were not asked about feeding and toileting. However, the incidence of disability in these ADLs is low among nondisabled, community-living older persons, and it is highly uncommon for disability to develop in these ADLs without concurrent disability in the ADLs within this analysis.^14,38

Finally, because our study participants were members of a single health plan in a small urban area and included nondisabled older persons living in the community, our findings may not be generalizable to geriatric patients in other settings. Nonetheless, the demographics of our cohort reflect those of older persons in New Haven County, Connecticut, which are similar to the demographics of the US population, with the exception of race and ethnicity. In addition, the generalizability of our results are strengthened by the study’s high participation rate and minimal attrition.

Within 6 months of ACSC-related hospitalizations, community-living older persons exhibited greater total disability scores than those immediately preceding hospitalization. In the same time frame, 3 of 10 older persons did not achieve functional recovery, and half experienced incident NH admission. These results provide evidence regarding the continued recognition of ACSC-related hospitalizations in federal quality measurement and payment programs and suggests the need for preventive and comprehensive interventions to meaningfully improve longitudinal outcomes.

We thank Denise Shepard, BSN, MBA, Andrea Benjamin, BSN, Barbara Foster, and Amy Shelton, MPH, for assistance with data collection; Geraldine Hawthorne, BS, for assistance with data entry and management; Peter Charpentier, MPH, for design and development of the study database and participant tracking system; and Joanne McGloin, MDiv, MBA, for leadership and advice as the Project Director. Each of these persons were paid employees of Yale School of Medicine during the conduct of this study.

Acute illnesses requiring hospitalization serve as a sentinel event, with many older adults requiring assistance with activities of daily living (ADLs) upon discharge.^1-3 Older adults who are frail experience even higher rates of hospital-associated disability, and rates of recovery to baseline functional status have varied.^4,5 Loss of independence in ADLs has been associated with nursing home (NH) utilization, caregiver burden, and mortality.⁶

To date, studies have characterized functional trajectories before and after hospitalization in older persons for broad medical conditions, noting persistence of disability and incomplete recovery to baseline functional status.⁷ Prior evaluations have also noted the long-term disabling impact of critical conditions such as acute myocardial infarction, stroke, and sepsis,^8,9 but a knowledge gap exists regarding the subsequent functional disability, recovery, and incident NH admission among older persons who are hospitalized for ambulatory care sensitive conditions (ACSCs). Often considered potentially preventable with optimal ambulatory care,^10,11 ACSCs represent acute, chronic, and vaccine-preventable conditions, including urinary tract infection, congestive heart failure, diabetes mellitus, and pneumonia. Investigating the aforementioned patient-centered measures post hospitalization could provide valuable supporting evidence for the continued recognition of ACSC-related hospitalizations in national quality payment programs set forth by the Centers for Medicare & Medicaid Services (CMS).¹² Demonstrating adverse outcomes after ACSC-related hospitalizations may help support interventions that target potentially preventable ACSC-related hospitalizations, such as home-based care or telehealth, with the goal of improving functional outcomes and reducing NH admission in older persons.

To address these gaps, we evaluated ACSC-related hospitalizations among participants of the Precipitating Events Project (PEP), a 19-year longitudinal study of community-living persons who were initially nondisabled in their basic functional activities. In the 6 months following an ACSC-related hospitalization, our objectives were to describe: (1) the 6-month course of postdischarge functional disability, (2) the cumulative monthly probability of functional recovery, and (3) the cumulative monthly probability of incident NH admission.

Study Population

Participants were drawn from the PEP study, an ongoing, prospective, longitudinal study of 754 community-dwelling persons aged 70 years or older.¹³ Potential participants were members of a large health plan in greater New Haven, Connecticut, and were enrolled from March 1998 through October 1999. As previously described,¹⁴ persons were oversampled if they were physically frail, as denoted by a timed score >10 seconds on the rapid gait test. Exclusion criteria included significant cognitive impairment with no available proxy, life expectancy less than 12 months, plans to leave the area, and inability to speak English. Participants were initially required to be nondisabled in four basic activities of daily living (bathing, dressing, walking across a room, and transferring from a chair). Eligibility was determined during a screening telephone interview and was confirmed during an in-home assessment. Of the eligible members, 75.2% agreed to participate in the project, and persons who declined to participate did not significantly differ in age or sex from those who were enrolled. The Yale Human Investigation Committee approved the study protocol, and all participants provided verbal informed consent.

Data Collection

From 1998 to 2017, comprehensive home-based assessments were completed by trained research nurses at baseline and at 18-month intervals over 234 months (except at 126 months), and telephone interviews were completed monthly through June 2018, to obtain information on disability over time. For participants who had significant cognitive impairment or who were unavailable, we interviewed a proxy informant using a rigorous protocol with demonstrated reliability and validity.¹⁴ All incident NH admissions, including both short- and long-term stays, were identified using the CMS Skilled Nursing Facility claims file and Long Term Care Minimum Data Set. Deaths were ascertained by review of obituaries and/or from a proxy informant, with a completion rate of 100%. A total of 688 participants (91.2%) had died after a median follow-up of 108 months, while 43 participants (5.7%) dropped out of the study after a median follow-up of 27 months. Among all participants, data were otherwise available for 99.2% of 85,531 monthly telephone interviews.

Assembly of Analytic Sample

PEP participants were considered for inclusion in the analytic sample if they had a hospitalization with an ACSC as the primary diagnosis on linked Medicare claims data. The complete list of ACSCs was defined using specifications from the Agency for Healthcare Research and Quality,¹⁵ and was assembled using the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) classification prior to October 1, 2015, and ICD Tenth Revision, Clinical Modification (ICD-10-CM) classification after October 1, 2015 (Appendix Table 1). Examples of ACSCs include congestive heart failure, dehydration, urinary tract infection, and angina without procedure. As performed previously,^16,17 two ACSCs (low birthweight; asthma in younger adults 18-39 years) were not included in this analysis because they were not based on full adult populations.

ACSC-related hospitalizations were included through December 2017. Participants could contribute more than one ACSC-related hospitalization over the course of the study based on the following criteria: (1) participant did not have a prior non-ACSC-related hospitalization within an 18-month interval; (2) participant did not have a prior ACSC-related hospitalization or treat-and-release emergency department (ED) visit within an 18-month interval (to ensure independence of observations if the participant was still recovering from the prior event and because some of the characteristics within Table 1 are susceptible to change in the setting of an intervening event and, hence, would not accurately reflect the status of the participant prior to ACSC-related hospitalization); (3) participant was not admitted from a NH; (4) participant did not have an in-hospital intensive care unit (ICU) stay (because persons with critical illness are a distinct population with frequent disability and prolonged recovery, as previously described¹⁸), in-hospital death, or death before first follow-up interview (because our aim was to evaluate disability and recovery after the hospitalization⁷).

Assembly of the primary analytic sample is depicted in the Appendix Figure. Of the 814 patients who were identified with ACSC-related hospitalizations, 107 had a prior non-ACSC-related hospitalization and 275 had a prior ACSC-related hospitalization or a treat-and-release ED visit within an 18-month interval. Of the remaining 432 ACSC-related hospitalizations, 181 were excluded: 114 patients were admitted from a NH, 38 had an in-hospital ICU stay, 3 died in the hospital, 11 died before their first follow-up interview, and 15 had withdrawn from the study. The primary analytic sample included the remaining 251 ACSC-related hospitalizations, contributed by 196 participants. Specifically, nine participants contributed three ACSC-related hospitalizations each, 37 participants contributed two hospitalizations each, and the remaining 150 participants contributed one hospitalization each. During the 6-month follow-up period, 40 participants contributing ACSC-related hospitalizations died after a median (interquartile range [IQR]) of 4 (2-5) months, and 1 person refused continued participation.

Comprehensive Assessments

During the comprehensive in-home assessments, data were obtained on demographic characteristics. Age was measured in years at the time of the ACSC-related hospitalization. In addition, we describe factors from the comprehensive assessment immediately prior to the ACSC-related hospitalization, grouped into two additional domains related to disability¹⁹: health-related and cognitive-psychosocial. The health-related factors included nine self-reported, physician-diagnosed chronic conditions and frailty. The cognitive-psychosocial factors included social support, cognitive impairment, and depressive symptoms.

Assessment of Disability

Complete details about the assessment of disability have been previously described.^13,14,19,20 Briefly, disability was assessed during the monthly telephone interviews, and included four basic activities (bathing, dressing, walking across a room, and transferring from a chair), five instrumental activities (shopping, housework, meal preparation, taking medications, and managing finances), and three mobility activities (walking a quarter mile, climbing a flight of stairs, and lifting or carrying 10 lb). Participants were asked, “At the present time, do you need help from another person to [complete the task]?” Disability was operationalized as the need for personal assistance or an inability to perform the task. Participants were also asked about a fourth mobility activity, “Have you driven a car during the past month?” Those who responded no were classified as being disabled in driving.¹⁹

The number of disabilities overall and for each functional domain (basic, instrumental, and mobility) was summed. Possible disability scores ranged from 0 to 13, with a score of 0 indicating complete independence in all of the items, and a score of 13 indicating complete dependence. Worse postdischarge disability was defined as a total disability score (0-13) at the first telephone interview after an ACSC-related hospitalization that was greater than the total disability score from the telephone interview immediately preceding hospitalization.

Outcome Measures

The primary outcome was the number of disabilities in all 13 basic, instrumental, and mobility activities in each of the 6 months following discharge from an ACSC-related hospitalization. To determine whether our findings were consistent across the three functional domains, we also evaluated the number of disabilities in the four basic, five instrumental, and four mobility activities separately. As secondary outcomes, we evaluated: (1) the cumulative probability of recovery within the 6-month follow-up time frame after an ACSC-related hospitalization, with “recovery” defined as return to the participant’s pre-ACSC-related hospitalization total disability score, and (2) the cumulative probability of incident NH admission within the 6 months after an ACSC-related hospitalization. Aligned with CMS and prior literature,^21,22 we defined a short-term NH stay as ≤100 days and a long-term NH stay as >100 days.

Statistical Analysis

Pre-ACSC-related hospitalization characteristics were summarized by means (SDs) and frequencies with proportions. We determined the mean number of disabilities in each of the 6 months following hospital discharge, with the prehospitalization value included as a reference point. We also determined the mean (SD) number of disabilities for the three subscales of disability (basic activities of daily living [BADLs], instrumental activities of daily living [IADLs], and mobility activities). We calculated the cumulative probability of recovery within 6 months of hospital discharge. Finally, we determined the cumulative probability of incident NH admission during the 6 months after hospital discharge.

To test the robustness of our main results, we conducted a sensitivity analysis assessing disability scores of the 150 participants that contributed only one ACSC-related hospitalization. All analyses were performed using Stata, version 16.0, statistical software (StataCorp).

Table 1 shows the characteristics of the 251 ACSC-related hospitalizations immediately prior to hospitalization. Participants’ mean (SD) age was 85.1 (6.0) years, and the mean total disability score was 5.4. The majority were female, non-Hispanic White, frail, and lived alone. As shown in Appendix Table 2, the three most common reasons for ACSC-related hospitalizations were congestive heart failure (n = 69), bacterial pneumonia (n = 53), and dehydration (n = 44).

The Figure shows the disability scores during the 6-month follow-up period for total, basic, instrumental, and mobility activities, in panels A, B, C, and D, respectively. The exact values are provided in Appendix Table 3. After hospitalization, disability scores for total, basic, instrumental, and mobility activities peaked at month 1 and tended to improve modestly over the next 5 months, but remained greater, on average, than pre-hospitalization scores. Of the 40 participants who died within the 6-month follow-up period, 36 (90%) had worse disability scores in their last month of life than in the month prior to their ACSC-related hospitalization.

Table 2 shows the cumulative probability of functional recovery after ACSC-related hospitalizations. Recovery was incomplete, with only 70% (95% CI, 64%-76%) of hospitalizations achieving a return to the pre-hospitalization total disability score within 6 months of hospitalization.

Table 3 shows the cumulative probability of incident NH admission after an ACSC-related hospitalization. Of the 251 ACSC-related hospitalizations, incident NH admission was experienced by 38% (95% CI, 32%-44%) within 1 month and 50% (95% CI, 43%-56%) within 6 months of discharge. Short-term NH stays accounted for 90 (75.6%) of the 119 incident NH admissions within the 6 months after ACSC-related hospitalizations. Sensitivity analyses yielded comparable disability scores, shown in Appendix Table 4.

In this longitudinal study of community-living older persons, we evaluated functional disability, recovery, and incident NH admission within 6 months of hospitalization for an ACSC. Our study has three major findings. First, disability scores for total, basic, instrumental, and mobility activities at months 1 to 6 of follow-up were greater on average than pre-hospitalization scores. Second, functional recovery was not achieved by 3 of 10 participants after an ACSC-related hospitalization. Third, half of them experienced an incident NH admission within 6 months of discharge from an ACSC-related hospitalization, although about three-quarters of these were short-term stays. Our findings provide evidence that older persons experience clinically meaningful adverse patient-reported outcomes after ACSC-related hospitalizations.

Prior research involving ACSCs has focused largely on rates of hospitalization as a measure of access to primary care and the associated factors predictive of ACSC-related hospitalizations,^23-26 and has not addressed subsequent patient-reported outcomes. The findings in this analysis highlight that older persons experience worsening disability immediately after an ACSC-related hospitalization, which persists for prolonged periods and often results in incomplete recovery. Prior research has assessed pre-hospitalization functional status through retrospective recall approaches,² included only older adults discharged with incident disability,³ and examined functional status after all-cause medical illness hospitalizations.⁵ Our prospective analysis extends the literature by reliably capturing pre-hospital disability scores and uniquely assessing the cohort of older persons hospitalized with ACSCs.

Our work is relevant to the continued evaluation of ACSC-related hospitalizations in national quality measurement and payment initiatives among Medicare beneficiaries. In prior evaluations of ACSC-related quality measures, stakeholders have criticized the measures for limited validity due to a lack of evidence linking each utilization outcome to other patient-centered outcomes.^10,27 Our work addresses this gap by demonstrating that ACSC-related hospitalizations are linked to persistent disability, incomplete functional recovery, and incident NH admissions. Given the large body of evidence demonstrating the priority older persons place on these patient-reported outcomes,^28,29 our work should reassure policymakers seeking to transform quality measurement programs into a more patient-oriented enterprise.

Our findings have several clinical practice, research, and policy implications. First, more-effective clinical strategies to minimize the level of care required for acute exacerbations of ACSC-related illnesses may include: (1) substituting home-based care³⁰ and telehealth interventions³¹ for traditional inpatient hospitalization, (2) making in-ED resources (ie, case management services, geriatric-focused advanced practice providers) more accessible for older persons with ACSC-related illnesses, thereby enhancing care transitions and follow-up to avoid potential current and subsequent hospitalizations, and (3) ensuring adequate ambulatory care access to all older persons, as prior work has shown variation in ACSC hospital admission rates dependent on population factors such as high-poverty neighborhoods,¹⁶ insurance status,^16,32 and race/ethnicity.³³

Clinical strategies have been narrow and not holistic for ACSCs; for example, many institutions have focused on pneumonia vaccinations to reduce hospitalizations, but our work supports the need to further evaluate the impact of preventing ACSC-related hospitalizations and their associated disabling consequences. For patients admitted to the hospital, clinical strategies, such as in-hospital or post-hospital mobility and activity programs, have been shown to be protective against hospital-associated disability.^34,35 Furthermore, hospital discharge planning could include preparing older persons for anticipated functional disabilities, associated recoveries, and NH admission after ACSC-related hospitalizations. Risk factors contributing to post-hospitalization functional disability and recovery have been identified,^19,20,36 but future work is needed to: (1) identify target populations (including those most likely to worsen) so that interventions can be offered earlier in the course of care to those who would benefit most, and (2) identify and learn from those who are resilient and have recovered, to better understand factors contributing to their success.

Our study has several strengths. First, the study is unique due to its longitudinal design, with monthly assessments of functional status. Since functional status was assessed prospectively before the ACSC-related hospitalization, we also have avoided any potential concern for recall bias that may be present if assessed after the hospitalization. Additionally, through the use of Medicare claims and the Minimum Data Set, the ascertainment of hospitalizations and NH admissions was likely complete for the studied population.

However, the study has limitations. First, functional measures were based on self-reports rather than objective measurements. Nevertheless, the self-report function is often used to guide coverage determinations in the Medicare program, as it has been shown to be associated with poor health outcomes.³⁷ Second, we are unable to comment on the rate of functional decline or NH admission when an older person was not hospitalized in relation to an ACSC. Future analyses may benefit from using a control group (eg, older adults without an ACSC hospitalization or older adults with a non-ACSC hospitalization). Third, we used strict exclusion criteria to identify a population of older adults without recent hospitalizations to determine the isolated impact of ACSC hospitalization on disability, incident NH admission, and functional recovery. Considering this potential selection bias, our findings are likely conservative estimates of the patient-centered outcomes evaluated. Fourth, participants were not asked about feeding and toileting. However, the incidence of disability in these ADLs is low among nondisabled, community-living older persons, and it is highly uncommon for disability to develop in these ADLs without concurrent disability in the ADLs within this analysis.^14,38

Finally, because our study participants were members of a single health plan in a small urban area and included nondisabled older persons living in the community, our findings may not be generalizable to geriatric patients in other settings. Nonetheless, the demographics of our cohort reflect those of older persons in New Haven County, Connecticut, which are similar to the demographics of the US population, with the exception of race and ethnicity. In addition, the generalizability of our results are strengthened by the study’s high participation rate and minimal attrition.

Within 6 months of ACSC-related hospitalizations, community-living older persons exhibited greater total disability scores than those immediately preceding hospitalization. In the same time frame, 3 of 10 older persons did not achieve functional recovery, and half experienced incident NH admission. These results provide evidence regarding the continued recognition of ACSC-related hospitalizations in federal quality measurement and payment programs and suggests the need for preventive and comprehensive interventions to meaningfully improve longitudinal outcomes.

We thank Denise Shepard, BSN, MBA, Andrea Benjamin, BSN, Barbara Foster, and Amy Shelton, MPH, for assistance with data collection; Geraldine Hawthorne, BS, for assistance with data entry and management; Peter Charpentier, MPH, for design and development of the study database and participant tracking system; and Joanne McGloin, MDiv, MBA, for leadership and advice as the Project Director. Each of these persons were paid employees of Yale School of Medicine during the conduct of this study.

One of the most striking features of the early COVID-19 pandemic was the sudden and sharp reductions in emergency department (ED) visits and hospitalizations throughout the United States.^1-4 Several studies have documented lower rates of hospitalization for many emergent, time-sensitive conditions, such as acute myocardial infarction, stroke, and hyperglycemic crises, starting shortly after community transmission of COVID-19 was recognized and social distancing guidelines were implemented.^5-8 In most cases, hospital volumes rebounded after an initial drop, stabilizing at somewhat lower levels than those expected from historic trends.⁹

The observed shifts in hospital use largely have been attributed to patients’ forgoing or delaying necessary care,¹⁰ which underscores the indirect effects of the pandemic on patients without COVID-19.¹¹ To date, the extent to which outcomes for patients without COVID-19 have been adversely affected is less well understood. Evidence suggests patients with acute and chronic illnesses have experienced increased morbidity and mortality since the onset of the pandemic. For example, in northern California, abrupt declines in ED visits for cardiac symptoms were coupled with higher rates of out-of-hospital cardiac arrest.¹² Moreover, states with higher rates of COVID-19 also reported increased deaths attributed to heart disease, diabetes, and other conditions.¹³

To better understand these potential indirect effects, this study used data from a large, multistate health care system to examine changes in hospital volume and its relationship to in-hospital mortality for patients without COVID-19 during the first 10 months of the pandemic.

Setting and Participants

We examined unplanned hospitalizations from January 2019 to December 2020 at 51 community hospitals across 6 states (Alaska, Washington, Montana, Oregon, California, and Texas) in the Providence St. Joseph Health system. Hospitals within the Providence system share a common standard dataset for each encounter with a centralized cloud data warehouse from which we extracted clinical and demographic data. No hospitals entered or left the system during the study period. Hospitalizations were considered unplanned if they had an “urgent” or “emergency” service type in the record; most originated in the ED. Hospitalizations for children younger than 18 years and those with evidence of COVID-19 (International Classification of Disease, Tenth Revision, Clinical Modification U07.1, a positive COVID-19 polymerase chain reaction test during the encounter, or an infection control-assigned label of COVID-19) were excluded. The Providence St. Joseph Health Institutional Review Board approved this study.

Measures

Trends in daily hospitalizations and their relationship to adjusted in-hospital mortality (percentage of patients who died during their hospital admission) were examined over time. In preliminary models using segmented regression, we identified three distinct pandemic periods with different trends in daily hospitalizations: (1) a 10-week period corresponding to the spring COVID-19 surge (March 4 to May 13, 2020; Period 1), (2) an intervening period extending over the summer and early fall (May 14 to October 19, 2020; Period 2), and (3) a second 10-week period corresponding to the fall COVID-19 surge (October 20 to December 31, 2020; Period 3). In-hospital mortality for these periods was compared with a baseline period (pre-COVID-19) from January 1, 2019 to March 3, 2020. To further assess differences in mortality by clinical condition, hospitalizations were first grouped by primary diagnosis using Clinical Classifications Software Refined (CCSR) categories from the Agency for Healthcare Research and Quality¹⁴ and ranked by the number of observed deaths and the percentage of patients who died while hospitalized in 2020. We selected common conditions that had >35 total deaths and an in-hospital mortality rate ≥1% for condition-specific analyses, of which 30 met these criteria.

Analysis

Multivariate logistic regression was used to evaluate changes in mortality for each of the pandemic periods compared with baseline for the overall cohort and selected diagnosis groups. Our main model adjusted for age, sex, race/ethnicity (White, Black, Latinx, Asian or Pacific Islander, and other), primary payor (commercial, Medicaid, Medicare, other, and self-pay), the presence or absence of 31 chronic comorbidities in the medical record, primary admitting diagnosis grouped by CCSR category (456 total diagnostic groups), and hospital fixed-effects to account for clustering. Results are expressed as the average marginal effects of each pandemic period on in-hospital mortality (eg, adjusted percentage point change in mortality over baseline). The number of excess deaths in each period was calculated by multiplying the estimated percentage point change in mortality for each period by the total number of hospitalizations. These excess deaths were subtracted from the number of observed deaths to derive the number of deaths that would be expected if pre-pandemic mortality rates persisted.

To further assess whether changes in adjusted mortality could be attributed to a smaller, sicker population of patients presenting to the hospital during the pandemic (meaning that less acutely ill patients stayed home), we conducted two sensitivity analyses. First, we tested whether substituting indicators for Medicare Severity Diagnosis Groups (MS-DRG) in lieu of CCSR categories had any impact on our results. MS-DRGs are designed to account for a patient’s illness severity and expected costs, whereas CCSR categories do not.¹⁵ MS-DRGs also better distinguish between surgical versus medical conditions. We re-ran our main model using indicators for CCSR to control for diagnostic mix, but further adjusted for severity using the DRG weight for the primary diagnosis and Modified Early Warning Score (MEWS) as continuous covariates. MEWS is a physiologic scoring system that incorporates abnormal vital signs and data related to mental status during the first 24 hours of a patient’s hospitalization into a risk-based score that has been shown to predict hospital mortality and need for intensive care.^16,17 These sensitivity analyses were performed on a subset of inpatient admissions because DRG data are not available for hospitalizations billed as an observation stay, and only approximately 70% of hospitals in the sample contributed vital sign data to the Providence data warehouse. All statistical analyses were conducted with R, version 3.6.3 (R Foundation for Statistical Computing) and SAS Enterprise Guide 7.1 (SAS Institute Inc).

The characteristics of our sample are described in Table 1. A total of 61,300, 159,430, and 65,923 hospitalizations occurred in each of the three pandemic periods, respectively, compared with 503,190 hospitalizations in the pre-pandemic period. The mean (SD) age of patients in the study was 63.2 (19.4) years; most were women (52.4%), White (70.6%), and had Medicare as their primary payor (53.7%). Less than half (42.7%) of hospitalizations occurred in California, and just under one-quarter were observation stays (23.2%). Patient characteristics were similar in the pre-COVID-19 and COVID-19 pandemic periods.

Figure 1 shows trends in hospital volume and mortality. Overall daily hospitalizations declined abruptly from a mean of 1176 per day in the pre-pandemic period to 617 per day (47.5% relative decrease) during the first 3 weeks of Period 1. Mean daily hospitalizations began to rise over the next 2 months (Period 1), reaching steady state at <1000 hospitalizations per day (15% relative decrease from baseline) during Period 2. During Period 3, we observed a decline in mean daily hospitalizations, with a low point of 882 per day on December 31, 2020 (25% relative decrease from baseline), corresponding to the end of our study period. Although hospital volumes declined during both COVID-19 surge periods, the percentage of patients who died during their hospitalization increased. There was an initial spike in in-hospital mortality that peaked approximately 1 month into the pandemic (middle of Period 1), a return to levels at or slightly below that before the pandemic by the beginning of Period 2, and then a rise throughout the autumn COVID-19 surge in Period 3, not yet peaking by the end of the study.

Adjusted in-hospital mortality for the three COVID-19 periods compared with the pre-pandemic period is presented in Table 2. The percentage of patients who died during their hospitalization rose from 2.9% in the pre-pandemic period to 3.4% during Period 1 (absolute difference, 0.6 percentage points; 95% CI, 0.5-0.7), corresponding to a 19.3% relative increase during the spring COVID-19 surge. Among the subset of patients hospitalized with 1 of the 30 conditions selected for individual analysis, mortality increased from 5.0% to 5.9% during the same time period (absolute difference, 0.9 percentage points; 95% CI, 0.8-1.1), corresponding to an 18.9% relative increase. In Period 2, in-hospital mortality was similar to that noted pre-pandemic for the overall cohort and the 30 selected conditions. During Period 3, in-hospital mortality increased by a magnitude similar to that observed in Period 1 for all hospitalizations combined (absolute difference, 0.5 percentage points; 95% CI, 0.0-0.6; corresponding to a 16.5% relative increase) as well as the subgroup with 1 of the 30 selected conditions (0.9 percentage points; 95% CI, 0.8-1.0; corresponding to an 18% relative increase). Further adjustment for severity by swapping CCSR categories with MS-DRG indicators or inclusion of DRG weight and MEWS score as covariates in our sensitivity analyses did not change our results.

Table 3 and the Appendix Figure describe changes in volume and adjusted in-hospital mortality for the 30 conditions selected for analysis. There was a decrease in the mean daily admissions for all conditions studied. Among the 30 conditions, 26 showed increased mortality during Period 1, although the increase was only statistically significant for 16 of these conditions. Among the 10 most commonly admitted conditions (by number of daily hospital admissions during the baseline period), there was a statistically significant relative increase in mortality for patients with sepsis (20.1%), heart failure (17.6%), ischemic stroke (12.5%), device/graft/surgical complications (14.0%), cardiac dysrhythmias (14.4%), pneumonia (24.5%), respiratory failure (16.1%), and gastrointestinal hemorrhage (23.3%). In general, mortality returned to baseline or improved during Period 2. Thereafter, all 30 conditions showed increased mortality in Period 3. This increase was significant for only 16 conditions, which were not the same ones noted during Period 1. Of note, although there was higher mortality for some cardiovascular conditions (heart failure cardiac dysrhythmias), mortality for myocardial infarction remained unchanged from baseline across all 3 periods. In contrast, several solid cancer–related conditions showed progressively worsening mortality throughout the study, with 7.7% higher mortality in Period 1, 10.3% higher mortality in Period 2, and 16.5% higher mortality in Period 3, respectively, compared with baseline. Although a similar pattern was observed for acute renal failure and some neurologic conditions (traumatic brain injury, seizure, other nervous system disorders), mortality for drug poisonings and gastrointestinal bleeds improved over time.

In this study of unplanned hospitalizations from 51 community hospitals across 6 states in the US West, we found a significant increase in mortality—at a rate of approximately 5 to 6 excess deaths per 1000 hospitalizations—among patients admitted during the pandemic with a variety of non-COVID-19 illnesses and injuries. Higher in-hospital mortality was observed in the spring (March to May) and fall (October to December) of 2020 when COVID-19 case counts surged and shelter-in-place mandates were implemented. With the initial surge, higher mortality rates were largely transient, and, for most conditions evaluated, returned to baseline approximately 3 months after the pandemic onset. For the fall surge, mortality rates had not peaked by the end of the study period. Changes in mortality were closely and inversely correlated with hospital volume for non-COVID-19 illnesses during both surge periods.

Higher morbidity and mortality for patients without COVID-19 appears to be an unfortunate spillover effect that has been reported in several studies. Recent work examining national surveillance data suggest that up to one-third of excess deaths (deaths higher than those expected for season) early in the pandemic have occurred among patients without known COVID-19.^13,18-20 Specifically, these studies estimate that mortality rates in the United States increased by 15% to 19% in the spring of 2020; of the identified excess deaths, only 38% to 77% could be attributed to COVID-19, with the remainder attributed to cardiovascular disease, diabetes, and Alzheimer’s disease, among others. In addition, reports from several European countries and China examining population death data have found similar trends,^21-25 as well as a recent study examining excess deaths in nursing homes.²⁶ Our results are largely consistent with these earlier studies in that we describe higher mortality in a sample of patients hospitalized with a variety of common conditions that otherwise are routinely treated in US hospitals. Reporting these indirect casualties of COVID-19 is important to fully understand the pandemic’s toll on patients and healthcare systems.

Our work builds on the current body of literature, highlighting the consistent relationship between rising COVID-19 case counts, hospital volume, and excess mortality over more than one surge period. Although several studies have looked at trends in hospital admissions or population mortality rates, few have examined the two outcomes together. The close correlation between daily hospital admissions and in-hospital mortality in this study suggests that the pandemic changed how patients use healthcare resources in ways that were important for their health and outcomes. The higher mortality rate that we and others have observed likely is related to patients’ delaying care because of fear of contracting COVID-19. In one survey, more than 4 in 10 adults in the United States reported that they avoided medical care during the early pandemic.¹⁰ Importantly, even a few days delay for many conditions, such as heart failure or sepsis, can result in precipitous declines in clinical status and outcomes.

It also is possible that we found increased rates of in-hospital mortality simply because patients with more moderate illness chose to stay home, resulting in a patient population enriched with those more likely to die. We found mixed evidence in our data that the observed increases in mortality could be attributable to a smaller, sicker population. Some characteristics that might be protective, such as a slightly younger mean age and lower mean DRG weight, were more common among those hospitalized during the pandemic. However, other characteristics, such as a slightly higher MEWS score and a greater percentage of total hospitalizations in the higher mortality subgroup, also were noted during the pandemic (Table 1). We do note, however, that the differences in these severity-related characteristics were small across the study periods. Further adjusting for these characteristics in our sensitivity analyses did not appreciably change our main findings, suggesting that the mortality increase could not be explained by changes in case-mix alone.

Other factors not dependent on patient behavior, such as barriers to accessing timely ambulatory care and impacts in the quality of care delivered, might have contributed. Shelter-in-place orders, reduced in-person access to clinicians in the ambulatory setting, slow implementation of telehealth services (with uncertainty about their equivalence to in-person exams), as well as delays in diagnostic tests and outpatient procedures could have played a role, especially during early months of the pandemic.²⁷ Significant changes to ambulatory health care delivery might have left many patients with chronic illnesses or complex medical needs with limited care options. Importantly, these care interruptions might have had greater implications for some patients, such as those with cancer who rely on intensive, largely outpatient-based treatment.^28,29 This, in part, could explain why we found persistently increased mortality among patients hospitalized with cancer after the spring surge. Later into the pandemic, however, most health systems had developed processes that allowed clinicians to resume timely care of ambulatory patients. Because of this, increases in mortality observed during the fall surge likely stem from other factors, such as patient behavior.

It is possible that care delays or changes in the quality of care delivered during the index hospitalization or pre-hospital setting might have contributed to the observed increase in mortality. This is particularly true for acute, time-sensitive conditions such as sepsis and stroke. Extra time spent donning personal protective equipment and/or new protocols instituted during the pandemic likely impacted the speed of emergency medical services transport, timeliness of ED evaluation, and delivery of definitive therapy. Although most hospitals in this study were not overwhelmed by the pandemic, the complexities associated with caring for known and suspected COVID-19 patients alongside those without the disease might have altered ideal care practices and strained healthcare teams.³⁰ In addition, nearly all hospitalized patients during this period were deprived of in-person advocacy by family members, who were not permitted to visit.

Important limitations with this study exist. First, the data come only from hospitals in the western United States. Second, some data elements such as triage scores or vital signs were not available for the entire population, potentially limiting some risk-adjustment. Third, we were unable to determine the root cause of excess mortality based on our study design and the coded variables available. It is unknown to what extent undiagnosed COVID-19 played a role. Early in the pandemic, many community hospitals did not have access to timely COVID-19 testing, and some cases might have not been diagnosed.³¹ However, we do not expect this to be a significant concern in the later months of the pandemic, as testing became more widespread and hospitals implemented surveillance screening for COVID-19 for inpatients.

Our study indicates that the COVID-19 pandemic was associated with increased mortality among patients hospitalized for a range of clinical conditions. Although higher observed mortality rates were limited to periods of high COVID-19 activity, future studies will need to tease out the extent to which these findings relate to patient factors (ie, delayed presentation and more severe disease) or systemic factors (reduction in access or changes in quality of care). This is of key importance, and appropriate solutions will need to be developed to mitigate adverse impacts with this and future pandemics.