Specialty Sections From CHEST® Physician

Obstructive sleep apnea (OSA) is characterized by repetitive upper airway collapse resulting in intermittent hypoxemia and hypercapnia, large intrathoracic pressure swings, and cortical arousals. The rate of apneas and hypopneas observed during sleep, the apnea-hypopnea index (AHI), has been used for decades to diagnose OSA and to classify its severity. Despite the wide acceptance of this metric by the sleep medicine community, clinical research has found poor correlations between the AHI- and OSA-related complications or symptoms. We have come to learn that the AHI is an oversimplification of a complex and diverse disease process. (Punjabi. Chest. 2016;149[1]:16-9).

The most important features of a disease metric are reliability, and the ability to predict clinically relevant outcomes. The reliability of the AHI has been in question due to substantial night-to-night variability that can lead to missed diagnosis and disease severity misclassification (Dzierzewski et al. J Clin Sleep Med. 2020;16[4]:539-44). Furthermore, the AHI fails to reflect some important physiologic derangements resulting from respiratory events. Apart from imperfectly set thresholds for scoring, it disregards the depth and the duration of ventilatory disturbances. For example, a hypopnea lasting 30 seconds and resulting in a decrease of 10% in oxyhemoglobin saturation is considered equivalent to a hypopnea lasting 10 seconds and resulting in a decrease of 4% in oxyhemoglobin saturation. The AHI also assumes that apneas and hypopneas are equal in their biological effects regardless of when they occur during sleep (NREM vs REM), despite reports suggesting that the sequalae of OSA are sleep-stage dependent (Varga, Mokhlesi. Sleep Breath. 2019;23[2]:413-23). This is further complicated by the varying hypopnea definitions and the difficulties in differentiating obstructive vs central hypopneas. It is doubtful that these events, which differ in mechanism, would result in similar outcomes.
 

Over the past decade, our understanding of the different pathophysiological mechanisms leading to OSA has grown substantially, suggesting the need for a phenotype-specific treatment approach (Zinchuk, Yaggi. Chest. 2020;157[2]:403-20). The reliance on a single metric that does not capture this heterogeneity may prove detrimental to our therapeutic efforts. One extremely important dimension that is missed by the AHI is the patient. Individual response to airway obstruction varies with age, genetics, gender, and comorbidities, among other things. This may explain the difference in symptoms and outcomes experienced by patients with the same AHI. During the era of precision medicine, the concept of defining a clinical condition by a single test result, without regard to patient characteristics, is antiquated.

Several studies have attempted to propose complementary metrics that may better characterize OSA and predict outcomes. The hypoxic burden has gained a lot of attention as it is generally felt that hypoxemia is a major factor contributing to the pathogenesis of OSA-related comorbidities. Azarbarzin, et al. reported a hypoxic burden metric by measuring the area under the oxygen desaturation curve during a respiratory event (Azarbarzin et al. Eur Heart J. 2019;40[14]:1149-57). It factors the length and depth of the desaturations into a single value that expresses the average desaturation burden per hour of sleep time. The hypoxic burden was independently predictive of cardiovascular mortality in two large cohorts. Interestingly, the AHI did not have such an association. Similarly, another novel proposed parameter, the oxygen desaturation rate (ODR), outperformed the AHI in predicting cardiovascular outcomes in severe OSA patients (Wang et al. J Clin Sleep Med. 2020;16[7]:1055-62). The ODR measures the speed of an oxygen desaturation during an apnea event. Subjects with a faster ODR were found to have higher blood pressure values and variability. The authors hypothesized that slower desaturations generate hypoxemia-conditioning that may protect from exaggerated hemodynamic changes. These findings of novel hypoxemia metrics, albeit having their own limitations, recapitulate the need to move beyond the AHI to characterize OSA.

The apnea-hypopnea event duration is another overlooked feature that may impact OSA outcomes. Butler, et al. demonstrated that shorter event duration predicted a higher all-cause mortality over and beyond that predicted by AHI (Butler et al. Am J Respir Crit Care Med. 2019;199[7]:903-12). These results contrast views that early arousals in response to respiratory events may improve outcomes as they reflect a protective mechanism to prevent further hypoxemia and sympatho-excitation. For example, Ma, et al. found that higher percentage of total sleep time spent in apnea/hypopnea (AHT%) predicted worse daytime sleepiness to a higher degree than standard AHI (Ma et al. Sci Rep. 2021;11[1]:4702). However, shorter event duration may represent lower arousal thresholds (increased excitability), and ventilatory control instability (higher loop gain), predisposing patients to augmented sympathetic activity. Along similar lines, the intensity of respiratory-related arousals (as measured by EEG wavelet transformation) was found to be independent of preceding respiratory stimulus, with higher arousal intensity levels correlating with higher respiratory and heart rate responses (Amatoury et al. Sleep. 2016;39[12]:2091-100). The contribution of arousals to OSA morbidity is of particular importance for women in whom long-term outcomes of elevated AHI are poorly understood. Bearing in mind the differences in the metrics used, these results underscore the role of event duration and arousability in the pathogenesis of OSA-related morbidity.

The AHI is certainly an important piece of data that is informative and somewhat predictive. However, when used as a sole disease-defining metric, it has yielded disappointing results, especially after OSA treatment trials failed to show cardiovascular benefits despite therapies achieving a low residual AHI. As we aim to achieve a more personalized approach for diagnosing and treating OSA, we need to explore beyond the concept of a single metric to define a heterogenous and complex disorder. Instead of relying on the frequency of respiratory events, it is time to use complementary polysomnographic data that better reflect the origin and systemic effects of these disturbances. Machine-learning methods may offer sophisticated approaches to identifying polysomnographic patterns for future research. Clinical characteristics will also likely need to be considered in OSA severity scales. The identification of symptom subtypes or blood biomarkers may help identify patient groups who may be impacted differently by OSA, and consequently have a different treatment response (Malhotra et al. Sleep. 2021;44[7]:zsab030).

Almost half a century has lapsed since the original descriptions of OSA. Since then, our understanding of the disorder has improved greatly, with much still to be discovered, but our method of disease capture is unwavering. Future research requires a focus on novel measures aimed at identifying OSA endophenotypes, which will transform our understanding of disease traits and propel us into personalized therapies.
 

Dr. Mansour is Assistant Professor of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University School of Medicine, Durham, North Carolina. Dr. Won is Associate Professor of Medicine, Section of Pulmonary, Critical Care, and Sleep Medicine, Yale University School of Medicine; and VA Connecticut Healthcare System, West Haven, Connecticut.

Obstructive sleep apnea (OSA) is characterized by repetitive upper airway collapse resulting in intermittent hypoxemia and hypercapnia, large intrathoracic pressure swings, and cortical arousals. The rate of apneas and hypopneas observed during sleep, the apnea-hypopnea index (AHI), has been used for decades to diagnose OSA and to classify its severity. Despite the wide acceptance of this metric by the sleep medicine community, clinical research has found poor correlations between the AHI- and OSA-related complications or symptoms. We have come to learn that the AHI is an oversimplification of a complex and diverse disease process. (Punjabi. Chest. 2016;149[1]:16-9).

The most important features of a disease metric are reliability, and the ability to predict clinically relevant outcomes. The reliability of the AHI has been in question due to substantial night-to-night variability that can lead to missed diagnosis and disease severity misclassification (Dzierzewski et al. J Clin Sleep Med. 2020;16[4]:539-44). Furthermore, the AHI fails to reflect some important physiologic derangements resulting from respiratory events. Apart from imperfectly set thresholds for scoring, it disregards the depth and the duration of ventilatory disturbances. For example, a hypopnea lasting 30 seconds and resulting in a decrease of 10% in oxyhemoglobin saturation is considered equivalent to a hypopnea lasting 10 seconds and resulting in a decrease of 4% in oxyhemoglobin saturation. The AHI also assumes that apneas and hypopneas are equal in their biological effects regardless of when they occur during sleep (NREM vs REM), despite reports suggesting that the sequalae of OSA are sleep-stage dependent (Varga, Mokhlesi. Sleep Breath. 2019;23[2]:413-23). This is further complicated by the varying hypopnea definitions and the difficulties in differentiating obstructive vs central hypopneas. It is doubtful that these events, which differ in mechanism, would result in similar outcomes.
 

Over the past decade, our understanding of the different pathophysiological mechanisms leading to OSA has grown substantially, suggesting the need for a phenotype-specific treatment approach (Zinchuk, Yaggi. Chest. 2020;157[2]:403-20). The reliance on a single metric that does not capture this heterogeneity may prove detrimental to our therapeutic efforts. One extremely important dimension that is missed by the AHI is the patient. Individual response to airway obstruction varies with age, genetics, gender, and comorbidities, among other things. This may explain the difference in symptoms and outcomes experienced by patients with the same AHI. During the era of precision medicine, the concept of defining a clinical condition by a single test result, without regard to patient characteristics, is antiquated.

Several studies have attempted to propose complementary metrics that may better characterize OSA and predict outcomes. The hypoxic burden has gained a lot of attention as it is generally felt that hypoxemia is a major factor contributing to the pathogenesis of OSA-related comorbidities. Azarbarzin, et al. reported a hypoxic burden metric by measuring the area under the oxygen desaturation curve during a respiratory event (Azarbarzin et al. Eur Heart J. 2019;40[14]:1149-57). It factors the length and depth of the desaturations into a single value that expresses the average desaturation burden per hour of sleep time. The hypoxic burden was independently predictive of cardiovascular mortality in two large cohorts. Interestingly, the AHI did not have such an association. Similarly, another novel proposed parameter, the oxygen desaturation rate (ODR), outperformed the AHI in predicting cardiovascular outcomes in severe OSA patients (Wang et al. J Clin Sleep Med. 2020;16[7]:1055-62). The ODR measures the speed of an oxygen desaturation during an apnea event. Subjects with a faster ODR were found to have higher blood pressure values and variability. The authors hypothesized that slower desaturations generate hypoxemia-conditioning that may protect from exaggerated hemodynamic changes. These findings of novel hypoxemia metrics, albeit having their own limitations, recapitulate the need to move beyond the AHI to characterize OSA.

The apnea-hypopnea event duration is another overlooked feature that may impact OSA outcomes. Butler, et al. demonstrated that shorter event duration predicted a higher all-cause mortality over and beyond that predicted by AHI (Butler et al. Am J Respir Crit Care Med. 2019;199[7]:903-12). These results contrast views that early arousals in response to respiratory events may improve outcomes as they reflect a protective mechanism to prevent further hypoxemia and sympatho-excitation. For example, Ma, et al. found that higher percentage of total sleep time spent in apnea/hypopnea (AHT%) predicted worse daytime sleepiness to a higher degree than standard AHI (Ma et al. Sci Rep. 2021;11[1]:4702). However, shorter event duration may represent lower arousal thresholds (increased excitability), and ventilatory control instability (higher loop gain), predisposing patients to augmented sympathetic activity. Along similar lines, the intensity of respiratory-related arousals (as measured by EEG wavelet transformation) was found to be independent of preceding respiratory stimulus, with higher arousal intensity levels correlating with higher respiratory and heart rate responses (Amatoury et al. Sleep. 2016;39[12]:2091-100). The contribution of arousals to OSA morbidity is of particular importance for women in whom long-term outcomes of elevated AHI are poorly understood. Bearing in mind the differences in the metrics used, these results underscore the role of event duration and arousability in the pathogenesis of OSA-related morbidity.

The AHI is certainly an important piece of data that is informative and somewhat predictive. However, when used as a sole disease-defining metric, it has yielded disappointing results, especially after OSA treatment trials failed to show cardiovascular benefits despite therapies achieving a low residual AHI. As we aim to achieve a more personalized approach for diagnosing and treating OSA, we need to explore beyond the concept of a single metric to define a heterogenous and complex disorder. Instead of relying on the frequency of respiratory events, it is time to use complementary polysomnographic data that better reflect the origin and systemic effects of these disturbances. Machine-learning methods may offer sophisticated approaches to identifying polysomnographic patterns for future research. Clinical characteristics will also likely need to be considered in OSA severity scales. The identification of symptom subtypes or blood biomarkers may help identify patient groups who may be impacted differently by OSA, and consequently have a different treatment response (Malhotra et al. Sleep. 2021;44[7]:zsab030).

Almost half a century has lapsed since the original descriptions of OSA. Since then, our understanding of the disorder has improved greatly, with much still to be discovered, but our method of disease capture is unwavering. Future research requires a focus on novel measures aimed at identifying OSA endophenotypes, which will transform our understanding of disease traits and propel us into personalized therapies.
 

Dr. Mansour is Assistant Professor of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University School of Medicine, Durham, North Carolina. Dr. Won is Associate Professor of Medicine, Section of Pulmonary, Critical Care, and Sleep Medicine, Yale University School of Medicine; and VA Connecticut Healthcare System, West Haven, Connecticut.

Obstructive sleep apnea (OSA) is characterized by repetitive upper airway collapse resulting in intermittent hypoxemia and hypercapnia, large intrathoracic pressure swings, and cortical arousals. The rate of apneas and hypopneas observed during sleep, the apnea-hypopnea index (AHI), has been used for decades to diagnose OSA and to classify its severity. Despite the wide acceptance of this metric by the sleep medicine community, clinical research has found poor correlations between the AHI- and OSA-related complications or symptoms. We have come to learn that the AHI is an oversimplification of a complex and diverse disease process. (Punjabi. Chest. 2016;149[1]:16-9).

The most important features of a disease metric are reliability, and the ability to predict clinically relevant outcomes. The reliability of the AHI has been in question due to substantial night-to-night variability that can lead to missed diagnosis and disease severity misclassification (Dzierzewski et al. J Clin Sleep Med. 2020;16[4]:539-44). Furthermore, the AHI fails to reflect some important physiologic derangements resulting from respiratory events. Apart from imperfectly set thresholds for scoring, it disregards the depth and the duration of ventilatory disturbances. For example, a hypopnea lasting 30 seconds and resulting in a decrease of 10% in oxyhemoglobin saturation is considered equivalent to a hypopnea lasting 10 seconds and resulting in a decrease of 4% in oxyhemoglobin saturation. The AHI also assumes that apneas and hypopneas are equal in their biological effects regardless of when they occur during sleep (NREM vs REM), despite reports suggesting that the sequalae of OSA are sleep-stage dependent (Varga, Mokhlesi. Sleep Breath. 2019;23[2]:413-23). This is further complicated by the varying hypopnea definitions and the difficulties in differentiating obstructive vs central hypopneas. It is doubtful that these events, which differ in mechanism, would result in similar outcomes.
 

Over the past decade, our understanding of the different pathophysiological mechanisms leading to OSA has grown substantially, suggesting the need for a phenotype-specific treatment approach (Zinchuk, Yaggi. Chest. 2020;157[2]:403-20). The reliance on a single metric that does not capture this heterogeneity may prove detrimental to our therapeutic efforts. One extremely important dimension that is missed by the AHI is the patient. Individual response to airway obstruction varies with age, genetics, gender, and comorbidities, among other things. This may explain the difference in symptoms and outcomes experienced by patients with the same AHI. During the era of precision medicine, the concept of defining a clinical condition by a single test result, without regard to patient characteristics, is antiquated.

Several studies have attempted to propose complementary metrics that may better characterize OSA and predict outcomes. The hypoxic burden has gained a lot of attention as it is generally felt that hypoxemia is a major factor contributing to the pathogenesis of OSA-related comorbidities. Azarbarzin, et al. reported a hypoxic burden metric by measuring the area under the oxygen desaturation curve during a respiratory event (Azarbarzin et al. Eur Heart J. 2019;40[14]:1149-57). It factors the length and depth of the desaturations into a single value that expresses the average desaturation burden per hour of sleep time. The hypoxic burden was independently predictive of cardiovascular mortality in two large cohorts. Interestingly, the AHI did not have such an association. Similarly, another novel proposed parameter, the oxygen desaturation rate (ODR), outperformed the AHI in predicting cardiovascular outcomes in severe OSA patients (Wang et al. J Clin Sleep Med. 2020;16[7]:1055-62). The ODR measures the speed of an oxygen desaturation during an apnea event. Subjects with a faster ODR were found to have higher blood pressure values and variability. The authors hypothesized that slower desaturations generate hypoxemia-conditioning that may protect from exaggerated hemodynamic changes. These findings of novel hypoxemia metrics, albeit having their own limitations, recapitulate the need to move beyond the AHI to characterize OSA.

The apnea-hypopnea event duration is another overlooked feature that may impact OSA outcomes. Butler, et al. demonstrated that shorter event duration predicted a higher all-cause mortality over and beyond that predicted by AHI (Butler et al. Am J Respir Crit Care Med. 2019;199[7]:903-12). These results contrast views that early arousals in response to respiratory events may improve outcomes as they reflect a protective mechanism to prevent further hypoxemia and sympatho-excitation. For example, Ma, et al. found that higher percentage of total sleep time spent in apnea/hypopnea (AHT%) predicted worse daytime sleepiness to a higher degree than standard AHI (Ma et al. Sci Rep. 2021;11[1]:4702). However, shorter event duration may represent lower arousal thresholds (increased excitability), and ventilatory control instability (higher loop gain), predisposing patients to augmented sympathetic activity. Along similar lines, the intensity of respiratory-related arousals (as measured by EEG wavelet transformation) was found to be independent of preceding respiratory stimulus, with higher arousal intensity levels correlating with higher respiratory and heart rate responses (Amatoury et al. Sleep. 2016;39[12]:2091-100). The contribution of arousals to OSA morbidity is of particular importance for women in whom long-term outcomes of elevated AHI are poorly understood. Bearing in mind the differences in the metrics used, these results underscore the role of event duration and arousability in the pathogenesis of OSA-related morbidity.

The AHI is certainly an important piece of data that is informative and somewhat predictive. However, when used as a sole disease-defining metric, it has yielded disappointing results, especially after OSA treatment trials failed to show cardiovascular benefits despite therapies achieving a low residual AHI. As we aim to achieve a more personalized approach for diagnosing and treating OSA, we need to explore beyond the concept of a single metric to define a heterogenous and complex disorder. Instead of relying on the frequency of respiratory events, it is time to use complementary polysomnographic data that better reflect the origin and systemic effects of these disturbances. Machine-learning methods may offer sophisticated approaches to identifying polysomnographic patterns for future research. Clinical characteristics will also likely need to be considered in OSA severity scales. The identification of symptom subtypes or blood biomarkers may help identify patient groups who may be impacted differently by OSA, and consequently have a different treatment response (Malhotra et al. Sleep. 2021;44[7]:zsab030).

Almost half a century has lapsed since the original descriptions of OSA. Since then, our understanding of the disorder has improved greatly, with much still to be discovered, but our method of disease capture is unwavering. Future research requires a focus on novel measures aimed at identifying OSA endophenotypes, which will transform our understanding of disease traits and propel us into personalized therapies.
 

Dr. Mansour is Assistant Professor of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University School of Medicine, Durham, North Carolina. Dr. Won is Associate Professor of Medicine, Section of Pulmonary, Critical Care, and Sleep Medicine, Yale University School of Medicine; and VA Connecticut Healthcare System, West Haven, Connecticut.

Animal and human models of the effects of therapeutic hypothermia, now called targeted temperature management (TTM), began to surface in the late 1980s. The first randomized clinical trial employing TTM as a neuroprotective strategy following cardiac arrest did not appear until the early 2000s. When compared with normothermia, the HACA trial (Holzer M, et al. N Engl J Med. 2002;346[8]:549-56) demonstrated a 14% reduction in mortality and improved neurologic outcomes following out of hospital cardiac arrest (OHCA) due to ventricular fibrillation (VF) or ventricular tachycardia (VT) when maintaining body temperature between 32˚C and 34˚C post-arrest. Following the results of this trial, TTM in comatose patients following cardiac arrest was recommended by international guidelines and became the standard of care. It was not until the publication of the TTM1 trial (Nielsen N, et al. N Engl J Med. 2013;369[23]:2197-206) about a decade later, that serious questions regarding the efficacy of TTM were raised. The TTM1 trial showed no difference in mortality or neurologic outcomes when comparing TTM at 33˚C vs 36˚C for OHCA. The results of this trial heralded widespread practice change, with many abandoning deep cooling, and often active cooling measures, in favor of fever avoidance. The HYPERION trial (Lascarrou J, et al. N Engl J Med. 2019;381:2327-37) came next, comparing TTM at 33˚C to normothermia (<37.5˚C) for cardiac arrest with non-hockable rhythm. This study did not identify any improvement in mortality with utilization of TTM but suggested it may be associated with more favorable neurologic outcomes, albeit in a small number of patients.

Courtesy of American College of Chest Physicians

The TTM2 trial (Dankiewicz J, et al. N Engl J Med. 2021;384:2283-94) is the most recent trial to address the question of TTM post-cardiac arrest. The TTM2 trial was an international, randomized controlled superiority trial of TTM at 33˚C vs normothermia (≤37.8˚C) for patients with coma following OHCA with any initial rhythm. It was conducted by the same group as the TTM1 trial and, to date, represents the largest (N= 1,850) and most robust trial conducted in this area. The trial spanned 61 institutions across 14 countries and had nearly complete follow-up at 6 months. Once again, there was no significant difference in all-cause mortality at 6 months in the TTM group when compared with the normothermia group. Equally important, there were no differences observed in secondary outcomes, including functional neurologic status and health-related quality of life at 6 months. With the results of the TTM1 and TTM2 trials failing to show any neurologic or mortality benefit to TTM, we are left wondering, is there anything therapeutic about “therapeutic hypothermia”?

Both the 2020 American Heart Association (AHA) and 2021 European Resuscitation Council (ERC) guidelines predate this trial; they recommend cooling any OHCA or in-hospital cardiac arrest (IHCA) patient who remains unresponsive after return of spontaneous circulation (ROSC) regardless of initial rhythm. They further suggest maintaining a target temperature between 32˚C and 36˚C for at least 24 hours, followed by avoidance of fever (>37.7˚C) for at least 72 hours after ROSC in patients who remain comatose. While it will be interesting to see what future iterations of the guidelines recommend, the results from the TTM1 and TTM2 trials support a shift in clinical practice away from TTM and toward more active fever avoidance. Additionally, careful review of adverse events in the TTM2 trial suggests that induced hypothermia is not without risk of harm. When compared with the normothermia group in the TTM2 trial, the hypothermia group experienced higher rates of arrhythmias with hemodynamic instability (16% vs 24%), increased exposure to sedation, increased use of neuromuscular blockade, and increased duration of mechanical ventilation.

While the results of the TTM2 trial move the needle away from therapeutic hypothermia for OHCA patients, there is some nuance that warrants further discussion. First, the initial HACA trial, upon which the standard of TTM was based, included only patients with an initial shockable rhythm (VT/VF). Inherently, the etiology of these arrests is likely to be cardiac and more reversible in nature. Most subsequent landmark trials on TTM, including the TTM2 trial, have included OHCA patients with both shockable and nonshockable initial rhythms. Still, the majority of patients in the TTM2 trial had an initial shockable rhythm on presentation (72% hypothermia vs 75% normothermia). This may limit broad generalizability of study findings as an increasing number of OHCA patients are presenting with nonshockable initial rhythms. Next, it is well known that bystander CPR improves outcomes following OHCA. Impressively, over 75% of patients in both groups in the TTM2 trial received bystander CPR compared with an average of 46% of arrest patients in the US according to AHA data. Finally, like most of its predecessors, the TTM2 trial only included OHCA patients meaning no real conclusions can be drawn regarding application of TTM to IHCA patients. Of the major trials to date, only the HYPERION trial included IHCA patients – representing about 25% of the study population. Thus, the utility of TTM in the setting of IHCA remains largely unknown.

Taken in summation, recent trials, including TTM2, suggest that fever-avoidance post-cardiac arrest is likely the best option for improving mortality and neurologic outcomes while mitigating risk to the patient. We must remain vigilant in our enforcement of normothermia though as worse neurologic outcomes have been observed with hyperthermia in the early post-arrest period (Zeiner A, et al. Arch Intern Med. 2001;161[16]:2007-12). A key takeaway from recent trials is that maintaining normothermia without active temperature control measures is likely to be difficult to achieve. A criticism of the HYPERION trial was that a “substantial proportion” of patients in the normothermia group had temperatures above 38˚C. Similarly, 10% to15% of patients in the TTM2 trial had body temperatures above 37.7˚C, 40 to 72 hours after randomization and, ultimately, 46% of patients in the normothermia group required cooling with a temperature management device. Thus, we can conclude that maintenance of strict normothermia will likely continue to require active control with a temperature management device.

Despite an increasing number of well conducted studies in this area, there are several questions that remain unanswered. The first is whether cooling patients even earlier post-arrest is felt to increase the likelihood of survival with improved neurologic outcomes. Like HACA and HYPERION, the rate of cooling in the TTM2 trial was relatively quick with a time to randomization after onset of cardiac arrest of about 2 hours in both groups and a median time from intervention until reaching target temperature of 3 hours. While some retrospective data suggest ultra-early cooling may be beneficial, neither induction of therapeutic hypothermia during OHCA using a rapid infusion of cold saline (Bernard SA, et al. Circulation. 2016;134[11]:797-805) nor transnasal evaporative cooling in the pre-hospital setting (Nordeberg P, et al. JAMA. 2019;321(17):1677-85) has shown improvement in survival with good neurologic outcomes. Next, if we are going to continue TTM, the TTM2 trial does not provide guidance on optimal duration of cooling. Although the current guidelines are to cool for at least 24 hours after ROSC, it is unclear for how long strict temperature control should be continued. The currently enrolling ICECAP study aims to further elucidate the optimal duration of TTM for OHCA patients with both shockable and non-shockable initial rhythms.

Post-cardiac arrest management continues to be a significant area of interest in clinical research and for good reason. Although steady improvement has occurred with regards to survival and neurologic function for IHCA, of the approximately 350,000 nontraumatic OHCA that occur in a year in the United States, only about 10.2% of those patients will survive their initial hospitalization, and only about 8.2% of those who survive will have good functional status (American Heart Association. Circulation. 2020;142(suppl 2):S366-S468). There remains much room for continued study and improvement.
 

Dr. Capp is a Pulmonary and Critical Care Fellow; and Dr. Pendleton is Assistant Professor of Medicine; Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine; University of Minnesota, Minneapolis, Minnesota.

Animal and human models of the effects of therapeutic hypothermia, now called targeted temperature management (TTM), began to surface in the late 1980s. The first randomized clinical trial employing TTM as a neuroprotective strategy following cardiac arrest did not appear until the early 2000s. When compared with normothermia, the HACA trial (Holzer M, et al. N Engl J Med. 2002;346[8]:549-56) demonstrated a 14% reduction in mortality and improved neurologic outcomes following out of hospital cardiac arrest (OHCA) due to ventricular fibrillation (VF) or ventricular tachycardia (VT) when maintaining body temperature between 32˚C and 34˚C post-arrest. Following the results of this trial, TTM in comatose patients following cardiac arrest was recommended by international guidelines and became the standard of care. It was not until the publication of the TTM1 trial (Nielsen N, et al. N Engl J Med. 2013;369[23]:2197-206) about a decade later, that serious questions regarding the efficacy of TTM were raised. The TTM1 trial showed no difference in mortality or neurologic outcomes when comparing TTM at 33˚C vs 36˚C for OHCA. The results of this trial heralded widespread practice change, with many abandoning deep cooling, and often active cooling measures, in favor of fever avoidance. The HYPERION trial (Lascarrou J, et al. N Engl J Med. 2019;381:2327-37) came next, comparing TTM at 33˚C to normothermia (<37.5˚C) for cardiac arrest with non-hockable rhythm. This study did not identify any improvement in mortality with utilization of TTM but suggested it may be associated with more favorable neurologic outcomes, albeit in a small number of patients.

Courtesy of American College of Chest Physicians

The TTM2 trial (Dankiewicz J, et al. N Engl J Med. 2021;384:2283-94) is the most recent trial to address the question of TTM post-cardiac arrest. The TTM2 trial was an international, randomized controlled superiority trial of TTM at 33˚C vs normothermia (≤37.8˚C) for patients with coma following OHCA with any initial rhythm. It was conducted by the same group as the TTM1 trial and, to date, represents the largest (N= 1,850) and most robust trial conducted in this area. The trial spanned 61 institutions across 14 countries and had nearly complete follow-up at 6 months. Once again, there was no significant difference in all-cause mortality at 6 months in the TTM group when compared with the normothermia group. Equally important, there were no differences observed in secondary outcomes, including functional neurologic status and health-related quality of life at 6 months. With the results of the TTM1 and TTM2 trials failing to show any neurologic or mortality benefit to TTM, we are left wondering, is there anything therapeutic about “therapeutic hypothermia”?

Both the 2020 American Heart Association (AHA) and 2021 European Resuscitation Council (ERC) guidelines predate this trial; they recommend cooling any OHCA or in-hospital cardiac arrest (IHCA) patient who remains unresponsive after return of spontaneous circulation (ROSC) regardless of initial rhythm. They further suggest maintaining a target temperature between 32˚C and 36˚C for at least 24 hours, followed by avoidance of fever (>37.7˚C) for at least 72 hours after ROSC in patients who remain comatose. While it will be interesting to see what future iterations of the guidelines recommend, the results from the TTM1 and TTM2 trials support a shift in clinical practice away from TTM and toward more active fever avoidance. Additionally, careful review of adverse events in the TTM2 trial suggests that induced hypothermia is not without risk of harm. When compared with the normothermia group in the TTM2 trial, the hypothermia group experienced higher rates of arrhythmias with hemodynamic instability (16% vs 24%), increased exposure to sedation, increased use of neuromuscular blockade, and increased duration of mechanical ventilation.

While the results of the TTM2 trial move the needle away from therapeutic hypothermia for OHCA patients, there is some nuance that warrants further discussion. First, the initial HACA trial, upon which the standard of TTM was based, included only patients with an initial shockable rhythm (VT/VF). Inherently, the etiology of these arrests is likely to be cardiac and more reversible in nature. Most subsequent landmark trials on TTM, including the TTM2 trial, have included OHCA patients with both shockable and nonshockable initial rhythms. Still, the majority of patients in the TTM2 trial had an initial shockable rhythm on presentation (72% hypothermia vs 75% normothermia). This may limit broad generalizability of study findings as an increasing number of OHCA patients are presenting with nonshockable initial rhythms. Next, it is well known that bystander CPR improves outcomes following OHCA. Impressively, over 75% of patients in both groups in the TTM2 trial received bystander CPR compared with an average of 46% of arrest patients in the US according to AHA data. Finally, like most of its predecessors, the TTM2 trial only included OHCA patients meaning no real conclusions can be drawn regarding application of TTM to IHCA patients. Of the major trials to date, only the HYPERION trial included IHCA patients – representing about 25% of the study population. Thus, the utility of TTM in the setting of IHCA remains largely unknown.

Taken in summation, recent trials, including TTM2, suggest that fever-avoidance post-cardiac arrest is likely the best option for improving mortality and neurologic outcomes while mitigating risk to the patient. We must remain vigilant in our enforcement of normothermia though as worse neurologic outcomes have been observed with hyperthermia in the early post-arrest period (Zeiner A, et al. Arch Intern Med. 2001;161[16]:2007-12). A key takeaway from recent trials is that maintaining normothermia without active temperature control measures is likely to be difficult to achieve. A criticism of the HYPERION trial was that a “substantial proportion” of patients in the normothermia group had temperatures above 38˚C. Similarly, 10% to15% of patients in the TTM2 trial had body temperatures above 37.7˚C, 40 to 72 hours after randomization and, ultimately, 46% of patients in the normothermia group required cooling with a temperature management device. Thus, we can conclude that maintenance of strict normothermia will likely continue to require active control with a temperature management device.

Despite an increasing number of well conducted studies in this area, there are several questions that remain unanswered. The first is whether cooling patients even earlier post-arrest is felt to increase the likelihood of survival with improved neurologic outcomes. Like HACA and HYPERION, the rate of cooling in the TTM2 trial was relatively quick with a time to randomization after onset of cardiac arrest of about 2 hours in both groups and a median time from intervention until reaching target temperature of 3 hours. While some retrospective data suggest ultra-early cooling may be beneficial, neither induction of therapeutic hypothermia during OHCA using a rapid infusion of cold saline (Bernard SA, et al. Circulation. 2016;134[11]:797-805) nor transnasal evaporative cooling in the pre-hospital setting (Nordeberg P, et al. JAMA. 2019;321(17):1677-85) has shown improvement in survival with good neurologic outcomes. Next, if we are going to continue TTM, the TTM2 trial does not provide guidance on optimal duration of cooling. Although the current guidelines are to cool for at least 24 hours after ROSC, it is unclear for how long strict temperature control should be continued. The currently enrolling ICECAP study aims to further elucidate the optimal duration of TTM for OHCA patients with both shockable and non-shockable initial rhythms.

Post-cardiac arrest management continues to be a significant area of interest in clinical research and for good reason. Although steady improvement has occurred with regards to survival and neurologic function for IHCA, of the approximately 350,000 nontraumatic OHCA that occur in a year in the United States, only about 10.2% of those patients will survive their initial hospitalization, and only about 8.2% of those who survive will have good functional status (American Heart Association. Circulation. 2020;142(suppl 2):S366-S468). There remains much room for continued study and improvement.
 

Dr. Capp is a Pulmonary and Critical Care Fellow; and Dr. Pendleton is Assistant Professor of Medicine; Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine; University of Minnesota, Minneapolis, Minnesota.

Animal and human models of the effects of therapeutic hypothermia, now called targeted temperature management (TTM), began to surface in the late 1980s. The first randomized clinical trial employing TTM as a neuroprotective strategy following cardiac arrest did not appear until the early 2000s. When compared with normothermia, the HACA trial (Holzer M, et al. N Engl J Med. 2002;346[8]:549-56) demonstrated a 14% reduction in mortality and improved neurologic outcomes following out of hospital cardiac arrest (OHCA) due to ventricular fibrillation (VF) or ventricular tachycardia (VT) when maintaining body temperature between 32˚C and 34˚C post-arrest. Following the results of this trial, TTM in comatose patients following cardiac arrest was recommended by international guidelines and became the standard of care. It was not until the publication of the TTM1 trial (Nielsen N, et al. N Engl J Med. 2013;369[23]:2197-206) about a decade later, that serious questions regarding the efficacy of TTM were raised. The TTM1 trial showed no difference in mortality or neurologic outcomes when comparing TTM at 33˚C vs 36˚C for OHCA. The results of this trial heralded widespread practice change, with many abandoning deep cooling, and often active cooling measures, in favor of fever avoidance. The HYPERION trial (Lascarrou J, et al. N Engl J Med. 2019;381:2327-37) came next, comparing TTM at 33˚C to normothermia (<37.5˚C) for cardiac arrest with non-hockable rhythm. This study did not identify any improvement in mortality with utilization of TTM but suggested it may be associated with more favorable neurologic outcomes, albeit in a small number of patients.

Courtesy of American College of Chest Physicians

The TTM2 trial (Dankiewicz J, et al. N Engl J Med. 2021;384:2283-94) is the most recent trial to address the question of TTM post-cardiac arrest. The TTM2 trial was an international, randomized controlled superiority trial of TTM at 33˚C vs normothermia (≤37.8˚C) for patients with coma following OHCA with any initial rhythm. It was conducted by the same group as the TTM1 trial and, to date, represents the largest (N= 1,850) and most robust trial conducted in this area. The trial spanned 61 institutions across 14 countries and had nearly complete follow-up at 6 months. Once again, there was no significant difference in all-cause mortality at 6 months in the TTM group when compared with the normothermia group. Equally important, there were no differences observed in secondary outcomes, including functional neurologic status and health-related quality of life at 6 months. With the results of the TTM1 and TTM2 trials failing to show any neurologic or mortality benefit to TTM, we are left wondering, is there anything therapeutic about “therapeutic hypothermia”?

Both the 2020 American Heart Association (AHA) and 2021 European Resuscitation Council (ERC) guidelines predate this trial; they recommend cooling any OHCA or in-hospital cardiac arrest (IHCA) patient who remains unresponsive after return of spontaneous circulation (ROSC) regardless of initial rhythm. They further suggest maintaining a target temperature between 32˚C and 36˚C for at least 24 hours, followed by avoidance of fever (>37.7˚C) for at least 72 hours after ROSC in patients who remain comatose. While it will be interesting to see what future iterations of the guidelines recommend, the results from the TTM1 and TTM2 trials support a shift in clinical practice away from TTM and toward more active fever avoidance. Additionally, careful review of adverse events in the TTM2 trial suggests that induced hypothermia is not without risk of harm. When compared with the normothermia group in the TTM2 trial, the hypothermia group experienced higher rates of arrhythmias with hemodynamic instability (16% vs 24%), increased exposure to sedation, increased use of neuromuscular blockade, and increased duration of mechanical ventilation.

While the results of the TTM2 trial move the needle away from therapeutic hypothermia for OHCA patients, there is some nuance that warrants further discussion. First, the initial HACA trial, upon which the standard of TTM was based, included only patients with an initial shockable rhythm (VT/VF). Inherently, the etiology of these arrests is likely to be cardiac and more reversible in nature. Most subsequent landmark trials on TTM, including the TTM2 trial, have included OHCA patients with both shockable and nonshockable initial rhythms. Still, the majority of patients in the TTM2 trial had an initial shockable rhythm on presentation (72% hypothermia vs 75% normothermia). This may limit broad generalizability of study findings as an increasing number of OHCA patients are presenting with nonshockable initial rhythms. Next, it is well known that bystander CPR improves outcomes following OHCA. Impressively, over 75% of patients in both groups in the TTM2 trial received bystander CPR compared with an average of 46% of arrest patients in the US according to AHA data. Finally, like most of its predecessors, the TTM2 trial only included OHCA patients meaning no real conclusions can be drawn regarding application of TTM to IHCA patients. Of the major trials to date, only the HYPERION trial included IHCA patients – representing about 25% of the study population. Thus, the utility of TTM in the setting of IHCA remains largely unknown.

Taken in summation, recent trials, including TTM2, suggest that fever-avoidance post-cardiac arrest is likely the best option for improving mortality and neurologic outcomes while mitigating risk to the patient. We must remain vigilant in our enforcement of normothermia though as worse neurologic outcomes have been observed with hyperthermia in the early post-arrest period (Zeiner A, et al. Arch Intern Med. 2001;161[16]:2007-12). A key takeaway from recent trials is that maintaining normothermia without active temperature control measures is likely to be difficult to achieve. A criticism of the HYPERION trial was that a “substantial proportion” of patients in the normothermia group had temperatures above 38˚C. Similarly, 10% to15% of patients in the TTM2 trial had body temperatures above 37.7˚C, 40 to 72 hours after randomization and, ultimately, 46% of patients in the normothermia group required cooling with a temperature management device. Thus, we can conclude that maintenance of strict normothermia will likely continue to require active control with a temperature management device.

Despite an increasing number of well conducted studies in this area, there are several questions that remain unanswered. The first is whether cooling patients even earlier post-arrest is felt to increase the likelihood of survival with improved neurologic outcomes. Like HACA and HYPERION, the rate of cooling in the TTM2 trial was relatively quick with a time to randomization after onset of cardiac arrest of about 2 hours in both groups and a median time from intervention until reaching target temperature of 3 hours. While some retrospective data suggest ultra-early cooling may be beneficial, neither induction of therapeutic hypothermia during OHCA using a rapid infusion of cold saline (Bernard SA, et al. Circulation. 2016;134[11]:797-805) nor transnasal evaporative cooling in the pre-hospital setting (Nordeberg P, et al. JAMA. 2019;321(17):1677-85) has shown improvement in survival with good neurologic outcomes. Next, if we are going to continue TTM, the TTM2 trial does not provide guidance on optimal duration of cooling. Although the current guidelines are to cool for at least 24 hours after ROSC, it is unclear for how long strict temperature control should be continued. The currently enrolling ICECAP study aims to further elucidate the optimal duration of TTM for OHCA patients with both shockable and non-shockable initial rhythms.

Post-cardiac arrest management continues to be a significant area of interest in clinical research and for good reason. Although steady improvement has occurred with regards to survival and neurologic function for IHCA, of the approximately 350,000 nontraumatic OHCA that occur in a year in the United States, only about 10.2% of those patients will survive their initial hospitalization, and only about 8.2% of those who survive will have good functional status (American Heart Association. Circulation. 2020;142(suppl 2):S366-S468). There remains much room for continued study and improvement.
 

Dr. Capp is a Pulmonary and Critical Care Fellow; and Dr. Pendleton is Assistant Professor of Medicine; Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine; University of Minnesota, Minneapolis, Minnesota.

As of September 2021, over 222 million people worldwide (WHO, 2021) and 40 million Americans (CDC, 2021) have been infected with the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The total number of infections in the United States began climbing again this summer with the persistence of vaccine reluctance among a significant proportion of the population and the emergence of the much more infectious B.1.617.2 (Delta) variant. While the clinical illness caused by the SARS-CoV-2 virus, referred to as the Coronavirus disease 2019 (COVID-19), is mostly mild, approximately 10% of cases develop acute respiratory distress syndrome (ARDS) (Remuzzi A, et al. Lancet. 2020;395[10231]:1225-8). A small but substantial proportion of patients with COVID-19 ARDS fails to respond to the various supportive measures and requires extracorporeal membrane oxygenation (ECMO) support. The overarching goal of the different support strategies, including ECMO, is to provide time for the lungs to recover from ARDS. ECMO has the theoretical advantage over other strategies in facilitating recovery by allowing the injured lungs to ‘rest’ as the oxygenation and ventilation needs are met in an extracorporeal fashion. Regardless, a small number of patients with COVID-19 ARDS will not recover enough pulmonary function to allow them to be weaned from the various respiratory support strategies.

For patients with irreversible lung injury, lung transplantation (LT) is a potential consideration. Earlier in the pandemic, older patients with significant comorbid illnesses were more vulnerable to severe COVID-19, often precluding consideration for transplantation. However, the emergence of the Delta variant may have altered this dynamic via a substantial increase in the incidence of COVID-19 ARDS among younger and healthier patients. A handful of patients with COVID-19 ARDS have already had successful transplantation. However, the overall number is still small (Bharat A, et al. Sci Translat Med. 2020 Dec 16;12[574]:eabe4282. doi: 10.1126/scitranslmed.abe4282. Epub 2020 Nov 30; and Hawkins R, et al. Transplantation. 2021;6:1381-7), and there is a lack of long-term outcomes data among these patients.

Dr. Quinn and Dr. Banga are with the Lung Transplant Program, Divisions of Pulmonary and Critical Care Medicine, University of Texas Southwestern Medical Center, Dallas.

As of September 2021, over 222 million people worldwide (WHO, 2021) and 40 million Americans (CDC, 2021) have been infected with the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The total number of infections in the United States began climbing again this summer with the persistence of vaccine reluctance among a significant proportion of the population and the emergence of the much more infectious B.1.617.2 (Delta) variant. While the clinical illness caused by the SARS-CoV-2 virus, referred to as the Coronavirus disease 2019 (COVID-19), is mostly mild, approximately 10% of cases develop acute respiratory distress syndrome (ARDS) (Remuzzi A, et al. Lancet. 2020;395[10231]:1225-8). A small but substantial proportion of patients with COVID-19 ARDS fails to respond to the various supportive measures and requires extracorporeal membrane oxygenation (ECMO) support. The overarching goal of the different support strategies, including ECMO, is to provide time for the lungs to recover from ARDS. ECMO has the theoretical advantage over other strategies in facilitating recovery by allowing the injured lungs to ‘rest’ as the oxygenation and ventilation needs are met in an extracorporeal fashion. Regardless, a small number of patients with COVID-19 ARDS will not recover enough pulmonary function to allow them to be weaned from the various respiratory support strategies.

For patients with irreversible lung injury, lung transplantation (LT) is a potential consideration. Earlier in the pandemic, older patients with significant comorbid illnesses were more vulnerable to severe COVID-19, often precluding consideration for transplantation. However, the emergence of the Delta variant may have altered this dynamic via a substantial increase in the incidence of COVID-19 ARDS among younger and healthier patients. A handful of patients with COVID-19 ARDS have already had successful transplantation. However, the overall number is still small (Bharat A, et al. Sci Translat Med. 2020 Dec 16;12[574]:eabe4282. doi: 10.1126/scitranslmed.abe4282. Epub 2020 Nov 30; and Hawkins R, et al. Transplantation. 2021;6:1381-7), and there is a lack of long-term outcomes data among these patients.

Dr. Quinn and Dr. Banga are with the Lung Transplant Program, Divisions of Pulmonary and Critical Care Medicine, University of Texas Southwestern Medical Center, Dallas.

As of September 2021, over 222 million people worldwide (WHO, 2021) and 40 million Americans (CDC, 2021) have been infected with the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The total number of infections in the United States began climbing again this summer with the persistence of vaccine reluctance among a significant proportion of the population and the emergence of the much more infectious B.1.617.2 (Delta) variant. While the clinical illness caused by the SARS-CoV-2 virus, referred to as the Coronavirus disease 2019 (COVID-19), is mostly mild, approximately 10% of cases develop acute respiratory distress syndrome (ARDS) (Remuzzi A, et al. Lancet. 2020;395[10231]:1225-8). A small but substantial proportion of patients with COVID-19 ARDS fails to respond to the various supportive measures and requires extracorporeal membrane oxygenation (ECMO) support. The overarching goal of the different support strategies, including ECMO, is to provide time for the lungs to recover from ARDS. ECMO has the theoretical advantage over other strategies in facilitating recovery by allowing the injured lungs to ‘rest’ as the oxygenation and ventilation needs are met in an extracorporeal fashion. Regardless, a small number of patients with COVID-19 ARDS will not recover enough pulmonary function to allow them to be weaned from the various respiratory support strategies.

For patients with irreversible lung injury, lung transplantation (LT) is a potential consideration. Earlier in the pandemic, older patients with significant comorbid illnesses were more vulnerable to severe COVID-19, often precluding consideration for transplantation. However, the emergence of the Delta variant may have altered this dynamic via a substantial increase in the incidence of COVID-19 ARDS among younger and healthier patients. A handful of patients with COVID-19 ARDS have already had successful transplantation. However, the overall number is still small (Bharat A, et al. Sci Translat Med. 2020 Dec 16;12[574]:eabe4282. doi: 10.1126/scitranslmed.abe4282. Epub 2020 Nov 30; and Hawkins R, et al. Transplantation. 2021;6:1381-7), and there is a lack of long-term outcomes data among these patients.

Dr. Quinn and Dr. Banga are with the Lung Transplant Program, Divisions of Pulmonary and Critical Care Medicine, University of Texas Southwestern Medical Center, Dallas.

With Siri and Alexa sitting at our kitchen tables and listening to our conversations, we have all but forgotten about the before times – when we had to use the Yellow Pages to look up a number or address and when we had no idea how many steps we took in a given day. Wearable technology has become ubiquitous and has us watching not only our step count but also our sleep. Did I get enough deep sleep? What does my sleep score of 82 mean? Should I be worried?

As clinicians, we must also navigate how this information impacts our clinical decision-making and consider how our patients are interpreting these data on a daily basis. There is an inherent assumption that we, as sleep clinicians, will understand the nuances of each consumer-facing sleep technology (CST) whether it is a wearable, a nearable (a device that sits near the body but not on the body), or an app. Very little validation data exist, as most of these technologies are marketed as wellness devices and are not intended to render a diagnosis. It therefore falls to us to determine how to utilize this information in an already busy clinic.

One strategy is to use these technologies as patient engagement tools – a way to increase public awareness of the importance of sleep. While this certainly should be beneficial, oftentimes, the data are confusing and can lead to misunderstandings about what normal sleep should look like. Approaching these data as partners to our patients allows us to set expectations around normal sleep cycles and sleep duration. It also allows us to discuss appropriate sleep timing and sleep hygiene.

Many wearable devices have incorporated oximetry into their metrics, and some claim to have accuracy that is better than hospital-grade oximeters. Many of these companies are no longer in business. Others specify higher accuracy in dark-skinned individuals (“CIRCUL Ring Pulse Oximeter in Dark-Pigmented Individuals: Clinical Study Validates Efficacy and Reliability,” Medical Device News Magazine, Feb. 26, 2021).

Despite these claims, they are registered as wellness devices with the FDA and are not diagnostic devices. Logically, if one of these devices demonstrates worrisome data, then it can prompt further clinical queries and, potentially, objective testing for obstructive sleep apnea (OSA). The reverse, however, cannot be claimed. A normal reading by CST does not obviate the need for objective testing if the clinical symptoms warrant it.

There are CSTs that have been created around very specific needs - such as jet lag- and provide guidance for how to quickly acclimate to the destination time zone by providing nudges for light exposure and timed melatonin or dark glasses (https://www.timeshifter.com/).

Others analyze the sleep space for extrinsic sounds (https://www.sleepcycle.com/), while a plethora of apps provides advice for how to optimize your sleep environment and wind-down routine. There is even a sleep robot designed to facilitate sleep onset (https://somnox.com/). This bean-shaped device is designed to “breathe” as you hold it, and the user is meant to emulate those same breathing patterns. It is a take on the 4-7-8 breathing pattern long endorsed by yogis.

Although validation data are lacking for the vast majority of CST, a recent study (www.ncbi.nlm.nih.gov/pmc/articles/PMC8120339/pdf/zsaa291.pdf).demonstrated that CST had high performance when compared with actigraphy in assessing sleep and wakefulness and, as such, may improve the evaluation of sleep and wake opportunities prior to MSLT or improve identification of circadian sleep-wake disorders. Many practices do not currently utilize actigraphy due to its expense and very limited potential for reimbursement. Using a patient’s sleep-tracking device may allow access to these data without financial outlay. While these data demonstrate the ability of CST to potentially differentiate sleep from wakefulness, it is notable that this study also found that the determination of individual sleep stages is less robust. In general, CST cannot identify an underlying sleep disorder, however, may raise awareness that a disorder might be present.

This leads to more reflection on the role of CST in a typical sleep clinic. Many years ago, discussion around this technology was primarily patient-initiated and often times met with skepticism on the part of the clinician. As technology has improved and has become more accessible, there appears to be more acceptance among our colleagues – not, perhaps, in terms of absolute actionable data, but rather as an opportunity to discuss sleep with our patients and to support their own efforts at improving their sleep. Trends in the data in response to CBT-I or medications can be observed. Abnormalities identified via CST often serve as the initial prompt for a clinical visit and, as such, should not be eschewed. Rather, reframing the use of this information while also addressing other sleep issues is likely to be the more appropriate path forward.

Assessing this information can be time-consuming, and best practice suggests establishing expectations around this process (J Clin Sleep Med 2018 May 15. doi: 10.5664/jcsm.7128).

Agreements can be made with patients that the data are reviewed in the context of a clinical visit rather than longitudinally as data are uploaded and then sent via messaging unless such an understanding has already been agreed upon. RPM billing codes may ultimately allow for reimbursement and recognition of this workload. At the present time, RPM billing is limited to FDA-cleared, prescription devices, and CST does not yet qualify.

There also needs to be recognition of potential harm from CST. Inevitably, some patients will develop orthosomnia, a term coined by Dr. Kelly Baron, where patients become so fixated on achieving perfect sleep scores that it contributes to insomnia. In this case, identification of orthosomnia is made via the clinical visit and patients are advised to stop tracking their sleep for a set period of time. This allows the anxiety around achieving “perfect sleep” to dissipate.

Google and the AASM recently announced a partnership. Essentially, the Google Nest Hub will serve to detect sleep concerns (such as timing of sleep, snoring, insufficient sleep, etc.) and will direct the user to educational resources such as www.sleepeducation.org. The idea behind this is that people are often unaware of an underlying sleep disorder such as OSA and don’t know what to search for. The Nest Hub uses information it collects and directs users to appropriate resources, thus obviating the need to know what to Google.

Clearly, big tech has invested heavily in our field. Between the copious wearables, nearables, and apps that are sleep-focused, these industry giants obviously believe that sleep is worthy of such a significant allocation of resources. This has improved the overall awareness of the importance of sleep and of identifying and treating sleep disorders. While these technologies are no replacement for a clinical evaluation, they can serve as patient engagement tools, as well as potentially large-scale OSA screening tools and may help us improve the percentage of patients with undiagnosed OSA, estimated to be 80% (Frost and Sullivan, “Hidden Health Crisis Costing America Billions,” American Academy of Sleep Medicine, 2016).

CST may allow us to better identify circadian sleep-wake disorders and evaluate sleep satiation prior to MLST that no longer requires investment in expensive actigraphy devices. They also allow us to partner with our patients by meeting them where they are and recognizing the efforts they have already made to improve their sleep before we even meet them.
 

Dr. Khosla is Medical Director, North Dakota Center for Sleep, Fargo, North Dakota.

With Siri and Alexa sitting at our kitchen tables and listening to our conversations, we have all but forgotten about the before times – when we had to use the Yellow Pages to look up a number or address and when we had no idea how many steps we took in a given day. Wearable technology has become ubiquitous and has us watching not only our step count but also our sleep. Did I get enough deep sleep? What does my sleep score of 82 mean? Should I be worried?

As clinicians, we must also navigate how this information impacts our clinical decision-making and consider how our patients are interpreting these data on a daily basis. There is an inherent assumption that we, as sleep clinicians, will understand the nuances of each consumer-facing sleep technology (CST) whether it is a wearable, a nearable (a device that sits near the body but not on the body), or an app. Very little validation data exist, as most of these technologies are marketed as wellness devices and are not intended to render a diagnosis. It therefore falls to us to determine how to utilize this information in an already busy clinic.

One strategy is to use these technologies as patient engagement tools – a way to increase public awareness of the importance of sleep. While this certainly should be beneficial, oftentimes, the data are confusing and can lead to misunderstandings about what normal sleep should look like. Approaching these data as partners to our patients allows us to set expectations around normal sleep cycles and sleep duration. It also allows us to discuss appropriate sleep timing and sleep hygiene.

Many wearable devices have incorporated oximetry into their metrics, and some claim to have accuracy that is better than hospital-grade oximeters. Many of these companies are no longer in business. Others specify higher accuracy in dark-skinned individuals (“CIRCUL Ring Pulse Oximeter in Dark-Pigmented Individuals: Clinical Study Validates Efficacy and Reliability,” Medical Device News Magazine, Feb. 26, 2021).

Despite these claims, they are registered as wellness devices with the FDA and are not diagnostic devices. Logically, if one of these devices demonstrates worrisome data, then it can prompt further clinical queries and, potentially, objective testing for obstructive sleep apnea (OSA). The reverse, however, cannot be claimed. A normal reading by CST does not obviate the need for objective testing if the clinical symptoms warrant it.

There are CSTs that have been created around very specific needs - such as jet lag- and provide guidance for how to quickly acclimate to the destination time zone by providing nudges for light exposure and timed melatonin or dark glasses (https://www.timeshifter.com/).

Others analyze the sleep space for extrinsic sounds (https://www.sleepcycle.com/), while a plethora of apps provides advice for how to optimize your sleep environment and wind-down routine. There is even a sleep robot designed to facilitate sleep onset (https://somnox.com/). This bean-shaped device is designed to “breathe” as you hold it, and the user is meant to emulate those same breathing patterns. It is a take on the 4-7-8 breathing pattern long endorsed by yogis.

Although validation data are lacking for the vast majority of CST, a recent study (www.ncbi.nlm.nih.gov/pmc/articles/PMC8120339/pdf/zsaa291.pdf).demonstrated that CST had high performance when compared with actigraphy in assessing sleep and wakefulness and, as such, may improve the evaluation of sleep and wake opportunities prior to MSLT or improve identification of circadian sleep-wake disorders. Many practices do not currently utilize actigraphy due to its expense and very limited potential for reimbursement. Using a patient’s sleep-tracking device may allow access to these data without financial outlay. While these data demonstrate the ability of CST to potentially differentiate sleep from wakefulness, it is notable that this study also found that the determination of individual sleep stages is less robust. In general, CST cannot identify an underlying sleep disorder, however, may raise awareness that a disorder might be present.

This leads to more reflection on the role of CST in a typical sleep clinic. Many years ago, discussion around this technology was primarily patient-initiated and often times met with skepticism on the part of the clinician. As technology has improved and has become more accessible, there appears to be more acceptance among our colleagues – not, perhaps, in terms of absolute actionable data, but rather as an opportunity to discuss sleep with our patients and to support their own efforts at improving their sleep. Trends in the data in response to CBT-I or medications can be observed. Abnormalities identified via CST often serve as the initial prompt for a clinical visit and, as such, should not be eschewed. Rather, reframing the use of this information while also addressing other sleep issues is likely to be the more appropriate path forward.

Assessing this information can be time-consuming, and best practice suggests establishing expectations around this process (J Clin Sleep Med 2018 May 15. doi: 10.5664/jcsm.7128).

Agreements can be made with patients that the data are reviewed in the context of a clinical visit rather than longitudinally as data are uploaded and then sent via messaging unless such an understanding has already been agreed upon. RPM billing codes may ultimately allow for reimbursement and recognition of this workload. At the present time, RPM billing is limited to FDA-cleared, prescription devices, and CST does not yet qualify.

There also needs to be recognition of potential harm from CST. Inevitably, some patients will develop orthosomnia, a term coined by Dr. Kelly Baron, where patients become so fixated on achieving perfect sleep scores that it contributes to insomnia. In this case, identification of orthosomnia is made via the clinical visit and patients are advised to stop tracking their sleep for a set period of time. This allows the anxiety around achieving “perfect sleep” to dissipate.

Google and the AASM recently announced a partnership. Essentially, the Google Nest Hub will serve to detect sleep concerns (such as timing of sleep, snoring, insufficient sleep, etc.) and will direct the user to educational resources such as www.sleepeducation.org. The idea behind this is that people are often unaware of an underlying sleep disorder such as OSA and don’t know what to search for. The Nest Hub uses information it collects and directs users to appropriate resources, thus obviating the need to know what to Google.

Clearly, big tech has invested heavily in our field. Between the copious wearables, nearables, and apps that are sleep-focused, these industry giants obviously believe that sleep is worthy of such a significant allocation of resources. This has improved the overall awareness of the importance of sleep and of identifying and treating sleep disorders. While these technologies are no replacement for a clinical evaluation, they can serve as patient engagement tools, as well as potentially large-scale OSA screening tools and may help us improve the percentage of patients with undiagnosed OSA, estimated to be 80% (Frost and Sullivan, “Hidden Health Crisis Costing America Billions,” American Academy of Sleep Medicine, 2016).

CST may allow us to better identify circadian sleep-wake disorders and evaluate sleep satiation prior to MLST that no longer requires investment in expensive actigraphy devices. They also allow us to partner with our patients by meeting them where they are and recognizing the efforts they have already made to improve their sleep before we even meet them.
 

Dr. Khosla is Medical Director, North Dakota Center for Sleep, Fargo, North Dakota.

With Siri and Alexa sitting at our kitchen tables and listening to our conversations, we have all but forgotten about the before times – when we had to use the Yellow Pages to look up a number or address and when we had no idea how many steps we took in a given day. Wearable technology has become ubiquitous and has us watching not only our step count but also our sleep. Did I get enough deep sleep? What does my sleep score of 82 mean? Should I be worried?

As clinicians, we must also navigate how this information impacts our clinical decision-making and consider how our patients are interpreting these data on a daily basis. There is an inherent assumption that we, as sleep clinicians, will understand the nuances of each consumer-facing sleep technology (CST) whether it is a wearable, a nearable (a device that sits near the body but not on the body), or an app. Very little validation data exist, as most of these technologies are marketed as wellness devices and are not intended to render a diagnosis. It therefore falls to us to determine how to utilize this information in an already busy clinic.

One strategy is to use these technologies as patient engagement tools – a way to increase public awareness of the importance of sleep. While this certainly should be beneficial, oftentimes, the data are confusing and can lead to misunderstandings about what normal sleep should look like. Approaching these data as partners to our patients allows us to set expectations around normal sleep cycles and sleep duration. It also allows us to discuss appropriate sleep timing and sleep hygiene.

Many wearable devices have incorporated oximetry into their metrics, and some claim to have accuracy that is better than hospital-grade oximeters. Many of these companies are no longer in business. Others specify higher accuracy in dark-skinned individuals (“CIRCUL Ring Pulse Oximeter in Dark-Pigmented Individuals: Clinical Study Validates Efficacy and Reliability,” Medical Device News Magazine, Feb. 26, 2021).

Despite these claims, they are registered as wellness devices with the FDA and are not diagnostic devices. Logically, if one of these devices demonstrates worrisome data, then it can prompt further clinical queries and, potentially, objective testing for obstructive sleep apnea (OSA). The reverse, however, cannot be claimed. A normal reading by CST does not obviate the need for objective testing if the clinical symptoms warrant it.

There are CSTs that have been created around very specific needs - such as jet lag- and provide guidance for how to quickly acclimate to the destination time zone by providing nudges for light exposure and timed melatonin or dark glasses (https://www.timeshifter.com/).

Others analyze the sleep space for extrinsic sounds (https://www.sleepcycle.com/), while a plethora of apps provides advice for how to optimize your sleep environment and wind-down routine. There is even a sleep robot designed to facilitate sleep onset (https://somnox.com/). This bean-shaped device is designed to “breathe” as you hold it, and the user is meant to emulate those same breathing patterns. It is a take on the 4-7-8 breathing pattern long endorsed by yogis.

Although validation data are lacking for the vast majority of CST, a recent study (www.ncbi.nlm.nih.gov/pmc/articles/PMC8120339/pdf/zsaa291.pdf).demonstrated that CST had high performance when compared with actigraphy in assessing sleep and wakefulness and, as such, may improve the evaluation of sleep and wake opportunities prior to MSLT or improve identification of circadian sleep-wake disorders. Many practices do not currently utilize actigraphy due to its expense and very limited potential for reimbursement. Using a patient’s sleep-tracking device may allow access to these data without financial outlay. While these data demonstrate the ability of CST to potentially differentiate sleep from wakefulness, it is notable that this study also found that the determination of individual sleep stages is less robust. In general, CST cannot identify an underlying sleep disorder, however, may raise awareness that a disorder might be present.

This leads to more reflection on the role of CST in a typical sleep clinic. Many years ago, discussion around this technology was primarily patient-initiated and often times met with skepticism on the part of the clinician. As technology has improved and has become more accessible, there appears to be more acceptance among our colleagues – not, perhaps, in terms of absolute actionable data, but rather as an opportunity to discuss sleep with our patients and to support their own efforts at improving their sleep. Trends in the data in response to CBT-I or medications can be observed. Abnormalities identified via CST often serve as the initial prompt for a clinical visit and, as such, should not be eschewed. Rather, reframing the use of this information while also addressing other sleep issues is likely to be the more appropriate path forward.

Assessing this information can be time-consuming, and best practice suggests establishing expectations around this process (J Clin Sleep Med 2018 May 15. doi: 10.5664/jcsm.7128).

Agreements can be made with patients that the data are reviewed in the context of a clinical visit rather than longitudinally as data are uploaded and then sent via messaging unless such an understanding has already been agreed upon. RPM billing codes may ultimately allow for reimbursement and recognition of this workload. At the present time, RPM billing is limited to FDA-cleared, prescription devices, and CST does not yet qualify.

There also needs to be recognition of potential harm from CST. Inevitably, some patients will develop orthosomnia, a term coined by Dr. Kelly Baron, where patients become so fixated on achieving perfect sleep scores that it contributes to insomnia. In this case, identification of orthosomnia is made via the clinical visit and patients are advised to stop tracking their sleep for a set period of time. This allows the anxiety around achieving “perfect sleep” to dissipate.

Google and the AASM recently announced a partnership. Essentially, the Google Nest Hub will serve to detect sleep concerns (such as timing of sleep, snoring, insufficient sleep, etc.) and will direct the user to educational resources such as www.sleepeducation.org. The idea behind this is that people are often unaware of an underlying sleep disorder such as OSA and don’t know what to search for. The Nest Hub uses information it collects and directs users to appropriate resources, thus obviating the need to know what to Google.

Clearly, big tech has invested heavily in our field. Between the copious wearables, nearables, and apps that are sleep-focused, these industry giants obviously believe that sleep is worthy of such a significant allocation of resources. This has improved the overall awareness of the importance of sleep and of identifying and treating sleep disorders. While these technologies are no replacement for a clinical evaluation, they can serve as patient engagement tools, as well as potentially large-scale OSA screening tools and may help us improve the percentage of patients with undiagnosed OSA, estimated to be 80% (Frost and Sullivan, “Hidden Health Crisis Costing America Billions,” American Academy of Sleep Medicine, 2016).

CST may allow us to better identify circadian sleep-wake disorders and evaluate sleep satiation prior to MLST that no longer requires investment in expensive actigraphy devices. They also allow us to partner with our patients by meeting them where they are and recognizing the efforts they have already made to improve their sleep before we even meet them.
 

Dr. Khosla is Medical Director, North Dakota Center for Sleep, Fargo, North Dakota.

Delirium is a frequent form of organ failure among the critically ill, impacting up to 80% of mechanically ventilated patients (Ely EW et al. JAMA. 2004;291[14]:1753-62). Its cardinal manifestations include disturbances in attention and cognition that occur acutely (e.g., hours to days) that are not better explained by another disease process (such as a toxidrome or dementia) (American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. 5th ed., 2013). Duration of delirium in the intensive care unit (ICU) is independently associated with poor outcomes, such as mortality and hospital length of stay, even when accounting for comorbidities, coma duration, sedative use, and severity of illness. Delirium during critical illness is an important bellwether for a patient’s clinical status, often serving as a harbinger for severe or worsening disease.

Over the last two decades, the critical care community has come to understand the importance of recognizing delirium, which is often underdiagnosed, as well as delirium prevention. In the ICU, several factors coalesce to form the perfect environment for the development of delirium. Patients often have preexisting comorbidities that predispose to delirium, such as preexisting cognitive impairment, and the severity of critical illness increases the risk of delirium further. There are also bedside factors, however, that are important for the intensivist to address, many of which are modifiable. These include routinely screening for delirium and assessing level of consciousness, implementing early mobility and rehabilitation, targeting light sedation, and avoiding deliriogenic medications such as benzodiazepines. These evidence-based care practices form the foundation of the 2018 Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU (i.e., PADIS guidelines), which aim to reduce delirium and iatrogenesis from critical care (Devlin JW et al. Crit Care Med. 2018;46[9]:e825-e873). The severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) pathogen that has caused the coronavirus disease 2019 (COVID-19) pandemic, however, has brought unprecedented challenges to critical care. One unfortunate side effect has been increased use of deep sedation and, thus, a greater incidence of delirium (Pun BT et al. Lancet Respir Med. 2021;9[3]:239-50). While the impact of the pandemic is unprecedented, thoughtful and careful sedation use remains vital to providing optimal care for the critically ill patient.
 

The link between sedation and delirium

The advent of modern mechanical ventilation brought critical care medicine into a period of rapid growth. Practices derived from the operating room, such as deep sedation and paralysis, became commonplace. Yet, starting in the late 1990s and early 2000s, evidence started growing regarding the impact of delirium and the unique aspects of the ICU that made it so prevalent. Delirium is strongly linked to inpatient mortality in mechanically ventilated adults, and it is best understood as an additional form of organ failure, much like other organ failures commonly recognized and treated by intensivists, such as respiratory or renal failure. Certain medications and sedation practices are associated with the development and duration of delirium. Benzodiazepines, a common sedative medication, are strongly linked to the development of delirium. In a study comparing commonly used sedative and analgesic agents, the use of lorazepam was associated with a greater risk of delirium the following day among critically ill, mechanically ventilated patients (Pandhariphande PP et al. Anesthesiology. 2006;104[1]:21-6). Given how commonly benzodiazepines are used and delirium develops in the ICU, this association has striking implications for clinical care and outcomes such as mortality. It is also significant, given that benzodiazepine use has increased during the pandemic, potentially creating significant downstream consequences. Benzodiazepines should be actively avoided when at all possible, given their propensity to lead to delirium, in accordance with the most recent guidelines.

Which sedation agent to choose?

While the negative effects of benzodiazepine-based sedation are well established, the optimal sedation agent remains unclear. Several other drugs are commonly used in the ICU, including propofol, dexmedetomidine, and opioid agents such as fentanyl and morphine. Propofol and dexmedetomidine are used specifically for their sedative properties, though they have dramatically different effects on the depth of sedation and different mechanisms of action. Opioid agents are most commonly used for their analgesic effect; however, in higher doses or combined with other medications, they have the secondary effect of inducing sedation. No particular sedation agent, however, beyond the avoidance of benzodiazepines has been recommended for use in the most recent guidelines. In the PRODEX and MIDEX studies, dexmedetomidine was noninferior to both midazolam and propofol in achieving targeted light to moderate sedation, and dexmedetomidine was associated with a shorter duration of mechanical ventilation compared to midazolam (Jakob SM et al. JAMA. 2012;307[11]:1151-60). More recently, the SPICE-III trial studied dexmedetomidine vs. usual care and found no difference in 90-day mortality (Shehabi Y et al. N Engl J Med. 2019;380[26]:2506-17).

In choosing the best sedation agent to avoid delirium, the largest and most applicable trial to date is the “Maximizing the Efficacy of Sedation and Reducing Neurological Dysfunction and Mortality in Septic Patients with Acute Respiratory Failure,” or MENDS2 trial (Hughes CG et al. N Engl J Med. 2021;384:1424-36). This study was a double-blind, multicenter randomized controlled trial of dexmedetomidine vs propofol in critically ill patients with sepsis receiving mechanical ventilation. The primary outcome was days alive without delirium or coma over the 14-day intervention period. The study enrolled 438 patients between 13 sites, with 422 patients receiving either dexmedetomidine or propofol. Hughes and colleagues found no difference in the primary outcome of days alive without delirium or coma between the dexmedetomidine and the propofol arms. The study also found no difference in secondary outcomes, including ventilator-free days, 90-day mortality, and 6-month global cognition, as well as no difference in safety endpoints. Importantly, there was excellent compliance with guideline-recommended practices of spontaneous awakening and breathing trials and early mobility, both of which are associated with reduced sedation exposure. The study did have some notable nuances, however. The overall doses of trial drugs were relatively low, and there was a moderate use of rescue sedation. There was also a small amount of crossover use of propofol and dexmedetomidine between treatment arms (10%), although the authors note that this was lower than in prior related studies. Overall, the MENDS2 study suggests there is likely clinical equipoise between propofol and dexmedetomidine in terms of delirium outcomes when combined with best practices, such targeted light sedation, paired awakening and breathing trials, and early mobility.
 

How should we manage sedation to prevent delirium?

Building off of the recent MENDS2 study and earlier work in the field, along with the 2018 PADIS guidelines, the general paradigm of sedation management should be focused on using light sedation with sedation interruptions to minimize overall sedation exposure. Based on the best available evidence to date, targeting less overall sedation leads to improved outcomes in critically ill patients, including mortality and duration of mechanical ventilation. Benzodiazepines should be avoided due to their association with delirium, but currently there is no evidence to suggest one nonbenzodiazepine sedative is better than another. Intensivists can feel comfortable choosing between agents based on a patient’s individual clinical needs, especially when patients are receiving paired spontaneous awakening and breathing trials and early rehabilitation. These same principles should be applied to sedation management and delirium patients in COVID-19 patients as well. While certain circumstances will necessitate deeper sedation at times (e.g., refractory hypoxemia due to ARDS from COVID-19), clinicians should continually reassess the actual sedation needs of the patient with the goal of reducing overall sedation. Focusing effort on these evidence-based practices will help reduce the incidence of delirium and ultimately improve patient outcomes.
 

Dr. Mart is with the Division of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center; Critical Illness, Brain Dysfunction, and Survivorship (CIBS) Center; and VA Tennessee Valley Healthcare System Geriatric Research Education and Clinical Center (GRECC), Nashville, Tennessee.

Delirium is a frequent form of organ failure among the critically ill, impacting up to 80% of mechanically ventilated patients (Ely EW et al. JAMA. 2004;291[14]:1753-62). Its cardinal manifestations include disturbances in attention and cognition that occur acutely (e.g., hours to days) that are not better explained by another disease process (such as a toxidrome or dementia) (American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. 5th ed., 2013). Duration of delirium in the intensive care unit (ICU) is independently associated with poor outcomes, such as mortality and hospital length of stay, even when accounting for comorbidities, coma duration, sedative use, and severity of illness. Delirium during critical illness is an important bellwether for a patient’s clinical status, often serving as a harbinger for severe or worsening disease.

Over the last two decades, the critical care community has come to understand the importance of recognizing delirium, which is often underdiagnosed, as well as delirium prevention. In the ICU, several factors coalesce to form the perfect environment for the development of delirium. Patients often have preexisting comorbidities that predispose to delirium, such as preexisting cognitive impairment, and the severity of critical illness increases the risk of delirium further. There are also bedside factors, however, that are important for the intensivist to address, many of which are modifiable. These include routinely screening for delirium and assessing level of consciousness, implementing early mobility and rehabilitation, targeting light sedation, and avoiding deliriogenic medications such as benzodiazepines. These evidence-based care practices form the foundation of the 2018 Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU (i.e., PADIS guidelines), which aim to reduce delirium and iatrogenesis from critical care (Devlin JW et al. Crit Care Med. 2018;46[9]:e825-e873). The severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) pathogen that has caused the coronavirus disease 2019 (COVID-19) pandemic, however, has brought unprecedented challenges to critical care. One unfortunate side effect has been increased use of deep sedation and, thus, a greater incidence of delirium (Pun BT et al. Lancet Respir Med. 2021;9[3]:239-50). While the impact of the pandemic is unprecedented, thoughtful and careful sedation use remains vital to providing optimal care for the critically ill patient.
 

The link between sedation and delirium

The advent of modern mechanical ventilation brought critical care medicine into a period of rapid growth. Practices derived from the operating room, such as deep sedation and paralysis, became commonplace. Yet, starting in the late 1990s and early 2000s, evidence started growing regarding the impact of delirium and the unique aspects of the ICU that made it so prevalent. Delirium is strongly linked to inpatient mortality in mechanically ventilated adults, and it is best understood as an additional form of organ failure, much like other organ failures commonly recognized and treated by intensivists, such as respiratory or renal failure. Certain medications and sedation practices are associated with the development and duration of delirium. Benzodiazepines, a common sedative medication, are strongly linked to the development of delirium. In a study comparing commonly used sedative and analgesic agents, the use of lorazepam was associated with a greater risk of delirium the following day among critically ill, mechanically ventilated patients (Pandhariphande PP et al. Anesthesiology. 2006;104[1]:21-6). Given how commonly benzodiazepines are used and delirium develops in the ICU, this association has striking implications for clinical care and outcomes such as mortality. It is also significant, given that benzodiazepine use has increased during the pandemic, potentially creating significant downstream consequences. Benzodiazepines should be actively avoided when at all possible, given their propensity to lead to delirium, in accordance with the most recent guidelines.

Which sedation agent to choose?

While the negative effects of benzodiazepine-based sedation are well established, the optimal sedation agent remains unclear. Several other drugs are commonly used in the ICU, including propofol, dexmedetomidine, and opioid agents such as fentanyl and morphine. Propofol and dexmedetomidine are used specifically for their sedative properties, though they have dramatically different effects on the depth of sedation and different mechanisms of action. Opioid agents are most commonly used for their analgesic effect; however, in higher doses or combined with other medications, they have the secondary effect of inducing sedation. No particular sedation agent, however, beyond the avoidance of benzodiazepines has been recommended for use in the most recent guidelines. In the PRODEX and MIDEX studies, dexmedetomidine was noninferior to both midazolam and propofol in achieving targeted light to moderate sedation, and dexmedetomidine was associated with a shorter duration of mechanical ventilation compared to midazolam (Jakob SM et al. JAMA. 2012;307[11]:1151-60). More recently, the SPICE-III trial studied dexmedetomidine vs. usual care and found no difference in 90-day mortality (Shehabi Y et al. N Engl J Med. 2019;380[26]:2506-17).

In choosing the best sedation agent to avoid delirium, the largest and most applicable trial to date is the “Maximizing the Efficacy of Sedation and Reducing Neurological Dysfunction and Mortality in Septic Patients with Acute Respiratory Failure,” or MENDS2 trial (Hughes CG et al. N Engl J Med. 2021;384:1424-36). This study was a double-blind, multicenter randomized controlled trial of dexmedetomidine vs propofol in critically ill patients with sepsis receiving mechanical ventilation. The primary outcome was days alive without delirium or coma over the 14-day intervention period. The study enrolled 438 patients between 13 sites, with 422 patients receiving either dexmedetomidine or propofol. Hughes and colleagues found no difference in the primary outcome of days alive without delirium or coma between the dexmedetomidine and the propofol arms. The study also found no difference in secondary outcomes, including ventilator-free days, 90-day mortality, and 6-month global cognition, as well as no difference in safety endpoints. Importantly, there was excellent compliance with guideline-recommended practices of spontaneous awakening and breathing trials and early mobility, both of which are associated with reduced sedation exposure. The study did have some notable nuances, however. The overall doses of trial drugs were relatively low, and there was a moderate use of rescue sedation. There was also a small amount of crossover use of propofol and dexmedetomidine between treatment arms (10%), although the authors note that this was lower than in prior related studies. Overall, the MENDS2 study suggests there is likely clinical equipoise between propofol and dexmedetomidine in terms of delirium outcomes when combined with best practices, such targeted light sedation, paired awakening and breathing trials, and early mobility.
 

How should we manage sedation to prevent delirium?

Building off of the recent MENDS2 study and earlier work in the field, along with the 2018 PADIS guidelines, the general paradigm of sedation management should be focused on using light sedation with sedation interruptions to minimize overall sedation exposure. Based on the best available evidence to date, targeting less overall sedation leads to improved outcomes in critically ill patients, including mortality and duration of mechanical ventilation. Benzodiazepines should be avoided due to their association with delirium, but currently there is no evidence to suggest one nonbenzodiazepine sedative is better than another. Intensivists can feel comfortable choosing between agents based on a patient’s individual clinical needs, especially when patients are receiving paired spontaneous awakening and breathing trials and early rehabilitation. These same principles should be applied to sedation management and delirium patients in COVID-19 patients as well. While certain circumstances will necessitate deeper sedation at times (e.g., refractory hypoxemia due to ARDS from COVID-19), clinicians should continually reassess the actual sedation needs of the patient with the goal of reducing overall sedation. Focusing effort on these evidence-based practices will help reduce the incidence of delirium and ultimately improve patient outcomes.
 

Dr. Mart is with the Division of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center; Critical Illness, Brain Dysfunction, and Survivorship (CIBS) Center; and VA Tennessee Valley Healthcare System Geriatric Research Education and Clinical Center (GRECC), Nashville, Tennessee.

Delirium is a frequent form of organ failure among the critically ill, impacting up to 80% of mechanically ventilated patients (Ely EW et al. JAMA. 2004;291[14]:1753-62). Its cardinal manifestations include disturbances in attention and cognition that occur acutely (e.g., hours to days) that are not better explained by another disease process (such as a toxidrome or dementia) (American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. 5th ed., 2013). Duration of delirium in the intensive care unit (ICU) is independently associated with poor outcomes, such as mortality and hospital length of stay, even when accounting for comorbidities, coma duration, sedative use, and severity of illness. Delirium during critical illness is an important bellwether for a patient’s clinical status, often serving as a harbinger for severe or worsening disease.

Over the last two decades, the critical care community has come to understand the importance of recognizing delirium, which is often underdiagnosed, as well as delirium prevention. In the ICU, several factors coalesce to form the perfect environment for the development of delirium. Patients often have preexisting comorbidities that predispose to delirium, such as preexisting cognitive impairment, and the severity of critical illness increases the risk of delirium further. There are also bedside factors, however, that are important for the intensivist to address, many of which are modifiable. These include routinely screening for delirium and assessing level of consciousness, implementing early mobility and rehabilitation, targeting light sedation, and avoiding deliriogenic medications such as benzodiazepines. These evidence-based care practices form the foundation of the 2018 Clinical Practice Guidelines for the Prevention and Management of Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU (i.e., PADIS guidelines), which aim to reduce delirium and iatrogenesis from critical care (Devlin JW et al. Crit Care Med. 2018;46[9]:e825-e873). The severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) pathogen that has caused the coronavirus disease 2019 (COVID-19) pandemic, however, has brought unprecedented challenges to critical care. One unfortunate side effect has been increased use of deep sedation and, thus, a greater incidence of delirium (Pun BT et al. Lancet Respir Med. 2021;9[3]:239-50). While the impact of the pandemic is unprecedented, thoughtful and careful sedation use remains vital to providing optimal care for the critically ill patient.
 

The link between sedation and delirium

The advent of modern mechanical ventilation brought critical care medicine into a period of rapid growth. Practices derived from the operating room, such as deep sedation and paralysis, became commonplace. Yet, starting in the late 1990s and early 2000s, evidence started growing regarding the impact of delirium and the unique aspects of the ICU that made it so prevalent. Delirium is strongly linked to inpatient mortality in mechanically ventilated adults, and it is best understood as an additional form of organ failure, much like other organ failures commonly recognized and treated by intensivists, such as respiratory or renal failure. Certain medications and sedation practices are associated with the development and duration of delirium. Benzodiazepines, a common sedative medication, are strongly linked to the development of delirium. In a study comparing commonly used sedative and analgesic agents, the use of lorazepam was associated with a greater risk of delirium the following day among critically ill, mechanically ventilated patients (Pandhariphande PP et al. Anesthesiology. 2006;104[1]:21-6). Given how commonly benzodiazepines are used and delirium develops in the ICU, this association has striking implications for clinical care and outcomes such as mortality. It is also significant, given that benzodiazepine use has increased during the pandemic, potentially creating significant downstream consequences. Benzodiazepines should be actively avoided when at all possible, given their propensity to lead to delirium, in accordance with the most recent guidelines.

Which sedation agent to choose?

While the negative effects of benzodiazepine-based sedation are well established, the optimal sedation agent remains unclear. Several other drugs are commonly used in the ICU, including propofol, dexmedetomidine, and opioid agents such as fentanyl and morphine. Propofol and dexmedetomidine are used specifically for their sedative properties, though they have dramatically different effects on the depth of sedation and different mechanisms of action. Opioid agents are most commonly used for their analgesic effect; however, in higher doses or combined with other medications, they have the secondary effect of inducing sedation. No particular sedation agent, however, beyond the avoidance of benzodiazepines has been recommended for use in the most recent guidelines. In the PRODEX and MIDEX studies, dexmedetomidine was noninferior to both midazolam and propofol in achieving targeted light to moderate sedation, and dexmedetomidine was associated with a shorter duration of mechanical ventilation compared to midazolam (Jakob SM et al. JAMA. 2012;307[11]:1151-60). More recently, the SPICE-III trial studied dexmedetomidine vs. usual care and found no difference in 90-day mortality (Shehabi Y et al. N Engl J Med. 2019;380[26]:2506-17).

In choosing the best sedation agent to avoid delirium, the largest and most applicable trial to date is the “Maximizing the Efficacy of Sedation and Reducing Neurological Dysfunction and Mortality in Septic Patients with Acute Respiratory Failure,” or MENDS2 trial (Hughes CG et al. N Engl J Med. 2021;384:1424-36). This study was a double-blind, multicenter randomized controlled trial of dexmedetomidine vs propofol in critically ill patients with sepsis receiving mechanical ventilation. The primary outcome was days alive without delirium or coma over the 14-day intervention period. The study enrolled 438 patients between 13 sites, with 422 patients receiving either dexmedetomidine or propofol. Hughes and colleagues found no difference in the primary outcome of days alive without delirium or coma between the dexmedetomidine and the propofol arms. The study also found no difference in secondary outcomes, including ventilator-free days, 90-day mortality, and 6-month global cognition, as well as no difference in safety endpoints. Importantly, there was excellent compliance with guideline-recommended practices of spontaneous awakening and breathing trials and early mobility, both of which are associated with reduced sedation exposure. The study did have some notable nuances, however. The overall doses of trial drugs were relatively low, and there was a moderate use of rescue sedation. There was also a small amount of crossover use of propofol and dexmedetomidine between treatment arms (10%), although the authors note that this was lower than in prior related studies. Overall, the MENDS2 study suggests there is likely clinical equipoise between propofol and dexmedetomidine in terms of delirium outcomes when combined with best practices, such targeted light sedation, paired awakening and breathing trials, and early mobility.
 

How should we manage sedation to prevent delirium?

Building off of the recent MENDS2 study and earlier work in the field, along with the 2018 PADIS guidelines, the general paradigm of sedation management should be focused on using light sedation with sedation interruptions to minimize overall sedation exposure. Based on the best available evidence to date, targeting less overall sedation leads to improved outcomes in critically ill patients, including mortality and duration of mechanical ventilation. Benzodiazepines should be avoided due to their association with delirium, but currently there is no evidence to suggest one nonbenzodiazepine sedative is better than another. Intensivists can feel comfortable choosing between agents based on a patient’s individual clinical needs, especially when patients are receiving paired spontaneous awakening and breathing trials and early rehabilitation. These same principles should be applied to sedation management and delirium patients in COVID-19 patients as well. While certain circumstances will necessitate deeper sedation at times (e.g., refractory hypoxemia due to ARDS from COVID-19), clinicians should continually reassess the actual sedation needs of the patient with the goal of reducing overall sedation. Focusing effort on these evidence-based practices will help reduce the incidence of delirium and ultimately improve patient outcomes.
 

Dr. Mart is with the Division of Allergy, Pulmonary, and Critical Care Medicine, Vanderbilt University Medical Center; Critical Illness, Brain Dysfunction, and Survivorship (CIBS) Center; and VA Tennessee Valley Healthcare System Geriatric Research Education and Clinical Center (GRECC), Nashville, Tennessee.

As of 2019, lung cancer remained the leading cause of cancer death in the United States. In March 2021, the USPSTF updated the guidelines for lung cancer screening, increasing the number of eligible patients in order to identify malignancies in the early stages when more treatment options exist. With the growth of lung cancer screening, increasingly smaller pulmonary nodules are being identified in more peripheral locations previously thought to be unreachable with bronchoscopy. While bronchoscopy has been utilized for over a century for therapeutic interventions, the development of the fiberoptic bronchoscope in 1967 ushered in an era of evolving diagnostic functions. From the initial endobronchial and transbronchial biopsy techniques, to the introduction of endobronchial ultrasound, and now the latest navigational and robotic modalities, these advances have opened a new realm of interventions available in our diagnostic approach to lung cancer.

Bronchoscopy has become essential in the diagnosis of thoracic malignancies, providing both diagnostic and staging information in one procedural setting. By first assessing the mediastinal and hilar lymph nodes with endobronchial ultrasound and transbronchial needle aspiration, involved lymph nodes can give both diagnosis and staging information required to guide treatment. This is particularly important in the case of non-small cell lung cancer, which utilizes the TNM staging system. Through the use of convex probe endobronchial ultrasound (CP-EBUS), combined with rapid on-site evaluation (ROSE) by pathologic condition, we can more accurately target the individual lymph nodes for biopsy without the need for any additional procedures that are often more complex and invasive, such as mediastinoscopy. It is important to note the role of CP-EBUS extends beyond the lymph node assessment and can also be utilized for the evaluation of other mediastinal lesions, such as central parenchymal masses. These would otherwise be difficult to access due to the lack of a clear airway to the lesion (Argento and Puchalski. Respir Med. 2016;116:55-8).

While EBUS has improved the sampling of lymph nodes, advanced imaging technologies and subsequent increases in lung cancer screening have increased the number of lung malignancies identified in earlier stages before extension to the lymph nodes occurs. This scenario requires a direct biopsy of the primary nodule or lung mass. While CP-EBUS can be utilized for some central parenchymal lesions, peripheral nodules pose a greater challenge to the bronchoscopist as they cannot be directly visualized with the conventional bronchoscope. These lesions are amenable to traditional sampling techniques such as bronchial brushings and washings in addition to transbronchial needle aspiration and transbronchial biopsy. However, the yield for peripheral lesions is less than that for central tumors and depends on lesion size, distance from hilum, spatial positioning from bronchus, and operator experience. To help localize peripheral lesions, a separate form of endobronchial ultrasound is available that can be used in combination with fluoroscopy to target a lesion. Radial probe endobronchial ultrasound (RP-EBUS) utilizes a rotating ultrasound transducer that can be advanced either through the working channel of the bronchoscope or through a guide sheath to extend to airways beyond what the conventional bronchoscope can reach. This assists the bronchoscopist with locating the correct airway and, therefore, increases the yield of sampling techniques. The use of RP-EBUS has reported diagnostic yields of almost 85% if the ultrasound is located within the lesion, but less than 50% if adjacent to the lesion (Chen et al. Ann Am Thorac Soc. 2014;11[4]:578-82). While this improves the yield beyond that achieved with conventional bronchoscopy alone, it continues to challenge the bronchoscopist to locate an accessible airway from a series of branching bronchi that are beyond the level of direct visualization.

Due to the historical difficulty in accurately reaching peripheral lesions, alternative technologies for sampling these lesions, such as image-guided biopsies or surgical resection, were employed. While CT scan-guided biopsies traditionally have high diagnostic yields, they also carry a higher rate of complications, including pneumothorax and bleeding. This has led to a significant increase over the past 2 decades in new bronchoscopic technologies targeting safer and more accurate sampling of increasingly smaller, peripheral lesions.

Traditionally, any new technologies created were intended to be used alongside flexible fiberoptic bronchoscopy. The more recently introduced technologies, however, aim to provide a safer, more accurate procedure through virtual bronchoscopy. By obtaining CT scan images prior to the procedure, a 3D visualization is constructed of the tracheobronchial tree, allowing for directed guidance of endobronchial accessories to more distal airways. Where the bronchoscopist was previously limited in navigating the bronchial tree to the subsegmental bronchi, virtual bronchoscopy can depict the airways up to the 7th order subdivision. This is a significant improvement in airway visualization – however, only when partnered with guidance technologies can the model be accurately navigated.

One modality that is often coupled with virtual bronchoscopy to accurately reach peripheral lesions is electromagnetic navigation bronchoscopy (ENB). Multiple ENB software systems have been created and continue to be highly utilized by bronchoscopists to target peripheral lesions, as it has often been likened to a GPS for the lungs. With the addition of specific hardware components, a magnetic field is created around the patient where the sensor position can be elicited to within 1-mm accuracy. When overlaid with the CT scan images, the bronchoscopist can have real-time positioning of the probe in all three planes and guide the necessary sampling tools to the lesion of interest. The reported yields for ENB vary but have been shown to increase in the presence of specific image findings such as a positive bronchus sign – an air-filled bronchus leading into the lesion. The presence of this finding can increase the yield up to almost 75% from just under 50% in the absence of a positive bronchus sign. (Ali et al. Ann Am Thorac Soc. 2018;15[8]:978-87). However, regardless of this finding, the overall diagnostic yields for ENB continue to fall below that seen with other image-guided biopsy techniques. The procedural complications, however, are significantly less and, therefore, many physicians continue to advocate for ENB as the initial procedure in attempt to decrease risk for the patient.

The newest technology to be introduced to target peripheral lung lesions and to improve upon the shortcomings of other techniques is robotic-assisted bronchoscopy. While surgical specialties have seen success with robotic techniques over many years, the first robotic bronchoscopy system was not introduced until 2018. At present, there are two systems available: the Monarch^® system by Auris Health and the Ion Endoluminal^® System by Intuitive Surgical. These systems allow for increased bronchoscope stability, improved visualization, adjustable angulation of biopsy tools, and an improved ability to make even subtle turns in the airways. Early studies on both systems were cadaver based, but an increasing number of patient trials are now being reported or actively enrolling. Both systems have shown high rates of lesion localization, greater than 85%, with varying diagnostic yields from 69-79%. Some cadaver studies that utilized artificial tumors reported higher diagnostic yields – over 90% – but this was not seen in initial patient-based studies. (Agrawal et al. J Thorac Dis. 2020;12[6]:3279-86) More data related to the robotic-assisted bronchoscopy systems can be expected in the future as more experience is gained, but initial results are promising in the system’s ability to diagnose early lung cancers safely and accurately.

With increasing technologies and equipment available, bronchoscopy has quickly become an essential step in the diagnosis of lung cancer. While other techniques exist beyond those described here, these are some of the more widely used options currently available. It is not possible at this time to define one technology as the best tool for the diagnosis of lung cancer, as patient factors will always have to be taken into consideration to ensure safety and accuracy. However, with constantly changing technologies, the bronchoscopist now has a variety of tools available to help target previously “unreachable” lesions as we aim to decrease the historically high mortality rates of lung cancer.

Dr. Jewani and Dr. Johnson are from Loyola University Medical Center, Department of Pulmonary and Critical Care Medicine, Maywood, Illinois.


1. Agrawal, Abhinav et al. “Robotic bronchoscopy for pulmonary lesions: a review of existing technologies and clinical data.” Journal of thoracic disease vol. 12,6 (2020): 3279-3286. doi:10.21037/jtd.2020.03.35

2. Ali MS, Sethi J, Taneja A, Musani A, Maldonado F. Computed Tomography Bronchus Sign and the Diagnostic Yield of Guided Bronchoscopy for Peripheral Pulmonary Lesions. A Systematic Review and Meta-Analysis. Ann Am Thorac Soc. 2018 Aug;15(8):978-987. doi: 10.1513/AnnalsATS.201711-856OC. PMID: 29877715.

3. Argento AC, Puchalski J. Convex probe EBUS for centrally located parenchymal lesions without a bronchus sign. Respir Med. 2016 Jul;116:55-8. doi: 10.1016/j.rmed.2016.04.012. Epub 2016 Apr 29. PMID: 27296821.

4. Chen A, Chenna P, Loiselle A, Massoni J, Mayse M, Misselhorn D. Radial probe endobronchial ultrasound for peripheral pulmonary lesions. A 5-year institutional experience. Ann Am Thorac Soc. 2014 May;11(4):578-82. doi: 10.1513/AnnalsATS.201311-384OC. PMID: 24635641.
 

As of 2019, lung cancer remained the leading cause of cancer death in the United States. In March 2021, the USPSTF updated the guidelines for lung cancer screening, increasing the number of eligible patients in order to identify malignancies in the early stages when more treatment options exist. With the growth of lung cancer screening, increasingly smaller pulmonary nodules are being identified in more peripheral locations previously thought to be unreachable with bronchoscopy. While bronchoscopy has been utilized for over a century for therapeutic interventions, the development of the fiberoptic bronchoscope in 1967 ushered in an era of evolving diagnostic functions. From the initial endobronchial and transbronchial biopsy techniques, to the introduction of endobronchial ultrasound, and now the latest navigational and robotic modalities, these advances have opened a new realm of interventions available in our diagnostic approach to lung cancer.

Bronchoscopy has become essential in the diagnosis of thoracic malignancies, providing both diagnostic and staging information in one procedural setting. By first assessing the mediastinal and hilar lymph nodes with endobronchial ultrasound and transbronchial needle aspiration, involved lymph nodes can give both diagnosis and staging information required to guide treatment. This is particularly important in the case of non-small cell lung cancer, which utilizes the TNM staging system. Through the use of convex probe endobronchial ultrasound (CP-EBUS), combined with rapid on-site evaluation (ROSE) by pathologic condition, we can more accurately target the individual lymph nodes for biopsy without the need for any additional procedures that are often more complex and invasive, such as mediastinoscopy. It is important to note the role of CP-EBUS extends beyond the lymph node assessment and can also be utilized for the evaluation of other mediastinal lesions, such as central parenchymal masses. These would otherwise be difficult to access due to the lack of a clear airway to the lesion (Argento and Puchalski. Respir Med. 2016;116:55-8).

While EBUS has improved the sampling of lymph nodes, advanced imaging technologies and subsequent increases in lung cancer screening have increased the number of lung malignancies identified in earlier stages before extension to the lymph nodes occurs. This scenario requires a direct biopsy of the primary nodule or lung mass. While CP-EBUS can be utilized for some central parenchymal lesions, peripheral nodules pose a greater challenge to the bronchoscopist as they cannot be directly visualized with the conventional bronchoscope. These lesions are amenable to traditional sampling techniques such as bronchial brushings and washings in addition to transbronchial needle aspiration and transbronchial biopsy. However, the yield for peripheral lesions is less than that for central tumors and depends on lesion size, distance from hilum, spatial positioning from bronchus, and operator experience. To help localize peripheral lesions, a separate form of endobronchial ultrasound is available that can be used in combination with fluoroscopy to target a lesion. Radial probe endobronchial ultrasound (RP-EBUS) utilizes a rotating ultrasound transducer that can be advanced either through the working channel of the bronchoscope or through a guide sheath to extend to airways beyond what the conventional bronchoscope can reach. This assists the bronchoscopist with locating the correct airway and, therefore, increases the yield of sampling techniques. The use of RP-EBUS has reported diagnostic yields of almost 85% if the ultrasound is located within the lesion, but less than 50% if adjacent to the lesion (Chen et al. Ann Am Thorac Soc. 2014;11[4]:578-82). While this improves the yield beyond that achieved with conventional bronchoscopy alone, it continues to challenge the bronchoscopist to locate an accessible airway from a series of branching bronchi that are beyond the level of direct visualization.

Due to the historical difficulty in accurately reaching peripheral lesions, alternative technologies for sampling these lesions, such as image-guided biopsies or surgical resection, were employed. While CT scan-guided biopsies traditionally have high diagnostic yields, they also carry a higher rate of complications, including pneumothorax and bleeding. This has led to a significant increase over the past 2 decades in new bronchoscopic technologies targeting safer and more accurate sampling of increasingly smaller, peripheral lesions.

Traditionally, any new technologies created were intended to be used alongside flexible fiberoptic bronchoscopy. The more recently introduced technologies, however, aim to provide a safer, more accurate procedure through virtual bronchoscopy. By obtaining CT scan images prior to the procedure, a 3D visualization is constructed of the tracheobronchial tree, allowing for directed guidance of endobronchial accessories to more distal airways. Where the bronchoscopist was previously limited in navigating the bronchial tree to the subsegmental bronchi, virtual bronchoscopy can depict the airways up to the 7th order subdivision. This is a significant improvement in airway visualization – however, only when partnered with guidance technologies can the model be accurately navigated.

One modality that is often coupled with virtual bronchoscopy to accurately reach peripheral lesions is electromagnetic navigation bronchoscopy (ENB). Multiple ENB software systems have been created and continue to be highly utilized by bronchoscopists to target peripheral lesions, as it has often been likened to a GPS for the lungs. With the addition of specific hardware components, a magnetic field is created around the patient where the sensor position can be elicited to within 1-mm accuracy. When overlaid with the CT scan images, the bronchoscopist can have real-time positioning of the probe in all three planes and guide the necessary sampling tools to the lesion of interest. The reported yields for ENB vary but have been shown to increase in the presence of specific image findings such as a positive bronchus sign – an air-filled bronchus leading into the lesion. The presence of this finding can increase the yield up to almost 75% from just under 50% in the absence of a positive bronchus sign. (Ali et al. Ann Am Thorac Soc. 2018;15[8]:978-87). However, regardless of this finding, the overall diagnostic yields for ENB continue to fall below that seen with other image-guided biopsy techniques. The procedural complications, however, are significantly less and, therefore, many physicians continue to advocate for ENB as the initial procedure in attempt to decrease risk for the patient.

The newest technology to be introduced to target peripheral lung lesions and to improve upon the shortcomings of other techniques is robotic-assisted bronchoscopy. While surgical specialties have seen success with robotic techniques over many years, the first robotic bronchoscopy system was not introduced until 2018. At present, there are two systems available: the Monarch^® system by Auris Health and the Ion Endoluminal^® System by Intuitive Surgical. These systems allow for increased bronchoscope stability, improved visualization, adjustable angulation of biopsy tools, and an improved ability to make even subtle turns in the airways. Early studies on both systems were cadaver based, but an increasing number of patient trials are now being reported or actively enrolling. Both systems have shown high rates of lesion localization, greater than 85%, with varying diagnostic yields from 69-79%. Some cadaver studies that utilized artificial tumors reported higher diagnostic yields – over 90% – but this was not seen in initial patient-based studies. (Agrawal et al. J Thorac Dis. 2020;12[6]:3279-86) More data related to the robotic-assisted bronchoscopy systems can be expected in the future as more experience is gained, but initial results are promising in the system’s ability to diagnose early lung cancers safely and accurately.

With increasing technologies and equipment available, bronchoscopy has quickly become an essential step in the diagnosis of lung cancer. While other techniques exist beyond those described here, these are some of the more widely used options currently available. It is not possible at this time to define one technology as the best tool for the diagnosis of lung cancer, as patient factors will always have to be taken into consideration to ensure safety and accuracy. However, with constantly changing technologies, the bronchoscopist now has a variety of tools available to help target previously “unreachable” lesions as we aim to decrease the historically high mortality rates of lung cancer.

Dr. Jewani and Dr. Johnson are from Loyola University Medical Center, Department of Pulmonary and Critical Care Medicine, Maywood, Illinois.


1. Agrawal, Abhinav et al. “Robotic bronchoscopy for pulmonary lesions: a review of existing technologies and clinical data.” Journal of thoracic disease vol. 12,6 (2020): 3279-3286. doi:10.21037/jtd.2020.03.35

2. Ali MS, Sethi J, Taneja A, Musani A, Maldonado F. Computed Tomography Bronchus Sign and the Diagnostic Yield of Guided Bronchoscopy for Peripheral Pulmonary Lesions. A Systematic Review and Meta-Analysis. Ann Am Thorac Soc. 2018 Aug;15(8):978-987. doi: 10.1513/AnnalsATS.201711-856OC. PMID: 29877715.

3. Argento AC, Puchalski J. Convex probe EBUS for centrally located parenchymal lesions without a bronchus sign. Respir Med. 2016 Jul;116:55-8. doi: 10.1016/j.rmed.2016.04.012. Epub 2016 Apr 29. PMID: 27296821.

4. Chen A, Chenna P, Loiselle A, Massoni J, Mayse M, Misselhorn D. Radial probe endobronchial ultrasound for peripheral pulmonary lesions. A 5-year institutional experience. Ann Am Thorac Soc. 2014 May;11(4):578-82. doi: 10.1513/AnnalsATS.201311-384OC. PMID: 24635641.
 

As of 2019, lung cancer remained the leading cause of cancer death in the United States. In March 2021, the USPSTF updated the guidelines for lung cancer screening, increasing the number of eligible patients in order to identify malignancies in the early stages when more treatment options exist. With the growth of lung cancer screening, increasingly smaller pulmonary nodules are being identified in more peripheral locations previously thought to be unreachable with bronchoscopy. While bronchoscopy has been utilized for over a century for therapeutic interventions, the development of the fiberoptic bronchoscope in 1967 ushered in an era of evolving diagnostic functions. From the initial endobronchial and transbronchial biopsy techniques, to the introduction of endobronchial ultrasound, and now the latest navigational and robotic modalities, these advances have opened a new realm of interventions available in our diagnostic approach to lung cancer.

Bronchoscopy has become essential in the diagnosis of thoracic malignancies, providing both diagnostic and staging information in one procedural setting. By first assessing the mediastinal and hilar lymph nodes with endobronchial ultrasound and transbronchial needle aspiration, involved lymph nodes can give both diagnosis and staging information required to guide treatment. This is particularly important in the case of non-small cell lung cancer, which utilizes the TNM staging system. Through the use of convex probe endobronchial ultrasound (CP-EBUS), combined with rapid on-site evaluation (ROSE) by pathologic condition, we can more accurately target the individual lymph nodes for biopsy without the need for any additional procedures that are often more complex and invasive, such as mediastinoscopy. It is important to note the role of CP-EBUS extends beyond the lymph node assessment and can also be utilized for the evaluation of other mediastinal lesions, such as central parenchymal masses. These would otherwise be difficult to access due to the lack of a clear airway to the lesion (Argento and Puchalski. Respir Med. 2016;116:55-8).

While EBUS has improved the sampling of lymph nodes, advanced imaging technologies and subsequent increases in lung cancer screening have increased the number of lung malignancies identified in earlier stages before extension to the lymph nodes occurs. This scenario requires a direct biopsy of the primary nodule or lung mass. While CP-EBUS can be utilized for some central parenchymal lesions, peripheral nodules pose a greater challenge to the bronchoscopist as they cannot be directly visualized with the conventional bronchoscope. These lesions are amenable to traditional sampling techniques such as bronchial brushings and washings in addition to transbronchial needle aspiration and transbronchial biopsy. However, the yield for peripheral lesions is less than that for central tumors and depends on lesion size, distance from hilum, spatial positioning from bronchus, and operator experience. To help localize peripheral lesions, a separate form of endobronchial ultrasound is available that can be used in combination with fluoroscopy to target a lesion. Radial probe endobronchial ultrasound (RP-EBUS) utilizes a rotating ultrasound transducer that can be advanced either through the working channel of the bronchoscope or through a guide sheath to extend to airways beyond what the conventional bronchoscope can reach. This assists the bronchoscopist with locating the correct airway and, therefore, increases the yield of sampling techniques. The use of RP-EBUS has reported diagnostic yields of almost 85% if the ultrasound is located within the lesion, but less than 50% if adjacent to the lesion (Chen et al. Ann Am Thorac Soc. 2014;11[4]:578-82). While this improves the yield beyond that achieved with conventional bronchoscopy alone, it continues to challenge the bronchoscopist to locate an accessible airway from a series of branching bronchi that are beyond the level of direct visualization.

Due to the historical difficulty in accurately reaching peripheral lesions, alternative technologies for sampling these lesions, such as image-guided biopsies or surgical resection, were employed. While CT scan-guided biopsies traditionally have high diagnostic yields, they also carry a higher rate of complications, including pneumothorax and bleeding. This has led to a significant increase over the past 2 decades in new bronchoscopic technologies targeting safer and more accurate sampling of increasingly smaller, peripheral lesions.

Traditionally, any new technologies created were intended to be used alongside flexible fiberoptic bronchoscopy. The more recently introduced technologies, however, aim to provide a safer, more accurate procedure through virtual bronchoscopy. By obtaining CT scan images prior to the procedure, a 3D visualization is constructed of the tracheobronchial tree, allowing for directed guidance of endobronchial accessories to more distal airways. Where the bronchoscopist was previously limited in navigating the bronchial tree to the subsegmental bronchi, virtual bronchoscopy can depict the airways up to the 7th order subdivision. This is a significant improvement in airway visualization – however, only when partnered with guidance technologies can the model be accurately navigated.

One modality that is often coupled with virtual bronchoscopy to accurately reach peripheral lesions is electromagnetic navigation bronchoscopy (ENB). Multiple ENB software systems have been created and continue to be highly utilized by bronchoscopists to target peripheral lesions, as it has often been likened to a GPS for the lungs. With the addition of specific hardware components, a magnetic field is created around the patient where the sensor position can be elicited to within 1-mm accuracy. When overlaid with the CT scan images, the bronchoscopist can have real-time positioning of the probe in all three planes and guide the necessary sampling tools to the lesion of interest. The reported yields for ENB vary but have been shown to increase in the presence of specific image findings such as a positive bronchus sign – an air-filled bronchus leading into the lesion. The presence of this finding can increase the yield up to almost 75% from just under 50% in the absence of a positive bronchus sign. (Ali et al. Ann Am Thorac Soc. 2018;15[8]:978-87). However, regardless of this finding, the overall diagnostic yields for ENB continue to fall below that seen with other image-guided biopsy techniques. The procedural complications, however, are significantly less and, therefore, many physicians continue to advocate for ENB as the initial procedure in attempt to decrease risk for the patient.

The newest technology to be introduced to target peripheral lung lesions and to improve upon the shortcomings of other techniques is robotic-assisted bronchoscopy. While surgical specialties have seen success with robotic techniques over many years, the first robotic bronchoscopy system was not introduced until 2018. At present, there are two systems available: the Monarch^® system by Auris Health and the Ion Endoluminal^® System by Intuitive Surgical. These systems allow for increased bronchoscope stability, improved visualization, adjustable angulation of biopsy tools, and an improved ability to make even subtle turns in the airways. Early studies on both systems were cadaver based, but an increasing number of patient trials are now being reported or actively enrolling. Both systems have shown high rates of lesion localization, greater than 85%, with varying diagnostic yields from 69-79%. Some cadaver studies that utilized artificial tumors reported higher diagnostic yields – over 90% – but this was not seen in initial patient-based studies. (Agrawal et al. J Thorac Dis. 2020;12[6]:3279-86) More data related to the robotic-assisted bronchoscopy systems can be expected in the future as more experience is gained, but initial results are promising in the system’s ability to diagnose early lung cancers safely and accurately.

With increasing technologies and equipment available, bronchoscopy has quickly become an essential step in the diagnosis of lung cancer. While other techniques exist beyond those described here, these are some of the more widely used options currently available. It is not possible at this time to define one technology as the best tool for the diagnosis of lung cancer, as patient factors will always have to be taken into consideration to ensure safety and accuracy. However, with constantly changing technologies, the bronchoscopist now has a variety of tools available to help target previously “unreachable” lesions as we aim to decrease the historically high mortality rates of lung cancer.

Dr. Jewani and Dr. Johnson are from Loyola University Medical Center, Department of Pulmonary and Critical Care Medicine, Maywood, Illinois.


1. Agrawal, Abhinav et al. “Robotic bronchoscopy for pulmonary lesions: a review of existing technologies and clinical data.” Journal of thoracic disease vol. 12,6 (2020): 3279-3286. doi:10.21037/jtd.2020.03.35

2. Ali MS, Sethi J, Taneja A, Musani A, Maldonado F. Computed Tomography Bronchus Sign and the Diagnostic Yield of Guided Bronchoscopy for Peripheral Pulmonary Lesions. A Systematic Review and Meta-Analysis. Ann Am Thorac Soc. 2018 Aug;15(8):978-987. doi: 10.1513/AnnalsATS.201711-856OC. PMID: 29877715.

3. Argento AC, Puchalski J. Convex probe EBUS for centrally located parenchymal lesions without a bronchus sign. Respir Med. 2016 Jul;116:55-8. doi: 10.1016/j.rmed.2016.04.012. Epub 2016 Apr 29. PMID: 27296821.

4. Chen A, Chenna P, Loiselle A, Massoni J, Mayse M, Misselhorn D. Radial probe endobronchial ultrasound for peripheral pulmonary lesions. A 5-year institutional experience. Ann Am Thorac Soc. 2014 May;11(4):578-82. doi: 10.1513/AnnalsATS.201311-384OC. PMID: 24635641.
 

Background

Well into its second year, the worldwide COVID-19 pandemic continues to pose substantial challenges for health care access and delivery. Regulatory agencies such as the Centers for Disease Control (CDC) do not currently have guidance related to COVID-19 specific to sleep centers and laboratories. In March 2020, within days of the World Health Organization pandemic declaration, the American Academy of Sleep Medicine (AASM) posted detailed guidance on mitigation strategies for sleep medicine practices (COVID-19 Resources).

This initial guidance has been previously reported in this publication (Sullivan S, Gurubhagavatula I. CHEST Physician 2020 May 8), and the guidance has been periodically updated during the pandemic. It was restructured in mid-2020 to include sections summarizing CDC recommendations germane for sleep practices; additional sleep medicine-specific guidance from the AASM COVID-19 Task Force (TF); and a frequently asked questions (FAQ) section. The last major update from the task force occurred on Jan. 18, 2021, though subsequent posts – especially related to recent CDC changes in masking guidelines – were made in May 2021. The purpose of this article is to summarize these updates and to call attention to areas of ongoing interest to sleep medicine. Notably, the AASM Task Force guidance is nonbinding and offered as a framework for considering best practices in this evolving situation, acknowledging the importance of weighing local factors, conditions, and regulations, as well as the interests of and risks to the patient, staff, and providers.

Key updates

Data on exposure and transmission risks specific to sleep medicine

Measures for reducing viral transmission have been central to managing the spread of the virus in clinical settings. In its last major update, the AASM TF noted that no known outbreaks of COVID-19 related to sleep center exposure have been reported. A perspective and data published in the Journal of the American Medical Association concluded that hospital transmission of the virus “in the setting of universal masking is likely rare, even during periods of high community prevalence.” It also concluded that hospital-based outbreaks are more likely to occur in small workrooms and during mealtime when staff are less adherent to masking and physical distancing (Richterman A, et al. JAMA. 2020;324[21]:2155-6). The TF elaborated on considerations to reduce transmission, which include not just telework and foundational infection control practices, but also broader workplace considerations such as optimizing ventilation, taking advantage of outdoor spaces (e.g., for breaks and eating), scheduling to reduce interactions between personnel from different teams, minimizing contact in meeting/break rooms, removing tables and chairs from lounge areas, and following CDC guidance for effective facility operations.

Vaccination

In the January update, the AASM COVID-19 TF stated that, “sleep facility leaders should encourage staff and patients to be vaccinated in accordance with CDC guidance.” The role of the sleep medicine community in encouraging healthy sleep habits before and after vaccination was emphasized, pointing to evidence linking sleep and immunity, specifically between sleep duration and vaccination response (Healthy sleep and immune response to COVID-19 vaccination. 2021 Jan.).

In an FAQ update from March 26, 2021, considering whether continued COVID-19 testing was needed following full vaccination, the AASM advised testing prior to potential aerosol-generating procedures should be made on the basis of a risk-benefit assessment by the sleep clinician. Several considerations were highlighted, including recent COVID-19 infection, vaccination status of contacts, local prevalence of newer variants, and whether individuals are receiving positive airway pressure therapy. The TF focused on the vigilance for residents and staff in long-term care facilities, which have been associated with a number of outbreaks.
 

Masking in the context of the COVID-19 vaccine

The most significant change in recommendations is the recent relaxation of masking guidance by the CDC in the setting of the approval and distribution of COVID-19 vaccinations. In May, the CDC stated that fully vaccinated individuals can resume activities without masking or physically distancing except in scenarios of travel and where required by laws, regulations, and local businesses, due to the efficacy of the vaccines, increasing evidence of reduced asymptomatic carriage and transmission after vaccination, and anticipated increased uptake of vaccination. However, the CDC also noted that these updates did not apply to health care facilities, where the recommendation remains that patients and visitors should continue to mask throughout their stay. Additionally, fully vaccinated health care workers should continue to practice infection control measures while working with patients. On May 14, the AASM TF provided a detailed FAQ acknowledging the CDC’s new guidance, emphasizing that masking guidance in health care facilities remains unchanged, and encouraging individuals to follow CDC guidance regarding vaccination, noting that emergence of newer variants continues to be monitored, and existing vaccines still appear to induce neutralizing antibodies even if to a somewhat lower degree. The situation for pediatric sleep centers has been highlighted in particular because the potential risk posed by newer variants to children remains under investigation, and children under age 12 are not approved for vaccination.
 

Important caveats to discussions around vaccination status are the lack of a centralized method to identify vaccinated individuals, the unknown duration of immunity, and reports of the use of fake vaccine cards. At this time, in health care settings, vaccination status should not exempt mask usage for any individual.
 

Sleep medicine care for those with COVID-19

Regarding the duration of isolation and precautions for adults with COVID-19, the TF highlighted the CDC’s symptom-based strategy, rather than test-based strategy, for ending isolation of these patients, availing them of sleep medicine services in person.

In line with the CDC guidance, this approach indicates that scheduling in-person care such as polysomnography for a COVID-19–positive patient may be appropriate at least 10 days after symptom onset (or after a positive test if the patient never developed symptoms); or at least 20 days after symptom onset if the illness was severe; or if at least 90 days have elapsed since symptom onset, consider preappointment COVID-19 screening. In the context of immunocompromised individuals, involvement from infectious disease specialists may be needed to help guide decisions.
 

Patient communications

For many, a repercussion of the pandemic has been delaying care or avoiding addressing medical issues, including sleep disorders. The AASM encouraged practices to consider communicating with patients that delaying needed care can increase health risks; COVID-19 transmission to patients in health care settings has been low; effective safety procedures are in place; and whether remote/telehealth services are available.

Disparities in care

In addition to the specific guidance above, there are ongoing concerns regarding disparities in care resulting from a variety of sources and becoming more evident during the pandemic. Complex factors, ranging from economic, geographic, contextual, occupational, and others contribute to disparities that health care systems – and sleep medicine - have not been able to adequately address (Jackson CL and Johnson DA. J Clin Sleep Med. 16[8]:1401-2). More specific differences may include Internet access, reduced access due to socioeconomic barriers, transportation limitations, medical mistrust, and membership in a medically vulnerable group such as children, the elderly, and those with high acuity needs. For example, in pediatric patients there exist few evidence-based alternatives and guidelines to in-lab testing and care, which may have negatively impacted access to needed sleep medicine services (Sullivan S et al. J Clin Sleep Med. 2021 Mar 1;17[3]:361-2).
 

Economics in the COVID-19 pandemic

The economic effects of COVID-19 on medical institutions and in sleep medicine is a story that continues to unfold. Reductions in patient visits and elective procedures, infection control measures limiting capacity, increased costs to maintain such measures, and variability of responses by payer and region are just a few of the issues. The Centers for Medicare & Medicaid Services has employed waivers to increased flexibility and promote safe and effective care including the use of telemedicine during the public health emergency, but the future of these waivers remains uncertain. Alarmingly, a sizeable portion of sleep practices reported financial solvency concerns related to the pandemic (Ramar K. J Clin Sleep Med. 2020;16[11]:1939-42).

Conclusion

As the COVID-19 pandemic and related public health guidance continues to evolve, sleep medicine practices continue to adapt. Vaccination, new variants, changes in mask guidance, new outbreaks around the globe, financial and staffing uncertainties, as well as addressing disparities in care and outcomes that may be augmented by the pandemic remain salient areas of ongoing development.

Dr. Lee is a Postdoctoral and Pediatric Pulmonary Fellow, Department of Pediatrics, Division of Pulmonary, Asthma, and Sleep Medicine, Stanford University School of Medicine; Dr. Sullivan is Clinical Professor, Department of Pediatrics, Division of Pulmonary, Asthma, and Sleep Medicine, and by courtesy, Division of Sleep Medicine, Department of Psychiatry, Stanford University School of Medicine, Palo Alto, CA.

Background

Well into its second year, the worldwide COVID-19 pandemic continues to pose substantial challenges for health care access and delivery. Regulatory agencies such as the Centers for Disease Control (CDC) do not currently have guidance related to COVID-19 specific to sleep centers and laboratories. In March 2020, within days of the World Health Organization pandemic declaration, the American Academy of Sleep Medicine (AASM) posted detailed guidance on mitigation strategies for sleep medicine practices (COVID-19 Resources).

This initial guidance has been previously reported in this publication (Sullivan S, Gurubhagavatula I. CHEST Physician 2020 May 8), and the guidance has been periodically updated during the pandemic. It was restructured in mid-2020 to include sections summarizing CDC recommendations germane for sleep practices; additional sleep medicine-specific guidance from the AASM COVID-19 Task Force (TF); and a frequently asked questions (FAQ) section. The last major update from the task force occurred on Jan. 18, 2021, though subsequent posts – especially related to recent CDC changes in masking guidelines – were made in May 2021. The purpose of this article is to summarize these updates and to call attention to areas of ongoing interest to sleep medicine. Notably, the AASM Task Force guidance is nonbinding and offered as a framework for considering best practices in this evolving situation, acknowledging the importance of weighing local factors, conditions, and regulations, as well as the interests of and risks to the patient, staff, and providers.

Key updates

Data on exposure and transmission risks specific to sleep medicine

Measures for reducing viral transmission have been central to managing the spread of the virus in clinical settings. In its last major update, the AASM TF noted that no known outbreaks of COVID-19 related to sleep center exposure have been reported. A perspective and data published in the Journal of the American Medical Association concluded that hospital transmission of the virus “in the setting of universal masking is likely rare, even during periods of high community prevalence.” It also concluded that hospital-based outbreaks are more likely to occur in small workrooms and during mealtime when staff are less adherent to masking and physical distancing (Richterman A, et al. JAMA. 2020;324[21]:2155-6). The TF elaborated on considerations to reduce transmission, which include not just telework and foundational infection control practices, but also broader workplace considerations such as optimizing ventilation, taking advantage of outdoor spaces (e.g., for breaks and eating), scheduling to reduce interactions between personnel from different teams, minimizing contact in meeting/break rooms, removing tables and chairs from lounge areas, and following CDC guidance for effective facility operations.

Vaccination

In the January update, the AASM COVID-19 TF stated that, “sleep facility leaders should encourage staff and patients to be vaccinated in accordance with CDC guidance.” The role of the sleep medicine community in encouraging healthy sleep habits before and after vaccination was emphasized, pointing to evidence linking sleep and immunity, specifically between sleep duration and vaccination response (Healthy sleep and immune response to COVID-19 vaccination. 2021 Jan.).

In an FAQ update from March 26, 2021, considering whether continued COVID-19 testing was needed following full vaccination, the AASM advised testing prior to potential aerosol-generating procedures should be made on the basis of a risk-benefit assessment by the sleep clinician. Several considerations were highlighted, including recent COVID-19 infection, vaccination status of contacts, local prevalence of newer variants, and whether individuals are receiving positive airway pressure therapy. The TF focused on the vigilance for residents and staff in long-term care facilities, which have been associated with a number of outbreaks.
 

Masking in the context of the COVID-19 vaccine

The most significant change in recommendations is the recent relaxation of masking guidance by the CDC in the setting of the approval and distribution of COVID-19 vaccinations. In May, the CDC stated that fully vaccinated individuals can resume activities without masking or physically distancing except in scenarios of travel and where required by laws, regulations, and local businesses, due to the efficacy of the vaccines, increasing evidence of reduced asymptomatic carriage and transmission after vaccination, and anticipated increased uptake of vaccination. However, the CDC also noted that these updates did not apply to health care facilities, where the recommendation remains that patients and visitors should continue to mask throughout their stay. Additionally, fully vaccinated health care workers should continue to practice infection control measures while working with patients. On May 14, the AASM TF provided a detailed FAQ acknowledging the CDC’s new guidance, emphasizing that masking guidance in health care facilities remains unchanged, and encouraging individuals to follow CDC guidance regarding vaccination, noting that emergence of newer variants continues to be monitored, and existing vaccines still appear to induce neutralizing antibodies even if to a somewhat lower degree. The situation for pediatric sleep centers has been highlighted in particular because the potential risk posed by newer variants to children remains under investigation, and children under age 12 are not approved for vaccination.
 

Important caveats to discussions around vaccination status are the lack of a centralized method to identify vaccinated individuals, the unknown duration of immunity, and reports of the use of fake vaccine cards. At this time, in health care settings, vaccination status should not exempt mask usage for any individual.
 

Sleep medicine care for those with COVID-19

Regarding the duration of isolation and precautions for adults with COVID-19, the TF highlighted the CDC’s symptom-based strategy, rather than test-based strategy, for ending isolation of these patients, availing them of sleep medicine services in person.

In line with the CDC guidance, this approach indicates that scheduling in-person care such as polysomnography for a COVID-19–positive patient may be appropriate at least 10 days after symptom onset (or after a positive test if the patient never developed symptoms); or at least 20 days after symptom onset if the illness was severe; or if at least 90 days have elapsed since symptom onset, consider preappointment COVID-19 screening. In the context of immunocompromised individuals, involvement from infectious disease specialists may be needed to help guide decisions.
 

Patient communications

For many, a repercussion of the pandemic has been delaying care or avoiding addressing medical issues, including sleep disorders. The AASM encouraged practices to consider communicating with patients that delaying needed care can increase health risks; COVID-19 transmission to patients in health care settings has been low; effective safety procedures are in place; and whether remote/telehealth services are available.

Disparities in care

In addition to the specific guidance above, there are ongoing concerns regarding disparities in care resulting from a variety of sources and becoming more evident during the pandemic. Complex factors, ranging from economic, geographic, contextual, occupational, and others contribute to disparities that health care systems – and sleep medicine - have not been able to adequately address (Jackson CL and Johnson DA. J Clin Sleep Med. 16[8]:1401-2). More specific differences may include Internet access, reduced access due to socioeconomic barriers, transportation limitations, medical mistrust, and membership in a medically vulnerable group such as children, the elderly, and those with high acuity needs. For example, in pediatric patients there exist few evidence-based alternatives and guidelines to in-lab testing and care, which may have negatively impacted access to needed sleep medicine services (Sullivan S et al. J Clin Sleep Med. 2021 Mar 1;17[3]:361-2).
 

Economics in the COVID-19 pandemic

The economic effects of COVID-19 on medical institutions and in sleep medicine is a story that continues to unfold. Reductions in patient visits and elective procedures, infection control measures limiting capacity, increased costs to maintain such measures, and variability of responses by payer and region are just a few of the issues. The Centers for Medicare & Medicaid Services has employed waivers to increased flexibility and promote safe and effective care including the use of telemedicine during the public health emergency, but the future of these waivers remains uncertain. Alarmingly, a sizeable portion of sleep practices reported financial solvency concerns related to the pandemic (Ramar K. J Clin Sleep Med. 2020;16[11]:1939-42).

Conclusion

As the COVID-19 pandemic and related public health guidance continues to evolve, sleep medicine practices continue to adapt. Vaccination, new variants, changes in mask guidance, new outbreaks around the globe, financial and staffing uncertainties, as well as addressing disparities in care and outcomes that may be augmented by the pandemic remain salient areas of ongoing development.

Dr. Lee is a Postdoctoral and Pediatric Pulmonary Fellow, Department of Pediatrics, Division of Pulmonary, Asthma, and Sleep Medicine, Stanford University School of Medicine; Dr. Sullivan is Clinical Professor, Department of Pediatrics, Division of Pulmonary, Asthma, and Sleep Medicine, and by courtesy, Division of Sleep Medicine, Department of Psychiatry, Stanford University School of Medicine, Palo Alto, CA.

Background

Well into its second year, the worldwide COVID-19 pandemic continues to pose substantial challenges for health care access and delivery. Regulatory agencies such as the Centers for Disease Control (CDC) do not currently have guidance related to COVID-19 specific to sleep centers and laboratories. In March 2020, within days of the World Health Organization pandemic declaration, the American Academy of Sleep Medicine (AASM) posted detailed guidance on mitigation strategies for sleep medicine practices (COVID-19 Resources).

This initial guidance has been previously reported in this publication (Sullivan S, Gurubhagavatula I. CHEST Physician 2020 May 8), and the guidance has been periodically updated during the pandemic. It was restructured in mid-2020 to include sections summarizing CDC recommendations germane for sleep practices; additional sleep medicine-specific guidance from the AASM COVID-19 Task Force (TF); and a frequently asked questions (FAQ) section. The last major update from the task force occurred on Jan. 18, 2021, though subsequent posts – especially related to recent CDC changes in masking guidelines – were made in May 2021. The purpose of this article is to summarize these updates and to call attention to areas of ongoing interest to sleep medicine. Notably, the AASM Task Force guidance is nonbinding and offered as a framework for considering best practices in this evolving situation, acknowledging the importance of weighing local factors, conditions, and regulations, as well as the interests of and risks to the patient, staff, and providers.

Key updates

Data on exposure and transmission risks specific to sleep medicine

Measures for reducing viral transmission have been central to managing the spread of the virus in clinical settings. In its last major update, the AASM TF noted that no known outbreaks of COVID-19 related to sleep center exposure have been reported. A perspective and data published in the Journal of the American Medical Association concluded that hospital transmission of the virus “in the setting of universal masking is likely rare, even during periods of high community prevalence.” It also concluded that hospital-based outbreaks are more likely to occur in small workrooms and during mealtime when staff are less adherent to masking and physical distancing (Richterman A, et al. JAMA. 2020;324[21]:2155-6). The TF elaborated on considerations to reduce transmission, which include not just telework and foundational infection control practices, but also broader workplace considerations such as optimizing ventilation, taking advantage of outdoor spaces (e.g., for breaks and eating), scheduling to reduce interactions between personnel from different teams, minimizing contact in meeting/break rooms, removing tables and chairs from lounge areas, and following CDC guidance for effective facility operations.

Vaccination

In the January update, the AASM COVID-19 TF stated that, “sleep facility leaders should encourage staff and patients to be vaccinated in accordance with CDC guidance.” The role of the sleep medicine community in encouraging healthy sleep habits before and after vaccination was emphasized, pointing to evidence linking sleep and immunity, specifically between sleep duration and vaccination response (Healthy sleep and immune response to COVID-19 vaccination. 2021 Jan.).

In an FAQ update from March 26, 2021, considering whether continued COVID-19 testing was needed following full vaccination, the AASM advised testing prior to potential aerosol-generating procedures should be made on the basis of a risk-benefit assessment by the sleep clinician. Several considerations were highlighted, including recent COVID-19 infection, vaccination status of contacts, local prevalence of newer variants, and whether individuals are receiving positive airway pressure therapy. The TF focused on the vigilance for residents and staff in long-term care facilities, which have been associated with a number of outbreaks.
 

Masking in the context of the COVID-19 vaccine

The most significant change in recommendations is the recent relaxation of masking guidance by the CDC in the setting of the approval and distribution of COVID-19 vaccinations. In May, the CDC stated that fully vaccinated individuals can resume activities without masking or physically distancing except in scenarios of travel and where required by laws, regulations, and local businesses, due to the efficacy of the vaccines, increasing evidence of reduced asymptomatic carriage and transmission after vaccination, and anticipated increased uptake of vaccination. However, the CDC also noted that these updates did not apply to health care facilities, where the recommendation remains that patients and visitors should continue to mask throughout their stay. Additionally, fully vaccinated health care workers should continue to practice infection control measures while working with patients. On May 14, the AASM TF provided a detailed FAQ acknowledging the CDC’s new guidance, emphasizing that masking guidance in health care facilities remains unchanged, and encouraging individuals to follow CDC guidance regarding vaccination, noting that emergence of newer variants continues to be monitored, and existing vaccines still appear to induce neutralizing antibodies even if to a somewhat lower degree. The situation for pediatric sleep centers has been highlighted in particular because the potential risk posed by newer variants to children remains under investigation, and children under age 12 are not approved for vaccination.
 

Important caveats to discussions around vaccination status are the lack of a centralized method to identify vaccinated individuals, the unknown duration of immunity, and reports of the use of fake vaccine cards. At this time, in health care settings, vaccination status should not exempt mask usage for any individual.
 

Sleep medicine care for those with COVID-19

Regarding the duration of isolation and precautions for adults with COVID-19, the TF highlighted the CDC’s symptom-based strategy, rather than test-based strategy, for ending isolation of these patients, availing them of sleep medicine services in person.

In line with the CDC guidance, this approach indicates that scheduling in-person care such as polysomnography for a COVID-19–positive patient may be appropriate at least 10 days after symptom onset (or after a positive test if the patient never developed symptoms); or at least 20 days after symptom onset if the illness was severe; or if at least 90 days have elapsed since symptom onset, consider preappointment COVID-19 screening. In the context of immunocompromised individuals, involvement from infectious disease specialists may be needed to help guide decisions.
 

Patient communications

For many, a repercussion of the pandemic has been delaying care or avoiding addressing medical issues, including sleep disorders. The AASM encouraged practices to consider communicating with patients that delaying needed care can increase health risks; COVID-19 transmission to patients in health care settings has been low; effective safety procedures are in place; and whether remote/telehealth services are available.

Disparities in care

In addition to the specific guidance above, there are ongoing concerns regarding disparities in care resulting from a variety of sources and becoming more evident during the pandemic. Complex factors, ranging from economic, geographic, contextual, occupational, and others contribute to disparities that health care systems – and sleep medicine - have not been able to adequately address (Jackson CL and Johnson DA. J Clin Sleep Med. 16[8]:1401-2). More specific differences may include Internet access, reduced access due to socioeconomic barriers, transportation limitations, medical mistrust, and membership in a medically vulnerable group such as children, the elderly, and those with high acuity needs. For example, in pediatric patients there exist few evidence-based alternatives and guidelines to in-lab testing and care, which may have negatively impacted access to needed sleep medicine services (Sullivan S et al. J Clin Sleep Med. 2021 Mar 1;17[3]:361-2).
 

Economics in the COVID-19 pandemic

The economic effects of COVID-19 on medical institutions and in sleep medicine is a story that continues to unfold. Reductions in patient visits and elective procedures, infection control measures limiting capacity, increased costs to maintain such measures, and variability of responses by payer and region are just a few of the issues. The Centers for Medicare & Medicaid Services has employed waivers to increased flexibility and promote safe and effective care including the use of telemedicine during the public health emergency, but the future of these waivers remains uncertain. Alarmingly, a sizeable portion of sleep practices reported financial solvency concerns related to the pandemic (Ramar K. J Clin Sleep Med. 2020;16[11]:1939-42).

Conclusion

As the COVID-19 pandemic and related public health guidance continues to evolve, sleep medicine practices continue to adapt. Vaccination, new variants, changes in mask guidance, new outbreaks around the globe, financial and staffing uncertainties, as well as addressing disparities in care and outcomes that may be augmented by the pandemic remain salient areas of ongoing development.

Dr. Lee is a Postdoctoral and Pediatric Pulmonary Fellow, Department of Pediatrics, Division of Pulmonary, Asthma, and Sleep Medicine, Stanford University School of Medicine; Dr. Sullivan is Clinical Professor, Department of Pediatrics, Division of Pulmonary, Asthma, and Sleep Medicine, and by courtesy, Division of Sleep Medicine, Department of Psychiatry, Stanford University School of Medicine, Palo Alto, CA.

Lung cancer is the second-most common cancer and one of the leading causes of mortality in the United States among both men and women. It accounts for almost 25% of all cancer deaths, and every year more people die of lung cancer than colon, breast, and prostate cancers combined. The American Cancer Society estimates about 235,760 new lung cancer cases and about 131,880 deaths from lung cancer in 2021.

Smoking and increasing age are the two most important risk factors for lung cancer. Lung cancer has a higher incidence among Black men than White men, and among White women compared with Black women. These differences are likely related to smoking exposure. Early diagnosis of lung cancer can improve survival, and hence screening for lung cancer in high-risk populations is desired. Among the available cancer screening tests, radiology is primarily involved in breast and lung cancer screening (LCS). In 2011, the National Lung Screening Trial (NLST) showed a benefit of annual low- dose chest CT for LCS, with about 20% reduction in lung cancer-related mortality in high-risk participants compared with chest radiographs (Aberle DR, et al. N Engl J Med. 2011 Aug 4;365[5]:395-409).

Dr. Stowell and Dr. Sonavane are with the Mayo Clinic in Jacksonville, Fla.

Lung cancer is the second-most common cancer and one of the leading causes of mortality in the United States among both men and women. It accounts for almost 25% of all cancer deaths, and every year more people die of lung cancer than colon, breast, and prostate cancers combined. The American Cancer Society estimates about 235,760 new lung cancer cases and about 131,880 deaths from lung cancer in 2021.

Smoking and increasing age are the two most important risk factors for lung cancer. Lung cancer has a higher incidence among Black men than White men, and among White women compared with Black women. These differences are likely related to smoking exposure. Early diagnosis of lung cancer can improve survival, and hence screening for lung cancer in high-risk populations is desired. Among the available cancer screening tests, radiology is primarily involved in breast and lung cancer screening (LCS). In 2011, the National Lung Screening Trial (NLST) showed a benefit of annual low- dose chest CT for LCS, with about 20% reduction in lung cancer-related mortality in high-risk participants compared with chest radiographs (Aberle DR, et al. N Engl J Med. 2011 Aug 4;365[5]:395-409).

Dr. Stowell and Dr. Sonavane are with the Mayo Clinic in Jacksonville, Fla.

Lung cancer is the second-most common cancer and one of the leading causes of mortality in the United States among both men and women. It accounts for almost 25% of all cancer deaths, and every year more people die of lung cancer than colon, breast, and prostate cancers combined. The American Cancer Society estimates about 235,760 new lung cancer cases and about 131,880 deaths from lung cancer in 2021.

Smoking and increasing age are the two most important risk factors for lung cancer. Lung cancer has a higher incidence among Black men than White men, and among White women compared with Black women. These differences are likely related to smoking exposure. Early diagnosis of lung cancer can improve survival, and hence screening for lung cancer in high-risk populations is desired. Among the available cancer screening tests, radiology is primarily involved in breast and lung cancer screening (LCS). In 2011, the National Lung Screening Trial (NLST) showed a benefit of annual low- dose chest CT for LCS, with about 20% reduction in lung cancer-related mortality in high-risk participants compared with chest radiographs (Aberle DR, et al. N Engl J Med. 2011 Aug 4;365[5]:395-409).

Dr. Stowell and Dr. Sonavane are with the Mayo Clinic in Jacksonville, Fla.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused by the novel coronavirus of the year 2019 (COVID-19) has had a major impact on global health and economy. United States reported a total caseload of 28,998,834 patients and total mortality of 525,031 as of March 2021 (NPR.org; worldometer. Accessed March 8, 2021). The beginning of 2021 ushered positivity with the development of multiple highly effective SARS-CoV-2 vaccines. Although the medical world has gained much knowledge about this deadly disease, there are many unknowns and still much to be learned.

Two early landmark studies from Italy (Lombardy) and United States (New York City area) provided initial insight on comorbid conditions associated with increased risk of severe COVID-19 infection (Richardson S, et al. JAMA. 2020;323[20]:2052; Grasselli G, et al. JAMA Intern Med. 2020;180[10]:1345). In the United States cohort, hypertension (HTN), obesity, and diabetes (DM) were independent risk factors for severe disease, while in the Italy cohort, older age, male, COPD, hypercholesterolemia, and diabetes were independent risk factors for increased mortality. Obstructive sleep apnea (OSA) was not mentioned as a comorbid risk factor.

There is much speculation regarding OSA as an independent risk factor for severe COVID-19 infection. OSA is a common sleep-related breathing disorder with increased prevalence in men, older age, and higher body mass index (BMI); and OSA is associated with hypertension, obesity, and diabetes, all of which are risk factors for severe COVID-19. Because of the shared similarities in pathophysiology between OSA and COVID-19 (Tufik S, et al. J Clin Sleep Med. 2020;16[8]:1425), and shared comorbid conditions associated with increased risk of severe COVID-19 disease, OSA has been suggested as an independent risk factor for unfavorable COVID-19-related outcomes.

SARS-CoV-2 triggers a severe inflammatory response involving type-II pneumocytes and angiotensin-converting enzyme 2 pathway. OSA is characterized by intermittent hypoxia and sleep fragmentation, leading to a cascade of systemic inflammatory response involving oxidative stress, pro-inflammatory cytokines, endothelial dysfunction, and consequent cardiovascular injury (Jose RJ, et al. Lancet Respir Med. 2020;8[6]:e46; Saxena K, et al. Sleep Medicine. 2021;79:223). In this regard, OSA may contribute to COVID-19 “cytokine storm” by causing or exacerbating endothelial dysfunction, inflammation, and oxidative stress.

Multiple studies have recently been published on the impact of OSA on COVID-19 outcomes. The Coronavirus SARS-CoV-2 and Diabetes Outcomes (CORONADO) study was one of the initial studies that analyzed the relationship between OSA and COVID-19-related outcomes. This was a multicenter observational study involving diabetic patients hospitalized with COVID-19. The primary outcome was mechanical ventilation and/or death within 7 days of admission. Multivariate adjustment showed that age, BMI, and OSA, among other factors, were independently associated with risk of death on day 7 (Cariou B, et al. Diabetologia. 2020;63[8]:1500). Strausz and colleagues also evaluated OSA as an independent risk factor for severe COVID-19 in a large registry of hospital discharge patients (FinnGen study). The authors reported that although the risk of contracting COVID-19 was the same for patients with or without OSA, after adjusting for age, sex, and BMI, OSA was associated with higher risk of hospitalization (Strausz S, et al. BMJ Open Resp Res. 2021;8:e000845). Similar findings were confirmed by the Maas et al. study, which utilized a large socioeconomically diverse database composed of 10 hospital systems. Diagnoses and outcomes were identified by ICD-10 coding and medical record data. After adjustments for diabetes, HTN, and BMI, OSA conferred an eight-fold risk for COVID-19 infection, was associated with increased risk of hospitalization, and doubled the risk of developing respiratory failure (Maas MB, et al. Sleep Breath. 2020 Sep; 29:1-3. doi: 10.1007/s11325-020-02203-0).

Peker and colleagues conducted a prospective multicenter observational study comparing clinical outcomes of severe COVID-19 infection in patients with low vs high pretest probability of having OSA based on the Berlin questionnaire. The authors reported a clinically significant risk of poorer clinical outcomes in the high pretest probability OSA group after adjustments for age, sex, and comorbidities (Peker Y, et al. Ann Am Thorac Soc. 2021. Feb 17. doi: 10.1513/AnnalsATS.202011-1409OC). A timely meta-analysis including 21 studies (19 with retrospective design) with 54,276 COVID-19 patients and 4,640 OSA patients concluded poor composite outcomes including severe COVID-19, intensive care unit admission, mechanical ventilatory support, and death in association with OSA (OR – 1.72 95% CI 1.55-1.91, P< .00001). In patients with obesity, OSA is a highly prevalent co-morbid condition. BMI, however, was not adjusted in this model (Hariyanto TI, et al. Sleep Med. 2021. doi: 10.1016/j.sleep.2021.03.029).

Other studies have concluded the opposite with OSA not being an independent risk factor for severe COVID-19 infection. Cade and colleagues conducted a retrospective analysis from a comprehensive electronic health dataset using ICD codes to identify OSA patients with severe COVID-19 infection. A significant association between OSA and COVID-19 death was noted after adjustment for demographics (ethnicity, age, sex). However, when fully adjusted for demographics, BMI, asthma, COPD, HTN, or DM, OSA was not an independent risk factor for COVID-19-related mortality and hospitalization (Cade BE, et al. Am J Respir Crit Care Med. 2020;202[10]:1462). The FinnGen study (Strausz et al.) was part of a meta-analysis examining the association between OSA and severe COVID-19 with and without adjustments for BMI. This meta-analysis consisted of 15,835 COVID-19 patients including 1,294 with OSA. The authors found that OSA was a risk factor with a two-fold increased risk of severe COVID-19 infection (OR = 2.37, P = .021). However, after adjustments were made for BMI, this finding lost statistical significance (OR=1.55, P=.13) (Strausz S, et al. BMJ Open Resp Res. 2021;8:e000845).

It is worth noting that a majority of studies identified OSA by indirect and imperfect methods through chart review, ICD codes, and databases. Confirmed OSA based on formal testing with a sleep study in COVID-19 patients remains a challenge. Perhaps well performed screening questionnaires, such as STOP-Bang, Berlin, or NoSAS, can be utilized as was the case in one study. It is also unclear if outcomes of COVID-19 infection differ in patients with treated or untreated OSA, as raised by the CORONADO study. A recent cross-sectional telephone interview survey of patients with confirmed OSA in Iran alluded to higher prevalence of COVID-19 in patients with severe OSA with suggestion of lower prevalence in patients who were currently receiving OSA treatment with positive airway pressure (PAP) therapy (Najafi A, et al. Sleep Health. 2021 Feb;7[1]:14). This is a crucial question as PAP therapy is considered an aerosol-generating procedure (Lance CG. Cleve Clin J Med. 2020 May 5. doi: 10.3949/ccjm.87a.ccc003). Studies have suggested continued use of PAP therapy with additional measures to mitigate the spread of virus, since failure to use PAP could be deleterious to the patient’s quality of life. Interestingly, PAP adherence seemed to have improved during the pandemic as evidenced by a telephonic survey done in New York City that showed 88% of patients with OSA used a PAP device consistently (Attias D, et al. Eur Respir J. 2020 Jul 30;56[1]:2001607. doi: 10.1183/13993003.01607-2020).

In summary, the jury is still out on whether OSA is a facilitator for viral replication, or an independent risk factor for poor prognosis related to COVID-19 infection, or has no clinical relevance to COVID-19. COVID-19 and OSA share comorbidities and pathways leading to a systemic inflammatory cascade. Theoretically, it would make sense that OSA is a risk factor for severe COVID-19 infection; however, it remains to be proven. The recent studies are limited by retrospective and observational nature, imprecise OSA classification/diagnostic criteria, and confounded by difficult to control variables. Further research is needed to expand our understanding of OSA -induced intermittent hypoxemia, inflammation, and endothelial dysfunction that may play a role in COVID-19 morbidity and mortality. Until we have more clarity, close monitoring of OSA patients infected with COVID-19 is recommended along with implementation of safe protocols for continuation of PAP usage during the infectious phase. Identifying underlying comorbid conditions that contribute to worsening of a COVID-19 infectious course is a crucial step in improving clinical outcomes.
 

Dr. Sahni is Assistant Professor of Clinical Medicine, Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, University of Illinois at Chicago. Dr. Cao is Clinical Associate Professor, Division of Sleep Medicine and Division of Neuromuscular Medicine, Department of Psychiatry and Department of Neurology, Stanford (Calif.) University.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused by the novel coronavirus of the year 2019 (COVID-19) has had a major impact on global health and economy. United States reported a total caseload of 28,998,834 patients and total mortality of 525,031 as of March 2021 (NPR.org; worldometer. Accessed March 8, 2021). The beginning of 2021 ushered positivity with the development of multiple highly effective SARS-CoV-2 vaccines. Although the medical world has gained much knowledge about this deadly disease, there are many unknowns and still much to be learned.

Two early landmark studies from Italy (Lombardy) and United States (New York City area) provided initial insight on comorbid conditions associated with increased risk of severe COVID-19 infection (Richardson S, et al. JAMA. 2020;323[20]:2052; Grasselli G, et al. JAMA Intern Med. 2020;180[10]:1345). In the United States cohort, hypertension (HTN), obesity, and diabetes (DM) were independent risk factors for severe disease, while in the Italy cohort, older age, male, COPD, hypercholesterolemia, and diabetes were independent risk factors for increased mortality. Obstructive sleep apnea (OSA) was not mentioned as a comorbid risk factor.

There is much speculation regarding OSA as an independent risk factor for severe COVID-19 infection. OSA is a common sleep-related breathing disorder with increased prevalence in men, older age, and higher body mass index (BMI); and OSA is associated with hypertension, obesity, and diabetes, all of which are risk factors for severe COVID-19. Because of the shared similarities in pathophysiology between OSA and COVID-19 (Tufik S, et al. J Clin Sleep Med. 2020;16[8]:1425), and shared comorbid conditions associated with increased risk of severe COVID-19 disease, OSA has been suggested as an independent risk factor for unfavorable COVID-19-related outcomes.

SARS-CoV-2 triggers a severe inflammatory response involving type-II pneumocytes and angiotensin-converting enzyme 2 pathway. OSA is characterized by intermittent hypoxia and sleep fragmentation, leading to a cascade of systemic inflammatory response involving oxidative stress, pro-inflammatory cytokines, endothelial dysfunction, and consequent cardiovascular injury (Jose RJ, et al. Lancet Respir Med. 2020;8[6]:e46; Saxena K, et al. Sleep Medicine. 2021;79:223). In this regard, OSA may contribute to COVID-19 “cytokine storm” by causing or exacerbating endothelial dysfunction, inflammation, and oxidative stress.

Multiple studies have recently been published on the impact of OSA on COVID-19 outcomes. The Coronavirus SARS-CoV-2 and Diabetes Outcomes (CORONADO) study was one of the initial studies that analyzed the relationship between OSA and COVID-19-related outcomes. This was a multicenter observational study involving diabetic patients hospitalized with COVID-19. The primary outcome was mechanical ventilation and/or death within 7 days of admission. Multivariate adjustment showed that age, BMI, and OSA, among other factors, were independently associated with risk of death on day 7 (Cariou B, et al. Diabetologia. 2020;63[8]:1500). Strausz and colleagues also evaluated OSA as an independent risk factor for severe COVID-19 in a large registry of hospital discharge patients (FinnGen study). The authors reported that although the risk of contracting COVID-19 was the same for patients with or without OSA, after adjusting for age, sex, and BMI, OSA was associated with higher risk of hospitalization (Strausz S, et al. BMJ Open Resp Res. 2021;8:e000845). Similar findings were confirmed by the Maas et al. study, which utilized a large socioeconomically diverse database composed of 10 hospital systems. Diagnoses and outcomes were identified by ICD-10 coding and medical record data. After adjustments for diabetes, HTN, and BMI, OSA conferred an eight-fold risk for COVID-19 infection, was associated with increased risk of hospitalization, and doubled the risk of developing respiratory failure (Maas MB, et al. Sleep Breath. 2020 Sep; 29:1-3. doi: 10.1007/s11325-020-02203-0).

Peker and colleagues conducted a prospective multicenter observational study comparing clinical outcomes of severe COVID-19 infection in patients with low vs high pretest probability of having OSA based on the Berlin questionnaire. The authors reported a clinically significant risk of poorer clinical outcomes in the high pretest probability OSA group after adjustments for age, sex, and comorbidities (Peker Y, et al. Ann Am Thorac Soc. 2021. Feb 17. doi: 10.1513/AnnalsATS.202011-1409OC). A timely meta-analysis including 21 studies (19 with retrospective design) with 54,276 COVID-19 patients and 4,640 OSA patients concluded poor composite outcomes including severe COVID-19, intensive care unit admission, mechanical ventilatory support, and death in association with OSA (OR – 1.72 95% CI 1.55-1.91, P< .00001). In patients with obesity, OSA is a highly prevalent co-morbid condition. BMI, however, was not adjusted in this model (Hariyanto TI, et al. Sleep Med. 2021. doi: 10.1016/j.sleep.2021.03.029).

Other studies have concluded the opposite with OSA not being an independent risk factor for severe COVID-19 infection. Cade and colleagues conducted a retrospective analysis from a comprehensive electronic health dataset using ICD codes to identify OSA patients with severe COVID-19 infection. A significant association between OSA and COVID-19 death was noted after adjustment for demographics (ethnicity, age, sex). However, when fully adjusted for demographics, BMI, asthma, COPD, HTN, or DM, OSA was not an independent risk factor for COVID-19-related mortality and hospitalization (Cade BE, et al. Am J Respir Crit Care Med. 2020;202[10]:1462). The FinnGen study (Strausz et al.) was part of a meta-analysis examining the association between OSA and severe COVID-19 with and without adjustments for BMI. This meta-analysis consisted of 15,835 COVID-19 patients including 1,294 with OSA. The authors found that OSA was a risk factor with a two-fold increased risk of severe COVID-19 infection (OR = 2.37, P = .021). However, after adjustments were made for BMI, this finding lost statistical significance (OR=1.55, P=.13) (Strausz S, et al. BMJ Open Resp Res. 2021;8:e000845).

It is worth noting that a majority of studies identified OSA by indirect and imperfect methods through chart review, ICD codes, and databases. Confirmed OSA based on formal testing with a sleep study in COVID-19 patients remains a challenge. Perhaps well performed screening questionnaires, such as STOP-Bang, Berlin, or NoSAS, can be utilized as was the case in one study. It is also unclear if outcomes of COVID-19 infection differ in patients with treated or untreated OSA, as raised by the CORONADO study. A recent cross-sectional telephone interview survey of patients with confirmed OSA in Iran alluded to higher prevalence of COVID-19 in patients with severe OSA with suggestion of lower prevalence in patients who were currently receiving OSA treatment with positive airway pressure (PAP) therapy (Najafi A, et al. Sleep Health. 2021 Feb;7[1]:14). This is a crucial question as PAP therapy is considered an aerosol-generating procedure (Lance CG. Cleve Clin J Med. 2020 May 5. doi: 10.3949/ccjm.87a.ccc003). Studies have suggested continued use of PAP therapy with additional measures to mitigate the spread of virus, since failure to use PAP could be deleterious to the patient’s quality of life. Interestingly, PAP adherence seemed to have improved during the pandemic as evidenced by a telephonic survey done in New York City that showed 88% of patients with OSA used a PAP device consistently (Attias D, et al. Eur Respir J. 2020 Jul 30;56[1]:2001607. doi: 10.1183/13993003.01607-2020).

In summary, the jury is still out on whether OSA is a facilitator for viral replication, or an independent risk factor for poor prognosis related to COVID-19 infection, or has no clinical relevance to COVID-19. COVID-19 and OSA share comorbidities and pathways leading to a systemic inflammatory cascade. Theoretically, it would make sense that OSA is a risk factor for severe COVID-19 infection; however, it remains to be proven. The recent studies are limited by retrospective and observational nature, imprecise OSA classification/diagnostic criteria, and confounded by difficult to control variables. Further research is needed to expand our understanding of OSA -induced intermittent hypoxemia, inflammation, and endothelial dysfunction that may play a role in COVID-19 morbidity and mortality. Until we have more clarity, close monitoring of OSA patients infected with COVID-19 is recommended along with implementation of safe protocols for continuation of PAP usage during the infectious phase. Identifying underlying comorbid conditions that contribute to worsening of a COVID-19 infectious course is a crucial step in improving clinical outcomes.
 

Dr. Sahni is Assistant Professor of Clinical Medicine, Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, University of Illinois at Chicago. Dr. Cao is Clinical Associate Professor, Division of Sleep Medicine and Division of Neuromuscular Medicine, Department of Psychiatry and Department of Neurology, Stanford (Calif.) University.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused by the novel coronavirus of the year 2019 (COVID-19) has had a major impact on global health and economy. United States reported a total caseload of 28,998,834 patients and total mortality of 525,031 as of March 2021 (NPR.org; worldometer. Accessed March 8, 2021). The beginning of 2021 ushered positivity with the development of multiple highly effective SARS-CoV-2 vaccines. Although the medical world has gained much knowledge about this deadly disease, there are many unknowns and still much to be learned.

Two early landmark studies from Italy (Lombardy) and United States (New York City area) provided initial insight on comorbid conditions associated with increased risk of severe COVID-19 infection (Richardson S, et al. JAMA. 2020;323[20]:2052; Grasselli G, et al. JAMA Intern Med. 2020;180[10]:1345). In the United States cohort, hypertension (HTN), obesity, and diabetes (DM) were independent risk factors for severe disease, while in the Italy cohort, older age, male, COPD, hypercholesterolemia, and diabetes were independent risk factors for increased mortality. Obstructive sleep apnea (OSA) was not mentioned as a comorbid risk factor.

There is much speculation regarding OSA as an independent risk factor for severe COVID-19 infection. OSA is a common sleep-related breathing disorder with increased prevalence in men, older age, and higher body mass index (BMI); and OSA is associated with hypertension, obesity, and diabetes, all of which are risk factors for severe COVID-19. Because of the shared similarities in pathophysiology between OSA and COVID-19 (Tufik S, et al. J Clin Sleep Med. 2020;16[8]:1425), and shared comorbid conditions associated with increased risk of severe COVID-19 disease, OSA has been suggested as an independent risk factor for unfavorable COVID-19-related outcomes.

SARS-CoV-2 triggers a severe inflammatory response involving type-II pneumocytes and angiotensin-converting enzyme 2 pathway. OSA is characterized by intermittent hypoxia and sleep fragmentation, leading to a cascade of systemic inflammatory response involving oxidative stress, pro-inflammatory cytokines, endothelial dysfunction, and consequent cardiovascular injury (Jose RJ, et al. Lancet Respir Med. 2020;8[6]:e46; Saxena K, et al. Sleep Medicine. 2021;79:223). In this regard, OSA may contribute to COVID-19 “cytokine storm” by causing or exacerbating endothelial dysfunction, inflammation, and oxidative stress.

Multiple studies have recently been published on the impact of OSA on COVID-19 outcomes. The Coronavirus SARS-CoV-2 and Diabetes Outcomes (CORONADO) study was one of the initial studies that analyzed the relationship between OSA and COVID-19-related outcomes. This was a multicenter observational study involving diabetic patients hospitalized with COVID-19. The primary outcome was mechanical ventilation and/or death within 7 days of admission. Multivariate adjustment showed that age, BMI, and OSA, among other factors, were independently associated with risk of death on day 7 (Cariou B, et al. Diabetologia. 2020;63[8]:1500). Strausz and colleagues also evaluated OSA as an independent risk factor for severe COVID-19 in a large registry of hospital discharge patients (FinnGen study). The authors reported that although the risk of contracting COVID-19 was the same for patients with or without OSA, after adjusting for age, sex, and BMI, OSA was associated with higher risk of hospitalization (Strausz S, et al. BMJ Open Resp Res. 2021;8:e000845). Similar findings were confirmed by the Maas et al. study, which utilized a large socioeconomically diverse database composed of 10 hospital systems. Diagnoses and outcomes were identified by ICD-10 coding and medical record data. After adjustments for diabetes, HTN, and BMI, OSA conferred an eight-fold risk for COVID-19 infection, was associated with increased risk of hospitalization, and doubled the risk of developing respiratory failure (Maas MB, et al. Sleep Breath. 2020 Sep; 29:1-3. doi: 10.1007/s11325-020-02203-0).

Peker and colleagues conducted a prospective multicenter observational study comparing clinical outcomes of severe COVID-19 infection in patients with low vs high pretest probability of having OSA based on the Berlin questionnaire. The authors reported a clinically significant risk of poorer clinical outcomes in the high pretest probability OSA group after adjustments for age, sex, and comorbidities (Peker Y, et al. Ann Am Thorac Soc. 2021. Feb 17. doi: 10.1513/AnnalsATS.202011-1409OC). A timely meta-analysis including 21 studies (19 with retrospective design) with 54,276 COVID-19 patients and 4,640 OSA patients concluded poor composite outcomes including severe COVID-19, intensive care unit admission, mechanical ventilatory support, and death in association with OSA (OR – 1.72 95% CI 1.55-1.91, P< .00001). In patients with obesity, OSA is a highly prevalent co-morbid condition. BMI, however, was not adjusted in this model (Hariyanto TI, et al. Sleep Med. 2021. doi: 10.1016/j.sleep.2021.03.029).

Other studies have concluded the opposite with OSA not being an independent risk factor for severe COVID-19 infection. Cade and colleagues conducted a retrospective analysis from a comprehensive electronic health dataset using ICD codes to identify OSA patients with severe COVID-19 infection. A significant association between OSA and COVID-19 death was noted after adjustment for demographics (ethnicity, age, sex). However, when fully adjusted for demographics, BMI, asthma, COPD, HTN, or DM, OSA was not an independent risk factor for COVID-19-related mortality and hospitalization (Cade BE, et al. Am J Respir Crit Care Med. 2020;202[10]:1462). The FinnGen study (Strausz et al.) was part of a meta-analysis examining the association between OSA and severe COVID-19 with and without adjustments for BMI. This meta-analysis consisted of 15,835 COVID-19 patients including 1,294 with OSA. The authors found that OSA was a risk factor with a two-fold increased risk of severe COVID-19 infection (OR = 2.37, P = .021). However, after adjustments were made for BMI, this finding lost statistical significance (OR=1.55, P=.13) (Strausz S, et al. BMJ Open Resp Res. 2021;8:e000845).

It is worth noting that a majority of studies identified OSA by indirect and imperfect methods through chart review, ICD codes, and databases. Confirmed OSA based on formal testing with a sleep study in COVID-19 patients remains a challenge. Perhaps well performed screening questionnaires, such as STOP-Bang, Berlin, or NoSAS, can be utilized as was the case in one study. It is also unclear if outcomes of COVID-19 infection differ in patients with treated or untreated OSA, as raised by the CORONADO study. A recent cross-sectional telephone interview survey of patients with confirmed OSA in Iran alluded to higher prevalence of COVID-19 in patients with severe OSA with suggestion of lower prevalence in patients who were currently receiving OSA treatment with positive airway pressure (PAP) therapy (Najafi A, et al. Sleep Health. 2021 Feb;7[1]:14). This is a crucial question as PAP therapy is considered an aerosol-generating procedure (Lance CG. Cleve Clin J Med. 2020 May 5. doi: 10.3949/ccjm.87a.ccc003). Studies have suggested continued use of PAP therapy with additional measures to mitigate the spread of virus, since failure to use PAP could be deleterious to the patient’s quality of life. Interestingly, PAP adherence seemed to have improved during the pandemic as evidenced by a telephonic survey done in New York City that showed 88% of patients with OSA used a PAP device consistently (Attias D, et al. Eur Respir J. 2020 Jul 30;56[1]:2001607. doi: 10.1183/13993003.01607-2020).

In summary, the jury is still out on whether OSA is a facilitator for viral replication, or an independent risk factor for poor prognosis related to COVID-19 infection, or has no clinical relevance to COVID-19. COVID-19 and OSA share comorbidities and pathways leading to a systemic inflammatory cascade. Theoretically, it would make sense that OSA is a risk factor for severe COVID-19 infection; however, it remains to be proven. The recent studies are limited by retrospective and observational nature, imprecise OSA classification/diagnostic criteria, and confounded by difficult to control variables. Further research is needed to expand our understanding of OSA -induced intermittent hypoxemia, inflammation, and endothelial dysfunction that may play a role in COVID-19 morbidity and mortality. Until we have more clarity, close monitoring of OSA patients infected with COVID-19 is recommended along with implementation of safe protocols for continuation of PAP usage during the infectious phase. Identifying underlying comorbid conditions that contribute to worsening of a COVID-19 infectious course is a crucial step in improving clinical outcomes.
 

Dr. Sahni is Assistant Professor of Clinical Medicine, Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, University of Illinois at Chicago. Dr. Cao is Clinical Associate Professor, Division of Sleep Medicine and Division of Neuromuscular Medicine, Department of Psychiatry and Department of Neurology, Stanford (Calif.) University.

Over a year has passed since the first case of COVID-19 was reported in the United States, with over 114 million cases now reported worldwide, and over 2.5 million deaths at the time of this writing (Dong E, et al. Lancet Infect Dis. doi: 10.1016/S1473-3099[20]30120-1). While our vaccination efforts here in the United States have provided a much-needed glimmer of hope, it has been bittersweet, as we recently surpassed the grim milestone of 500,000 COVID-19-related deaths.

The infectious nature of SARS-CoV-2, coupled with the lack of adequate PPE early in the pandemic, led to radical changes in most hospital visitor policies. Rather than welcoming families into the care setting as we have been accustomed, we were forced to restrict access. While well-intentioned, the impact of this on patients, their families – and as we later learned, ourselves – has been devastating. Patients found themselves alone in an unfamiliar environment, infected with a disease there was no effective treatment for, hearing dismal news regarding inpatient and ICU mortality rates on news networks, and families could not see for themselves how their loved ones were progressing in their hospital course.
 

The impact on patient-centered care

The impact of this pandemic on patients and health care providers alike cannot be overstated. Arguably, one of the greatest challenges created by COVID-19 has been its direct assault on the core values of patient-centered care that we have spent decades striving to promote and embody.

Since its identification as a quality gap by the Institute of Medicine in 2001, the definition of patient-centered care has been tweaked over the past 20 years (Institute of Medicine (IOM). Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, D.C: National Academy Press; 2001). Most frameworks include the active participation of patients and their families as part of the health care team, encouraging and facilitating the presence of family members in the care setting, and focusing on patients’ physical comfort and emotional well-being as fundamental tenets of patient centeredness (NEJM Catalyst: What is Patient-Centered Care? Explore the definition, benefits, and examples of patient-centered care. How does patient-centered care translate to new delivery models? January 1,2017).

Families, the “F” in the ABCDEF Bundle, have been recognized as an integral part of care in the ICU setting (Ely EW. Crit Care Med. 2017;45[2]:321). While engagement of family members began with our recognition of their role in emotionally supporting patients and efforts to improve communication, we have also seen the impact of family participation on reducing ICU delirium through frequent re-orientation and encouragement of early mobility (McKenzie J, et al. Australas J Ageing. 2020;39:21). In fact, a recent study has suggested that family members could play an even more active role in detecting and assessing ICU delirium using objective assessment tools (Fiest K, et al. Crit Care Med. 2020;48[7]:954). Post-ICU PTSD has been well described in both ICU survivors as well as in their family members, with evidence that family participation in care of patients during their ICU stay leads to its reduction (Amass TH, et al. Crit Care Med. 2020[Feb];48[2]:176).
 

The emotional toll

Comforting patients and families in times of distress and suffering is something that comes naturally to many in critical care, and our training further improves our ability to do this effectively. No amount of training, however, could have prepared us for the degree and volume of suffering we bore witness to this past year and the resulting moral injury many are still dealing with. We were present for families’ most intimate moments, holding phones and tablets up to patients so their families could say their goodbyes, listening to the “I love yous,” “I’ll miss yous,” “I’m sorrys,” and “Please don’t gos.” Nurses held patients’ hands as they took their last breaths so they wouldn’t die alone and worked to move husbands and wives into the same room so they could be together in their final moments. Entrenched in each of our identities is the role of healer, and we found ourselves questioning our effectiveness in rising to meet suffering on a scale we had never seen before. Little did we understand that while our paradigms were reinforcing the benefits of patient-centered care for patients and their families, that framework was also serving to facilitate our role as healers – that without it, we all suffer.

Rising to the challenge

These unprecedented circumstances led to creative efforts to bridge some of these barriers. Health systems created photo lanyards that providers wore over their PPE so patients could identify their health care team and connect with them on a more human level. Video conferencing technology was brought to the patient bedside using smartphones and tablets to assist them in communicating with their families. Doctors and nurses coordinated multiple calls throughout the day to ensure families felt included in the care plans and were always abreast of any new developments.

All these initiatives were our way of attempting to alleviate some of the suffering we were witnessing, and in some ways felt complicit in. It is in hindsight that we can look back and question if we could have done things differently. We treated family as visitors, when in fact, they are fundamental members of the care team who play an active and critical role in patient care. This was, in part, driven by national unpreparedness when it came to PPE supplies, in addition to misinformation and inconsistent messaging early in the pandemic with regards to the mechanism of transmission of disease from various health organizations. While we did our best given the circumstances, we must not allow this experience to lead us away from the tenets we know to be essential to patient, family, and health care provider well-being.

All in health care met the call to action – nurses, physicians, advanced practice providers, respiratory therapists, nutritionists, pharmacists, physical therapists, patient transporters, environmental service workers, and all others who kept our hospitals and patient care facilities open through this pandemic and embarked on what amounted to a collective, global, ongoing “code-blue alert,” resuscitating patient after patient, hotspot after hotspot, region after region, and country after country. We expanded hospital bed capacities, created ICU beds where there were none, developed novel process protocols, and learned in real time what seemed to help (or not) in treating this novel disease, all while participating in incredible international scientific collaboration and information sharing that has contributed in getting the collective “us” through this first year of the pandemic. We did what we were trained and called to do.
 

Preparing for the future

There will inevitably be another public health crisis, and we must advocate for better preparedness next time, insisting on overall stronger public health systems and pandemic preparedness. We must address our PPE stores and supply chains. We must have disaster preparedness plans that go beyond the scope of mass casualty events and bioterrorism. Beyond physical recovery, we must tend to the factors that impact patients’ long-term recovery, with attention to emotional and psychological well-being. We must advocate for all of this now, while the memories are fresh and before the impact of this collective suffering begins to fade. It can never again be acceptable to exclude families from the health care setting. We must advocate for our patients and for the resources, systems, processes, and support that will allow us to do better.

Dr. Hegab is Associate Director, Pulmonary Hypertension Program, Medical Director, Pulmonary Embolism Response Team, Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital; and Assistant Professor, Wayne State University School of Medicine, Detroit.

Over a year has passed since the first case of COVID-19 was reported in the United States, with over 114 million cases now reported worldwide, and over 2.5 million deaths at the time of this writing (Dong E, et al. Lancet Infect Dis. doi: 10.1016/S1473-3099[20]30120-1). While our vaccination efforts here in the United States have provided a much-needed glimmer of hope, it has been bittersweet, as we recently surpassed the grim milestone of 500,000 COVID-19-related deaths.

The infectious nature of SARS-CoV-2, coupled with the lack of adequate PPE early in the pandemic, led to radical changes in most hospital visitor policies. Rather than welcoming families into the care setting as we have been accustomed, we were forced to restrict access. While well-intentioned, the impact of this on patients, their families – and as we later learned, ourselves – has been devastating. Patients found themselves alone in an unfamiliar environment, infected with a disease there was no effective treatment for, hearing dismal news regarding inpatient and ICU mortality rates on news networks, and families could not see for themselves how their loved ones were progressing in their hospital course.
 

The impact on patient-centered care

The impact of this pandemic on patients and health care providers alike cannot be overstated. Arguably, one of the greatest challenges created by COVID-19 has been its direct assault on the core values of patient-centered care that we have spent decades striving to promote and embody.

Since its identification as a quality gap by the Institute of Medicine in 2001, the definition of patient-centered care has been tweaked over the past 20 years (Institute of Medicine (IOM). Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, D.C: National Academy Press; 2001). Most frameworks include the active participation of patients and their families as part of the health care team, encouraging and facilitating the presence of family members in the care setting, and focusing on patients’ physical comfort and emotional well-being as fundamental tenets of patient centeredness (NEJM Catalyst: What is Patient-Centered Care? Explore the definition, benefits, and examples of patient-centered care. How does patient-centered care translate to new delivery models? January 1,2017).

Families, the “F” in the ABCDEF Bundle, have been recognized as an integral part of care in the ICU setting (Ely EW. Crit Care Med. 2017;45[2]:321). While engagement of family members began with our recognition of their role in emotionally supporting patients and efforts to improve communication, we have also seen the impact of family participation on reducing ICU delirium through frequent re-orientation and encouragement of early mobility (McKenzie J, et al. Australas J Ageing. 2020;39:21). In fact, a recent study has suggested that family members could play an even more active role in detecting and assessing ICU delirium using objective assessment tools (Fiest K, et al. Crit Care Med. 2020;48[7]:954). Post-ICU PTSD has been well described in both ICU survivors as well as in their family members, with evidence that family participation in care of patients during their ICU stay leads to its reduction (Amass TH, et al. Crit Care Med. 2020[Feb];48[2]:176).
 

The emotional toll

Comforting patients and families in times of distress and suffering is something that comes naturally to many in critical care, and our training further improves our ability to do this effectively. No amount of training, however, could have prepared us for the degree and volume of suffering we bore witness to this past year and the resulting moral injury many are still dealing with. We were present for families’ most intimate moments, holding phones and tablets up to patients so their families could say their goodbyes, listening to the “I love yous,” “I’ll miss yous,” “I’m sorrys,” and “Please don’t gos.” Nurses held patients’ hands as they took their last breaths so they wouldn’t die alone and worked to move husbands and wives into the same room so they could be together in their final moments. Entrenched in each of our identities is the role of healer, and we found ourselves questioning our effectiveness in rising to meet suffering on a scale we had never seen before. Little did we understand that while our paradigms were reinforcing the benefits of patient-centered care for patients and their families, that framework was also serving to facilitate our role as healers – that without it, we all suffer.

Rising to the challenge

These unprecedented circumstances led to creative efforts to bridge some of these barriers. Health systems created photo lanyards that providers wore over their PPE so patients could identify their health care team and connect with them on a more human level. Video conferencing technology was brought to the patient bedside using smartphones and tablets to assist them in communicating with their families. Doctors and nurses coordinated multiple calls throughout the day to ensure families felt included in the care plans and were always abreast of any new developments.

All these initiatives were our way of attempting to alleviate some of the suffering we were witnessing, and in some ways felt complicit in. It is in hindsight that we can look back and question if we could have done things differently. We treated family as visitors, when in fact, they are fundamental members of the care team who play an active and critical role in patient care. This was, in part, driven by national unpreparedness when it came to PPE supplies, in addition to misinformation and inconsistent messaging early in the pandemic with regards to the mechanism of transmission of disease from various health organizations. While we did our best given the circumstances, we must not allow this experience to lead us away from the tenets we know to be essential to patient, family, and health care provider well-being.

All in health care met the call to action – nurses, physicians, advanced practice providers, respiratory therapists, nutritionists, pharmacists, physical therapists, patient transporters, environmental service workers, and all others who kept our hospitals and patient care facilities open through this pandemic and embarked on what amounted to a collective, global, ongoing “code-blue alert,” resuscitating patient after patient, hotspot after hotspot, region after region, and country after country. We expanded hospital bed capacities, created ICU beds where there were none, developed novel process protocols, and learned in real time what seemed to help (or not) in treating this novel disease, all while participating in incredible international scientific collaboration and information sharing that has contributed in getting the collective “us” through this first year of the pandemic. We did what we were trained and called to do.
 

Preparing for the future

There will inevitably be another public health crisis, and we must advocate for better preparedness next time, insisting on overall stronger public health systems and pandemic preparedness. We must address our PPE stores and supply chains. We must have disaster preparedness plans that go beyond the scope of mass casualty events and bioterrorism. Beyond physical recovery, we must tend to the factors that impact patients’ long-term recovery, with attention to emotional and psychological well-being. We must advocate for all of this now, while the memories are fresh and before the impact of this collective suffering begins to fade. It can never again be acceptable to exclude families from the health care setting. We must advocate for our patients and for the resources, systems, processes, and support that will allow us to do better.

Dr. Hegab is Associate Director, Pulmonary Hypertension Program, Medical Director, Pulmonary Embolism Response Team, Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital; and Assistant Professor, Wayne State University School of Medicine, Detroit.

Over a year has passed since the first case of COVID-19 was reported in the United States, with over 114 million cases now reported worldwide, and over 2.5 million deaths at the time of this writing (Dong E, et al. Lancet Infect Dis. doi: 10.1016/S1473-3099[20]30120-1). While our vaccination efforts here in the United States have provided a much-needed glimmer of hope, it has been bittersweet, as we recently surpassed the grim milestone of 500,000 COVID-19-related deaths.

The infectious nature of SARS-CoV-2, coupled with the lack of adequate PPE early in the pandemic, led to radical changes in most hospital visitor policies. Rather than welcoming families into the care setting as we have been accustomed, we were forced to restrict access. While well-intentioned, the impact of this on patients, their families – and as we later learned, ourselves – has been devastating. Patients found themselves alone in an unfamiliar environment, infected with a disease there was no effective treatment for, hearing dismal news regarding inpatient and ICU mortality rates on news networks, and families could not see for themselves how their loved ones were progressing in their hospital course.
 

The impact on patient-centered care

The impact of this pandemic on patients and health care providers alike cannot be overstated. Arguably, one of the greatest challenges created by COVID-19 has been its direct assault on the core values of patient-centered care that we have spent decades striving to promote and embody.

Since its identification as a quality gap by the Institute of Medicine in 2001, the definition of patient-centered care has been tweaked over the past 20 years (Institute of Medicine (IOM). Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, D.C: National Academy Press; 2001). Most frameworks include the active participation of patients and their families as part of the health care team, encouraging and facilitating the presence of family members in the care setting, and focusing on patients’ physical comfort and emotional well-being as fundamental tenets of patient centeredness (NEJM Catalyst: What is Patient-Centered Care? Explore the definition, benefits, and examples of patient-centered care. How does patient-centered care translate to new delivery models? January 1,2017).

Families, the “F” in the ABCDEF Bundle, have been recognized as an integral part of care in the ICU setting (Ely EW. Crit Care Med. 2017;45[2]:321). While engagement of family members began with our recognition of their role in emotionally supporting patients and efforts to improve communication, we have also seen the impact of family participation on reducing ICU delirium through frequent re-orientation and encouragement of early mobility (McKenzie J, et al. Australas J Ageing. 2020;39:21). In fact, a recent study has suggested that family members could play an even more active role in detecting and assessing ICU delirium using objective assessment tools (Fiest K, et al. Crit Care Med. 2020;48[7]:954). Post-ICU PTSD has been well described in both ICU survivors as well as in their family members, with evidence that family participation in care of patients during their ICU stay leads to its reduction (Amass TH, et al. Crit Care Med. 2020[Feb];48[2]:176).
 

The emotional toll

Comforting patients and families in times of distress and suffering is something that comes naturally to many in critical care, and our training further improves our ability to do this effectively. No amount of training, however, could have prepared us for the degree and volume of suffering we bore witness to this past year and the resulting moral injury many are still dealing with. We were present for families’ most intimate moments, holding phones and tablets up to patients so their families could say their goodbyes, listening to the “I love yous,” “I’ll miss yous,” “I’m sorrys,” and “Please don’t gos.” Nurses held patients’ hands as they took their last breaths so they wouldn’t die alone and worked to move husbands and wives into the same room so they could be together in their final moments. Entrenched in each of our identities is the role of healer, and we found ourselves questioning our effectiveness in rising to meet suffering on a scale we had never seen before. Little did we understand that while our paradigms were reinforcing the benefits of patient-centered care for patients and their families, that framework was also serving to facilitate our role as healers – that without it, we all suffer.

Rising to the challenge

These unprecedented circumstances led to creative efforts to bridge some of these barriers. Health systems created photo lanyards that providers wore over their PPE so patients could identify their health care team and connect with them on a more human level. Video conferencing technology was brought to the patient bedside using smartphones and tablets to assist them in communicating with their families. Doctors and nurses coordinated multiple calls throughout the day to ensure families felt included in the care plans and were always abreast of any new developments.

All these initiatives were our way of attempting to alleviate some of the suffering we were witnessing, and in some ways felt complicit in. It is in hindsight that we can look back and question if we could have done things differently. We treated family as visitors, when in fact, they are fundamental members of the care team who play an active and critical role in patient care. This was, in part, driven by national unpreparedness when it came to PPE supplies, in addition to misinformation and inconsistent messaging early in the pandemic with regards to the mechanism of transmission of disease from various health organizations. While we did our best given the circumstances, we must not allow this experience to lead us away from the tenets we know to be essential to patient, family, and health care provider well-being.

All in health care met the call to action – nurses, physicians, advanced practice providers, respiratory therapists, nutritionists, pharmacists, physical therapists, patient transporters, environmental service workers, and all others who kept our hospitals and patient care facilities open through this pandemic and embarked on what amounted to a collective, global, ongoing “code-blue alert,” resuscitating patient after patient, hotspot after hotspot, region after region, and country after country. We expanded hospital bed capacities, created ICU beds where there were none, developed novel process protocols, and learned in real time what seemed to help (or not) in treating this novel disease, all while participating in incredible international scientific collaboration and information sharing that has contributed in getting the collective “us” through this first year of the pandemic. We did what we were trained and called to do.
 

Preparing for the future

There will inevitably be another public health crisis, and we must advocate for better preparedness next time, insisting on overall stronger public health systems and pandemic preparedness. We must address our PPE stores and supply chains. We must have disaster preparedness plans that go beyond the scope of mass casualty events and bioterrorism. Beyond physical recovery, we must tend to the factors that impact patients’ long-term recovery, with attention to emotional and psychological well-being. We must advocate for all of this now, while the memories are fresh and before the impact of this collective suffering begins to fade. It can never again be acceptable to exclude families from the health care setting. We must advocate for our patients and for the resources, systems, processes, and support that will allow us to do better.

Dr. Hegab is Associate Director, Pulmonary Hypertension Program, Medical Director, Pulmonary Embolism Response Team, Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital; and Assistant Professor, Wayne State University School of Medicine, Detroit.