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New ACR/EULAR gout classification criteria offer better sensitivity, specificity
The presence of monosodium urate monohydrate crystals in a symptomatic joint, bursa, or tophus is sufficient to diagnose gout, according to new gout classification criteria from the American College of Rheumatology and the European League Against Rheumatism.
When symptomatic urate crystals are missing, other signs and symptoms are considered and scored; a score of 8 or more constitutes gout. “The threshold chosen for this classification criteria set yielded the best combination of sensitivity and specificity,” at 92% and 89%, respectively, and outperformed previous classification schemes, said the authors, led by Dr. Tuhina Neogi of Boston University.
To qualify for gout, patients must first have at least one episode of swelling, pain, or tenderness in a peripheral joint or bursa. They get a score of 1 if that happens in the ankle or midfoot, and a score of 2 if it involves a metatarsophalangeal joint. If the affected joint is red and too painful to touch and use, patients get an additional score of 3. Chalklike drainage from a subcutaneous nodule in a gout-prone area, and serum urate at or above 10 mg/dL, both get a score of 4. Imaging of one or more gout erosions in the hands or feet also gets a score of 4 (Arthritis Rheumatol. 2015 Oct;67[10]:2557-68. doi: 10.1002/art.39254).
Overall, the criteria incorporate clinical, laboratory, and imaging evidence. A web-based calculator makes the scoring easy.
“Although MSU [monosodium urate monohydrate] crystal results are extremely helpful when positive, they are not a feasible universal standard, particularly because many potential study subjects are likely to be recruited from nonrheumatology settings. We aimed to develop a new set of criteria that could be flexible enough to enable accurate classification of gout regardless of MSU status,” the authors said.
“This classification criteria set will enable a standardized approach to identifying a relatively homogeneous group of individuals who have the clinical entity of gout for enrollment into studies. The criteria permit characterization of an individual as having gout regardless of whether he or she is currently experiencing an acute symptomatic episode and regardless of any comorbidities,” they said.
The hope of the work is to facilitate a better understanding of gout and speed development of new trials and treatments. The criteria will “help to ensure that patients with the same disease are being evaluated, which will enhance our ability to study the disease, including performing outcomes studies and clinical trials,” Dr. Neogi said in a written statement.
Previous gout classification criteria were developed when advanced imaging was not available. “Additionally, the increasing prevalence of gout, advances in therapeutics, and the development of international research collaborations to understand the impact, mechanisms, and optimal treatment of this condition emphasize the need for accurate and uniform classification criteria for gout,” according to the statement.
The new criteria are based on a systematic review of the literature on advanced gout imaging; a diagnostic study in which the presence of MSU crystals in synovial fluid or tophi was the gold standard; a ranking exercise of paper patient cases; and a multicriterion decision analysis exercise. The criteria were then validated in 330 patients.
The work was supported in part by the National Institutes of Health, the Agency for Healthcare Research and Quality, and Arthritis New Zealand. Numerous authors reported receiving consulting fees, speaking fees, and/or honoraria from companies that market drugs or specialty foods for gout.
The presence of monosodium urate monohydrate crystals in a symptomatic joint, bursa, or tophus is sufficient to diagnose gout, according to new gout classification criteria from the American College of Rheumatology and the European League Against Rheumatism.
When symptomatic urate crystals are missing, other signs and symptoms are considered and scored; a score of 8 or more constitutes gout. “The threshold chosen for this classification criteria set yielded the best combination of sensitivity and specificity,” at 92% and 89%, respectively, and outperformed previous classification schemes, said the authors, led by Dr. Tuhina Neogi of Boston University.
To qualify for gout, patients must first have at least one episode of swelling, pain, or tenderness in a peripheral joint or bursa. They get a score of 1 if that happens in the ankle or midfoot, and a score of 2 if it involves a metatarsophalangeal joint. If the affected joint is red and too painful to touch and use, patients get an additional score of 3. Chalklike drainage from a subcutaneous nodule in a gout-prone area, and serum urate at or above 10 mg/dL, both get a score of 4. Imaging of one or more gout erosions in the hands or feet also gets a score of 4 (Arthritis Rheumatol. 2015 Oct;67[10]:2557-68. doi: 10.1002/art.39254).
Overall, the criteria incorporate clinical, laboratory, and imaging evidence. A web-based calculator makes the scoring easy.
“Although MSU [monosodium urate monohydrate] crystal results are extremely helpful when positive, they are not a feasible universal standard, particularly because many potential study subjects are likely to be recruited from nonrheumatology settings. We aimed to develop a new set of criteria that could be flexible enough to enable accurate classification of gout regardless of MSU status,” the authors said.
“This classification criteria set will enable a standardized approach to identifying a relatively homogeneous group of individuals who have the clinical entity of gout for enrollment into studies. The criteria permit characterization of an individual as having gout regardless of whether he or she is currently experiencing an acute symptomatic episode and regardless of any comorbidities,” they said.
The hope of the work is to facilitate a better understanding of gout and speed development of new trials and treatments. The criteria will “help to ensure that patients with the same disease are being evaluated, which will enhance our ability to study the disease, including performing outcomes studies and clinical trials,” Dr. Neogi said in a written statement.
Previous gout classification criteria were developed when advanced imaging was not available. “Additionally, the increasing prevalence of gout, advances in therapeutics, and the development of international research collaborations to understand the impact, mechanisms, and optimal treatment of this condition emphasize the need for accurate and uniform classification criteria for gout,” according to the statement.
The new criteria are based on a systematic review of the literature on advanced gout imaging; a diagnostic study in which the presence of MSU crystals in synovial fluid or tophi was the gold standard; a ranking exercise of paper patient cases; and a multicriterion decision analysis exercise. The criteria were then validated in 330 patients.
The work was supported in part by the National Institutes of Health, the Agency for Healthcare Research and Quality, and Arthritis New Zealand. Numerous authors reported receiving consulting fees, speaking fees, and/or honoraria from companies that market drugs or specialty foods for gout.
The presence of monosodium urate monohydrate crystals in a symptomatic joint, bursa, or tophus is sufficient to diagnose gout, according to new gout classification criteria from the American College of Rheumatology and the European League Against Rheumatism.
When symptomatic urate crystals are missing, other signs and symptoms are considered and scored; a score of 8 or more constitutes gout. “The threshold chosen for this classification criteria set yielded the best combination of sensitivity and specificity,” at 92% and 89%, respectively, and outperformed previous classification schemes, said the authors, led by Dr. Tuhina Neogi of Boston University.
To qualify for gout, patients must first have at least one episode of swelling, pain, or tenderness in a peripheral joint or bursa. They get a score of 1 if that happens in the ankle or midfoot, and a score of 2 if it involves a metatarsophalangeal joint. If the affected joint is red and too painful to touch and use, patients get an additional score of 3. Chalklike drainage from a subcutaneous nodule in a gout-prone area, and serum urate at or above 10 mg/dL, both get a score of 4. Imaging of one or more gout erosions in the hands or feet also gets a score of 4 (Arthritis Rheumatol. 2015 Oct;67[10]:2557-68. doi: 10.1002/art.39254).
Overall, the criteria incorporate clinical, laboratory, and imaging evidence. A web-based calculator makes the scoring easy.
“Although MSU [monosodium urate monohydrate] crystal results are extremely helpful when positive, they are not a feasible universal standard, particularly because many potential study subjects are likely to be recruited from nonrheumatology settings. We aimed to develop a new set of criteria that could be flexible enough to enable accurate classification of gout regardless of MSU status,” the authors said.
“This classification criteria set will enable a standardized approach to identifying a relatively homogeneous group of individuals who have the clinical entity of gout for enrollment into studies. The criteria permit characterization of an individual as having gout regardless of whether he or she is currently experiencing an acute symptomatic episode and regardless of any comorbidities,” they said.
The hope of the work is to facilitate a better understanding of gout and speed development of new trials and treatments. The criteria will “help to ensure that patients with the same disease are being evaluated, which will enhance our ability to study the disease, including performing outcomes studies and clinical trials,” Dr. Neogi said in a written statement.
Previous gout classification criteria were developed when advanced imaging was not available. “Additionally, the increasing prevalence of gout, advances in therapeutics, and the development of international research collaborations to understand the impact, mechanisms, and optimal treatment of this condition emphasize the need for accurate and uniform classification criteria for gout,” according to the statement.
The new criteria are based on a systematic review of the literature on advanced gout imaging; a diagnostic study in which the presence of MSU crystals in synovial fluid or tophi was the gold standard; a ranking exercise of paper patient cases; and a multicriterion decision analysis exercise. The criteria were then validated in 330 patients.
The work was supported in part by the National Institutes of Health, the Agency for Healthcare Research and Quality, and Arthritis New Zealand. Numerous authors reported receiving consulting fees, speaking fees, and/or honoraria from companies that market drugs or specialty foods for gout.
FROM ARTHRITIS & RHEUMATOLOGY
Joint Commission launches educational campaign on antibiotic use
The Joint Commission has introduced a multimedia campaign to educate the public on the health risks associated with antibiotic overuse, the group announced Sept. 14.
The Speak Up: Antibiotics program aims to educate consumers on appropriate use of antibiotics, and includes resources to help patients determine which illnesses may or may not need antibiotic treatment. The website includes an infographic, podcast, and animated video.
The initiative is part of the Speak Up series, a program that encourages patients to become more active in their medical decisions through self-education and advocacy.
About 2 million people in the United States become infected with antibiotic-resistant bacteria each year, the Joint Commission reported.
“Antibiotics also can kill good bacteria in the body, potentially leading to other problems such as diarrhea or yeast infections,” the organization said in a statement. “As a result, antibiotic overuse has become a critical health and patient safety concern, especially in young children and seniors, who are at higher risk for illness.”
Click here for more information on the Speak Up: Antibiotics campaign.
The Joint Commission has introduced a multimedia campaign to educate the public on the health risks associated with antibiotic overuse, the group announced Sept. 14.
The Speak Up: Antibiotics program aims to educate consumers on appropriate use of antibiotics, and includes resources to help patients determine which illnesses may or may not need antibiotic treatment. The website includes an infographic, podcast, and animated video.
The initiative is part of the Speak Up series, a program that encourages patients to become more active in their medical decisions through self-education and advocacy.
About 2 million people in the United States become infected with antibiotic-resistant bacteria each year, the Joint Commission reported.
“Antibiotics also can kill good bacteria in the body, potentially leading to other problems such as diarrhea or yeast infections,” the organization said in a statement. “As a result, antibiotic overuse has become a critical health and patient safety concern, especially in young children and seniors, who are at higher risk for illness.”
Click here for more information on the Speak Up: Antibiotics campaign.
The Joint Commission has introduced a multimedia campaign to educate the public on the health risks associated with antibiotic overuse, the group announced Sept. 14.
The Speak Up: Antibiotics program aims to educate consumers on appropriate use of antibiotics, and includes resources to help patients determine which illnesses may or may not need antibiotic treatment. The website includes an infographic, podcast, and animated video.
The initiative is part of the Speak Up series, a program that encourages patients to become more active in their medical decisions through self-education and advocacy.
About 2 million people in the United States become infected with antibiotic-resistant bacteria each year, the Joint Commission reported.
“Antibiotics also can kill good bacteria in the body, potentially leading to other problems such as diarrhea or yeast infections,” the organization said in a statement. “As a result, antibiotic overuse has become a critical health and patient safety concern, especially in young children and seniors, who are at higher risk for illness.”
Click here for more information on the Speak Up: Antibiotics campaign.
Psoriasis patients more likely to have type D personalities
Incidence of type D personality was significantly more common in patients with moderate to severe psoriasis, compared with a healthy control group, according to Dr. Alejandro Molina-Leyva of Hospital Torrecardenas, Almeria, Spain, and his associates.
People with type D, or distressed, personality tend to be more worried and irritable, and tend to display more negative emotions than do others. Of the 90 patients with moderate to severe psoriasis included in the study, 39% had type D personality, compared with 24% of the 82 members of the control group. The odds ratio for psoriasis patients developing type D personality was 2.1.
Psoriasis patients with type D personalities had significantly worse general, sexual, and psoriasis-related health-related quality of life, compared with psoriasis patients without type D personality. In addition, type D personality psoriasis patients were much more likely to experience anxiety or depression than were healthy people with type D personality, with an OR of 3.2.
“It may be that the higher prevalence of type D personality in moderate to severe psoriasis is, at least in part, the result of accumulated psychic damage over years of evolution of the disease. It is important to conduct prospective studies with incident cases of psoriasis to clarify the relationship between type D personality and psoriasis,” the investigators noted.
Find the full study here in the Journal of the European Academy of Dermatology and Venereology (doi: 10.1111/jdv.12960).
Incidence of type D personality was significantly more common in patients with moderate to severe psoriasis, compared with a healthy control group, according to Dr. Alejandro Molina-Leyva of Hospital Torrecardenas, Almeria, Spain, and his associates.
People with type D, or distressed, personality tend to be more worried and irritable, and tend to display more negative emotions than do others. Of the 90 patients with moderate to severe psoriasis included in the study, 39% had type D personality, compared with 24% of the 82 members of the control group. The odds ratio for psoriasis patients developing type D personality was 2.1.
Psoriasis patients with type D personalities had significantly worse general, sexual, and psoriasis-related health-related quality of life, compared with psoriasis patients without type D personality. In addition, type D personality psoriasis patients were much more likely to experience anxiety or depression than were healthy people with type D personality, with an OR of 3.2.
“It may be that the higher prevalence of type D personality in moderate to severe psoriasis is, at least in part, the result of accumulated psychic damage over years of evolution of the disease. It is important to conduct prospective studies with incident cases of psoriasis to clarify the relationship between type D personality and psoriasis,” the investigators noted.
Find the full study here in the Journal of the European Academy of Dermatology and Venereology (doi: 10.1111/jdv.12960).
Incidence of type D personality was significantly more common in patients with moderate to severe psoriasis, compared with a healthy control group, according to Dr. Alejandro Molina-Leyva of Hospital Torrecardenas, Almeria, Spain, and his associates.
People with type D, or distressed, personality tend to be more worried and irritable, and tend to display more negative emotions than do others. Of the 90 patients with moderate to severe psoriasis included in the study, 39% had type D personality, compared with 24% of the 82 members of the control group. The odds ratio for psoriasis patients developing type D personality was 2.1.
Psoriasis patients with type D personalities had significantly worse general, sexual, and psoriasis-related health-related quality of life, compared with psoriasis patients without type D personality. In addition, type D personality psoriasis patients were much more likely to experience anxiety or depression than were healthy people with type D personality, with an OR of 3.2.
“It may be that the higher prevalence of type D personality in moderate to severe psoriasis is, at least in part, the result of accumulated psychic damage over years of evolution of the disease. It is important to conduct prospective studies with incident cases of psoriasis to clarify the relationship between type D personality and psoriasis,” the investigators noted.
Find the full study here in the Journal of the European Academy of Dermatology and Venereology (doi: 10.1111/jdv.12960).
FROM THE JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY
7 Hours of Sleep Can Reduce Heart Disease
Too little sleep, or poor-quality sleep, may be linked to early markers of heart disease in asymptomatic healthy adults, a new study from South Korea suggests.
More than 47,000 men and women completed a sleep questionnaire and underwent assessments of coronary artery calcium and plaque as well as brachial-ankle pulse wave velocity (PWV).
Participants' average sleep duration was 6.4 hours per night, and about 84 percent said their sleep quality was "good," according to Dr. Chan-Won Kim of Kangbuk Samsung Hospital of Sungkyunkwan University School of Medicine in Seoul, South Korea and colleagues.
The researchers considered those who got five hours or less per night to be "short" sleepers, and those who got nine or more hours to be "long" sleepers.
Short sleepers had 50% more coronary artery calcium than those who slept for seven hours per night, according to the results in Arteriosclerosis, Thrombosis and Vascular Biology. Long sleepers had 70% more calcium than those who slept seven hours.
Those who reported poor sleep quality also tended to have more coronary calcium and more arterial stiffness.
In a 2013 study, people who tended to get less than six hours of sleep nightly were more likely to have high blood pressure, high cholesterol, diabetes and to be obese.
"Adults with poor sleep quality have stiffer arteries than those who sleep seven hours a day or had good sleep quality," co-lead author Dr. Yoosoo Chang of the Center for Cohort Studies at Kangbuk Samsung Hospital said in a statement accompanying the study. "Overall, we saw the lowest levels of vascular disease in adults sleeping seven hours a day and reporting good sleep quality."
Short sleepers were more likely than others to be older, have depression, type 2 diabetes or to be smokers.
"The associations of too short or too long sleep duration and of poor sleep quality with early indicators of heart disease, such as coronary calcium and arterial stiffness, provides strong support to the increasing body of evidence that links inadequate sleep with an increased risk of heart attacks," Kim said by email.
"It is still not clear if inadequate sleep is the cause or the consequence of ill health," but good sleep hygiene, including avoiding electronic media at bedtime, should be part of a healthy lifestyle, Kim said.
"For doctors, it can be helpful to evaluate sleep duration and sleep quality when assessing the health status of their patients," Kim said.
Too little sleep, or poor-quality sleep, may be linked to early markers of heart disease in asymptomatic healthy adults, a new study from South Korea suggests.
More than 47,000 men and women completed a sleep questionnaire and underwent assessments of coronary artery calcium and plaque as well as brachial-ankle pulse wave velocity (PWV).
Participants' average sleep duration was 6.4 hours per night, and about 84 percent said their sleep quality was "good," according to Dr. Chan-Won Kim of Kangbuk Samsung Hospital of Sungkyunkwan University School of Medicine in Seoul, South Korea and colleagues.
The researchers considered those who got five hours or less per night to be "short" sleepers, and those who got nine or more hours to be "long" sleepers.
Short sleepers had 50% more coronary artery calcium than those who slept for seven hours per night, according to the results in Arteriosclerosis, Thrombosis and Vascular Biology. Long sleepers had 70% more calcium than those who slept seven hours.
Those who reported poor sleep quality also tended to have more coronary calcium and more arterial stiffness.
In a 2013 study, people who tended to get less than six hours of sleep nightly were more likely to have high blood pressure, high cholesterol, diabetes and to be obese.
"Adults with poor sleep quality have stiffer arteries than those who sleep seven hours a day or had good sleep quality," co-lead author Dr. Yoosoo Chang of the Center for Cohort Studies at Kangbuk Samsung Hospital said in a statement accompanying the study. "Overall, we saw the lowest levels of vascular disease in adults sleeping seven hours a day and reporting good sleep quality."
Short sleepers were more likely than others to be older, have depression, type 2 diabetes or to be smokers.
"The associations of too short or too long sleep duration and of poor sleep quality with early indicators of heart disease, such as coronary calcium and arterial stiffness, provides strong support to the increasing body of evidence that links inadequate sleep with an increased risk of heart attacks," Kim said by email.
"It is still not clear if inadequate sleep is the cause or the consequence of ill health," but good sleep hygiene, including avoiding electronic media at bedtime, should be part of a healthy lifestyle, Kim said.
"For doctors, it can be helpful to evaluate sleep duration and sleep quality when assessing the health status of their patients," Kim said.
Too little sleep, or poor-quality sleep, may be linked to early markers of heart disease in asymptomatic healthy adults, a new study from South Korea suggests.
More than 47,000 men and women completed a sleep questionnaire and underwent assessments of coronary artery calcium and plaque as well as brachial-ankle pulse wave velocity (PWV).
Participants' average sleep duration was 6.4 hours per night, and about 84 percent said their sleep quality was "good," according to Dr. Chan-Won Kim of Kangbuk Samsung Hospital of Sungkyunkwan University School of Medicine in Seoul, South Korea and colleagues.
The researchers considered those who got five hours or less per night to be "short" sleepers, and those who got nine or more hours to be "long" sleepers.
Short sleepers had 50% more coronary artery calcium than those who slept for seven hours per night, according to the results in Arteriosclerosis, Thrombosis and Vascular Biology. Long sleepers had 70% more calcium than those who slept seven hours.
Those who reported poor sleep quality also tended to have more coronary calcium and more arterial stiffness.
In a 2013 study, people who tended to get less than six hours of sleep nightly were more likely to have high blood pressure, high cholesterol, diabetes and to be obese.
"Adults with poor sleep quality have stiffer arteries than those who sleep seven hours a day or had good sleep quality," co-lead author Dr. Yoosoo Chang of the Center for Cohort Studies at Kangbuk Samsung Hospital said in a statement accompanying the study. "Overall, we saw the lowest levels of vascular disease in adults sleeping seven hours a day and reporting good sleep quality."
Short sleepers were more likely than others to be older, have depression, type 2 diabetes or to be smokers.
"The associations of too short or too long sleep duration and of poor sleep quality with early indicators of heart disease, such as coronary calcium and arterial stiffness, provides strong support to the increasing body of evidence that links inadequate sleep with an increased risk of heart attacks," Kim said by email.
"It is still not clear if inadequate sleep is the cause or the consequence of ill health," but good sleep hygiene, including avoiding electronic media at bedtime, should be part of a healthy lifestyle, Kim said.
"For doctors, it can be helpful to evaluate sleep duration and sleep quality when assessing the health status of their patients," Kim said.
Gene linked to aggressive AML
Photo courtesy of NIH
The gene FOXC1 is associated with aggressive acute myeloid leukemia (AML), according to research published in Cancer Cell.
Researchers said tissue-inappropriate derepression of FOXC1 has functional consequences and prognostic significance in AML.
They found evidence suggesting that FOXC1 enhances clonogenic potential, helps block monocyte/macrophage differentiation, accelerates leukemia onset in mice, and leads to inferior survival in AML patients.
“This is an important finding which helps us understand how acute myeloid leukemia develops and why some cases of AML are more aggressive than others,” said study author Tim Somervaille, MBBS, PhD, of The University of Manchester in the UK.
“Here, instead of being faulty or mutated, this normal gene is turned on in the wrong place at the wrong time, which makes the cancer grow more rapidly. There are certain situations where this gene is necessary, as in the development of the eye and skeleton before birth, but when it’s switched on in the wrong tissue, it causes more aggressive forms of leukemia.”
Dr Somervaille and his colleagues said FOXC1 is expressed in at least 20% of human AML cases but not in normal hematopoietic populations.
The researchers analyzed levels of transcription factor genes in data from published studies to identify transcription regulators expressed in human AML hematopoietic stem and progenitor cells (HSPCs) but not normal HSPCs. In these studies, FOXC1 was among the genes that were most highly upregulated in AML HSPCs.
Further investigation revealed that FOXC1 expression is associated with mutations in NPM1 and t(6;9) but no other recurring mutations in AML.
When Dr Somervaille and his colleagues conducted experiments with human AML cells, they found that FOXC1 “contributes to oncogenic potential by maintaining differentiation block and clonogenic activity.”
In vitro experiments with normal HSPCs showed that FOXC1 expression temporarily impairs myeloid differentiation. In mice, expression of FOXC1 in normal HSPCs reduced donor:recipient chimerism in the blood and skewed differentiation toward the myeloid lineage and away from the B-cell lineage.
By comparing samples from AML patients, the researchers found that FOXC1 expression is associated with high HOX gene expression.
Subsequent experiments showed that FOXC1 collaborates with HOXA9 to enhance clonogenic potential and cell-cycle progression, help block monocyte/macrophage and B-lineage differentiation, and accelerate the onset of symptomatic leukemia in mice.
To determine if the same effects occur in humans, the researchers again analyzed data from AML patients. The results indicated that FOXC1 expression helps block monocyte/macrophage differentiation and leads to inferior survival.
Dr Somervaille and his colleagues said these findings may have therapeutic implications, as previous research has shown that, in basal-like breast cancer, high FOXC1 expression renders cells more susceptible to pharmacological inhibition of NF-kB. But additional research is needed to investigate therapeutic implications for AML. 
Photo courtesy of NIH
The gene FOXC1 is associated with aggressive acute myeloid leukemia (AML), according to research published in Cancer Cell.
Researchers said tissue-inappropriate derepression of FOXC1 has functional consequences and prognostic significance in AML.
They found evidence suggesting that FOXC1 enhances clonogenic potential, helps block monocyte/macrophage differentiation, accelerates leukemia onset in mice, and leads to inferior survival in AML patients.
“This is an important finding which helps us understand how acute myeloid leukemia develops and why some cases of AML are more aggressive than others,” said study author Tim Somervaille, MBBS, PhD, of The University of Manchester in the UK.
“Here, instead of being faulty or mutated, this normal gene is turned on in the wrong place at the wrong time, which makes the cancer grow more rapidly. There are certain situations where this gene is necessary, as in the development of the eye and skeleton before birth, but when it’s switched on in the wrong tissue, it causes more aggressive forms of leukemia.”
Dr Somervaille and his colleagues said FOXC1 is expressed in at least 20% of human AML cases but not in normal hematopoietic populations.
The researchers analyzed levels of transcription factor genes in data from published studies to identify transcription regulators expressed in human AML hematopoietic stem and progenitor cells (HSPCs) but not normal HSPCs. In these studies, FOXC1 was among the genes that were most highly upregulated in AML HSPCs.
Further investigation revealed that FOXC1 expression is associated with mutations in NPM1 and t(6;9) but no other recurring mutations in AML.
When Dr Somervaille and his colleagues conducted experiments with human AML cells, they found that FOXC1 “contributes to oncogenic potential by maintaining differentiation block and clonogenic activity.”
In vitro experiments with normal HSPCs showed that FOXC1 expression temporarily impairs myeloid differentiation. In mice, expression of FOXC1 in normal HSPCs reduced donor:recipient chimerism in the blood and skewed differentiation toward the myeloid lineage and away from the B-cell lineage.
By comparing samples from AML patients, the researchers found that FOXC1 expression is associated with high HOX gene expression.
Subsequent experiments showed that FOXC1 collaborates with HOXA9 to enhance clonogenic potential and cell-cycle progression, help block monocyte/macrophage and B-lineage differentiation, and accelerate the onset of symptomatic leukemia in mice.
To determine if the same effects occur in humans, the researchers again analyzed data from AML patients. The results indicated that FOXC1 expression helps block monocyte/macrophage differentiation and leads to inferior survival.
Dr Somervaille and his colleagues said these findings may have therapeutic implications, as previous research has shown that, in basal-like breast cancer, high FOXC1 expression renders cells more susceptible to pharmacological inhibition of NF-kB. But additional research is needed to investigate therapeutic implications for AML.
Photo courtesy of NIH
The gene FOXC1 is associated with aggressive acute myeloid leukemia (AML), according to research published in Cancer Cell.
Researchers said tissue-inappropriate derepression of FOXC1 has functional consequences and prognostic significance in AML.
They found evidence suggesting that FOXC1 enhances clonogenic potential, helps block monocyte/macrophage differentiation, accelerates leukemia onset in mice, and leads to inferior survival in AML patients.
“This is an important finding which helps us understand how acute myeloid leukemia develops and why some cases of AML are more aggressive than others,” said study author Tim Somervaille, MBBS, PhD, of The University of Manchester in the UK.
“Here, instead of being faulty or mutated, this normal gene is turned on in the wrong place at the wrong time, which makes the cancer grow more rapidly. There are certain situations where this gene is necessary, as in the development of the eye and skeleton before birth, but when it’s switched on in the wrong tissue, it causes more aggressive forms of leukemia.”
Dr Somervaille and his colleagues said FOXC1 is expressed in at least 20% of human AML cases but not in normal hematopoietic populations.
The researchers analyzed levels of transcription factor genes in data from published studies to identify transcription regulators expressed in human AML hematopoietic stem and progenitor cells (HSPCs) but not normal HSPCs. In these studies, FOXC1 was among the genes that were most highly upregulated in AML HSPCs.
Further investigation revealed that FOXC1 expression is associated with mutations in NPM1 and t(6;9) but no other recurring mutations in AML.
When Dr Somervaille and his colleagues conducted experiments with human AML cells, they found that FOXC1 “contributes to oncogenic potential by maintaining differentiation block and clonogenic activity.”
In vitro experiments with normal HSPCs showed that FOXC1 expression temporarily impairs myeloid differentiation. In mice, expression of FOXC1 in normal HSPCs reduced donor:recipient chimerism in the blood and skewed differentiation toward the myeloid lineage and away from the B-cell lineage.
By comparing samples from AML patients, the researchers found that FOXC1 expression is associated with high HOX gene expression.
Subsequent experiments showed that FOXC1 collaborates with HOXA9 to enhance clonogenic potential and cell-cycle progression, help block monocyte/macrophage and B-lineage differentiation, and accelerate the onset of symptomatic leukemia in mice.
To determine if the same effects occur in humans, the researchers again analyzed data from AML patients. The results indicated that FOXC1 expression helps block monocyte/macrophage differentiation and leads to inferior survival.
Dr Somervaille and his colleagues said these findings may have therapeutic implications, as previous research has shown that, in basal-like breast cancer, high FOXC1 expression renders cells more susceptible to pharmacological inhibition of NF-kB. But additional research is needed to investigate therapeutic implications for AML.
Living near dams increases malaria risk, study shows
Photo courtesy of the
International Water
Management Institute
More than 1 million people in sub-Saharan Africa will contract malaria this year because they live near a large dam, according to a study published in Malaria Journal.
For the first time, researchers correlated the location of large dams in sub-Saharan Africa with the incidence of malaria.
And they found evidence to suggest that construction of an expected 78 major new dams over the next few years will lead to an additional 56,000 malaria cases annually.
The researchers said these findings have major implications for new dam projects and how health impacts should be assessed prior to construction.
“Dams are at the center of much development planning in Africa,” said study author Solomon Kibret, a graduate student at the University of New England in Armidale, New South Wales, Australia.
“While dams clearly bring many benefits—contributing to economic growth, poverty alleviation, and food security—adverse malaria impacts need to be addressed or they will undermine the sustainability of Africa’s drive for development.”
As part of the CGIAR Research Program on Water, Land, and Ecosystems, Kibret and colleagues looked at 1268 dams in sub-Saharan Africa. Of these, just under two-thirds (n=723) are in malarious areas.
The researchers compared detailed maps of malaria incidence with the dam sites. The number of annual malaria cases associated with the dams was estimated by comparing the number of cases for communities less than 5 kilometers from the dam reservoir with the number of cases for communities further away.
The team found that 15 million people live within 5 kilometers of dam reservoirs and are therefore at risk of contracting malaria. And at least 1.1 million malaria cases annually are linked to the presence of the dams.
“Our study showed that the population at risk of malaria around dams is at least 4 times greater than previously estimated,” Kibret said, noting that the authors were conservative in all their analyses.
The risk is particularly high in areas of sub-Saharan Africa with “unstable” malaria transmission, where malaria is seasonal. The study indicated that the impact of dams on malaria in unstable areas could either lead to intensified malaria transmission or change the nature of transmission from seasonal to perennial.
Explaining the risk
Previous research revealed increases in malaria incidence near major sub-Saharan dams such as the Akosombo Dam in Ghana, the Koka Dam in Ethiopia, and the Kamburu Dam in Kenya. But until now, no attempt has been made to assess the cumulative effect of large dam-building on malaria.
Malaria is transmitted by the Anopheles mosquito, which needs slow-moving or stagnant water in which to breed. Dam reservoirs, particularly shallow puddles that often form along shorelines, provide a perfect environment for the insects to multiply. Thus, dam construction can intensify transmission and shift patterns of malaria infection.
Many African countries are planning new dams to help drive economic growth and increase water security. Improved water storage for growing populations, irrigation, and hydropower generation are needed for a fast-developing continent, but the researchers warn that building new dams has potential costs as well as benefits.
“Dams are an important option for governments anxious to develop,” said study author Matthew McCartney, PhD, of the International Water Management Institute in Vientiane, Laos.
“But it is unethical that people living close to them pay the price of that development through increased suffering and, possibly in extreme cases, loss of life due to disease.”
Lowering the risk
The researchers noted that, despite growing evidence of the impact of dams on malaria, there is scant evidence of their negative impacts being fully offset.
The team therefore made recommendations for managing the increased malaria risk. They said dam reservoirs could be more effectively designed and managed to reduce mosquito breeding. For instance, one option is to adopt operating schedules that, at critical times, dry out shoreline areas where mosquitoes tend to breed.
The researchers said dam developers should also consider increasing investment in integrated malaria intervention programs that include measures such as bed net distribution. Other environmental controls, such as introducing fish that eat mosquito larva in dam reservoirs, could also help reduce malaria cases in some instances.
“The bottom line is that adverse malaria impacts of dams routinely receive recognition in Environmental Impact Assessments, and areas around dams are frequently earmarked for intensive control efforts,” said study author Jonathan Lautze, PhD, of the International Water Management Institute in Pretoria, South Africa.
“The findings of our work hammer home the reality that this recognition and effort—well-intentioned though it may be—is simply not sufficient. Given the need for water resources development in Africa, malaria control around dams requires interdisciplinary cooperation, particularly between water and health communities. Malaria must be addressed while planning, designing, and operating African dams.”
Photo courtesy of the
International Water
Management Institute
More than 1 million people in sub-Saharan Africa will contract malaria this year because they live near a large dam, according to a study published in Malaria Journal.
For the first time, researchers correlated the location of large dams in sub-Saharan Africa with the incidence of malaria.
And they found evidence to suggest that construction of an expected 78 major new dams over the next few years will lead to an additional 56,000 malaria cases annually.
The researchers said these findings have major implications for new dam projects and how health impacts should be assessed prior to construction.
“Dams are at the center of much development planning in Africa,” said study author Solomon Kibret, a graduate student at the University of New England in Armidale, New South Wales, Australia.
“While dams clearly bring many benefits—contributing to economic growth, poverty alleviation, and food security—adverse malaria impacts need to be addressed or they will undermine the sustainability of Africa’s drive for development.”
As part of the CGIAR Research Program on Water, Land, and Ecosystems, Kibret and colleagues looked at 1268 dams in sub-Saharan Africa. Of these, just under two-thirds (n=723) are in malarious areas.
The researchers compared detailed maps of malaria incidence with the dam sites. The number of annual malaria cases associated with the dams was estimated by comparing the number of cases for communities less than 5 kilometers from the dam reservoir with the number of cases for communities further away.
The team found that 15 million people live within 5 kilometers of dam reservoirs and are therefore at risk of contracting malaria. And at least 1.1 million malaria cases annually are linked to the presence of the dams.
“Our study showed that the population at risk of malaria around dams is at least 4 times greater than previously estimated,” Kibret said, noting that the authors were conservative in all their analyses.
The risk is particularly high in areas of sub-Saharan Africa with “unstable” malaria transmission, where malaria is seasonal. The study indicated that the impact of dams on malaria in unstable areas could either lead to intensified malaria transmission or change the nature of transmission from seasonal to perennial.
Explaining the risk
Previous research revealed increases in malaria incidence near major sub-Saharan dams such as the Akosombo Dam in Ghana, the Koka Dam in Ethiopia, and the Kamburu Dam in Kenya. But until now, no attempt has been made to assess the cumulative effect of large dam-building on malaria.
Malaria is transmitted by the Anopheles mosquito, which needs slow-moving or stagnant water in which to breed. Dam reservoirs, particularly shallow puddles that often form along shorelines, provide a perfect environment for the insects to multiply. Thus, dam construction can intensify transmission and shift patterns of malaria infection.
Many African countries are planning new dams to help drive economic growth and increase water security. Improved water storage for growing populations, irrigation, and hydropower generation are needed for a fast-developing continent, but the researchers warn that building new dams has potential costs as well as benefits.
“Dams are an important option for governments anxious to develop,” said study author Matthew McCartney, PhD, of the International Water Management Institute in Vientiane, Laos.
“But it is unethical that people living close to them pay the price of that development through increased suffering and, possibly in extreme cases, loss of life due to disease.”
Lowering the risk
The researchers noted that, despite growing evidence of the impact of dams on malaria, there is scant evidence of their negative impacts being fully offset.
The team therefore made recommendations for managing the increased malaria risk. They said dam reservoirs could be more effectively designed and managed to reduce mosquito breeding. For instance, one option is to adopt operating schedules that, at critical times, dry out shoreline areas where mosquitoes tend to breed.
The researchers said dam developers should also consider increasing investment in integrated malaria intervention programs that include measures such as bed net distribution. Other environmental controls, such as introducing fish that eat mosquito larva in dam reservoirs, could also help reduce malaria cases in some instances.
“The bottom line is that adverse malaria impacts of dams routinely receive recognition in Environmental Impact Assessments, and areas around dams are frequently earmarked for intensive control efforts,” said study author Jonathan Lautze, PhD, of the International Water Management Institute in Pretoria, South Africa.
“The findings of our work hammer home the reality that this recognition and effort—well-intentioned though it may be—is simply not sufficient. Given the need for water resources development in Africa, malaria control around dams requires interdisciplinary cooperation, particularly between water and health communities. Malaria must be addressed while planning, designing, and operating African dams.”
Photo courtesy of the
International Water
Management Institute
More than 1 million people in sub-Saharan Africa will contract malaria this year because they live near a large dam, according to a study published in Malaria Journal.
For the first time, researchers correlated the location of large dams in sub-Saharan Africa with the incidence of malaria.
And they found evidence to suggest that construction of an expected 78 major new dams over the next few years will lead to an additional 56,000 malaria cases annually.
The researchers said these findings have major implications for new dam projects and how health impacts should be assessed prior to construction.
“Dams are at the center of much development planning in Africa,” said study author Solomon Kibret, a graduate student at the University of New England in Armidale, New South Wales, Australia.
“While dams clearly bring many benefits—contributing to economic growth, poverty alleviation, and food security—adverse malaria impacts need to be addressed or they will undermine the sustainability of Africa’s drive for development.”
As part of the CGIAR Research Program on Water, Land, and Ecosystems, Kibret and colleagues looked at 1268 dams in sub-Saharan Africa. Of these, just under two-thirds (n=723) are in malarious areas.
The researchers compared detailed maps of malaria incidence with the dam sites. The number of annual malaria cases associated with the dams was estimated by comparing the number of cases for communities less than 5 kilometers from the dam reservoir with the number of cases for communities further away.
The team found that 15 million people live within 5 kilometers of dam reservoirs and are therefore at risk of contracting malaria. And at least 1.1 million malaria cases annually are linked to the presence of the dams.
“Our study showed that the population at risk of malaria around dams is at least 4 times greater than previously estimated,” Kibret said, noting that the authors were conservative in all their analyses.
The risk is particularly high in areas of sub-Saharan Africa with “unstable” malaria transmission, where malaria is seasonal. The study indicated that the impact of dams on malaria in unstable areas could either lead to intensified malaria transmission or change the nature of transmission from seasonal to perennial.
Explaining the risk
Previous research revealed increases in malaria incidence near major sub-Saharan dams such as the Akosombo Dam in Ghana, the Koka Dam in Ethiopia, and the Kamburu Dam in Kenya. But until now, no attempt has been made to assess the cumulative effect of large dam-building on malaria.
Malaria is transmitted by the Anopheles mosquito, which needs slow-moving or stagnant water in which to breed. Dam reservoirs, particularly shallow puddles that often form along shorelines, provide a perfect environment for the insects to multiply. Thus, dam construction can intensify transmission and shift patterns of malaria infection.
Many African countries are planning new dams to help drive economic growth and increase water security. Improved water storage for growing populations, irrigation, and hydropower generation are needed for a fast-developing continent, but the researchers warn that building new dams has potential costs as well as benefits.
“Dams are an important option for governments anxious to develop,” said study author Matthew McCartney, PhD, of the International Water Management Institute in Vientiane, Laos.
“But it is unethical that people living close to them pay the price of that development through increased suffering and, possibly in extreme cases, loss of life due to disease.”
Lowering the risk
The researchers noted that, despite growing evidence of the impact of dams on malaria, there is scant evidence of their negative impacts being fully offset.
The team therefore made recommendations for managing the increased malaria risk. They said dam reservoirs could be more effectively designed and managed to reduce mosquito breeding. For instance, one option is to adopt operating schedules that, at critical times, dry out shoreline areas where mosquitoes tend to breed.
The researchers said dam developers should also consider increasing investment in integrated malaria intervention programs that include measures such as bed net distribution. Other environmental controls, such as introducing fish that eat mosquito larva in dam reservoirs, could also help reduce malaria cases in some instances.
“The bottom line is that adverse malaria impacts of dams routinely receive recognition in Environmental Impact Assessments, and areas around dams are frequently earmarked for intensive control efforts,” said study author Jonathan Lautze, PhD, of the International Water Management Institute in Pretoria, South Africa.
“The findings of our work hammer home the reality that this recognition and effort—well-intentioned though it may be—is simply not sufficient. Given the need for water resources development in Africa, malaria control around dams requires interdisciplinary cooperation, particularly between water and health communities. Malaria must be addressed while planning, designing, and operating African dams.”
Doc stresses importance of vitamin K shots
Photo by Vera Kratochvil
Cases of vitamin K-deficiency bleeding (VKDB) reported in infants have healthcare professionals concerned about parents refusing vitamin K shots for their newborns.
Some parents have been declining the shots in what is believed to be an extension of the anti-vaccination movement.
But avoiding vitamin K shots can result in dire consequences for newborns, said DeeAnne Jackson, MD, of the University of Alabama at Birmingham.
“Newborns have been receiving vitamin K booster injections since 1961 to prevent internal bleeding,” Dr Jackson noted. “These injections are necessary because babies have very low levels of vitamin K at birth, which can lead to serious bleeding problems if not supplemented. It is an essential nutrient babies need to assist the body in blood clot formation.”
In a recent issue of the Journal of Emergency Medicine, doctors in Ohio documented a case where a 10-week-old child had profound anemia and intracranial bleeding after the child’s parents refused both the vitamin K shot and the hepatitis B vaccine.
The parents brought the child to the emergency room when the mother noticed flecks of blood in the baby’s stool. Emergency physicians were able to stop the intracranial bleeding before it became severe with an infusion of vitamin K.
A previous report published in 2013 revealed 4 cases of VKDB at a hospital in Nashville, Tennessee. These incidents were directly related to newborns not receiving their vitamin K shot.
When the US Centers for Disease Control and Prevention investigated this issue, the agency found that 28% of parents with babies born at private birthing centers in Nashville had refused the shot.
An update published in 2014 detailed 5 cases of late VKDB treated at the aforementioned hospital between February and September 2013 and 2 additional infants who had severe vitamin K deficiency but no bleeding.
Dr Jackson believes incidents like these might be avoided by better communication between parents and healthcare professionals.
“I would encourage parents who may be nervous about vitamin K shots or vaccines to start these conversations prior to their baby’s delivery so they can learn more about why these treatments are recommended ahead of time,” she said.
“You really shouldn’t wait to see if your baby needs a vitamin K shot after birth, because delaying medical care can lead to serious and life-threatening consequences.”
Photo by Vera Kratochvil
Cases of vitamin K-deficiency bleeding (VKDB) reported in infants have healthcare professionals concerned about parents refusing vitamin K shots for their newborns.
Some parents have been declining the shots in what is believed to be an extension of the anti-vaccination movement.
But avoiding vitamin K shots can result in dire consequences for newborns, said DeeAnne Jackson, MD, of the University of Alabama at Birmingham.
“Newborns have been receiving vitamin K booster injections since 1961 to prevent internal bleeding,” Dr Jackson noted. “These injections are necessary because babies have very low levels of vitamin K at birth, which can lead to serious bleeding problems if not supplemented. It is an essential nutrient babies need to assist the body in blood clot formation.”
In a recent issue of the Journal of Emergency Medicine, doctors in Ohio documented a case where a 10-week-old child had profound anemia and intracranial bleeding after the child’s parents refused both the vitamin K shot and the hepatitis B vaccine.
The parents brought the child to the emergency room when the mother noticed flecks of blood in the baby’s stool. Emergency physicians were able to stop the intracranial bleeding before it became severe with an infusion of vitamin K.
A previous report published in 2013 revealed 4 cases of VKDB at a hospital in Nashville, Tennessee. These incidents were directly related to newborns not receiving their vitamin K shot.
When the US Centers for Disease Control and Prevention investigated this issue, the agency found that 28% of parents with babies born at private birthing centers in Nashville had refused the shot.
An update published in 2014 detailed 5 cases of late VKDB treated at the aforementioned hospital between February and September 2013 and 2 additional infants who had severe vitamin K deficiency but no bleeding.
Dr Jackson believes incidents like these might be avoided by better communication between parents and healthcare professionals.
“I would encourage parents who may be nervous about vitamin K shots or vaccines to start these conversations prior to their baby’s delivery so they can learn more about why these treatments are recommended ahead of time,” she said.
“You really shouldn’t wait to see if your baby needs a vitamin K shot after birth, because delaying medical care can lead to serious and life-threatening consequences.”
Photo by Vera Kratochvil
Cases of vitamin K-deficiency bleeding (VKDB) reported in infants have healthcare professionals concerned about parents refusing vitamin K shots for their newborns.
Some parents have been declining the shots in what is believed to be an extension of the anti-vaccination movement.
But avoiding vitamin K shots can result in dire consequences for newborns, said DeeAnne Jackson, MD, of the University of Alabama at Birmingham.
“Newborns have been receiving vitamin K booster injections since 1961 to prevent internal bleeding,” Dr Jackson noted. “These injections are necessary because babies have very low levels of vitamin K at birth, which can lead to serious bleeding problems if not supplemented. It is an essential nutrient babies need to assist the body in blood clot formation.”
In a recent issue of the Journal of Emergency Medicine, doctors in Ohio documented a case where a 10-week-old child had profound anemia and intracranial bleeding after the child’s parents refused both the vitamin K shot and the hepatitis B vaccine.
The parents brought the child to the emergency room when the mother noticed flecks of blood in the baby’s stool. Emergency physicians were able to stop the intracranial bleeding before it became severe with an infusion of vitamin K.
A previous report published in 2013 revealed 4 cases of VKDB at a hospital in Nashville, Tennessee. These incidents were directly related to newborns not receiving their vitamin K shot.
When the US Centers for Disease Control and Prevention investigated this issue, the agency found that 28% of parents with babies born at private birthing centers in Nashville had refused the shot.
An update published in 2014 detailed 5 cases of late VKDB treated at the aforementioned hospital between February and September 2013 and 2 additional infants who had severe vitamin K deficiency but no bleeding.
Dr Jackson believes incidents like these might be avoided by better communication between parents and healthcare professionals.
“I would encourage parents who may be nervous about vitamin K shots or vaccines to start these conversations prior to their baby’s delivery so they can learn more about why these treatments are recommended ahead of time,” she said.
“You really shouldn’t wait to see if your baby needs a vitamin K shot after birth, because delaying medical care can lead to serious and life-threatening consequences.”
Group creates guide for PICC use
A group of international experts has created a guide to promote the appropriate use of peripherally inserted central catheters (PICCs) in adults.
The guide, called Michigan Appropriateness Guide for Intravenous Catheters (MAGIC), was published in Annals of Internal Medicine.
MAGIC is based on a review of evidence and was designed to give clinicians an easy-to-use framework to pick the right venous access device for each patient.
“PICCs, or peripherally inserted central catheters, have become especially convenient to place, and their use has gone up dramatically, as have the complications from them,” said guideline author Vineet Chopra, MD, of the University of Michigan in Ann Arbor.
“The easiest way to prevent these complications is not to place a PICC in the first place. So we set out to determine when the use of a PICC is appropriate and when other choices are the best.”
The experts reviewed 665 scenarios in which PICCs were used. Their use was deemed appropriate in 38% (n=253) of cases and inappropriate in 43% (n=288). In 19% (n=124) of cases, the experts could not agree or were unsure about whether PICC use was appropriate.
The experts said that, in patients with cancer, PICCs are appropriate for irritant or vesicant infusion, regardless of the duration of use.
On the other hand, they said PICC use is inappropriate for peripherally compatible infusions when the proposed duration of use is 5 days or fewer. And when the duration is between 6 days and 14 days, midline and ultrasonography-guided peripheral intravenous catheters should be used over PICCs.
The experts also said that nontunneled central venous catheters should be used over PICCs in critically ill patients when the duration of use is likely to be 14 days or fewer.
How MAGIC happened
The panel of 15 experts included doctors and nurses from a range of fields where PICCs and other such devices are commonly used, such as vascular nursing, critical care, infectious disease, and oncology. Also participating was a patient who had suffered complications from various intravenous devices and still lives with the consequences.
The panel evaluated the scenarios and supporting medical literature, and made its recommendations, using the RAND/UCLA Appropriateness Method.
The panel did not consider pediatric use of PICCs and other vascular access devices, but they hope their work could provide a framework for a similar effort in pediatrics.
Putting MAGIC to the test
MAGIC is getting its first test in 47 Michigan hospitals taking part in a patient safety project known as the Michigan Hospital Medicine Safety Consortium.
Researchers also plan to test ways to deploy MAGIC across the Veterans Affairs health system, working with the VA National Center for Patient Safety and the No Preventable Harms Campaign.
Even as they evaluate MAGIC’s ability to improve appropriate use of different devices and reduce complications, the team behind the new guide hopes other clinicians will begin using it.
“IV devices of all kinds are being put into patients without much thought about risks, benefits, or alternatives,” Dr Chopra said. “At the end of the day, we hope MAGIC will give providers the information they need to make a good decision for their patient, one that will render these devices appropriate and safe.”
Dr Chopra and his colleagues have also launched a website, improvepicc.com, that provides links to research on PICCs and other resources for clinicians.
A group of international experts has created a guide to promote the appropriate use of peripherally inserted central catheters (PICCs) in adults.
The guide, called Michigan Appropriateness Guide for Intravenous Catheters (MAGIC), was published in Annals of Internal Medicine.
MAGIC is based on a review of evidence and was designed to give clinicians an easy-to-use framework to pick the right venous access device for each patient.
“PICCs, or peripherally inserted central catheters, have become especially convenient to place, and their use has gone up dramatically, as have the complications from them,” said guideline author Vineet Chopra, MD, of the University of Michigan in Ann Arbor.
“The easiest way to prevent these complications is not to place a PICC in the first place. So we set out to determine when the use of a PICC is appropriate and when other choices are the best.”
The experts reviewed 665 scenarios in which PICCs were used. Their use was deemed appropriate in 38% (n=253) of cases and inappropriate in 43% (n=288). In 19% (n=124) of cases, the experts could not agree or were unsure about whether PICC use was appropriate.
The experts said that, in patients with cancer, PICCs are appropriate for irritant or vesicant infusion, regardless of the duration of use.
On the other hand, they said PICC use is inappropriate for peripherally compatible infusions when the proposed duration of use is 5 days or fewer. And when the duration is between 6 days and 14 days, midline and ultrasonography-guided peripheral intravenous catheters should be used over PICCs.
The experts also said that nontunneled central venous catheters should be used over PICCs in critically ill patients when the duration of use is likely to be 14 days or fewer.
How MAGIC happened
The panel of 15 experts included doctors and nurses from a range of fields where PICCs and other such devices are commonly used, such as vascular nursing, critical care, infectious disease, and oncology. Also participating was a patient who had suffered complications from various intravenous devices and still lives with the consequences.
The panel evaluated the scenarios and supporting medical literature, and made its recommendations, using the RAND/UCLA Appropriateness Method.
The panel did not consider pediatric use of PICCs and other vascular access devices, but they hope their work could provide a framework for a similar effort in pediatrics.
Putting MAGIC to the test
MAGIC is getting its first test in 47 Michigan hospitals taking part in a patient safety project known as the Michigan Hospital Medicine Safety Consortium.
Researchers also plan to test ways to deploy MAGIC across the Veterans Affairs health system, working with the VA National Center for Patient Safety and the No Preventable Harms Campaign.
Even as they evaluate MAGIC’s ability to improve appropriate use of different devices and reduce complications, the team behind the new guide hopes other clinicians will begin using it.
“IV devices of all kinds are being put into patients without much thought about risks, benefits, or alternatives,” Dr Chopra said. “At the end of the day, we hope MAGIC will give providers the information they need to make a good decision for their patient, one that will render these devices appropriate and safe.”
Dr Chopra and his colleagues have also launched a website, improvepicc.com, that provides links to research on PICCs and other resources for clinicians.
A group of international experts has created a guide to promote the appropriate use of peripherally inserted central catheters (PICCs) in adults.
The guide, called Michigan Appropriateness Guide for Intravenous Catheters (MAGIC), was published in Annals of Internal Medicine.
MAGIC is based on a review of evidence and was designed to give clinicians an easy-to-use framework to pick the right venous access device for each patient.
“PICCs, or peripherally inserted central catheters, have become especially convenient to place, and their use has gone up dramatically, as have the complications from them,” said guideline author Vineet Chopra, MD, of the University of Michigan in Ann Arbor.
“The easiest way to prevent these complications is not to place a PICC in the first place. So we set out to determine when the use of a PICC is appropriate and when other choices are the best.”
The experts reviewed 665 scenarios in which PICCs were used. Their use was deemed appropriate in 38% (n=253) of cases and inappropriate in 43% (n=288). In 19% (n=124) of cases, the experts could not agree or were unsure about whether PICC use was appropriate.
The experts said that, in patients with cancer, PICCs are appropriate for irritant or vesicant infusion, regardless of the duration of use.
On the other hand, they said PICC use is inappropriate for peripherally compatible infusions when the proposed duration of use is 5 days or fewer. And when the duration is between 6 days and 14 days, midline and ultrasonography-guided peripheral intravenous catheters should be used over PICCs.
The experts also said that nontunneled central venous catheters should be used over PICCs in critically ill patients when the duration of use is likely to be 14 days or fewer.
How MAGIC happened
The panel of 15 experts included doctors and nurses from a range of fields where PICCs and other such devices are commonly used, such as vascular nursing, critical care, infectious disease, and oncology. Also participating was a patient who had suffered complications from various intravenous devices and still lives with the consequences.
The panel evaluated the scenarios and supporting medical literature, and made its recommendations, using the RAND/UCLA Appropriateness Method.
The panel did not consider pediatric use of PICCs and other vascular access devices, but they hope their work could provide a framework for a similar effort in pediatrics.
Putting MAGIC to the test
MAGIC is getting its first test in 47 Michigan hospitals taking part in a patient safety project known as the Michigan Hospital Medicine Safety Consortium.
Researchers also plan to test ways to deploy MAGIC across the Veterans Affairs health system, working with the VA National Center for Patient Safety and the No Preventable Harms Campaign.
Even as they evaluate MAGIC’s ability to improve appropriate use of different devices and reduce complications, the team behind the new guide hopes other clinicians will begin using it.
“IV devices of all kinds are being put into patients without much thought about risks, benefits, or alternatives,” Dr Chopra said. “At the end of the day, we hope MAGIC will give providers the information they need to make a good decision for their patient, one that will render these devices appropriate and safe.”
Dr Chopra and his colleagues have also launched a website, improvepicc.com, that provides links to research on PICCs and other resources for clinicians.
Two‐Item Bedside Test for Delirium
Delirium (acute confusion) is common in older adults and leads to poor outcomes, such as death, clinician and caregiver burden, and prolonged cognitive and functional decline.[1, 2, 3, 4] Delirium is extremely costly, with estimates ranging from $143 to $152 billion annually (2005 US$).[5, 6] Early detection and management may improve the poor outcomes and reduce costs attributable to delirium,[3, 7] yet delirium identification in clinical practice has been challenging, particularly when translating research tools to the bedside.[8, 9, 10]As a result, only 12% to 35% of delirium cases are detected in routine care, with hypoactive delirium and delirium superimposed on dementia most likely to be missed.[11, 12, 13, 14, 15]
To address these issues, we recently developed and published the three‐dimensional Confusion Assessment Method (3D‐CAM), the 3‐minute diagnostic assessment for CAM‐defined delirium.[16] The 3D‐CAM is a structured assessment tool that includes mental status testing, patient symptom probes, and guided interviewer observations for signs of delirium. 3D‐CAM items were selected through a rigorous process to determine the most informative items for the 4 CAM diagnostic features.[17] The 3D‐CAM can be completed in 3 minutes, and has 95% sensitivity and 94% specificity relative to a reference standard.[16]
Despite the capabilities of the 3D‐CAM, there are situations when even 3 minutes is too long to devote to delirium identification. Moreover, a 2‐step approach in which a sensitive ultrabrief screen is administered, followed by the 3D‐CAM in positives, may be the most efficient approach for large‐scale delirium case identification. The aim of the current study was to use the 3D‐CAM database to identify the most sensitive single item and pair of items in the diagnosis of delirium, using the reference standard in the diagnostic accuracy analysis. We hypothesized that we could identify a single item with greater than 80% sensitivity and a pair of items with greater than 90% sensitivity for detection of delirium.
METHODS
Study Sample and Design
We analyzed data from the 3D‐CAM validation study,[16] which prospectively enrolled participants from a large urban teaching hospital in Boston, Massachusetts, using a consecutive enrollment sampling strategy. Inclusion criteria were: (1) 75 years old, (2) admitted to general or geriatric medicine services, (3) able to communicate in English, (4) without terminal conditions, (5) expected hospital stay of 2 days, (6) not a previous study participant. Experienced clinicians screened patients for eligibility. If the patient lacked capacity to provide consent, the designated surrogate decision maker was contacted. The study was approved by the institutional review board.
Reference Standard Delirium Diagnosis
The reference standard delirium diagnosis was based on an extensive (45 minutes) face‐to‐face patient interview by experienced clinician assessors (neuropsychologists or advanced practice nurses), medical record review, and input from the nurse and family members. This comprehensive assessment included: (1) reason for hospital admission, hospital course, and presence of cognitive concerns, (2) family, social, and functional history, (3) Montreal Cognitive Assessment,[18] (4) Geriatric Depression Scale,[19] (5) medical record review including scoring of comorbidities using the Charlson index,[20] determination of functional status using the basic and Instrumental Activities of Daily Living,[21, 22] psychoactive medications administered, and (6) a family member interview to assess the patient's baseline cognitive status that included the Eight‐Item Interview to Differentiate Aging and Dementia,[23] to assess the presence of dementia. Using all of these data, an expert panel, including the clinical assessor, the study principal investigator (E.R.M.), a geriatrician, and an experienced neuropsychologist, adjudicated the final delirium diagnoses using Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM‐IV) criteria. The panel also adjudicated for the presence or absence of dementia and mild cognitive impairment based on National Institute on Aging‐Alzheimer's Association (NIA‐AA) criteria.[24] This approach has been used in other delirium studies.[25]
3D‐CAM Assessments
After the reference standard assessment, the 3D‐CAM was administered by trained research assistants (RAs) who were blinded to the results of the reference standard. To reduce the likelihood of fluctuations or temporal changes, all assessments were completed between 11:00 am and 2:00 pm and for each participant, within a 2‐hour time period (for example, 11:23 am to 1:23 pm).
Statistical Analyses to Determine the Best Single‐ and Two‐Item Screeners
To determine the best single 3D‐CAM item to identify delirium, the responses of the 20 individual items in the 3D‐CAM (see Supporting Table 1 in the online version of this article) were compared to the reference standard to determine their sensitivity and specificity. Similarly, an algorithm was used to generate all unique 2‐item combinations of the 20 items (190 unique pairs), which were compared to the reference. An error, no response, or an answer of I do not know by the patient was considered a positive screen for delirium. The 2‐item screeners were considered positive if 1 or both of the items were positive. Sensitivity and specificity were calculated along with 95% confidence intervals (CIs).
Subset analyses were performed to determine sensitivity and specificity of individual items and pairs of items stratified by the patient's baseline cognitive status. Two strata were createdpatients with dementia (N=56), and patients with normal baseline cognitive status or mild cognitive impairment (MCI) (N=145). We chose to group MCI with normal for 2 reasons: (1) dementia is a well‐established and strong risk factor for delirium, whereas the evidence for MCI being a risk factor for delirium is less established and (2) to achieve adequate allocation of delirious cases in both strata. Last, we report the sensitivity of altered level of consciousness (LOC), which included lethargy, stupor, coma, and hypervigilance as a single screening item for delirium in the overall sample and by cognitive status. Analyses were conducted using commercially available software (SAS version 9.3; SAS Institute, Inc., Cary, NC).
RESULTS
Characteristics of the patients are shown in Table 1. Subjects had a mean age of 84 years, 62% were female, and 28% had a baseline dementia. Forty‐two (21%) had delirium based on the clinical reference standard. Twenty (10%) had less than a high school education and 100 (49%) had at least a college education.
| Characteristic | N (%) |
|---|---|
| |
| Age, y, mean (SD) | 84 (5.4) |
| Sex, n (%) female | 125 (62) |
| White, n (%) | 177 (88) |
| Education, n (%) | |
| Less than high school | 20 (10) |
| High school graduate | 75 (38) |
| College plus | 100 (49) |
| Vision interfered with interview, n (%) | 5 (2) |
| Hearing interfered with interview, n (%) | 18 (9) |
| English second language n (%) | 10 (5) |
| Charlson, mean (SD) | 3 (2.3) |
| ADL, n (% impaired) | 110 (55) |
| IADL, n (% impaired) | 163 (81) |
| MCI, n (%) | 50 (25) |
| Dementia, n (%) | 56 (28) |
| Delirium, n (%) | 42 (21) |
| MoCA, mean (SD) | 19 (6.6) |
| MoCA, median (range) | 20 (030) |
Single Item Screens
Table 2 reports the results of single‐item screens for delirium with sensitivity, the ability to correctly identify delirium when it is present by the reference standard, and specificity, the ability to correctly identify patients without delirium when it is not present by reference standard and 95% CIs. Items are listed in descending order of sensitivity; in the case of ties, the item with the higher specificity is listed first. The screening items with the highest sensitivity for delirium are Months of the year backwards, and Four digits backwards, both with a sensitivity of 83% (95% CI: 69%‐93%). Of these 2 items, Months of the year backwards had a much better specificity of 69% (95% CI: 61%‐76%), whereas Four digits backwards had a specificity of 52% (95% CI: 44%‐60%). The item What is the day of the week? had lower sensitivity at 71% (95% CI: 55%‐84%), but excellent specificity at 92% (95% CI: 87%‐96%).
| Screen Item | Screen Positive (%)c | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR |
|---|---|---|---|---|---|
| |||||
| Months of the year backwards | 42 | 0.83 (0.69‐0.93) | 0.69 (0.61‐0.76) | 2.7 | 0.24 |
| Four digits backwards | 56 | 0.83 (0.69‐0.93) | 0.52 (0.44‐0.60) | 1.72 | 0.32 |
| What is the day of the week? | 21 | 0.71 (0.55‐0.84) | 0.92 (0.87‐0.96) | 9.46 | 0.31 |
| What is the year? | 16 | 0.55 (0.39‐0.70) | 0.94 (0.9‐0.97) | 9.67 | 0.48 |
| Have you felt confused during the past day? | 14 | 0.50 (0.34‐0.66) | 0.95 (0.9‐0.98) | 9.94 | 0.53 |
| Days of the week backwards | 15 | 0.50 (0.34‐0.66) | 0.94 (0.89‐0.97) | 7.95 | 0.53 |
| During the past day, did you see things that were not really there? | 11 | 0.45 (0.3‐0.61) | 0.97 (0.94‐0.99) | 17.98 | 0.56 |
| Three digits backwards | 15 | 0.45 (0.3‐0.61) | 0.92 (0.87‐0.96) | 5.99 | 0.59 |
| What type of place is this? | 9 | 0.38 (0.24‐0.54) | 0.99 (0.96‐1) | 30.29 | 0.63 |
| During the past day, did you think you were not in the hospital? | 10 | 0.38 (0.24‐0.54) | 0.97 (0.94‐0.99) | 15.14 | 0.64 |
We then examined performance of single‐item screeners in patients with and without dementia (Table 3). In persons with dementia, the best single item was also Months of the year backwards, with a sensitivity of 89% (95% CI: 72%‐98%) and a specificity of 61% (95% CI: 41%‐78%). In persons with normal baseline cognition or MCI, the best performing single item was Four digits backwards, with sensitivity of 79% (95% CI: 49%‐95%) and specificity of 51% (95% CI: 42%‐60%). Months of the year backwards also performed well, with sensitivity of 71% (95% CI: 42%‐92%) and specificity of 71% (95% CI: 62%‐79%).
| Test Item | Normal/MCI Patients (n=145) | Dementia Patients (n=56) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Screen Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | Screen Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | |
| ||||||||||
| Months backwards | 33 | 0.71 (0.42‐0.92) | 0.71 (0.62‐0.79) | 2.46 | 0.4 | 64 | 0.89 (0.72‐0.98) | 0.61 (0.41‐0.78) | 2.27 | 0.18 |
| Four digits backwards | 52 | 0.79 (0.49‐0.95) | 0.51 (0.42‐0.60) | 1.61 | 0.42 | 66 | 0.86 (0.67‐0.96) | 0.54 (0.34‐0.72) | 1.85 | 0.27 |
| What is the day of the week? | 10 | 0.64 (0.35‐0.87) | 0.96 (0.91‐0.99) | 16.84 | 0.37 | 50 | 0.75 (0.55‐0.89) | 0.75 (0.55‐0.89) | 3 | 0.33 |
Two‐Item Screens
Table 4 reports the results of 2‐item screens for delirium with sensitivity, specificity, and 95% CIs. Item pairs are listed in descending order of sensitivity following the same convention as in Table 2. The 2‐item screen with the highest sensitivity for delirium is the combination of What is the day of the week? and Months of the year backwards, with a sensitivity of 93% (95% CI: 81%‐99%) and specificity of 64% (95% CI: 56%‐70%). This screen had a positive and negative likelihood ratio (LR) of 2.59 and 0.11, respectively. The combination of What is the day of the week? and Four digits backwards had the same sensitivity 93% (95% CI: 81%‐99%), but lower specificity of 48% (95% CI: 40%‐56%). The combination of What type of place is this? (hospital) and Four digits backwards had a sensitivity of 90% (95% CI: 77%‐97%) and specificity of 51% (95% CI: 43%‐50%).
| Screen Item 1 | Screen Item 2 | Screen Positive (%)c | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR |
|---|---|---|---|---|---|---|
| ||||||
| What is the day of the week? | Months backwards | 48 | 0.93 (0.81‐0.99) | 0.64 (0.56‐0.70) | 2.59 | 0.11 |
| What is the day of the week? | Four digits backwards | 60 | 0.93 (0.81‐0.99) | 0.48 (0.4‐0.56) | 1.8 | 0.15 |
| Four digits backwards | Months backwards | 65 | 0.93 (0.81‐0.99) | 0.42 (0.34‐0.50) | 1.6 | 0.17 |
| What type of place is this? | Four digits backwards | 58 | 0.90 (0.77‐0.97) | 0.51 (0.43‐0.50) | 1.84 | 0.19 |
| What is the year? | Four digits backwards | 59 | 0.9 (0.77‐0.97) | 0.5 (0.42‐0.5) | 1.80 | 0.19 |
| What is the day of the week? | Three digits backwards | 30 | 0.88 (0.74‐0.96) | 0.86 (0.79‐0.90) | 6.09 | 0.14 |
| What is the year? | Months backwards | 44 | 0.88 (0.74‐0.96) | 0.68 (0.6‐0.75) | 2.75 | 0.18 |
| What type of place is this? | Months backwards | 43 | 0.86 (0.71‐0.95) | 0.69 (0.61‐0.70) | 2.73 | 0.21 |
| During the past day, did you think you were not in the hospital? | Months backwards | 43 | 0.86 (0.71‐0.95) | 0.69 (0.61‐0.70) | 2.73 | 0.21 |
| Days of the week backwards | Months backwards | 43 | 0.86 (0.71‐0.95) | 0.68 (0.6‐0.75) | 2.67 | 0.21 |
When subjects were stratified by baseline cognition, the best 2‐item screens for normal and MCI patients was What is the day of the week? and Four digits backwards, with 93% sensitivity (95% CI: 66%‐100%) and 50% specificity (95% CI: 42%‐59%). The best pair of items for patients with dementia (Table 5) was the same as the overall sample, What is the day of the week? and Months of the year backwards, but its performance differed with a higher sensitivity of 96% (95% CI: 82%‐100%) and lower specificity of 43% (95% CI: 24%‐63%). This same pair of items had 86% sensitivity (95% CI: 57%‐98%) and 69% (95% CI: 60%‐77%) specificity for persons with either normal cognition or MCI.
| Test Item 1 | Test Item 2 | Normal/MCI Patients (n=145) | Dementia Patients (n=56) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Item Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | Item Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | ||
| |||||||||||
| What is the day of the week? | Months backwards | 36 | 0.86 (0.57‐0.98) | 0.69 (0.60‐0.77) | 2.74 | 0.21 | 77 | 0.96 (0.82‐1) | 0.43 (0.24‐0.63) | 1.69 | 0.08 |
| What is the day of the week? | Four digits backwards | 54 | 0.93 (0.66‐1) | 0.5 (0.42‐0.59) | 1.87 | 0.14 | 77 | 0.93 (0.76‐0.99) | 0.39 (0.22‐0.59) | 1.53 | 0.18 |
| Four digits backwards | Months backwards | 61 | 0.93 (0.66‐1) | 0.43 (0.34‐0.52) | 1.62 | 0.17 | 77 | 0.93 (0.76‐0.99) | 0.39 (0.22‐0.59) | 1.53 | 0.18 |
Altered Level of Consciousness as a Screener for Delirium
Altered level of consciousness (ALOC) was uncommon in our sample, with an overall prevalence of 10/201 (4.9%). When examined as a screening item for delirium, ALOC had very poor sensitivity of 19% (95% CI: 9%‐34%) but had excellent specificity 99% (95% CI: 96%‐100%). Altered LOC also demonstrated poor screening performance when stratified by cognitive status, with a sensitivity of 14% in the normal and MCI group (95% CI: 2%‐43%) and sensitivity of 21% (95% CI: 8%‐41%) in persons with dementia.
Positive and Negative Predictive Values
Although we focused on sensitivity and specificity in evaluating 1‐ and 2‐item screeners, we also examined positive and negative predictive values. These values will vary depending on the overall prevalence of delirium, which was 21% in this dataset. The best 1‐item screener, Months of the year backwards, had a positive predictive value of 31% and negative predictive value of 94%. The best 2‐item screener, Months of the year backwards with What is the day of the week?, had a positive predictive value of 41% and negative predictive value of 97% (see Supporting Tables 2 and 3 in the online version of this article) LRs for the items are in Tables 2 through 5.
DISCUSSION
Identifying simple, efficient, bedside case‐identification methods for delirium is an essential step toward improving recognition of this highly morbid syndrome in hospitalized older adults. In this study, we identified a single cognitive item, Months of the year backwards, that identified 83% of delirium cases when compared with a reference standard diagnosis. Furthermore, we identified 2 items, Months of the year backwards and What is the day of the week? which when used in combination identified 93% of delirium cases. The same 1 and 2 items also worked well in patients with dementia, in whom delirium is often missed. Although these items require further clinical validation, the development of an ultrabrief 2‐item test that identifies over 90% of delirium cases and can be completed in less than 1 minute (recently, we administered the best 2‐item screener to 20 consecutive general medicine patients over age 70 years, and it was completed in a median of 36.5 seconds), holds great potential for simplifying bedside delirium screening and improving the care of hospitalized older adults.
Our current findings both confirm and extend the emerging literature on best screening items for delirium. Sands and colleagues (2010)[26] tested a single test for delirium, Do you think (name of patient) has been more confused lately? in 21 subjects and achieved a sensitivity of 80%. Han and colleagues developed a screening tool in emergency‐department patients using the LOC question from the Richmond Agitation‐Sedation Scale and spelling the word lunch backwards, and achieved 98% sensitivity, but in a younger emergency department population with a low prevalence of dementia.[27] O'Regan et al. recently also found Months of the year backwards to be the best single‐screening item for delirium in a large sample, but only tested a 1‐item screen.[28] Our study extends these studies in several important ways by: (1) employing a rigorous clinical reference standard diagnosis of delirium, (2) having a large sample with a high prevalence of patients with dementia, (3) use of a general medical population, and (4) examining the best 2‐item screens in addition to the best single item.
Systematic intervention programs[29, 30, 31] that focus on improved delirium evaluation and management have the potential to improve patient outcomes and reduce costs. However, targeting these programs to patients with delirium has proven difficult, as only 12% to 35% of delirium cases are recognized in routine clinical practice.[11, 12, 13, 14, 15] The 1‐ and 2‐item screeners we identified could play an important role in future delirium identification. The 3D‐CAM combines high sensitivity (95%) with high specificity (94%)[16] and therefore would be an excellent choice as the second step after a positive screen. The feasibility, effectiveness, and cost of administering these screeners, followed by a brief diagnostic tool such as the 3D‐CAM, should be evaluated in future work.
Our study has noteworthy strengths, including the use of a large purposefully challenging clinical sample with advanced age that included a substantial proportion with dementia, a detailed assessment, and the testing of very brief and practical tools for bedside delirium screening.[25] This study also has several important limitations. Most importantly, we presented secondary analysis of individual items and pairs of items drawn from the 3D CAM assessment; therefore, the 2‐item bedside screen requires prospective clinical validation. The reference standard was based on the DSM‐IV, because this study was conducted prior to the release of DSM‐V. In addition, the ordering of the reference standard and 3D‐CAM assessments was not randomized due to feasibility constraints. In addition, this study was cross‐sectional, involved only a single hospital, and enrolled only older medical patients during the day shift. Our sample was older (aged 75 years and older), and a younger sample may have had a different prevalence of delirium, which could affect the positive predictive value of our ultrabrief screen. We plan to test this in a sample of patients aged 70 years and older in future studies. Finally, it should be noted that these best 1‐item and 2‐item screeners miss 17% and 7% of delirium cases, respectively. In cases where this is unacceptably high, alternative approaches might be necessary.
It is important to remember that these 1‐ and 2‐item screeners are not diagnostic tools and therefore should not be used in isolation. Optimally, they will be followed by a more specific evaluation, such as the 3D‐CAM, as part of a systematic delirium identification process. For instance, in our sample (with a delirium rate of 21%), the best 2‐item screener had a positive predictive value of 41%, meaning that positive screens are more likely to be false positives than true positives (see Supporting Tables 2 and 3 in the online version of this article).[32] Nevertheless, by reducing the total number of patients who require diagnostic instrument administration, use of these ultrabrief screeners can improve efficiency and result in a net benefit to delirium case‐identification efforts.[32]
Time has been demonstrated to be a barrier to delirium identification in previous studies, but there are likely others. These may include, for instance, staff nihilism about screening making a difference, ambiguous responsibility for delirium screening and management, unsupportive system leadership, and absent payment for these activities.[31] Moreover, it is possible that the 2‐step process we propose may create an incentive for staff to avoid positive screens as they see it creating more work for themselves. We plan to identify and address such barriers in our future work.
In conclusion, we identified a single screening item for delirium, Months of the year backwards, with 83% sensitivity, and a pair of items, Months of the year backwards and What is the day of the week?, with 93% sensitivity relative to a rigorous reference standard diagnosis. These ultrabrief screening items work well in patients with and without dementia, and should require very little training of staff. Future studies should further validate these tools, and determine their translatability and scalability into programs for systematic, widespread delirium detection. Developing efficient and accurate case identification strategies is a necessary prerequisite to appropriately target delirium management protocols, enabling healthcare systems to effectively address this costly and deadly condition.
Disclosures
Author contributionsD.M.F. conceived the study idea, participated in its design and coordination, and drafted the initial manuscript. S.K.I. contributed to the study design and conceptualization, supervision, funding, preliminary analysis, and interpretation of the data, and critical revision of the manuscript. J.G. conducted the analysis for the study and critically revised the manuscript. L.N. supervised the analysis for the study and critically revised the manuscript. R.J. contributed to the study design and critical revision of the manuscript. J.S.S. critically revised the manuscript. E.R.M. obtained funding for the study, supervised all data collection, assisted in drafting and critically revising the manuscript, and contributed to the conceptualization, design, and supervision of the study. All authors have seen and agree with the contents of the manuscript.
This work was supported by the National Institute of Aging grant number R01AG030618 and K24AG035075 to Dr. Marcantonio. Dr. Inouye's time was supported in part by grants P01AG031720, R01AG044518, and K07AG041835 from the National Institute on Aging. Dr. Inouye holds the Milton and Shirley F. Levy Family Chair (Hebrew Senior Life/Harvard Medical School). Dr. Fick is partially supported from National Institute of Nursing Research grant number R01 NR011042. Dr. Saczynski was supported in part by funding from the National Institute on Aging (K01AG33643) and from the National Heart Lung and Blood Institute (U01HL105268). The funding agencies had no role and the authors retained full autonomy in the preparation of this article. All authors and coauthors have no financial or nonfinancial conflicts of interest to disclose regarding this article.
This article was presented at the Presidential Poster Session at the American Geriatrics Society 2014 Annual Meeting in Orlando, Florida, May 14, 2014.
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Delirium (acute confusion) is common in older adults and leads to poor outcomes, such as death, clinician and caregiver burden, and prolonged cognitive and functional decline.[1, 2, 3, 4] Delirium is extremely costly, with estimates ranging from $143 to $152 billion annually (2005 US$).[5, 6] Early detection and management may improve the poor outcomes and reduce costs attributable to delirium,[3, 7] yet delirium identification in clinical practice has been challenging, particularly when translating research tools to the bedside.[8, 9, 10]As a result, only 12% to 35% of delirium cases are detected in routine care, with hypoactive delirium and delirium superimposed on dementia most likely to be missed.[11, 12, 13, 14, 15]
To address these issues, we recently developed and published the three‐dimensional Confusion Assessment Method (3D‐CAM), the 3‐minute diagnostic assessment for CAM‐defined delirium.[16] The 3D‐CAM is a structured assessment tool that includes mental status testing, patient symptom probes, and guided interviewer observations for signs of delirium. 3D‐CAM items were selected through a rigorous process to determine the most informative items for the 4 CAM diagnostic features.[17] The 3D‐CAM can be completed in 3 minutes, and has 95% sensitivity and 94% specificity relative to a reference standard.[16]
Despite the capabilities of the 3D‐CAM, there are situations when even 3 minutes is too long to devote to delirium identification. Moreover, a 2‐step approach in which a sensitive ultrabrief screen is administered, followed by the 3D‐CAM in positives, may be the most efficient approach for large‐scale delirium case identification. The aim of the current study was to use the 3D‐CAM database to identify the most sensitive single item and pair of items in the diagnosis of delirium, using the reference standard in the diagnostic accuracy analysis. We hypothesized that we could identify a single item with greater than 80% sensitivity and a pair of items with greater than 90% sensitivity for detection of delirium.
METHODS
Study Sample and Design
We analyzed data from the 3D‐CAM validation study,[16] which prospectively enrolled participants from a large urban teaching hospital in Boston, Massachusetts, using a consecutive enrollment sampling strategy. Inclusion criteria were: (1) 75 years old, (2) admitted to general or geriatric medicine services, (3) able to communicate in English, (4) without terminal conditions, (5) expected hospital stay of 2 days, (6) not a previous study participant. Experienced clinicians screened patients for eligibility. If the patient lacked capacity to provide consent, the designated surrogate decision maker was contacted. The study was approved by the institutional review board.
Reference Standard Delirium Diagnosis
The reference standard delirium diagnosis was based on an extensive (45 minutes) face‐to‐face patient interview by experienced clinician assessors (neuropsychologists or advanced practice nurses), medical record review, and input from the nurse and family members. This comprehensive assessment included: (1) reason for hospital admission, hospital course, and presence of cognitive concerns, (2) family, social, and functional history, (3) Montreal Cognitive Assessment,[18] (4) Geriatric Depression Scale,[19] (5) medical record review including scoring of comorbidities using the Charlson index,[20] determination of functional status using the basic and Instrumental Activities of Daily Living,[21, 22] psychoactive medications administered, and (6) a family member interview to assess the patient's baseline cognitive status that included the Eight‐Item Interview to Differentiate Aging and Dementia,[23] to assess the presence of dementia. Using all of these data, an expert panel, including the clinical assessor, the study principal investigator (E.R.M.), a geriatrician, and an experienced neuropsychologist, adjudicated the final delirium diagnoses using Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM‐IV) criteria. The panel also adjudicated for the presence or absence of dementia and mild cognitive impairment based on National Institute on Aging‐Alzheimer's Association (NIA‐AA) criteria.[24] This approach has been used in other delirium studies.[25]
3D‐CAM Assessments
After the reference standard assessment, the 3D‐CAM was administered by trained research assistants (RAs) who were blinded to the results of the reference standard. To reduce the likelihood of fluctuations or temporal changes, all assessments were completed between 11:00 am and 2:00 pm and for each participant, within a 2‐hour time period (for example, 11:23 am to 1:23 pm).
Statistical Analyses to Determine the Best Single‐ and Two‐Item Screeners
To determine the best single 3D‐CAM item to identify delirium, the responses of the 20 individual items in the 3D‐CAM (see Supporting Table 1 in the online version of this article) were compared to the reference standard to determine their sensitivity and specificity. Similarly, an algorithm was used to generate all unique 2‐item combinations of the 20 items (190 unique pairs), which were compared to the reference. An error, no response, or an answer of I do not know by the patient was considered a positive screen for delirium. The 2‐item screeners were considered positive if 1 or both of the items were positive. Sensitivity and specificity were calculated along with 95% confidence intervals (CIs).
Subset analyses were performed to determine sensitivity and specificity of individual items and pairs of items stratified by the patient's baseline cognitive status. Two strata were createdpatients with dementia (N=56), and patients with normal baseline cognitive status or mild cognitive impairment (MCI) (N=145). We chose to group MCI with normal for 2 reasons: (1) dementia is a well‐established and strong risk factor for delirium, whereas the evidence for MCI being a risk factor for delirium is less established and (2) to achieve adequate allocation of delirious cases in both strata. Last, we report the sensitivity of altered level of consciousness (LOC), which included lethargy, stupor, coma, and hypervigilance as a single screening item for delirium in the overall sample and by cognitive status. Analyses were conducted using commercially available software (SAS version 9.3; SAS Institute, Inc., Cary, NC).
RESULTS
Characteristics of the patients are shown in Table 1. Subjects had a mean age of 84 years, 62% were female, and 28% had a baseline dementia. Forty‐two (21%) had delirium based on the clinical reference standard. Twenty (10%) had less than a high school education and 100 (49%) had at least a college education.
| Characteristic | N (%) |
|---|---|
| |
| Age, y, mean (SD) | 84 (5.4) |
| Sex, n (%) female | 125 (62) |
| White, n (%) | 177 (88) |
| Education, n (%) | |
| Less than high school | 20 (10) |
| High school graduate | 75 (38) |
| College plus | 100 (49) |
| Vision interfered with interview, n (%) | 5 (2) |
| Hearing interfered with interview, n (%) | 18 (9) |
| English second language n (%) | 10 (5) |
| Charlson, mean (SD) | 3 (2.3) |
| ADL, n (% impaired) | 110 (55) |
| IADL, n (% impaired) | 163 (81) |
| MCI, n (%) | 50 (25) |
| Dementia, n (%) | 56 (28) |
| Delirium, n (%) | 42 (21) |
| MoCA, mean (SD) | 19 (6.6) |
| MoCA, median (range) | 20 (030) |
Single Item Screens
Table 2 reports the results of single‐item screens for delirium with sensitivity, the ability to correctly identify delirium when it is present by the reference standard, and specificity, the ability to correctly identify patients without delirium when it is not present by reference standard and 95% CIs. Items are listed in descending order of sensitivity; in the case of ties, the item with the higher specificity is listed first. The screening items with the highest sensitivity for delirium are Months of the year backwards, and Four digits backwards, both with a sensitivity of 83% (95% CI: 69%‐93%). Of these 2 items, Months of the year backwards had a much better specificity of 69% (95% CI: 61%‐76%), whereas Four digits backwards had a specificity of 52% (95% CI: 44%‐60%). The item What is the day of the week? had lower sensitivity at 71% (95% CI: 55%‐84%), but excellent specificity at 92% (95% CI: 87%‐96%).
| Screen Item | Screen Positive (%)c | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR |
|---|---|---|---|---|---|
| |||||
| Months of the year backwards | 42 | 0.83 (0.69‐0.93) | 0.69 (0.61‐0.76) | 2.7 | 0.24 |
| Four digits backwards | 56 | 0.83 (0.69‐0.93) | 0.52 (0.44‐0.60) | 1.72 | 0.32 |
| What is the day of the week? | 21 | 0.71 (0.55‐0.84) | 0.92 (0.87‐0.96) | 9.46 | 0.31 |
| What is the year? | 16 | 0.55 (0.39‐0.70) | 0.94 (0.9‐0.97) | 9.67 | 0.48 |
| Have you felt confused during the past day? | 14 | 0.50 (0.34‐0.66) | 0.95 (0.9‐0.98) | 9.94 | 0.53 |
| Days of the week backwards | 15 | 0.50 (0.34‐0.66) | 0.94 (0.89‐0.97) | 7.95 | 0.53 |
| During the past day, did you see things that were not really there? | 11 | 0.45 (0.3‐0.61) | 0.97 (0.94‐0.99) | 17.98 | 0.56 |
| Three digits backwards | 15 | 0.45 (0.3‐0.61) | 0.92 (0.87‐0.96) | 5.99 | 0.59 |
| What type of place is this? | 9 | 0.38 (0.24‐0.54) | 0.99 (0.96‐1) | 30.29 | 0.63 |
| During the past day, did you think you were not in the hospital? | 10 | 0.38 (0.24‐0.54) | 0.97 (0.94‐0.99) | 15.14 | 0.64 |
We then examined performance of single‐item screeners in patients with and without dementia (Table 3). In persons with dementia, the best single item was also Months of the year backwards, with a sensitivity of 89% (95% CI: 72%‐98%) and a specificity of 61% (95% CI: 41%‐78%). In persons with normal baseline cognition or MCI, the best performing single item was Four digits backwards, with sensitivity of 79% (95% CI: 49%‐95%) and specificity of 51% (95% CI: 42%‐60%). Months of the year backwards also performed well, with sensitivity of 71% (95% CI: 42%‐92%) and specificity of 71% (95% CI: 62%‐79%).
| Test Item | Normal/MCI Patients (n=145) | Dementia Patients (n=56) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Screen Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | Screen Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | |
| ||||||||||
| Months backwards | 33 | 0.71 (0.42‐0.92) | 0.71 (0.62‐0.79) | 2.46 | 0.4 | 64 | 0.89 (0.72‐0.98) | 0.61 (0.41‐0.78) | 2.27 | 0.18 |
| Four digits backwards | 52 | 0.79 (0.49‐0.95) | 0.51 (0.42‐0.60) | 1.61 | 0.42 | 66 | 0.86 (0.67‐0.96) | 0.54 (0.34‐0.72) | 1.85 | 0.27 |
| What is the day of the week? | 10 | 0.64 (0.35‐0.87) | 0.96 (0.91‐0.99) | 16.84 | 0.37 | 50 | 0.75 (0.55‐0.89) | 0.75 (0.55‐0.89) | 3 | 0.33 |
Two‐Item Screens
Table 4 reports the results of 2‐item screens for delirium with sensitivity, specificity, and 95% CIs. Item pairs are listed in descending order of sensitivity following the same convention as in Table 2. The 2‐item screen with the highest sensitivity for delirium is the combination of What is the day of the week? and Months of the year backwards, with a sensitivity of 93% (95% CI: 81%‐99%) and specificity of 64% (95% CI: 56%‐70%). This screen had a positive and negative likelihood ratio (LR) of 2.59 and 0.11, respectively. The combination of What is the day of the week? and Four digits backwards had the same sensitivity 93% (95% CI: 81%‐99%), but lower specificity of 48% (95% CI: 40%‐56%). The combination of What type of place is this? (hospital) and Four digits backwards had a sensitivity of 90% (95% CI: 77%‐97%) and specificity of 51% (95% CI: 43%‐50%).
| Screen Item 1 | Screen Item 2 | Screen Positive (%)c | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR |
|---|---|---|---|---|---|---|
| ||||||
| What is the day of the week? | Months backwards | 48 | 0.93 (0.81‐0.99) | 0.64 (0.56‐0.70) | 2.59 | 0.11 |
| What is the day of the week? | Four digits backwards | 60 | 0.93 (0.81‐0.99) | 0.48 (0.4‐0.56) | 1.8 | 0.15 |
| Four digits backwards | Months backwards | 65 | 0.93 (0.81‐0.99) | 0.42 (0.34‐0.50) | 1.6 | 0.17 |
| What type of place is this? | Four digits backwards | 58 | 0.90 (0.77‐0.97) | 0.51 (0.43‐0.50) | 1.84 | 0.19 |
| What is the year? | Four digits backwards | 59 | 0.9 (0.77‐0.97) | 0.5 (0.42‐0.5) | 1.80 | 0.19 |
| What is the day of the week? | Three digits backwards | 30 | 0.88 (0.74‐0.96) | 0.86 (0.79‐0.90) | 6.09 | 0.14 |
| What is the year? | Months backwards | 44 | 0.88 (0.74‐0.96) | 0.68 (0.6‐0.75) | 2.75 | 0.18 |
| What type of place is this? | Months backwards | 43 | 0.86 (0.71‐0.95) | 0.69 (0.61‐0.70) | 2.73 | 0.21 |
| During the past day, did you think you were not in the hospital? | Months backwards | 43 | 0.86 (0.71‐0.95) | 0.69 (0.61‐0.70) | 2.73 | 0.21 |
| Days of the week backwards | Months backwards | 43 | 0.86 (0.71‐0.95) | 0.68 (0.6‐0.75) | 2.67 | 0.21 |
When subjects were stratified by baseline cognition, the best 2‐item screens for normal and MCI patients was What is the day of the week? and Four digits backwards, with 93% sensitivity (95% CI: 66%‐100%) and 50% specificity (95% CI: 42%‐59%). The best pair of items for patients with dementia (Table 5) was the same as the overall sample, What is the day of the week? and Months of the year backwards, but its performance differed with a higher sensitivity of 96% (95% CI: 82%‐100%) and lower specificity of 43% (95% CI: 24%‐63%). This same pair of items had 86% sensitivity (95% CI: 57%‐98%) and 69% (95% CI: 60%‐77%) specificity for persons with either normal cognition or MCI.
| Test Item 1 | Test Item 2 | Normal/MCI Patients (n=145) | Dementia Patients (n=56) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Item Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | Item Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | ||
| |||||||||||
| What is the day of the week? | Months backwards | 36 | 0.86 (0.57‐0.98) | 0.69 (0.60‐0.77) | 2.74 | 0.21 | 77 | 0.96 (0.82‐1) | 0.43 (0.24‐0.63) | 1.69 | 0.08 |
| What is the day of the week? | Four digits backwards | 54 | 0.93 (0.66‐1) | 0.5 (0.42‐0.59) | 1.87 | 0.14 | 77 | 0.93 (0.76‐0.99) | 0.39 (0.22‐0.59) | 1.53 | 0.18 |
| Four digits backwards | Months backwards | 61 | 0.93 (0.66‐1) | 0.43 (0.34‐0.52) | 1.62 | 0.17 | 77 | 0.93 (0.76‐0.99) | 0.39 (0.22‐0.59) | 1.53 | 0.18 |
Altered Level of Consciousness as a Screener for Delirium
Altered level of consciousness (ALOC) was uncommon in our sample, with an overall prevalence of 10/201 (4.9%). When examined as a screening item for delirium, ALOC had very poor sensitivity of 19% (95% CI: 9%‐34%) but had excellent specificity 99% (95% CI: 96%‐100%). Altered LOC also demonstrated poor screening performance when stratified by cognitive status, with a sensitivity of 14% in the normal and MCI group (95% CI: 2%‐43%) and sensitivity of 21% (95% CI: 8%‐41%) in persons with dementia.
Positive and Negative Predictive Values
Although we focused on sensitivity and specificity in evaluating 1‐ and 2‐item screeners, we also examined positive and negative predictive values. These values will vary depending on the overall prevalence of delirium, which was 21% in this dataset. The best 1‐item screener, Months of the year backwards, had a positive predictive value of 31% and negative predictive value of 94%. The best 2‐item screener, Months of the year backwards with What is the day of the week?, had a positive predictive value of 41% and negative predictive value of 97% (see Supporting Tables 2 and 3 in the online version of this article) LRs for the items are in Tables 2 through 5.
DISCUSSION
Identifying simple, efficient, bedside case‐identification methods for delirium is an essential step toward improving recognition of this highly morbid syndrome in hospitalized older adults. In this study, we identified a single cognitive item, Months of the year backwards, that identified 83% of delirium cases when compared with a reference standard diagnosis. Furthermore, we identified 2 items, Months of the year backwards and What is the day of the week? which when used in combination identified 93% of delirium cases. The same 1 and 2 items also worked well in patients with dementia, in whom delirium is often missed. Although these items require further clinical validation, the development of an ultrabrief 2‐item test that identifies over 90% of delirium cases and can be completed in less than 1 minute (recently, we administered the best 2‐item screener to 20 consecutive general medicine patients over age 70 years, and it was completed in a median of 36.5 seconds), holds great potential for simplifying bedside delirium screening and improving the care of hospitalized older adults.
Our current findings both confirm and extend the emerging literature on best screening items for delirium. Sands and colleagues (2010)[26] tested a single test for delirium, Do you think (name of patient) has been more confused lately? in 21 subjects and achieved a sensitivity of 80%. Han and colleagues developed a screening tool in emergency‐department patients using the LOC question from the Richmond Agitation‐Sedation Scale and spelling the word lunch backwards, and achieved 98% sensitivity, but in a younger emergency department population with a low prevalence of dementia.[27] O'Regan et al. recently also found Months of the year backwards to be the best single‐screening item for delirium in a large sample, but only tested a 1‐item screen.[28] Our study extends these studies in several important ways by: (1) employing a rigorous clinical reference standard diagnosis of delirium, (2) having a large sample with a high prevalence of patients with dementia, (3) use of a general medical population, and (4) examining the best 2‐item screens in addition to the best single item.
Systematic intervention programs[29, 30, 31] that focus on improved delirium evaluation and management have the potential to improve patient outcomes and reduce costs. However, targeting these programs to patients with delirium has proven difficult, as only 12% to 35% of delirium cases are recognized in routine clinical practice.[11, 12, 13, 14, 15] The 1‐ and 2‐item screeners we identified could play an important role in future delirium identification. The 3D‐CAM combines high sensitivity (95%) with high specificity (94%)[16] and therefore would be an excellent choice as the second step after a positive screen. The feasibility, effectiveness, and cost of administering these screeners, followed by a brief diagnostic tool such as the 3D‐CAM, should be evaluated in future work.
Our study has noteworthy strengths, including the use of a large purposefully challenging clinical sample with advanced age that included a substantial proportion with dementia, a detailed assessment, and the testing of very brief and practical tools for bedside delirium screening.[25] This study also has several important limitations. Most importantly, we presented secondary analysis of individual items and pairs of items drawn from the 3D CAM assessment; therefore, the 2‐item bedside screen requires prospective clinical validation. The reference standard was based on the DSM‐IV, because this study was conducted prior to the release of DSM‐V. In addition, the ordering of the reference standard and 3D‐CAM assessments was not randomized due to feasibility constraints. In addition, this study was cross‐sectional, involved only a single hospital, and enrolled only older medical patients during the day shift. Our sample was older (aged 75 years and older), and a younger sample may have had a different prevalence of delirium, which could affect the positive predictive value of our ultrabrief screen. We plan to test this in a sample of patients aged 70 years and older in future studies. Finally, it should be noted that these best 1‐item and 2‐item screeners miss 17% and 7% of delirium cases, respectively. In cases where this is unacceptably high, alternative approaches might be necessary.
It is important to remember that these 1‐ and 2‐item screeners are not diagnostic tools and therefore should not be used in isolation. Optimally, they will be followed by a more specific evaluation, such as the 3D‐CAM, as part of a systematic delirium identification process. For instance, in our sample (with a delirium rate of 21%), the best 2‐item screener had a positive predictive value of 41%, meaning that positive screens are more likely to be false positives than true positives (see Supporting Tables 2 and 3 in the online version of this article).[32] Nevertheless, by reducing the total number of patients who require diagnostic instrument administration, use of these ultrabrief screeners can improve efficiency and result in a net benefit to delirium case‐identification efforts.[32]
Time has been demonstrated to be a barrier to delirium identification in previous studies, but there are likely others. These may include, for instance, staff nihilism about screening making a difference, ambiguous responsibility for delirium screening and management, unsupportive system leadership, and absent payment for these activities.[31] Moreover, it is possible that the 2‐step process we propose may create an incentive for staff to avoid positive screens as they see it creating more work for themselves. We plan to identify and address such barriers in our future work.
In conclusion, we identified a single screening item for delirium, Months of the year backwards, with 83% sensitivity, and a pair of items, Months of the year backwards and What is the day of the week?, with 93% sensitivity relative to a rigorous reference standard diagnosis. These ultrabrief screening items work well in patients with and without dementia, and should require very little training of staff. Future studies should further validate these tools, and determine their translatability and scalability into programs for systematic, widespread delirium detection. Developing efficient and accurate case identification strategies is a necessary prerequisite to appropriately target delirium management protocols, enabling healthcare systems to effectively address this costly and deadly condition.
Disclosures
Author contributionsD.M.F. conceived the study idea, participated in its design and coordination, and drafted the initial manuscript. S.K.I. contributed to the study design and conceptualization, supervision, funding, preliminary analysis, and interpretation of the data, and critical revision of the manuscript. J.G. conducted the analysis for the study and critically revised the manuscript. L.N. supervised the analysis for the study and critically revised the manuscript. R.J. contributed to the study design and critical revision of the manuscript. J.S.S. critically revised the manuscript. E.R.M. obtained funding for the study, supervised all data collection, assisted in drafting and critically revising the manuscript, and contributed to the conceptualization, design, and supervision of the study. All authors have seen and agree with the contents of the manuscript.
This work was supported by the National Institute of Aging grant number R01AG030618 and K24AG035075 to Dr. Marcantonio. Dr. Inouye's time was supported in part by grants P01AG031720, R01AG044518, and K07AG041835 from the National Institute on Aging. Dr. Inouye holds the Milton and Shirley F. Levy Family Chair (Hebrew Senior Life/Harvard Medical School). Dr. Fick is partially supported from National Institute of Nursing Research grant number R01 NR011042. Dr. Saczynski was supported in part by funding from the National Institute on Aging (K01AG33643) and from the National Heart Lung and Blood Institute (U01HL105268). The funding agencies had no role and the authors retained full autonomy in the preparation of this article. All authors and coauthors have no financial or nonfinancial conflicts of interest to disclose regarding this article.
This article was presented at the Presidential Poster Session at the American Geriatrics Society 2014 Annual Meeting in Orlando, Florida, May 14, 2014.
Delirium (acute confusion) is common in older adults and leads to poor outcomes, such as death, clinician and caregiver burden, and prolonged cognitive and functional decline.[1, 2, 3, 4] Delirium is extremely costly, with estimates ranging from $143 to $152 billion annually (2005 US$).[5, 6] Early detection and management may improve the poor outcomes and reduce costs attributable to delirium,[3, 7] yet delirium identification in clinical practice has been challenging, particularly when translating research tools to the bedside.[8, 9, 10]As a result, only 12% to 35% of delirium cases are detected in routine care, with hypoactive delirium and delirium superimposed on dementia most likely to be missed.[11, 12, 13, 14, 15]
To address these issues, we recently developed and published the three‐dimensional Confusion Assessment Method (3D‐CAM), the 3‐minute diagnostic assessment for CAM‐defined delirium.[16] The 3D‐CAM is a structured assessment tool that includes mental status testing, patient symptom probes, and guided interviewer observations for signs of delirium. 3D‐CAM items were selected through a rigorous process to determine the most informative items for the 4 CAM diagnostic features.[17] The 3D‐CAM can be completed in 3 minutes, and has 95% sensitivity and 94% specificity relative to a reference standard.[16]
Despite the capabilities of the 3D‐CAM, there are situations when even 3 minutes is too long to devote to delirium identification. Moreover, a 2‐step approach in which a sensitive ultrabrief screen is administered, followed by the 3D‐CAM in positives, may be the most efficient approach for large‐scale delirium case identification. The aim of the current study was to use the 3D‐CAM database to identify the most sensitive single item and pair of items in the diagnosis of delirium, using the reference standard in the diagnostic accuracy analysis. We hypothesized that we could identify a single item with greater than 80% sensitivity and a pair of items with greater than 90% sensitivity for detection of delirium.
METHODS
Study Sample and Design
We analyzed data from the 3D‐CAM validation study,[16] which prospectively enrolled participants from a large urban teaching hospital in Boston, Massachusetts, using a consecutive enrollment sampling strategy. Inclusion criteria were: (1) 75 years old, (2) admitted to general or geriatric medicine services, (3) able to communicate in English, (4) without terminal conditions, (5) expected hospital stay of 2 days, (6) not a previous study participant. Experienced clinicians screened patients for eligibility. If the patient lacked capacity to provide consent, the designated surrogate decision maker was contacted. The study was approved by the institutional review board.
Reference Standard Delirium Diagnosis
The reference standard delirium diagnosis was based on an extensive (45 minutes) face‐to‐face patient interview by experienced clinician assessors (neuropsychologists or advanced practice nurses), medical record review, and input from the nurse and family members. This comprehensive assessment included: (1) reason for hospital admission, hospital course, and presence of cognitive concerns, (2) family, social, and functional history, (3) Montreal Cognitive Assessment,[18] (4) Geriatric Depression Scale,[19] (5) medical record review including scoring of comorbidities using the Charlson index,[20] determination of functional status using the basic and Instrumental Activities of Daily Living,[21, 22] psychoactive medications administered, and (6) a family member interview to assess the patient's baseline cognitive status that included the Eight‐Item Interview to Differentiate Aging and Dementia,[23] to assess the presence of dementia. Using all of these data, an expert panel, including the clinical assessor, the study principal investigator (E.R.M.), a geriatrician, and an experienced neuropsychologist, adjudicated the final delirium diagnoses using Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM‐IV) criteria. The panel also adjudicated for the presence or absence of dementia and mild cognitive impairment based on National Institute on Aging‐Alzheimer's Association (NIA‐AA) criteria.[24] This approach has been used in other delirium studies.[25]
3D‐CAM Assessments
After the reference standard assessment, the 3D‐CAM was administered by trained research assistants (RAs) who were blinded to the results of the reference standard. To reduce the likelihood of fluctuations or temporal changes, all assessments were completed between 11:00 am and 2:00 pm and for each participant, within a 2‐hour time period (for example, 11:23 am to 1:23 pm).
Statistical Analyses to Determine the Best Single‐ and Two‐Item Screeners
To determine the best single 3D‐CAM item to identify delirium, the responses of the 20 individual items in the 3D‐CAM (see Supporting Table 1 in the online version of this article) were compared to the reference standard to determine their sensitivity and specificity. Similarly, an algorithm was used to generate all unique 2‐item combinations of the 20 items (190 unique pairs), which were compared to the reference. An error, no response, or an answer of I do not know by the patient was considered a positive screen for delirium. The 2‐item screeners were considered positive if 1 or both of the items were positive. Sensitivity and specificity were calculated along with 95% confidence intervals (CIs).
Subset analyses were performed to determine sensitivity and specificity of individual items and pairs of items stratified by the patient's baseline cognitive status. Two strata were createdpatients with dementia (N=56), and patients with normal baseline cognitive status or mild cognitive impairment (MCI) (N=145). We chose to group MCI with normal for 2 reasons: (1) dementia is a well‐established and strong risk factor for delirium, whereas the evidence for MCI being a risk factor for delirium is less established and (2) to achieve adequate allocation of delirious cases in both strata. Last, we report the sensitivity of altered level of consciousness (LOC), which included lethargy, stupor, coma, and hypervigilance as a single screening item for delirium in the overall sample and by cognitive status. Analyses were conducted using commercially available software (SAS version 9.3; SAS Institute, Inc., Cary, NC).
RESULTS
Characteristics of the patients are shown in Table 1. Subjects had a mean age of 84 years, 62% were female, and 28% had a baseline dementia. Forty‐two (21%) had delirium based on the clinical reference standard. Twenty (10%) had less than a high school education and 100 (49%) had at least a college education.
| Characteristic | N (%) |
|---|---|
| |
| Age, y, mean (SD) | 84 (5.4) |
| Sex, n (%) female | 125 (62) |
| White, n (%) | 177 (88) |
| Education, n (%) | |
| Less than high school | 20 (10) |
| High school graduate | 75 (38) |
| College plus | 100 (49) |
| Vision interfered with interview, n (%) | 5 (2) |
| Hearing interfered with interview, n (%) | 18 (9) |
| English second language n (%) | 10 (5) |
| Charlson, mean (SD) | 3 (2.3) |
| ADL, n (% impaired) | 110 (55) |
| IADL, n (% impaired) | 163 (81) |
| MCI, n (%) | 50 (25) |
| Dementia, n (%) | 56 (28) |
| Delirium, n (%) | 42 (21) |
| MoCA, mean (SD) | 19 (6.6) |
| MoCA, median (range) | 20 (030) |
Single Item Screens
Table 2 reports the results of single‐item screens for delirium with sensitivity, the ability to correctly identify delirium when it is present by the reference standard, and specificity, the ability to correctly identify patients without delirium when it is not present by reference standard and 95% CIs. Items are listed in descending order of sensitivity; in the case of ties, the item with the higher specificity is listed first. The screening items with the highest sensitivity for delirium are Months of the year backwards, and Four digits backwards, both with a sensitivity of 83% (95% CI: 69%‐93%). Of these 2 items, Months of the year backwards had a much better specificity of 69% (95% CI: 61%‐76%), whereas Four digits backwards had a specificity of 52% (95% CI: 44%‐60%). The item What is the day of the week? had lower sensitivity at 71% (95% CI: 55%‐84%), but excellent specificity at 92% (95% CI: 87%‐96%).
| Screen Item | Screen Positive (%)c | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR |
|---|---|---|---|---|---|
| |||||
| Months of the year backwards | 42 | 0.83 (0.69‐0.93) | 0.69 (0.61‐0.76) | 2.7 | 0.24 |
| Four digits backwards | 56 | 0.83 (0.69‐0.93) | 0.52 (0.44‐0.60) | 1.72 | 0.32 |
| What is the day of the week? | 21 | 0.71 (0.55‐0.84) | 0.92 (0.87‐0.96) | 9.46 | 0.31 |
| What is the year? | 16 | 0.55 (0.39‐0.70) | 0.94 (0.9‐0.97) | 9.67 | 0.48 |
| Have you felt confused during the past day? | 14 | 0.50 (0.34‐0.66) | 0.95 (0.9‐0.98) | 9.94 | 0.53 |
| Days of the week backwards | 15 | 0.50 (0.34‐0.66) | 0.94 (0.89‐0.97) | 7.95 | 0.53 |
| During the past day, did you see things that were not really there? | 11 | 0.45 (0.3‐0.61) | 0.97 (0.94‐0.99) | 17.98 | 0.56 |
| Three digits backwards | 15 | 0.45 (0.3‐0.61) | 0.92 (0.87‐0.96) | 5.99 | 0.59 |
| What type of place is this? | 9 | 0.38 (0.24‐0.54) | 0.99 (0.96‐1) | 30.29 | 0.63 |
| During the past day, did you think you were not in the hospital? | 10 | 0.38 (0.24‐0.54) | 0.97 (0.94‐0.99) | 15.14 | 0.64 |
We then examined performance of single‐item screeners in patients with and without dementia (Table 3). In persons with dementia, the best single item was also Months of the year backwards, with a sensitivity of 89% (95% CI: 72%‐98%) and a specificity of 61% (95% CI: 41%‐78%). In persons with normal baseline cognition or MCI, the best performing single item was Four digits backwards, with sensitivity of 79% (95% CI: 49%‐95%) and specificity of 51% (95% CI: 42%‐60%). Months of the year backwards also performed well, with sensitivity of 71% (95% CI: 42%‐92%) and specificity of 71% (95% CI: 62%‐79%).
| Test Item | Normal/MCI Patients (n=145) | Dementia Patients (n=56) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Screen Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | Screen Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | |
| ||||||||||
| Months backwards | 33 | 0.71 (0.42‐0.92) | 0.71 (0.62‐0.79) | 2.46 | 0.4 | 64 | 0.89 (0.72‐0.98) | 0.61 (0.41‐0.78) | 2.27 | 0.18 |
| Four digits backwards | 52 | 0.79 (0.49‐0.95) | 0.51 (0.42‐0.60) | 1.61 | 0.42 | 66 | 0.86 (0.67‐0.96) | 0.54 (0.34‐0.72) | 1.85 | 0.27 |
| What is the day of the week? | 10 | 0.64 (0.35‐0.87) | 0.96 (0.91‐0.99) | 16.84 | 0.37 | 50 | 0.75 (0.55‐0.89) | 0.75 (0.55‐0.89) | 3 | 0.33 |
Two‐Item Screens
Table 4 reports the results of 2‐item screens for delirium with sensitivity, specificity, and 95% CIs. Item pairs are listed in descending order of sensitivity following the same convention as in Table 2. The 2‐item screen with the highest sensitivity for delirium is the combination of What is the day of the week? and Months of the year backwards, with a sensitivity of 93% (95% CI: 81%‐99%) and specificity of 64% (95% CI: 56%‐70%). This screen had a positive and negative likelihood ratio (LR) of 2.59 and 0.11, respectively. The combination of What is the day of the week? and Four digits backwards had the same sensitivity 93% (95% CI: 81%‐99%), but lower specificity of 48% (95% CI: 40%‐56%). The combination of What type of place is this? (hospital) and Four digits backwards had a sensitivity of 90% (95% CI: 77%‐97%) and specificity of 51% (95% CI: 43%‐50%).
| Screen Item 1 | Screen Item 2 | Screen Positive (%)c | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR |
|---|---|---|---|---|---|---|
| ||||||
| What is the day of the week? | Months backwards | 48 | 0.93 (0.81‐0.99) | 0.64 (0.56‐0.70) | 2.59 | 0.11 |
| What is the day of the week? | Four digits backwards | 60 | 0.93 (0.81‐0.99) | 0.48 (0.4‐0.56) | 1.8 | 0.15 |
| Four digits backwards | Months backwards | 65 | 0.93 (0.81‐0.99) | 0.42 (0.34‐0.50) | 1.6 | 0.17 |
| What type of place is this? | Four digits backwards | 58 | 0.90 (0.77‐0.97) | 0.51 (0.43‐0.50) | 1.84 | 0.19 |
| What is the year? | Four digits backwards | 59 | 0.9 (0.77‐0.97) | 0.5 (0.42‐0.5) | 1.80 | 0.19 |
| What is the day of the week? | Three digits backwards | 30 | 0.88 (0.74‐0.96) | 0.86 (0.79‐0.90) | 6.09 | 0.14 |
| What is the year? | Months backwards | 44 | 0.88 (0.74‐0.96) | 0.68 (0.6‐0.75) | 2.75 | 0.18 |
| What type of place is this? | Months backwards | 43 | 0.86 (0.71‐0.95) | 0.69 (0.61‐0.70) | 2.73 | 0.21 |
| During the past day, did you think you were not in the hospital? | Months backwards | 43 | 0.86 (0.71‐0.95) | 0.69 (0.61‐0.70) | 2.73 | 0.21 |
| Days of the week backwards | Months backwards | 43 | 0.86 (0.71‐0.95) | 0.68 (0.6‐0.75) | 2.67 | 0.21 |
When subjects were stratified by baseline cognition, the best 2‐item screens for normal and MCI patients was What is the day of the week? and Four digits backwards, with 93% sensitivity (95% CI: 66%‐100%) and 50% specificity (95% CI: 42%‐59%). The best pair of items for patients with dementia (Table 5) was the same as the overall sample, What is the day of the week? and Months of the year backwards, but its performance differed with a higher sensitivity of 96% (95% CI: 82%‐100%) and lower specificity of 43% (95% CI: 24%‐63%). This same pair of items had 86% sensitivity (95% CI: 57%‐98%) and 69% (95% CI: 60%‐77%) specificity for persons with either normal cognition or MCI.
| Test Item 1 | Test Item 2 | Normal/MCI Patients (n=145) | Dementia Patients (n=56) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Item Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | Item Positive (%)b | Sensitivity (95% CI) | Specificity (95% CI) | LR | LR | ||
| |||||||||||
| What is the day of the week? | Months backwards | 36 | 0.86 (0.57‐0.98) | 0.69 (0.60‐0.77) | 2.74 | 0.21 | 77 | 0.96 (0.82‐1) | 0.43 (0.24‐0.63) | 1.69 | 0.08 |
| What is the day of the week? | Four digits backwards | 54 | 0.93 (0.66‐1) | 0.5 (0.42‐0.59) | 1.87 | 0.14 | 77 | 0.93 (0.76‐0.99) | 0.39 (0.22‐0.59) | 1.53 | 0.18 |
| Four digits backwards | Months backwards | 61 | 0.93 (0.66‐1) | 0.43 (0.34‐0.52) | 1.62 | 0.17 | 77 | 0.93 (0.76‐0.99) | 0.39 (0.22‐0.59) | 1.53 | 0.18 |
Altered Level of Consciousness as a Screener for Delirium
Altered level of consciousness (ALOC) was uncommon in our sample, with an overall prevalence of 10/201 (4.9%). When examined as a screening item for delirium, ALOC had very poor sensitivity of 19% (95% CI: 9%‐34%) but had excellent specificity 99% (95% CI: 96%‐100%). Altered LOC also demonstrated poor screening performance when stratified by cognitive status, with a sensitivity of 14% in the normal and MCI group (95% CI: 2%‐43%) and sensitivity of 21% (95% CI: 8%‐41%) in persons with dementia.
Positive and Negative Predictive Values
Although we focused on sensitivity and specificity in evaluating 1‐ and 2‐item screeners, we also examined positive and negative predictive values. These values will vary depending on the overall prevalence of delirium, which was 21% in this dataset. The best 1‐item screener, Months of the year backwards, had a positive predictive value of 31% and negative predictive value of 94%. The best 2‐item screener, Months of the year backwards with What is the day of the week?, had a positive predictive value of 41% and negative predictive value of 97% (see Supporting Tables 2 and 3 in the online version of this article) LRs for the items are in Tables 2 through 5.
DISCUSSION
Identifying simple, efficient, bedside case‐identification methods for delirium is an essential step toward improving recognition of this highly morbid syndrome in hospitalized older adults. In this study, we identified a single cognitive item, Months of the year backwards, that identified 83% of delirium cases when compared with a reference standard diagnosis. Furthermore, we identified 2 items, Months of the year backwards and What is the day of the week? which when used in combination identified 93% of delirium cases. The same 1 and 2 items also worked well in patients with dementia, in whom delirium is often missed. Although these items require further clinical validation, the development of an ultrabrief 2‐item test that identifies over 90% of delirium cases and can be completed in less than 1 minute (recently, we administered the best 2‐item screener to 20 consecutive general medicine patients over age 70 years, and it was completed in a median of 36.5 seconds), holds great potential for simplifying bedside delirium screening and improving the care of hospitalized older adults.
Our current findings both confirm and extend the emerging literature on best screening items for delirium. Sands and colleagues (2010)[26] tested a single test for delirium, Do you think (name of patient) has been more confused lately? in 21 subjects and achieved a sensitivity of 80%. Han and colleagues developed a screening tool in emergency‐department patients using the LOC question from the Richmond Agitation‐Sedation Scale and spelling the word lunch backwards, and achieved 98% sensitivity, but in a younger emergency department population with a low prevalence of dementia.[27] O'Regan et al. recently also found Months of the year backwards to be the best single‐screening item for delirium in a large sample, but only tested a 1‐item screen.[28] Our study extends these studies in several important ways by: (1) employing a rigorous clinical reference standard diagnosis of delirium, (2) having a large sample with a high prevalence of patients with dementia, (3) use of a general medical population, and (4) examining the best 2‐item screens in addition to the best single item.
Systematic intervention programs[29, 30, 31] that focus on improved delirium evaluation and management have the potential to improve patient outcomes and reduce costs. However, targeting these programs to patients with delirium has proven difficult, as only 12% to 35% of delirium cases are recognized in routine clinical practice.[11, 12, 13, 14, 15] The 1‐ and 2‐item screeners we identified could play an important role in future delirium identification. The 3D‐CAM combines high sensitivity (95%) with high specificity (94%)[16] and therefore would be an excellent choice as the second step after a positive screen. The feasibility, effectiveness, and cost of administering these screeners, followed by a brief diagnostic tool such as the 3D‐CAM, should be evaluated in future work.
Our study has noteworthy strengths, including the use of a large purposefully challenging clinical sample with advanced age that included a substantial proportion with dementia, a detailed assessment, and the testing of very brief and practical tools for bedside delirium screening.[25] This study also has several important limitations. Most importantly, we presented secondary analysis of individual items and pairs of items drawn from the 3D CAM assessment; therefore, the 2‐item bedside screen requires prospective clinical validation. The reference standard was based on the DSM‐IV, because this study was conducted prior to the release of DSM‐V. In addition, the ordering of the reference standard and 3D‐CAM assessments was not randomized due to feasibility constraints. In addition, this study was cross‐sectional, involved only a single hospital, and enrolled only older medical patients during the day shift. Our sample was older (aged 75 years and older), and a younger sample may have had a different prevalence of delirium, which could affect the positive predictive value of our ultrabrief screen. We plan to test this in a sample of patients aged 70 years and older in future studies. Finally, it should be noted that these best 1‐item and 2‐item screeners miss 17% and 7% of delirium cases, respectively. In cases where this is unacceptably high, alternative approaches might be necessary.
It is important to remember that these 1‐ and 2‐item screeners are not diagnostic tools and therefore should not be used in isolation. Optimally, they will be followed by a more specific evaluation, such as the 3D‐CAM, as part of a systematic delirium identification process. For instance, in our sample (with a delirium rate of 21%), the best 2‐item screener had a positive predictive value of 41%, meaning that positive screens are more likely to be false positives than true positives (see Supporting Tables 2 and 3 in the online version of this article).[32] Nevertheless, by reducing the total number of patients who require diagnostic instrument administration, use of these ultrabrief screeners can improve efficiency and result in a net benefit to delirium case‐identification efforts.[32]
Time has been demonstrated to be a barrier to delirium identification in previous studies, but there are likely others. These may include, for instance, staff nihilism about screening making a difference, ambiguous responsibility for delirium screening and management, unsupportive system leadership, and absent payment for these activities.[31] Moreover, it is possible that the 2‐step process we propose may create an incentive for staff to avoid positive screens as they see it creating more work for themselves. We plan to identify and address such barriers in our future work.
In conclusion, we identified a single screening item for delirium, Months of the year backwards, with 83% sensitivity, and a pair of items, Months of the year backwards and What is the day of the week?, with 93% sensitivity relative to a rigorous reference standard diagnosis. These ultrabrief screening items work well in patients with and without dementia, and should require very little training of staff. Future studies should further validate these tools, and determine their translatability and scalability into programs for systematic, widespread delirium detection. Developing efficient and accurate case identification strategies is a necessary prerequisite to appropriately target delirium management protocols, enabling healthcare systems to effectively address this costly and deadly condition.
Disclosures
Author contributionsD.M.F. conceived the study idea, participated in its design and coordination, and drafted the initial manuscript. S.K.I. contributed to the study design and conceptualization, supervision, funding, preliminary analysis, and interpretation of the data, and critical revision of the manuscript. J.G. conducted the analysis for the study and critically revised the manuscript. L.N. supervised the analysis for the study and critically revised the manuscript. R.J. contributed to the study design and critical revision of the manuscript. J.S.S. critically revised the manuscript. E.R.M. obtained funding for the study, supervised all data collection, assisted in drafting and critically revising the manuscript, and contributed to the conceptualization, design, and supervision of the study. All authors have seen and agree with the contents of the manuscript.
This work was supported by the National Institute of Aging grant number R01AG030618 and K24AG035075 to Dr. Marcantonio. Dr. Inouye's time was supported in part by grants P01AG031720, R01AG044518, and K07AG041835 from the National Institute on Aging. Dr. Inouye holds the Milton and Shirley F. Levy Family Chair (Hebrew Senior Life/Harvard Medical School). Dr. Fick is partially supported from National Institute of Nursing Research grant number R01 NR011042. Dr. Saczynski was supported in part by funding from the National Institute on Aging (K01AG33643) and from the National Heart Lung and Blood Institute (U01HL105268). The funding agencies had no role and the authors retained full autonomy in the preparation of this article. All authors and coauthors have no financial or nonfinancial conflicts of interest to disclose regarding this article.
This article was presented at the Presidential Poster Session at the American Geriatrics Society 2014 Annual Meeting in Orlando, Florida, May 14, 2014.
- , , , , , Delirium in elderly patients and the risk of postdischarge mortality, institutionalization, and dementia: a meta‐analysis. JAMA. 2010;304(4):443–451.
- , , , et al. Cognitive trajectories after postoperative delirium. N Engl J Med. 2012;367(1):30–39.
- , , Delirium in elderly people. Lancet. 2014;383:911–922.
- , , , Delirium superimposed on dementia is associated with prolonged length of stay and poor outcomes in hospitalized older adults. J Hosp Med. 2013;8(9):500–505.
- , , , , One‐year health care costs associated with delirium in the elderly population. Arch Intern Med. 2008;168(1):27–32.
- , The importance of delirium: Economic and societal costs. J Am Geriatr Soc. 2011;59(suppl 2):S241–S243.
- Delirium. Ann Intern Med. 2011;154(11):ITC6.
- , , , , , Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4:50.
- , , , Mixed‐methods approach to understanding nurses' clinical reasoning in recognizing delirium in hospitalized older adults. J Contin Educ Nurs. 2014;45:1–13.
- , , Educational interventions to improve recognition of delirium: a systematic review. J Am Geriatr Soc. 2013;61(11):1983–1993.
- , Delirium superimposed on dementia: accuracy of nurse documentation. J Gerontol Nurs. 2012;38(1):32–42.
- , , , et al. Detection of delirium by bedside nurses using the confusion assessment method. J Am Geriatr Soc. 2006;54:685–689.
- , , , et al. Documentation of delirium in elderly patients with hip fracture. J Gerontol Nurs. 2002;28(11):23–29.
- , , , Recorded delirium in a national sample of elderly inpatients: potential implications for recognition. J Geriatr Psychiatry Neurol. 2003;16(1):32–38.
- , , , et al. A tale of two methods: chart and interview methods for identifying delirium. J Am Geriatr Soc. 2014;62(3):518–524.
- , , , et al. 3D‐CAM: Derivation and validation of a 3‐minute diagnostic interview for CAM‐defined delirium: a cross‐sectional diagnostic test study. Ann Intern Med. 2014;161(8):554–561.
- , , , et al. Selecting optimal screening items for delirium: an application of item response theory. BMC Med Res Methodol. 2013;13:8.
- , , , et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–699.
- Geriatric Depression Scale. Psychopharmacol Bull. 1988;24(4):709–711.
- , , , A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–383.
- , , , , Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185:914–919.
- , Assessment of older people: self‐maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179–186.
- , , , et al. The AD8: a brief informant interview to detect dementia. Neurology. 2005;65(4):559–564.
- , , , et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging‐Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7(3):263–269.
- , , , et al. Delirium diagnosis methodology used in research: a survey‐based study. Am J Geriatr Psychiatry. 2014;22(12):1513–1521.
- , , , , Single Question in Delirium (SQiD): testing its efficacy against psychiatrist interview, the Confusion Assessment Method and the Memorial Delirium Assessment Scale. Palliat Med. 2010;24(6):561–565.
- , , , et al. Diagnosing delirium in older emergency department patients: validity and reliability of the delirium triage screen and the brief confusion assessment method. Ann Emerg Med. 2013;62(5):457–465.
- , , , et al. Attention! A good bedside test for delirium? J Neurol Neurosurg Psychiatry. 2014;85(10):1122–1131.
- , , , , A model for management of delirious postacute care patients. J Am Geriatr Soc. 2005;53(10):1817–1825.
- , , , Computerized decision support for delirium superimposed on dementia in older adults: a pilot study. J Gerontol Nurs. 2011;37(4):39–47.
- , , , et al. Barriers and facilitators to implementing delirium rounds in a clinical trial across three diverse hospital settings. Clin Nurs Res. 2014;23(2):201–215.
- , Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores. Psychol Bull. 1955;52(3):194.
- , , , , , Delirium in elderly patients and the risk of postdischarge mortality, institutionalization, and dementia: a meta‐analysis. JAMA. 2010;304(4):443–451.
- , , , et al. Cognitive trajectories after postoperative delirium. N Engl J Med. 2012;367(1):30–39.
- , , Delirium in elderly people. Lancet. 2014;383:911–922.
- , , , Delirium superimposed on dementia is associated with prolonged length of stay and poor outcomes in hospitalized older adults. J Hosp Med. 2013;8(9):500–505.
- , , , , One‐year health care costs associated with delirium in the elderly population. Arch Intern Med. 2008;168(1):27–32.
- , The importance of delirium: Economic and societal costs. J Am Geriatr Soc. 2011;59(suppl 2):S241–S243.
- Delirium. Ann Intern Med. 2011;154(11):ITC6.
- , , , , , Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4:50.
- , , , Mixed‐methods approach to understanding nurses' clinical reasoning in recognizing delirium in hospitalized older adults. J Contin Educ Nurs. 2014;45:1–13.
- , , Educational interventions to improve recognition of delirium: a systematic review. J Am Geriatr Soc. 2013;61(11):1983–1993.
- , Delirium superimposed on dementia: accuracy of nurse documentation. J Gerontol Nurs. 2012;38(1):32–42.
- , , , et al. Detection of delirium by bedside nurses using the confusion assessment method. J Am Geriatr Soc. 2006;54:685–689.
- , , , et al. Documentation of delirium in elderly patients with hip fracture. J Gerontol Nurs. 2002;28(11):23–29.
- , , , Recorded delirium in a national sample of elderly inpatients: potential implications for recognition. J Geriatr Psychiatry Neurol. 2003;16(1):32–38.
- , , , et al. A tale of two methods: chart and interview methods for identifying delirium. J Am Geriatr Soc. 2014;62(3):518–524.
- , , , et al. 3D‐CAM: Derivation and validation of a 3‐minute diagnostic interview for CAM‐defined delirium: a cross‐sectional diagnostic test study. Ann Intern Med. 2014;161(8):554–561.
- , , , et al. Selecting optimal screening items for delirium: an application of item response theory. BMC Med Res Methodol. 2013;13:8.
- , , , et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–699.
- Geriatric Depression Scale. Psychopharmacol Bull. 1988;24(4):709–711.
- , , , A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–383.
- , , , , Studies of illness in the aged: the index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185:914–919.
- , Assessment of older people: self‐maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179–186.
- , , , et al. The AD8: a brief informant interview to detect dementia. Neurology. 2005;65(4):559–564.
- , , , et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging‐Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7(3):263–269.
- , , , et al. Delirium diagnosis methodology used in research: a survey‐based study. Am J Geriatr Psychiatry. 2014;22(12):1513–1521.
- , , , , Single Question in Delirium (SQiD): testing its efficacy against psychiatrist interview, the Confusion Assessment Method and the Memorial Delirium Assessment Scale. Palliat Med. 2010;24(6):561–565.
- , , , et al. Diagnosing delirium in older emergency department patients: validity and reliability of the delirium triage screen and the brief confusion assessment method. Ann Emerg Med. 2013;62(5):457–465.
- , , , et al. Attention! A good bedside test for delirium? J Neurol Neurosurg Psychiatry. 2014;85(10):1122–1131.
- , , , , A model for management of delirious postacute care patients. J Am Geriatr Soc. 2005;53(10):1817–1825.
- , , , Computerized decision support for delirium superimposed on dementia in older adults: a pilot study. J Gerontol Nurs. 2011;37(4):39–47.
- , , , et al. Barriers and facilitators to implementing delirium rounds in a clinical trial across three diverse hospital settings. Clin Nurs Res. 2014;23(2):201–215.
- , Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores. Psychol Bull. 1955;52(3):194.
© 2015 Society of Hospital Medicine
MedPAC to look at physician prescribing tools as a way to control drug spending
WASHINGTON – The Medicare Payment Advisory Commission is going to look at physician prescribing tools as part of a broader examination of how to rein in Medicare drug spending.
Members acknowledged during the Sept. 11, 2015, meeting that when it comes to the prices of drugs in the Medicare programs, the tools are limited to keep the prices low. Between statutory requirements for coverage of drugs in protected classes and a prohibition against the secretary of Health and Human Services negotiating prices for the Part D prescription drug benefit and other statutory requirements, even for intermediaries such as plan providers and hospital groups, leverage in price negotiations is very limited.
However, commission member Dr. Craig Samitt, former partner at Oliver Wyman of Paradise Valley, Ariz., suggested that the focus should be more on what leverage providers might have when it comes to utilization.
“So if we feel that neither CMS nor the intermediaries have sufficient leverage, well then who has significant leverage? The prescribing clinician,” Dr. Samitt said. “How well have we aligned interests around utilization in particular, not so much price, with the clinicians?”
Dr. Samitt noted that on the commercial side, there is a focus on utilization as a more effective driver of price, rather than simply targeting price first in the negotiation process, and suggested there might be room in Medicare for that kind of focus.
He also suggested that perhaps including drug utilization within the context of accountable care organizations could result in “additional focus on more effective prescribing patterns.”
The conversation occurred against a backdrop of examination of drug spending in general. MedPAC staff noted that Medicare is becoming a more prominent payer for drugs in the wake of Part D’s launch.
MedPAC staff estimates that in 2013, retail drugs made up 13% of Medicare spending, versus 9% of national health expenditures. Additionally, of the $574 billion spent by Medicare in that year, 19% was drugs and pharmacy, with the majority of drug spending (57%) coming from Part D.
The discussion was just the first on the subject as the group will look at other aspects of drug pricing and spending in future meetings. A specific timetable for offering policy recommendations was not discussed.
Dr. William Hall, professor at the University of Rochester (N.Y.) School of Medicine, added that it is not the price of the drug per se, but its value that needs to be focused on. He noted that the prices of the latest hepatitis C drugs might be high, but the value they have to the health care system is much greater and needs to be taken into consideration.
“One of the big differences from 2004 is we know a great deal more about the efficacy of drugs,” Dr. Hall said, suggesting that more needs to be done to educate clinicians on the proper use of medications as part of finding the right way to use physician prescribing patterns as leverage in price negotiations.
WASHINGTON – The Medicare Payment Advisory Commission is going to look at physician prescribing tools as part of a broader examination of how to rein in Medicare drug spending.
Members acknowledged during the Sept. 11, 2015, meeting that when it comes to the prices of drugs in the Medicare programs, the tools are limited to keep the prices low. Between statutory requirements for coverage of drugs in protected classes and a prohibition against the secretary of Health and Human Services negotiating prices for the Part D prescription drug benefit and other statutory requirements, even for intermediaries such as plan providers and hospital groups, leverage in price negotiations is very limited.
However, commission member Dr. Craig Samitt, former partner at Oliver Wyman of Paradise Valley, Ariz., suggested that the focus should be more on what leverage providers might have when it comes to utilization.
“So if we feel that neither CMS nor the intermediaries have sufficient leverage, well then who has significant leverage? The prescribing clinician,” Dr. Samitt said. “How well have we aligned interests around utilization in particular, not so much price, with the clinicians?”
Dr. Samitt noted that on the commercial side, there is a focus on utilization as a more effective driver of price, rather than simply targeting price first in the negotiation process, and suggested there might be room in Medicare for that kind of focus.
He also suggested that perhaps including drug utilization within the context of accountable care organizations could result in “additional focus on more effective prescribing patterns.”
The conversation occurred against a backdrop of examination of drug spending in general. MedPAC staff noted that Medicare is becoming a more prominent payer for drugs in the wake of Part D’s launch.
MedPAC staff estimates that in 2013, retail drugs made up 13% of Medicare spending, versus 9% of national health expenditures. Additionally, of the $574 billion spent by Medicare in that year, 19% was drugs and pharmacy, with the majority of drug spending (57%) coming from Part D.
The discussion was just the first on the subject as the group will look at other aspects of drug pricing and spending in future meetings. A specific timetable for offering policy recommendations was not discussed.
Dr. William Hall, professor at the University of Rochester (N.Y.) School of Medicine, added that it is not the price of the drug per se, but its value that needs to be focused on. He noted that the prices of the latest hepatitis C drugs might be high, but the value they have to the health care system is much greater and needs to be taken into consideration.
“One of the big differences from 2004 is we know a great deal more about the efficacy of drugs,” Dr. Hall said, suggesting that more needs to be done to educate clinicians on the proper use of medications as part of finding the right way to use physician prescribing patterns as leverage in price negotiations.
WASHINGTON – The Medicare Payment Advisory Commission is going to look at physician prescribing tools as part of a broader examination of how to rein in Medicare drug spending.
Members acknowledged during the Sept. 11, 2015, meeting that when it comes to the prices of drugs in the Medicare programs, the tools are limited to keep the prices low. Between statutory requirements for coverage of drugs in protected classes and a prohibition against the secretary of Health and Human Services negotiating prices for the Part D prescription drug benefit and other statutory requirements, even for intermediaries such as plan providers and hospital groups, leverage in price negotiations is very limited.
However, commission member Dr. Craig Samitt, former partner at Oliver Wyman of Paradise Valley, Ariz., suggested that the focus should be more on what leverage providers might have when it comes to utilization.
“So if we feel that neither CMS nor the intermediaries have sufficient leverage, well then who has significant leverage? The prescribing clinician,” Dr. Samitt said. “How well have we aligned interests around utilization in particular, not so much price, with the clinicians?”
Dr. Samitt noted that on the commercial side, there is a focus on utilization as a more effective driver of price, rather than simply targeting price first in the negotiation process, and suggested there might be room in Medicare for that kind of focus.
He also suggested that perhaps including drug utilization within the context of accountable care organizations could result in “additional focus on more effective prescribing patterns.”
The conversation occurred against a backdrop of examination of drug spending in general. MedPAC staff noted that Medicare is becoming a more prominent payer for drugs in the wake of Part D’s launch.
MedPAC staff estimates that in 2013, retail drugs made up 13% of Medicare spending, versus 9% of national health expenditures. Additionally, of the $574 billion spent by Medicare in that year, 19% was drugs and pharmacy, with the majority of drug spending (57%) coming from Part D.
The discussion was just the first on the subject as the group will look at other aspects of drug pricing and spending in future meetings. A specific timetable for offering policy recommendations was not discussed.
Dr. William Hall, professor at the University of Rochester (N.Y.) School of Medicine, added that it is not the price of the drug per se, but its value that needs to be focused on. He noted that the prices of the latest hepatitis C drugs might be high, but the value they have to the health care system is much greater and needs to be taken into consideration.
“One of the big differences from 2004 is we know a great deal more about the efficacy of drugs,” Dr. Hall said, suggesting that more needs to be done to educate clinicians on the proper use of medications as part of finding the right way to use physician prescribing patterns as leverage in price negotiations.
AT A MEETING OF THE MEDICARE PAYMENT ADVISORY COMMISSION
