Geriatrics

Muscle adiposity may be a novel risk factor for cognitive decline in older adults, new research suggests.

Investigators assessed muscle fat in more than 1,600 adults in their 70s and evaluated their cognitive function over a 10-year period. They found that increases in muscle adiposity from year 1 to year 6 were associated with greater cognitive decline over time, independent of total weight, other fat deposits, muscle characteristics, and traditional dementia risk factors.

The findings were similar between Black and White people and between men and women.

“Increasing adiposity – or fat deposition – in skeletal muscles predicted faster cognitive decline, irrespective of demographics or other disease, and this effect was distinct from that of other types of fat or other muscle characteristics, such as strength or mass,” study investigator Caterina Rosano MD, MPH, professor of epidemiology at the University of Pittsburgh, said in an interview.

The study was published in the Journal of the American Geriatrics Society.
 

Biologically plausible

“There has been a growing recognition that overall adiposity and muscle measures, such as strength and mass, are individual indicators of future dementia risk and both strengthen the algorithms to predict cognitive decline,” said Dr. Rosano, associate director for clinical translation at the University of Pittsburgh’s Aging Institute. “However, adiposity in the muscle has not been examined.”

Some evidence supports a “biologically plausible link” between muscle adiposity and dementia risk. For example, muscle adiposity increases the risk for type 2 diabetes and hypertension, both of which are dementia risk factors.

Skeletal muscle adiposity increases with older age, even in older adults who lose weight, and is “highly prevalent” among older adults of African ancestry.

The researchers examined a large, biracial sample of older adults participating in the Health, Aging and Body Composition study, which enrolled men and women aged between 70 and 79 years. Participants were followed for an average of 9.0 ± 1.8 years.

During years 1 and 6, participants’ body composition was analyzed, including intermuscular adipose tissue (IMAT), visceral and subcutaneous adiposity, total fat mass, and muscle area.

In years 1, 3, 5, 8, and 10, participants’ cognition was measured using the modified Mini-Mental State (3MS) exam.

The main independent variable was 5-year change in thigh IMAT (year 6 minus year 1), and the main dependent variable was 3MS decline (from year 5 to year 10).

The researchers adjusted all the models for traditional dementia risk factors at baseline including 3MS, education, apo E4 allele, diabetes, hypertension, and physical activity and also calculated interactions between IMAT change by race or sex.

These models also accounted for change in muscle strength, muscle area, body weight, abdominal subcutaneous and visceral adiposity, and total body fat mass as well as cytokines related to adiposity.
 

‘Rich and engaging crosstalk’

The final sample included 1634 participants (mean age, 73.38 years at baseline; 48% female; 35% Black; mean baseline 3MS score, 91.6).

Thigh IMAT increased by 39.0% in all participants from year 1 to year 6, which corresponded to an increase of 4.85 cm² or 0.97 cm²/year. During the same time period, muscle strength decreased by 14.0% (P < .05), although thigh muscle area remained stable, decreasing less than 0.5%.

There were decreases in both abdominal subcutaneous and visceral adiposity of 3.92% and 6.43%, respectively (P < .05). There was a decrease of 3.3% in 3MS from year 5 to year 10.

Several variables were associated with 3MS decline, independent of any change in thigh IMAT: older age, less education, and having at least one copy of the APOe4 allele. These variables were included in the model of IMAT change predicting 3MS change.

A statistically significant association of IMAT increase with 3MS decline was found. The IMAT increase of 4.85 cm² corresponded to a 3MS decline of an additional 3.6 points (P < .0001) from year 5 to year 10, “indicating a clinically important change.”

The association between increasing thigh IMAT with declining 3MS “remained statistically significant” after adjusting for race, age, education, and apo E4 (P < .0001) and was independent of changes in thigh muscle area, muscle strength, and other adiposity measures.

In participants with increased IMAT in years 1-6, the mean 3MS score fell to approximately 87 points at year 10, compared with those without increased IMAT, with a 3MS score that dropped to approximately 89 points.

Interactions by race and sex were not statistically significant (P > .08).

“Our results suggest that adiposity in muscles can predict cognitive decline, in addition to (not instead of) other traditional dementia risk factors,” said Dr. Rosano.

There is “a rich and engaging crosstalk between muscle, adipose tissue, and the brain all throughout our lives, happening through factors released in the bloodstream that can reach the brain, however, the specific identity of the factors responsible for the crosstalk of muscle adiposity and brain in older adults has not yet been discovered,” she noted.

Although muscle adiposity is “not yet routinely measured in clinical settings, it is being measured opportunistically on clinical CT scans obtained as part of routine patient care,” she added. “These CT measurements have already been validated in many studies of older adults; thus, clinicians could have access to this novel information without additional cost, time, or radiation exposure.”
 

Causality not proven

In a comment, Bruce Albala, PhD, professor, department of environmental and occupational health, University of California, Irvine, noted that the 3MS assessment is scored on a 100-point scale, with a score less than 78 “generally regarded as indicating cognitive impairment or approaching a dementia condition.” In the current study, the mean 3MS score of participants with increased IMAT was still “well above the dementia cut-off.”

Moreover, “even if there is a relationship or correlation between IMAT and cognition, this does not prove or even suggest causality, especially from a biological mechanistic approach,” said Dr. Albaba, an adjunct professor of neurology, who was not involved in the study. “Clearly, more research is needed even to understand the relationship between these two factors.”

The study was supported by the National Institute on Aging. Dr. Rosano and coauthors and Dr. Albala declared no relevant financial relationships.

A version of this article originally appeared on Medscape.com.

Muscle adiposity may be a novel risk factor for cognitive decline in older adults, new research suggests.

Investigators assessed muscle fat in more than 1,600 adults in their 70s and evaluated their cognitive function over a 10-year period. They found that increases in muscle adiposity from year 1 to year 6 were associated with greater cognitive decline over time, independent of total weight, other fat deposits, muscle characteristics, and traditional dementia risk factors.

The findings were similar between Black and White people and between men and women.

“Increasing adiposity – or fat deposition – in skeletal muscles predicted faster cognitive decline, irrespective of demographics or other disease, and this effect was distinct from that of other types of fat or other muscle characteristics, such as strength or mass,” study investigator Caterina Rosano MD, MPH, professor of epidemiology at the University of Pittsburgh, said in an interview.

The study was published in the Journal of the American Geriatrics Society.
 

Biologically plausible

“There has been a growing recognition that overall adiposity and muscle measures, such as strength and mass, are individual indicators of future dementia risk and both strengthen the algorithms to predict cognitive decline,” said Dr. Rosano, associate director for clinical translation at the University of Pittsburgh’s Aging Institute. “However, adiposity in the muscle has not been examined.”

Some evidence supports a “biologically plausible link” between muscle adiposity and dementia risk. For example, muscle adiposity increases the risk for type 2 diabetes and hypertension, both of which are dementia risk factors.

Skeletal muscle adiposity increases with older age, even in older adults who lose weight, and is “highly prevalent” among older adults of African ancestry.

The researchers examined a large, biracial sample of older adults participating in the Health, Aging and Body Composition study, which enrolled men and women aged between 70 and 79 years. Participants were followed for an average of 9.0 ± 1.8 years.

During years 1 and 6, participants’ body composition was analyzed, including intermuscular adipose tissue (IMAT), visceral and subcutaneous adiposity, total fat mass, and muscle area.

In years 1, 3, 5, 8, and 10, participants’ cognition was measured using the modified Mini-Mental State (3MS) exam.

The main independent variable was 5-year change in thigh IMAT (year 6 minus year 1), and the main dependent variable was 3MS decline (from year 5 to year 10).

The researchers adjusted all the models for traditional dementia risk factors at baseline including 3MS, education, apo E4 allele, diabetes, hypertension, and physical activity and also calculated interactions between IMAT change by race or sex.

These models also accounted for change in muscle strength, muscle area, body weight, abdominal subcutaneous and visceral adiposity, and total body fat mass as well as cytokines related to adiposity.
 

‘Rich and engaging crosstalk’

The final sample included 1634 participants (mean age, 73.38 years at baseline; 48% female; 35% Black; mean baseline 3MS score, 91.6).

Thigh IMAT increased by 39.0% in all participants from year 1 to year 6, which corresponded to an increase of 4.85 cm² or 0.97 cm²/year. During the same time period, muscle strength decreased by 14.0% (P < .05), although thigh muscle area remained stable, decreasing less than 0.5%.

There were decreases in both abdominal subcutaneous and visceral adiposity of 3.92% and 6.43%, respectively (P < .05). There was a decrease of 3.3% in 3MS from year 5 to year 10.

Several variables were associated with 3MS decline, independent of any change in thigh IMAT: older age, less education, and having at least one copy of the APOe4 allele. These variables were included in the model of IMAT change predicting 3MS change.

A statistically significant association of IMAT increase with 3MS decline was found. The IMAT increase of 4.85 cm² corresponded to a 3MS decline of an additional 3.6 points (P < .0001) from year 5 to year 10, “indicating a clinically important change.”

The association between increasing thigh IMAT with declining 3MS “remained statistically significant” after adjusting for race, age, education, and apo E4 (P < .0001) and was independent of changes in thigh muscle area, muscle strength, and other adiposity measures.

In participants with increased IMAT in years 1-6, the mean 3MS score fell to approximately 87 points at year 10, compared with those without increased IMAT, with a 3MS score that dropped to approximately 89 points.

Interactions by race and sex were not statistically significant (P > .08).

“Our results suggest that adiposity in muscles can predict cognitive decline, in addition to (not instead of) other traditional dementia risk factors,” said Dr. Rosano.

There is “a rich and engaging crosstalk between muscle, adipose tissue, and the brain all throughout our lives, happening through factors released in the bloodstream that can reach the brain, however, the specific identity of the factors responsible for the crosstalk of muscle adiposity and brain in older adults has not yet been discovered,” she noted.

Although muscle adiposity is “not yet routinely measured in clinical settings, it is being measured opportunistically on clinical CT scans obtained as part of routine patient care,” she added. “These CT measurements have already been validated in many studies of older adults; thus, clinicians could have access to this novel information without additional cost, time, or radiation exposure.”
 

Causality not proven

In a comment, Bruce Albala, PhD, professor, department of environmental and occupational health, University of California, Irvine, noted that the 3MS assessment is scored on a 100-point scale, with a score less than 78 “generally regarded as indicating cognitive impairment or approaching a dementia condition.” In the current study, the mean 3MS score of participants with increased IMAT was still “well above the dementia cut-off.”

Moreover, “even if there is a relationship or correlation between IMAT and cognition, this does not prove or even suggest causality, especially from a biological mechanistic approach,” said Dr. Albaba, an adjunct professor of neurology, who was not involved in the study. “Clearly, more research is needed even to understand the relationship between these two factors.”

The study was supported by the National Institute on Aging. Dr. Rosano and coauthors and Dr. Albala declared no relevant financial relationships.

A version of this article originally appeared on Medscape.com.

Muscle adiposity may be a novel risk factor for cognitive decline in older adults, new research suggests.

Investigators assessed muscle fat in more than 1,600 adults in their 70s and evaluated their cognitive function over a 10-year period. They found that increases in muscle adiposity from year 1 to year 6 were associated with greater cognitive decline over time, independent of total weight, other fat deposits, muscle characteristics, and traditional dementia risk factors.

The findings were similar between Black and White people and between men and women.

“Increasing adiposity – or fat deposition – in skeletal muscles predicted faster cognitive decline, irrespective of demographics or other disease, and this effect was distinct from that of other types of fat or other muscle characteristics, such as strength or mass,” study investigator Caterina Rosano MD, MPH, professor of epidemiology at the University of Pittsburgh, said in an interview.

The study was published in the Journal of the American Geriatrics Society.
 

Biologically plausible

“There has been a growing recognition that overall adiposity and muscle measures, such as strength and mass, are individual indicators of future dementia risk and both strengthen the algorithms to predict cognitive decline,” said Dr. Rosano, associate director for clinical translation at the University of Pittsburgh’s Aging Institute. “However, adiposity in the muscle has not been examined.”

Some evidence supports a “biologically plausible link” between muscle adiposity and dementia risk. For example, muscle adiposity increases the risk for type 2 diabetes and hypertension, both of which are dementia risk factors.

Skeletal muscle adiposity increases with older age, even in older adults who lose weight, and is “highly prevalent” among older adults of African ancestry.

The researchers examined a large, biracial sample of older adults participating in the Health, Aging and Body Composition study, which enrolled men and women aged between 70 and 79 years. Participants were followed for an average of 9.0 ± 1.8 years.

During years 1 and 6, participants’ body composition was analyzed, including intermuscular adipose tissue (IMAT), visceral and subcutaneous adiposity, total fat mass, and muscle area.

In years 1, 3, 5, 8, and 10, participants’ cognition was measured using the modified Mini-Mental State (3MS) exam.

The main independent variable was 5-year change in thigh IMAT (year 6 minus year 1), and the main dependent variable was 3MS decline (from year 5 to year 10).

The researchers adjusted all the models for traditional dementia risk factors at baseline including 3MS, education, apo E4 allele, diabetes, hypertension, and physical activity and also calculated interactions between IMAT change by race or sex.

These models also accounted for change in muscle strength, muscle area, body weight, abdominal subcutaneous and visceral adiposity, and total body fat mass as well as cytokines related to adiposity.
 

‘Rich and engaging crosstalk’

The final sample included 1634 participants (mean age, 73.38 years at baseline; 48% female; 35% Black; mean baseline 3MS score, 91.6).

Thigh IMAT increased by 39.0% in all participants from year 1 to year 6, which corresponded to an increase of 4.85 cm² or 0.97 cm²/year. During the same time period, muscle strength decreased by 14.0% (P < .05), although thigh muscle area remained stable, decreasing less than 0.5%.

There were decreases in both abdominal subcutaneous and visceral adiposity of 3.92% and 6.43%, respectively (P < .05). There was a decrease of 3.3% in 3MS from year 5 to year 10.

Several variables were associated with 3MS decline, independent of any change in thigh IMAT: older age, less education, and having at least one copy of the APOe4 allele. These variables were included in the model of IMAT change predicting 3MS change.

A statistically significant association of IMAT increase with 3MS decline was found. The IMAT increase of 4.85 cm² corresponded to a 3MS decline of an additional 3.6 points (P < .0001) from year 5 to year 10, “indicating a clinically important change.”

The association between increasing thigh IMAT with declining 3MS “remained statistically significant” after adjusting for race, age, education, and apo E4 (P < .0001) and was independent of changes in thigh muscle area, muscle strength, and other adiposity measures.

In participants with increased IMAT in years 1-6, the mean 3MS score fell to approximately 87 points at year 10, compared with those without increased IMAT, with a 3MS score that dropped to approximately 89 points.

Interactions by race and sex were not statistically significant (P > .08).

“Our results suggest that adiposity in muscles can predict cognitive decline, in addition to (not instead of) other traditional dementia risk factors,” said Dr. Rosano.

There is “a rich and engaging crosstalk between muscle, adipose tissue, and the brain all throughout our lives, happening through factors released in the bloodstream that can reach the brain, however, the specific identity of the factors responsible for the crosstalk of muscle adiposity and brain in older adults has not yet been discovered,” she noted.

Although muscle adiposity is “not yet routinely measured in clinical settings, it is being measured opportunistically on clinical CT scans obtained as part of routine patient care,” she added. “These CT measurements have already been validated in many studies of older adults; thus, clinicians could have access to this novel information without additional cost, time, or radiation exposure.”
 

Causality not proven

In a comment, Bruce Albala, PhD, professor, department of environmental and occupational health, University of California, Irvine, noted that the 3MS assessment is scored on a 100-point scale, with a score less than 78 “generally regarded as indicating cognitive impairment or approaching a dementia condition.” In the current study, the mean 3MS score of participants with increased IMAT was still “well above the dementia cut-off.”

Moreover, “even if there is a relationship or correlation between IMAT and cognition, this does not prove or even suggest causality, especially from a biological mechanistic approach,” said Dr. Albaba, an adjunct professor of neurology, who was not involved in the study. “Clearly, more research is needed even to understand the relationship between these two factors.”

The study was supported by the National Institute on Aging. Dr. Rosano and coauthors and Dr. Albala declared no relevant financial relationships.

A version of this article originally appeared on Medscape.com.

A blood biomarker that measures astrocyte reactivity may help determine who, among cognitively unimpaired older adults with amyloid-beta, will go on to develop Alzheimer’s disease (AD), new research suggests.

Investigators tested the blood of 1,000 cognitively healthy individuals with and without amyloid-beta pathology and found that only those with a combination of amyloid-beta burden and abnormal astrocyte activation subsequently progressed to AD.

“Our study argues that testing for the presence of brain amyloid along with blood biomarkers of astrocyte reactivity is the optimal screening to identify patients who are most at risk for progressing to Alzheimer’s disease,” senior investigator Tharick A. Pascoal, MD, PhD, associate professor of psychiatry and neurology, University of Pittsburgh, said in a release.

At this point, the biomarker is a research tool, but its application in clinical practice “is not very far away,” Dr. Pascoal told this news organization.

The study was published online  in Nature Medicine.  
 

Multicenter study

In AD, accumulation of amyloid-beta in the brain precedes tau pathology, but not everyone with amyloid-beta develops tau, and, consequently, clinical symptoms. Approximately 30% of older adults have brain amyloid but many never progress to AD, said Dr. Pascoal.

This suggests other biological processes may trigger the deleterious effects of amyloid-beta in the early stages of AD.

Finding predictive markers of early amyloid-beta–related tau pathology would help identify cognitively normal individuals who are more likely to develop AD.

Post-mortem studies show astrocyte reactivity – changes in glial cells in the brain and spinal cord because of an insult in the brain – is an early AD abnormality. Other research suggests a close link between amyloid-beta, astrocyte reactivity, and tau.

In addition, evidence suggests plasma measures of glial fibrillary acidic protein (GFAP) could be a strong proxy of astrocyte reactivity in the brain. Dr. Pascoal explained that when astrocytes are changed or become bigger, more GFAP is released.

The study included 1,016 cognitively normal individuals from three centers; some had amyloid pathology, some did not. Participants’ mean age was 69.6 years, and all were deemed negative or positive for astrocyte reactivity based on plasma GFAP levels.

Results showed amyloid-beta is associated with increased plasma phosphorylated tau only in individuals positive for astrocyte reactivity. In addition, analyses using PET scans showed an AD-like pattern of tau tangle accumulation as a function of amyloid-beta exclusively in those same individuals.
 

Early upstream event

The findings suggest abnormalities in astrocyte reactivity is an early upstream event that likely occurs prior to tau pathology, which is closely related to the development of neurodegeneration and cognitive decline.

It’s likely many types of insults or processes can lead to astrocyte reactivity, possibly including COVID, but more research in this area is needed, said Dr. Pascoal.

“Our study only looked at the consequence of having both amyloid and astrocyte reactivity; it did not elucidate what is causing either of them,” he said.

Although “we were able to have very good results” in the current study, additional studies are needed to better establish the cut-off for GFAP levels that signal progression, said Dr. Pascoal.

The effect of astrocyte reactivity on the association between amyloid-beta and tau phosphorylation was greater in men than women. Dr. Pascoal noted anti-amyloid therapies, which might be modifying the amyloid-beta-astrocyte-tau pathway, tend to have a much larger effect in men than women.

Further studies that measure amyloid-beta, tau, and GFAP biomarkers at multiple timepoints, and with long follow-up, are needed, the investigators note.

The results may have implications for clinical trials, which have increasingly focused on individuals in the earliest preclinical phases of AD. Future studies should include cognitively normal patients who are positive for both amyloid pathology and astrocyte reactivity but have no overt p-tau abnormality, said Dr. Pascoal.

This may provide a time window for interventions very early in the disease process in those at increased risk for AD-related progression.

The study did not determine whether participants with both amyloid and astrocyte reactivity will inevitably develop AD, and to do so would require a longer follow up. “Our outcome was correlation to tau in the brain, which is something we know will lead to AD.”

Although the cohort represents significant socioeconomic diversity, a main limitation of the study was that subjects were mainly White, which limits the generalizability of the findings to a more diverse population.

The study received support from the National Institute of Aging; National Heart Lung and Blood Institute; Alzheimer’s Association; Fonds de Recherche du Québec-Santé; Canadian Consortium of Neurodegeneration in Aging; Weston Brain Institute; Colin Adair Charitable Foundation; Swedish Research Council; Wallenberg Scholar; BrightFocus Foundation; Swedish Alzheimer Foundation; Swedish Brain Foundation; Agneta Prytz-Folkes & Gösta Folkes Foundation; European Union; Swedish State Support for Clinical Research; Alzheimer Drug Discovery Foundation; Bluefield Project, the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden; the UK Dementia Research Institute at UCL; National Academy of Neuropsychology; Fundação de Amparo a pesquisa do Rio Grande do Sul; Instituto Serrapilheira; and Hjärnfonden.

Dr. Pascoal reports no relevant financial relationships.

A version of this article first appeared on Medscape.com.

A blood biomarker that measures astrocyte reactivity may help determine who, among cognitively unimpaired older adults with amyloid-beta, will go on to develop Alzheimer’s disease (AD), new research suggests.

Investigators tested the blood of 1,000 cognitively healthy individuals with and without amyloid-beta pathology and found that only those with a combination of amyloid-beta burden and abnormal astrocyte activation subsequently progressed to AD.

“Our study argues that testing for the presence of brain amyloid along with blood biomarkers of astrocyte reactivity is the optimal screening to identify patients who are most at risk for progressing to Alzheimer’s disease,” senior investigator Tharick A. Pascoal, MD, PhD, associate professor of psychiatry and neurology, University of Pittsburgh, said in a release.

At this point, the biomarker is a research tool, but its application in clinical practice “is not very far away,” Dr. Pascoal told this news organization.

The study was published online  in Nature Medicine.  
 

Multicenter study

In AD, accumulation of amyloid-beta in the brain precedes tau pathology, but not everyone with amyloid-beta develops tau, and, consequently, clinical symptoms. Approximately 30% of older adults have brain amyloid but many never progress to AD, said Dr. Pascoal.

This suggests other biological processes may trigger the deleterious effects of amyloid-beta in the early stages of AD.

Finding predictive markers of early amyloid-beta–related tau pathology would help identify cognitively normal individuals who are more likely to develop AD.

Post-mortem studies show astrocyte reactivity – changes in glial cells in the brain and spinal cord because of an insult in the brain – is an early AD abnormality. Other research suggests a close link between amyloid-beta, astrocyte reactivity, and tau.

In addition, evidence suggests plasma measures of glial fibrillary acidic protein (GFAP) could be a strong proxy of astrocyte reactivity in the brain. Dr. Pascoal explained that when astrocytes are changed or become bigger, more GFAP is released.

The study included 1,016 cognitively normal individuals from three centers; some had amyloid pathology, some did not. Participants’ mean age was 69.6 years, and all were deemed negative or positive for astrocyte reactivity based on plasma GFAP levels.

Results showed amyloid-beta is associated with increased plasma phosphorylated tau only in individuals positive for astrocyte reactivity. In addition, analyses using PET scans showed an AD-like pattern of tau tangle accumulation as a function of amyloid-beta exclusively in those same individuals.
 

Early upstream event

The findings suggest abnormalities in astrocyte reactivity is an early upstream event that likely occurs prior to tau pathology, which is closely related to the development of neurodegeneration and cognitive decline.

It’s likely many types of insults or processes can lead to astrocyte reactivity, possibly including COVID, but more research in this area is needed, said Dr. Pascoal.

“Our study only looked at the consequence of having both amyloid and astrocyte reactivity; it did not elucidate what is causing either of them,” he said.

Although “we were able to have very good results” in the current study, additional studies are needed to better establish the cut-off for GFAP levels that signal progression, said Dr. Pascoal.

The effect of astrocyte reactivity on the association between amyloid-beta and tau phosphorylation was greater in men than women. Dr. Pascoal noted anti-amyloid therapies, which might be modifying the amyloid-beta-astrocyte-tau pathway, tend to have a much larger effect in men than women.

Further studies that measure amyloid-beta, tau, and GFAP biomarkers at multiple timepoints, and with long follow-up, are needed, the investigators note.

The results may have implications for clinical trials, which have increasingly focused on individuals in the earliest preclinical phases of AD. Future studies should include cognitively normal patients who are positive for both amyloid pathology and astrocyte reactivity but have no overt p-tau abnormality, said Dr. Pascoal.

This may provide a time window for interventions very early in the disease process in those at increased risk for AD-related progression.

The study did not determine whether participants with both amyloid and astrocyte reactivity will inevitably develop AD, and to do so would require a longer follow up. “Our outcome was correlation to tau in the brain, which is something we know will lead to AD.”

Although the cohort represents significant socioeconomic diversity, a main limitation of the study was that subjects were mainly White, which limits the generalizability of the findings to a more diverse population.

The study received support from the National Institute of Aging; National Heart Lung and Blood Institute; Alzheimer’s Association; Fonds de Recherche du Québec-Santé; Canadian Consortium of Neurodegeneration in Aging; Weston Brain Institute; Colin Adair Charitable Foundation; Swedish Research Council; Wallenberg Scholar; BrightFocus Foundation; Swedish Alzheimer Foundation; Swedish Brain Foundation; Agneta Prytz-Folkes & Gösta Folkes Foundation; European Union; Swedish State Support for Clinical Research; Alzheimer Drug Discovery Foundation; Bluefield Project, the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden; the UK Dementia Research Institute at UCL; National Academy of Neuropsychology; Fundação de Amparo a pesquisa do Rio Grande do Sul; Instituto Serrapilheira; and Hjärnfonden.

Dr. Pascoal reports no relevant financial relationships.

A version of this article first appeared on Medscape.com.

A blood biomarker that measures astrocyte reactivity may help determine who, among cognitively unimpaired older adults with amyloid-beta, will go on to develop Alzheimer’s disease (AD), new research suggests.

Investigators tested the blood of 1,000 cognitively healthy individuals with and without amyloid-beta pathology and found that only those with a combination of amyloid-beta burden and abnormal astrocyte activation subsequently progressed to AD.

“Our study argues that testing for the presence of brain amyloid along with blood biomarkers of astrocyte reactivity is the optimal screening to identify patients who are most at risk for progressing to Alzheimer’s disease,” senior investigator Tharick A. Pascoal, MD, PhD, associate professor of psychiatry and neurology, University of Pittsburgh, said in a release.

At this point, the biomarker is a research tool, but its application in clinical practice “is not very far away,” Dr. Pascoal told this news organization.

The study was published online  in Nature Medicine.  
 

Multicenter study

In AD, accumulation of amyloid-beta in the brain precedes tau pathology, but not everyone with amyloid-beta develops tau, and, consequently, clinical symptoms. Approximately 30% of older adults have brain amyloid but many never progress to AD, said Dr. Pascoal.

This suggests other biological processes may trigger the deleterious effects of amyloid-beta in the early stages of AD.

Finding predictive markers of early amyloid-beta–related tau pathology would help identify cognitively normal individuals who are more likely to develop AD.

Post-mortem studies show astrocyte reactivity – changes in glial cells in the brain and spinal cord because of an insult in the brain – is an early AD abnormality. Other research suggests a close link between amyloid-beta, astrocyte reactivity, and tau.

In addition, evidence suggests plasma measures of glial fibrillary acidic protein (GFAP) could be a strong proxy of astrocyte reactivity in the brain. Dr. Pascoal explained that when astrocytes are changed or become bigger, more GFAP is released.

The study included 1,016 cognitively normal individuals from three centers; some had amyloid pathology, some did not. Participants’ mean age was 69.6 years, and all were deemed negative or positive for astrocyte reactivity based on plasma GFAP levels.

Results showed amyloid-beta is associated with increased plasma phosphorylated tau only in individuals positive for astrocyte reactivity. In addition, analyses using PET scans showed an AD-like pattern of tau tangle accumulation as a function of amyloid-beta exclusively in those same individuals.
 

Early upstream event

The findings suggest abnormalities in astrocyte reactivity is an early upstream event that likely occurs prior to tau pathology, which is closely related to the development of neurodegeneration and cognitive decline.

It’s likely many types of insults or processes can lead to astrocyte reactivity, possibly including COVID, but more research in this area is needed, said Dr. Pascoal.

“Our study only looked at the consequence of having both amyloid and astrocyte reactivity; it did not elucidate what is causing either of them,” he said.

Although “we were able to have very good results” in the current study, additional studies are needed to better establish the cut-off for GFAP levels that signal progression, said Dr. Pascoal.

The effect of astrocyte reactivity on the association between amyloid-beta and tau phosphorylation was greater in men than women. Dr. Pascoal noted anti-amyloid therapies, which might be modifying the amyloid-beta-astrocyte-tau pathway, tend to have a much larger effect in men than women.

Further studies that measure amyloid-beta, tau, and GFAP biomarkers at multiple timepoints, and with long follow-up, are needed, the investigators note.

The results may have implications for clinical trials, which have increasingly focused on individuals in the earliest preclinical phases of AD. Future studies should include cognitively normal patients who are positive for both amyloid pathology and astrocyte reactivity but have no overt p-tau abnormality, said Dr. Pascoal.

This may provide a time window for interventions very early in the disease process in those at increased risk for AD-related progression.

The study did not determine whether participants with both amyloid and astrocyte reactivity will inevitably develop AD, and to do so would require a longer follow up. “Our outcome was correlation to tau in the brain, which is something we know will lead to AD.”

Although the cohort represents significant socioeconomic diversity, a main limitation of the study was that subjects were mainly White, which limits the generalizability of the findings to a more diverse population.

The study received support from the National Institute of Aging; National Heart Lung and Blood Institute; Alzheimer’s Association; Fonds de Recherche du Québec-Santé; Canadian Consortium of Neurodegeneration in Aging; Weston Brain Institute; Colin Adair Charitable Foundation; Swedish Research Council; Wallenberg Scholar; BrightFocus Foundation; Swedish Alzheimer Foundation; Swedish Brain Foundation; Agneta Prytz-Folkes & Gösta Folkes Foundation; European Union; Swedish State Support for Clinical Research; Alzheimer Drug Discovery Foundation; Bluefield Project, the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden; the UK Dementia Research Institute at UCL; National Academy of Neuropsychology; Fundação de Amparo a pesquisa do Rio Grande do Sul; Instituto Serrapilheira; and Hjärnfonden.

Dr. Pascoal reports no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Nearly 60% of Medicaid-covered adults with concurrent diabetes and heart failure did not receive guideline-concordant postdischarge care within 7-10 days of leaving the hospital, according to a large Alabama study. Moreover, affected Black and Hispanic/other Alabamians were less likely than were their White counterparts to receive recommended postdischarge care.

In comparison with White participants, Black and Hispanic adults were less likely to have any postdischarge ambulatory care visits after HF hospitalization or had a delayed visit, according to researchers led by Yulia Khodneva, MD, PhD, an internist at the University of Alabama at Birmingham. “This is likely a reflection of a structural racism and implicit bias against racial and ethnic minorities that persists in the U.S. health care system,” she and her colleagues wrote.

The findings point to the need for strategies to improve access to postdischarge care for lower-income HF patients.

Among U.S. states, Alabama is the sixth-poorest, the third in diabetes prevalence (14%), and has the highest rates of heart failure hospitalizations and cardiovascular mortality, the authors noted.

Study details

The cohort included 9,857 adults with diabetes and first hospitalizations for heart failure who were covered by Alabama Medicaid during 2010-2019. The investigators analyzed patients’ claims for ambulatory care (any, primary, cardiology, or endocrinology) within 60 days of discharge.

The mean age of participants was 53.7 years; 47.3% were Black; 41.8% non-Hispanic White; and 10.9% Hispanic/other, with other including those identifying as non-White Hispanic, American Indian, Pacific Islander, and Asian. About two-thirds (65.4%) of participants were women.

Analysis revealed low rates of follow-up care after hospital discharge; 26.7% had an ambulatory visit within 0-7 days, 15.2% within 8-14 days, 31.3% within 15-60 days, and 26.8% had no follow-up visit at all. Of those having a follow-up visit, 71% saw a primary care physician and 12% saw a cardiologist.

In contrast, a much higher proportion of heart failure patients in a Swedish registry – 63% – received ambulatory follow-up in cardiology.
 

Ethnic/gender/age disparities

Black and Hispanic/other adults were less likely to have any postdischarge ambulatory visit (P <.0001) or had the visit delayed by 1.8 days (P = .0006) and 2.8 days (P = .0016), respectively. They were less likely to see a primary care physician than were non-Hispanic White adults: adjusted incidence rate ratio, 0.96 (95% confidence interval [CI], 0.91-1.00) and 0.91 (95% CI, 0.89-0.98), respectively.

Men and those with longer-standing heart failure were less likely to be seen in primary care, while the presence of multiple comorbidities was associated with a higher likelihood of a postdischarge primary care visit. Men were more likely to be seen by a cardiologist, while older discharged patients were less likely to be seen by an endocrinologist within 60 days. There was a U-shaped relationship between the timing of the first postdischarge ambulatory visit and all-cause mortality among adults with diabetes and heart failure. Higher rates of 60-day all-cause mortality were observed both in those who had seen a provider within 0-7 days after discharge and in those who had not seen any provider during the 60-day study period compared with those having an ambulatory care visit within 7-14 or 15-60 days. “The group with early follow-up (0-7 days) likely represents a sicker population of patients with heart failure with more comorbidity burden and higher overall health care use, including readmissions, as was demonstrated in our analysis,” Dr. Khodneva and associates wrote. “Interventions that improve access to postdischarge ambulatory care for low-income patients with diabetes and heart failure and eliminate racial and ethnic disparities may be warranted,” they added.

This study was supported by the National Institute of Diabetes and Digestive and Kidney Diseases and the University of Alabama at Birmingham Diabetes Research Center. Dr. Khodneva reported funding from the University of Alabama at Birmingham and the Forge Ahead Center as well as from the NIDDK, the National Institutes of Health, the Agency for Healthcare Research and Quality, and the Alabama Medicaid Agency. Coauthor Emily Levitan, ScD, reported research funding from Amgen and has served on Amgen advisory boards. She has also served as a scientific consultant for a research project funded by Novartis.

Nearly 60% of Medicaid-covered adults with concurrent diabetes and heart failure did not receive guideline-concordant postdischarge care within 7-10 days of leaving the hospital, according to a large Alabama study. Moreover, affected Black and Hispanic/other Alabamians were less likely than were their White counterparts to receive recommended postdischarge care.

In comparison with White participants, Black and Hispanic adults were less likely to have any postdischarge ambulatory care visits after HF hospitalization or had a delayed visit, according to researchers led by Yulia Khodneva, MD, PhD, an internist at the University of Alabama at Birmingham. “This is likely a reflection of a structural racism and implicit bias against racial and ethnic minorities that persists in the U.S. health care system,” she and her colleagues wrote.

The findings point to the need for strategies to improve access to postdischarge care for lower-income HF patients.

Among U.S. states, Alabama is the sixth-poorest, the third in diabetes prevalence (14%), and has the highest rates of heart failure hospitalizations and cardiovascular mortality, the authors noted.

Study details

The cohort included 9,857 adults with diabetes and first hospitalizations for heart failure who were covered by Alabama Medicaid during 2010-2019. The investigators analyzed patients’ claims for ambulatory care (any, primary, cardiology, or endocrinology) within 60 days of discharge.

The mean age of participants was 53.7 years; 47.3% were Black; 41.8% non-Hispanic White; and 10.9% Hispanic/other, with other including those identifying as non-White Hispanic, American Indian, Pacific Islander, and Asian. About two-thirds (65.4%) of participants were women.

Analysis revealed low rates of follow-up care after hospital discharge; 26.7% had an ambulatory visit within 0-7 days, 15.2% within 8-14 days, 31.3% within 15-60 days, and 26.8% had no follow-up visit at all. Of those having a follow-up visit, 71% saw a primary care physician and 12% saw a cardiologist.

In contrast, a much higher proportion of heart failure patients in a Swedish registry – 63% – received ambulatory follow-up in cardiology.
 

Ethnic/gender/age disparities

Black and Hispanic/other adults were less likely to have any postdischarge ambulatory visit (P <.0001) or had the visit delayed by 1.8 days (P = .0006) and 2.8 days (P = .0016), respectively. They were less likely to see a primary care physician than were non-Hispanic White adults: adjusted incidence rate ratio, 0.96 (95% confidence interval [CI], 0.91-1.00) and 0.91 (95% CI, 0.89-0.98), respectively.

Men and those with longer-standing heart failure were less likely to be seen in primary care, while the presence of multiple comorbidities was associated with a higher likelihood of a postdischarge primary care visit. Men were more likely to be seen by a cardiologist, while older discharged patients were less likely to be seen by an endocrinologist within 60 days. There was a U-shaped relationship between the timing of the first postdischarge ambulatory visit and all-cause mortality among adults with diabetes and heart failure. Higher rates of 60-day all-cause mortality were observed both in those who had seen a provider within 0-7 days after discharge and in those who had not seen any provider during the 60-day study period compared with those having an ambulatory care visit within 7-14 or 15-60 days. “The group with early follow-up (0-7 days) likely represents a sicker population of patients with heart failure with more comorbidity burden and higher overall health care use, including readmissions, as was demonstrated in our analysis,” Dr. Khodneva and associates wrote. “Interventions that improve access to postdischarge ambulatory care for low-income patients with diabetes and heart failure and eliminate racial and ethnic disparities may be warranted,” they added.

This study was supported by the National Institute of Diabetes and Digestive and Kidney Diseases and the University of Alabama at Birmingham Diabetes Research Center. Dr. Khodneva reported funding from the University of Alabama at Birmingham and the Forge Ahead Center as well as from the NIDDK, the National Institutes of Health, the Agency for Healthcare Research and Quality, and the Alabama Medicaid Agency. Coauthor Emily Levitan, ScD, reported research funding from Amgen and has served on Amgen advisory boards. She has also served as a scientific consultant for a research project funded by Novartis.

Nearly 60% of Medicaid-covered adults with concurrent diabetes and heart failure did not receive guideline-concordant postdischarge care within 7-10 days of leaving the hospital, according to a large Alabama study. Moreover, affected Black and Hispanic/other Alabamians were less likely than were their White counterparts to receive recommended postdischarge care.

In comparison with White participants, Black and Hispanic adults were less likely to have any postdischarge ambulatory care visits after HF hospitalization or had a delayed visit, according to researchers led by Yulia Khodneva, MD, PhD, an internist at the University of Alabama at Birmingham. “This is likely a reflection of a structural racism and implicit bias against racial and ethnic minorities that persists in the U.S. health care system,” she and her colleagues wrote.

The findings point to the need for strategies to improve access to postdischarge care for lower-income HF patients.

Among U.S. states, Alabama is the sixth-poorest, the third in diabetes prevalence (14%), and has the highest rates of heart failure hospitalizations and cardiovascular mortality, the authors noted.

Study details

The cohort included 9,857 adults with diabetes and first hospitalizations for heart failure who were covered by Alabama Medicaid during 2010-2019. The investigators analyzed patients’ claims for ambulatory care (any, primary, cardiology, or endocrinology) within 60 days of discharge.

The mean age of participants was 53.7 years; 47.3% were Black; 41.8% non-Hispanic White; and 10.9% Hispanic/other, with other including those identifying as non-White Hispanic, American Indian, Pacific Islander, and Asian. About two-thirds (65.4%) of participants were women.

Analysis revealed low rates of follow-up care after hospital discharge; 26.7% had an ambulatory visit within 0-7 days, 15.2% within 8-14 days, 31.3% within 15-60 days, and 26.8% had no follow-up visit at all. Of those having a follow-up visit, 71% saw a primary care physician and 12% saw a cardiologist.

In contrast, a much higher proportion of heart failure patients in a Swedish registry – 63% – received ambulatory follow-up in cardiology.
 

Ethnic/gender/age disparities

Black and Hispanic/other adults were less likely to have any postdischarge ambulatory visit (P <.0001) or had the visit delayed by 1.8 days (P = .0006) and 2.8 days (P = .0016), respectively. They were less likely to see a primary care physician than were non-Hispanic White adults: adjusted incidence rate ratio, 0.96 (95% confidence interval [CI], 0.91-1.00) and 0.91 (95% CI, 0.89-0.98), respectively.

Men and those with longer-standing heart failure were less likely to be seen in primary care, while the presence of multiple comorbidities was associated with a higher likelihood of a postdischarge primary care visit. Men were more likely to be seen by a cardiologist, while older discharged patients were less likely to be seen by an endocrinologist within 60 days. There was a U-shaped relationship between the timing of the first postdischarge ambulatory visit and all-cause mortality among adults with diabetes and heart failure. Higher rates of 60-day all-cause mortality were observed both in those who had seen a provider within 0-7 days after discharge and in those who had not seen any provider during the 60-day study period compared with those having an ambulatory care visit within 7-14 or 15-60 days. “The group with early follow-up (0-7 days) likely represents a sicker population of patients with heart failure with more comorbidity burden and higher overall health care use, including readmissions, as was demonstrated in our analysis,” Dr. Khodneva and associates wrote. “Interventions that improve access to postdischarge ambulatory care for low-income patients with diabetes and heart failure and eliminate racial and ethnic disparities may be warranted,” they added.

This study was supported by the National Institute of Diabetes and Digestive and Kidney Diseases and the University of Alabama at Birmingham Diabetes Research Center. Dr. Khodneva reported funding from the University of Alabama at Birmingham and the Forge Ahead Center as well as from the NIDDK, the National Institutes of Health, the Agency for Healthcare Research and Quality, and the Alabama Medicaid Agency. Coauthor Emily Levitan, ScD, reported research funding from Amgen and has served on Amgen advisory boards. She has also served as a scientific consultant for a research project funded by Novartis.

The field of neurodegenerative dementias, particularly Alzheimer’s disease (AD), has been revolutionized by the development of imaging and cerebrospinal fluid biomarkers and is on the brink of a new development: emerging plasma biomarkers. Research now recognizes the relationship between the cognitive-behavioral syndromic diagnosis (that is, the illness) and the etiologic diagnosis (the disease) – and the need to consider each separately when developing a diagnostic formulation. The National Institute on Aging and Alzheimer’s Association Research Framework uses the amyloid, tau, and neurodegeneration system to define AD biologically in living patients. Here is an overview of the framework, which requires biomarker evidence of amyloid plaques (amyloid positivity) and neurofibrillary tangles (tau positivity), with evidence of neurodegeneration (neurodegeneration positivity) to support the diagnosis.

The diagnostic approach for symptomatic patients

The differential diagnosis in symptomatic patients with mild cognitive impairment (MCI), mild behavioral impairment, or dementia is broad and includes multiple neurodegenerative diseases (for example, AD, frontotemporal lobar degeneration, dementia with Lewy bodies, argyrophilic grain disease, hippocampal sclerosis); vascular ischemic brain injury (for example, stroke); tumors; infectious, inflammatory, paraneoplastic, or demyelinating diseases; trauma; hydrocephalus; toxic/metabolic insults; and other rare diseases. The patient’s clinical syndrome narrows the differential diagnosis.

Once the clinician has a prioritized differential diagnosis of the brain disease or condition that is probably causing or contributing to the patient’s signs and symptoms, they can then select appropriate assessments and tests, typically starting with a laboratory panel and brain MRI. Strong evidence backed by practice recommendations also supports the use of fluorodeoxyglucose PET as a marker of functional brain abnormalities associated with dementia. Although molecular biomarkers are typically considered at the later stage of the clinical workup, the anticipated future availability of plasma biomarkers will probably change the timing of molecular biomarker assessment in patients with suspected cognitive impairment owing to AD.
 

Molecular PET biomarkers

Three PET tracers approved by the U.S. Food and Drug Administration for the detection of cerebral amyloid plaques have high sensitivity (89%-98%) and specificity (88%-100%), compared with autopsy, the gold standard diagnostic tool. However, these scans are costly and are not reimbursed by Medicare and Medicaid. Because all amyloid PET scans are covered by the Veterans Administration, this test is more readily accessible for patients receiving VA benefits.

The appropriate-use criteria developed by the Amyloid Imaging Task Force recommends amyloid PET for patients with persistent or progressive MCI or dementia. In such patients, a negative amyloid PET scan would strongly weigh against AD, supporting a differential diagnosis of other etiologies. Although a positive amyloid PET scan in patients with MCI or dementia indicates the presence of amyloid plaques, it does not necessarily confirm AD as the cause. Cerebral amyloid plaques may coexist with other pathologies and increase with age, even in cognitively normal individuals.

The IDEAS study looked at the clinical utility of amyloid PET in a real-world dementia specialist setting. In the study, dementia subspecialists documented their presumed etiologic diagnosis (and level of confidence) before and after amyloid PET. Of the 11,409 patients who completed the study, the etiologic diagnosis changed from AD to non-AD in just over 25% of cases and from non-AD to AD in 10.5%. Clinical management changed in about 60% of patients with MCI and 63.5% of patients with dementia.

In May 2020, the FDA approved flortaucipir F-18, the first diagnostic tau radiotracer for use with PET to estimate the density and distribution of aggregated tau neurofibrillary tangles in adults with cognitive impairment undergoing evaluation for AD. Regulatory approval of flortaucipir F-18 was based on findings from two clinical trials of terminally ill patients who were followed to autopsy. The studies included patients with a spectrum of clinically diagnosed dementias and those with normal cognition. The primary outcome of the studies was accurate visual interpretation of the images in detecting advanced AD tau neurofibrillary tangle pathology (Braak stage V or VI tau pathology). Sensitivity of five trained readers ranged from 68% to 86%, and specificity ranged from 63% to 100%; interrater agreement was 0.87. Tau PET is not yet reimbursed and is therefore not yet readily available in the clinical setting. Moreover, appropriate use criteria have not yet been published.
 

Molecular fluid biomarkers

Cerebrospinal fluid (CSF) analysis is currently the most readily available and reimbursed test to aid in diagnosing AD, with appropriate-use criteria for patients with suspected AD. CSF biomarkers for AD are useful in cognitively impaired patients when the etiologic diagnosis is equivocal, there is only an intermediate level of diagnostic confidence, or there is very high confidence in the etiologic diagnosis. Testing for CSF biomarkers is also recommended for patients at very early clinical stages (for example, early MCI) or with atypical clinical presentations.

A decreased concentration of amyloid-beta 42 in CSF is a marker of amyloid neuritic plaques in the brain. An increased concentration of total tau in CSF reflects injury to neurons, and an increased concentration of specific isoforms of hyperphosphorylated tau reflects neurofibrillary tangles. Presently, the ratios of t-tau to amyloid-beta 42, amyloid-beta 42 to amyloid-beta 40, and phosphorylated-tau 181 to amyloid-beta 42 are the best-performing markers of AD neuropathologic changes and are more accurate than assessing individual biomarkers. These CSF biomarkers of AD have been validated against autopsy, and ratio values of CSF amyloid-beta 42 have been further validated against amyloid PET, with overall sensitivity and specificity of approximately 90% and 84%, respectively.

Some of the most exciting recent advances in AD center around the measurement of these proteins and others in plasma. Appropriate-use criteria for plasma biomarkers in the evaluation of patients with cognitive impairment were published in 2022. In addition to their use in clinical trials, these criteria cautiously recommend using these biomarkers in specialized memory clinics in the diagnostic workup of patients with cognitive symptoms, along with confirmatory CSF markers or PET. Additional data are needed before plasma biomarkers of AD are used as standalone diagnostic markers or considered in the primary care setting.

We have made remarkable progress toward more precise molecular diagnosis of brain diseases underlying cognitive impairment and dementia. Ongoing efforts to evaluate the utility of these measures in clinical practice include the need to increase diversity of patients and providers. Ultimately, the tremendous progress in molecular biomarkers for the diseases causing dementia will help the field work toward our common goal of early and accurate diagnosis, better management, and hope for people living with these diseases.

Bradford C. Dickerson, MD, MMSc, is a professor, department of neurology, Harvard Medical School, and director, Frontotemporal Disorders Unit, department of neurology, at Massachusetts General Hospital, both in Boston.

A version of this article first appeared on Medscape.com.

The field of neurodegenerative dementias, particularly Alzheimer’s disease (AD), has been revolutionized by the development of imaging and cerebrospinal fluid biomarkers and is on the brink of a new development: emerging plasma biomarkers. Research now recognizes the relationship between the cognitive-behavioral syndromic diagnosis (that is, the illness) and the etiologic diagnosis (the disease) – and the need to consider each separately when developing a diagnostic formulation. The National Institute on Aging and Alzheimer’s Association Research Framework uses the amyloid, tau, and neurodegeneration system to define AD biologically in living patients. Here is an overview of the framework, which requires biomarker evidence of amyloid plaques (amyloid positivity) and neurofibrillary tangles (tau positivity), with evidence of neurodegeneration (neurodegeneration positivity) to support the diagnosis.

The diagnostic approach for symptomatic patients

The differential diagnosis in symptomatic patients with mild cognitive impairment (MCI), mild behavioral impairment, or dementia is broad and includes multiple neurodegenerative diseases (for example, AD, frontotemporal lobar degeneration, dementia with Lewy bodies, argyrophilic grain disease, hippocampal sclerosis); vascular ischemic brain injury (for example, stroke); tumors; infectious, inflammatory, paraneoplastic, or demyelinating diseases; trauma; hydrocephalus; toxic/metabolic insults; and other rare diseases. The patient’s clinical syndrome narrows the differential diagnosis.

Once the clinician has a prioritized differential diagnosis of the brain disease or condition that is probably causing or contributing to the patient’s signs and symptoms, they can then select appropriate assessments and tests, typically starting with a laboratory panel and brain MRI. Strong evidence backed by practice recommendations also supports the use of fluorodeoxyglucose PET as a marker of functional brain abnormalities associated with dementia. Although molecular biomarkers are typically considered at the later stage of the clinical workup, the anticipated future availability of plasma biomarkers will probably change the timing of molecular biomarker assessment in patients with suspected cognitive impairment owing to AD.
 

Molecular PET biomarkers

Three PET tracers approved by the U.S. Food and Drug Administration for the detection of cerebral amyloid plaques have high sensitivity (89%-98%) and specificity (88%-100%), compared with autopsy, the gold standard diagnostic tool. However, these scans are costly and are not reimbursed by Medicare and Medicaid. Because all amyloid PET scans are covered by the Veterans Administration, this test is more readily accessible for patients receiving VA benefits.

The appropriate-use criteria developed by the Amyloid Imaging Task Force recommends amyloid PET for patients with persistent or progressive MCI or dementia. In such patients, a negative amyloid PET scan would strongly weigh against AD, supporting a differential diagnosis of other etiologies. Although a positive amyloid PET scan in patients with MCI or dementia indicates the presence of amyloid plaques, it does not necessarily confirm AD as the cause. Cerebral amyloid plaques may coexist with other pathologies and increase with age, even in cognitively normal individuals.

The IDEAS study looked at the clinical utility of amyloid PET in a real-world dementia specialist setting. In the study, dementia subspecialists documented their presumed etiologic diagnosis (and level of confidence) before and after amyloid PET. Of the 11,409 patients who completed the study, the etiologic diagnosis changed from AD to non-AD in just over 25% of cases and from non-AD to AD in 10.5%. Clinical management changed in about 60% of patients with MCI and 63.5% of patients with dementia.

In May 2020, the FDA approved flortaucipir F-18, the first diagnostic tau radiotracer for use with PET to estimate the density and distribution of aggregated tau neurofibrillary tangles in adults with cognitive impairment undergoing evaluation for AD. Regulatory approval of flortaucipir F-18 was based on findings from two clinical trials of terminally ill patients who were followed to autopsy. The studies included patients with a spectrum of clinically diagnosed dementias and those with normal cognition. The primary outcome of the studies was accurate visual interpretation of the images in detecting advanced AD tau neurofibrillary tangle pathology (Braak stage V or VI tau pathology). Sensitivity of five trained readers ranged from 68% to 86%, and specificity ranged from 63% to 100%; interrater agreement was 0.87. Tau PET is not yet reimbursed and is therefore not yet readily available in the clinical setting. Moreover, appropriate use criteria have not yet been published.
 

Molecular fluid biomarkers

Cerebrospinal fluid (CSF) analysis is currently the most readily available and reimbursed test to aid in diagnosing AD, with appropriate-use criteria for patients with suspected AD. CSF biomarkers for AD are useful in cognitively impaired patients when the etiologic diagnosis is equivocal, there is only an intermediate level of diagnostic confidence, or there is very high confidence in the etiologic diagnosis. Testing for CSF biomarkers is also recommended for patients at very early clinical stages (for example, early MCI) or with atypical clinical presentations.

A decreased concentration of amyloid-beta 42 in CSF is a marker of amyloid neuritic plaques in the brain. An increased concentration of total tau in CSF reflects injury to neurons, and an increased concentration of specific isoforms of hyperphosphorylated tau reflects neurofibrillary tangles. Presently, the ratios of t-tau to amyloid-beta 42, amyloid-beta 42 to amyloid-beta 40, and phosphorylated-tau 181 to amyloid-beta 42 are the best-performing markers of AD neuropathologic changes and are more accurate than assessing individual biomarkers. These CSF biomarkers of AD have been validated against autopsy, and ratio values of CSF amyloid-beta 42 have been further validated against amyloid PET, with overall sensitivity and specificity of approximately 90% and 84%, respectively.

Some of the most exciting recent advances in AD center around the measurement of these proteins and others in plasma. Appropriate-use criteria for plasma biomarkers in the evaluation of patients with cognitive impairment were published in 2022. In addition to their use in clinical trials, these criteria cautiously recommend using these biomarkers in specialized memory clinics in the diagnostic workup of patients with cognitive symptoms, along with confirmatory CSF markers or PET. Additional data are needed before plasma biomarkers of AD are used as standalone diagnostic markers or considered in the primary care setting.

We have made remarkable progress toward more precise molecular diagnosis of brain diseases underlying cognitive impairment and dementia. Ongoing efforts to evaluate the utility of these measures in clinical practice include the need to increase diversity of patients and providers. Ultimately, the tremendous progress in molecular biomarkers for the diseases causing dementia will help the field work toward our common goal of early and accurate diagnosis, better management, and hope for people living with these diseases.

Bradford C. Dickerson, MD, MMSc, is a professor, department of neurology, Harvard Medical School, and director, Frontotemporal Disorders Unit, department of neurology, at Massachusetts General Hospital, both in Boston.

A version of this article first appeared on Medscape.com.

The field of neurodegenerative dementias, particularly Alzheimer’s disease (AD), has been revolutionized by the development of imaging and cerebrospinal fluid biomarkers and is on the brink of a new development: emerging plasma biomarkers. Research now recognizes the relationship between the cognitive-behavioral syndromic diagnosis (that is, the illness) and the etiologic diagnosis (the disease) – and the need to consider each separately when developing a diagnostic formulation. The National Institute on Aging and Alzheimer’s Association Research Framework uses the amyloid, tau, and neurodegeneration system to define AD biologically in living patients. Here is an overview of the framework, which requires biomarker evidence of amyloid plaques (amyloid positivity) and neurofibrillary tangles (tau positivity), with evidence of neurodegeneration (neurodegeneration positivity) to support the diagnosis.

The diagnostic approach for symptomatic patients

The differential diagnosis in symptomatic patients with mild cognitive impairment (MCI), mild behavioral impairment, or dementia is broad and includes multiple neurodegenerative diseases (for example, AD, frontotemporal lobar degeneration, dementia with Lewy bodies, argyrophilic grain disease, hippocampal sclerosis); vascular ischemic brain injury (for example, stroke); tumors; infectious, inflammatory, paraneoplastic, or demyelinating diseases; trauma; hydrocephalus; toxic/metabolic insults; and other rare diseases. The patient’s clinical syndrome narrows the differential diagnosis.

Once the clinician has a prioritized differential diagnosis of the brain disease or condition that is probably causing or contributing to the patient’s signs and symptoms, they can then select appropriate assessments and tests, typically starting with a laboratory panel and brain MRI. Strong evidence backed by practice recommendations also supports the use of fluorodeoxyglucose PET as a marker of functional brain abnormalities associated with dementia. Although molecular biomarkers are typically considered at the later stage of the clinical workup, the anticipated future availability of plasma biomarkers will probably change the timing of molecular biomarker assessment in patients with suspected cognitive impairment owing to AD.
 

Molecular PET biomarkers

Three PET tracers approved by the U.S. Food and Drug Administration for the detection of cerebral amyloid plaques have high sensitivity (89%-98%) and specificity (88%-100%), compared with autopsy, the gold standard diagnostic tool. However, these scans are costly and are not reimbursed by Medicare and Medicaid. Because all amyloid PET scans are covered by the Veterans Administration, this test is more readily accessible for patients receiving VA benefits.

The appropriate-use criteria developed by the Amyloid Imaging Task Force recommends amyloid PET for patients with persistent or progressive MCI or dementia. In such patients, a negative amyloid PET scan would strongly weigh against AD, supporting a differential diagnosis of other etiologies. Although a positive amyloid PET scan in patients with MCI or dementia indicates the presence of amyloid plaques, it does not necessarily confirm AD as the cause. Cerebral amyloid plaques may coexist with other pathologies and increase with age, even in cognitively normal individuals.

The IDEAS study looked at the clinical utility of amyloid PET in a real-world dementia specialist setting. In the study, dementia subspecialists documented their presumed etiologic diagnosis (and level of confidence) before and after amyloid PET. Of the 11,409 patients who completed the study, the etiologic diagnosis changed from AD to non-AD in just over 25% of cases and from non-AD to AD in 10.5%. Clinical management changed in about 60% of patients with MCI and 63.5% of patients with dementia.

In May 2020, the FDA approved flortaucipir F-18, the first diagnostic tau radiotracer for use with PET to estimate the density and distribution of aggregated tau neurofibrillary tangles in adults with cognitive impairment undergoing evaluation for AD. Regulatory approval of flortaucipir F-18 was based on findings from two clinical trials of terminally ill patients who were followed to autopsy. The studies included patients with a spectrum of clinically diagnosed dementias and those with normal cognition. The primary outcome of the studies was accurate visual interpretation of the images in detecting advanced AD tau neurofibrillary tangle pathology (Braak stage V or VI tau pathology). Sensitivity of five trained readers ranged from 68% to 86%, and specificity ranged from 63% to 100%; interrater agreement was 0.87. Tau PET is not yet reimbursed and is therefore not yet readily available in the clinical setting. Moreover, appropriate use criteria have not yet been published.
 

Molecular fluid biomarkers

Cerebrospinal fluid (CSF) analysis is currently the most readily available and reimbursed test to aid in diagnosing AD, with appropriate-use criteria for patients with suspected AD. CSF biomarkers for AD are useful in cognitively impaired patients when the etiologic diagnosis is equivocal, there is only an intermediate level of diagnostic confidence, or there is very high confidence in the etiologic diagnosis. Testing for CSF biomarkers is also recommended for patients at very early clinical stages (for example, early MCI) or with atypical clinical presentations.

A decreased concentration of amyloid-beta 42 in CSF is a marker of amyloid neuritic plaques in the brain. An increased concentration of total tau in CSF reflects injury to neurons, and an increased concentration of specific isoforms of hyperphosphorylated tau reflects neurofibrillary tangles. Presently, the ratios of t-tau to amyloid-beta 42, amyloid-beta 42 to amyloid-beta 40, and phosphorylated-tau 181 to amyloid-beta 42 are the best-performing markers of AD neuropathologic changes and are more accurate than assessing individual biomarkers. These CSF biomarkers of AD have been validated against autopsy, and ratio values of CSF amyloid-beta 42 have been further validated against amyloid PET, with overall sensitivity and specificity of approximately 90% and 84%, respectively.

Some of the most exciting recent advances in AD center around the measurement of these proteins and others in plasma. Appropriate-use criteria for plasma biomarkers in the evaluation of patients with cognitive impairment were published in 2022. In addition to their use in clinical trials, these criteria cautiously recommend using these biomarkers in specialized memory clinics in the diagnostic workup of patients with cognitive symptoms, along with confirmatory CSF markers or PET. Additional data are needed before plasma biomarkers of AD are used as standalone diagnostic markers or considered in the primary care setting.

We have made remarkable progress toward more precise molecular diagnosis of brain diseases underlying cognitive impairment and dementia. Ongoing efforts to evaluate the utility of these measures in clinical practice include the need to increase diversity of patients and providers. Ultimately, the tremendous progress in molecular biomarkers for the diseases causing dementia will help the field work toward our common goal of early and accurate diagnosis, better management, and hope for people living with these diseases.

Bradford C. Dickerson, MD, MMSc, is a professor, department of neurology, Harvard Medical School, and director, Frontotemporal Disorders Unit, department of neurology, at Massachusetts General Hospital, both in Boston.

A version of this article first appeared on Medscape.com.

Compared with the complicated and ever-changing recommended vaccine schedule for infants and children, vaccines for adults have been straightforward. Adults without compromised immunity who received all their childhood vaccinations are eligible for a tetanus and diphtheria (Td) or tetanus, diphtheria, and pertussis (Tdap) booster every 10 years, recombinant herpes zoster vaccine at age 50, and pneumococcal vaccines at age 65, along with annual influenza and (likely) COVID-19 vaccines. Last year, due to rising rates of acute hepatitis B, the Centers for Disease Control and Prevention first recommended universal hepatitis B vaccination for adults aged 19-59 years without a record of previous hepatitis B infection or vaccination.

An additional routine vaccine for adults is now on the horizon. The U.S. Food and Drug Administration recently approved Arexvy, a vaccine against respiratory syncytial virus (RSV) for adults aged 60 years or older. Two more RSV vaccines are in the final stages of development. Why should family physicians prioritize vaccinating older adults against RSV, and how can we incorporate this new vaccine into our practices and overcome patient hesitancy to receive yet another vaccine?

Clinicians tend to think of RSV as a serious disease in young children – which it is – but data suggest that in 2019, RSV infection led to more than 100,000 hospitalizations and 7,700 deaths in older adults in the United States. In a randomized controlled trial of 25,000 adults aged 60 years or older with a median of 6.7 months of follow-up, Arexvy reduced severe RSV disease by 94% and RSV-related acute respiratory infections by 71%, with similar effectiveness in adults with underlying health conditions. That’s considerably better protection than current influenza vaccines and comparable to COVID-19 mRNA vaccines before variants became widespread. Pain and fatigue were the most common side effects and usually resolved within 1-2 days.

Although the seasonal pattern of RSV shifted during the COVID-19 pandemic, RSV season historically begins in October, peaks in December, and ends in April. If the vaccine is recommended by the CDC and is widely available by fall, as the manufacturer, GSK, expects, it could be administered around the same time as influenza and COVID-19 vaccines.

The challenges of incorporating this new vaccine into practice will feel familiar: Many of our patients won’t have heard about it, may feel that they don’t need it, or may decline it because of concerns about side effects, real or imagined. (Of note, the FDA is requiring GSK to perform a postmarketing study to rule out associations with rare cases of Guillain-Barré syndrome and acute disseminated encephalomyelitis, and the company also plans to monitor the incidence of atrial fibrillation, which was slightly more common in the vaccine group than the placebo group.)

While a strong recommendation from a family physician is often enough to convince patients to accept vaccination, rampant misinformation during the pandemic may have worsened vaccine hesitancy for some. It may feel like a fruitless exercise to try to convince adults who have refused COVID-19 and influenza vaccines to accept a newer vaccine against a respiratory virus that causes less serious illness overall. But with other RSV vaccines and monoclonal antibodies for older adults and infants likely to be approved soon, it’s important for us to start laying the groundwork now by educating colleagues, staff, and patients about preventing serious illness caused by RSV.

Dr. Lin is an associate professor in the Department of Family Medicine at Georgetown University and a staff physician atMedStar Health Center, both in Washington. He has received income from UpToDate, Wiley-Blackwell, and the American Academy of Family Physicians.

A version of this article first appeared on Medscape.com.

Compared with the complicated and ever-changing recommended vaccine schedule for infants and children, vaccines for adults have been straightforward. Adults without compromised immunity who received all their childhood vaccinations are eligible for a tetanus and diphtheria (Td) or tetanus, diphtheria, and pertussis (Tdap) booster every 10 years, recombinant herpes zoster vaccine at age 50, and pneumococcal vaccines at age 65, along with annual influenza and (likely) COVID-19 vaccines. Last year, due to rising rates of acute hepatitis B, the Centers for Disease Control and Prevention first recommended universal hepatitis B vaccination for adults aged 19-59 years without a record of previous hepatitis B infection or vaccination.

An additional routine vaccine for adults is now on the horizon. The U.S. Food and Drug Administration recently approved Arexvy, a vaccine against respiratory syncytial virus (RSV) for adults aged 60 years or older. Two more RSV vaccines are in the final stages of development. Why should family physicians prioritize vaccinating older adults against RSV, and how can we incorporate this new vaccine into our practices and overcome patient hesitancy to receive yet another vaccine?

Clinicians tend to think of RSV as a serious disease in young children – which it is – but data suggest that in 2019, RSV infection led to more than 100,000 hospitalizations and 7,700 deaths in older adults in the United States. In a randomized controlled trial of 25,000 adults aged 60 years or older with a median of 6.7 months of follow-up, Arexvy reduced severe RSV disease by 94% and RSV-related acute respiratory infections by 71%, with similar effectiveness in adults with underlying health conditions. That’s considerably better protection than current influenza vaccines and comparable to COVID-19 mRNA vaccines before variants became widespread. Pain and fatigue were the most common side effects and usually resolved within 1-2 days.

Although the seasonal pattern of RSV shifted during the COVID-19 pandemic, RSV season historically begins in October, peaks in December, and ends in April. If the vaccine is recommended by the CDC and is widely available by fall, as the manufacturer, GSK, expects, it could be administered around the same time as influenza and COVID-19 vaccines.

The challenges of incorporating this new vaccine into practice will feel familiar: Many of our patients won’t have heard about it, may feel that they don’t need it, or may decline it because of concerns about side effects, real or imagined. (Of note, the FDA is requiring GSK to perform a postmarketing study to rule out associations with rare cases of Guillain-Barré syndrome and acute disseminated encephalomyelitis, and the company also plans to monitor the incidence of atrial fibrillation, which was slightly more common in the vaccine group than the placebo group.)

While a strong recommendation from a family physician is often enough to convince patients to accept vaccination, rampant misinformation during the pandemic may have worsened vaccine hesitancy for some. It may feel like a fruitless exercise to try to convince adults who have refused COVID-19 and influenza vaccines to accept a newer vaccine against a respiratory virus that causes less serious illness overall. But with other RSV vaccines and monoclonal antibodies for older adults and infants likely to be approved soon, it’s important for us to start laying the groundwork now by educating colleagues, staff, and patients about preventing serious illness caused by RSV.

Dr. Lin is an associate professor in the Department of Family Medicine at Georgetown University and a staff physician atMedStar Health Center, both in Washington. He has received income from UpToDate, Wiley-Blackwell, and the American Academy of Family Physicians.

A version of this article first appeared on Medscape.com.

Compared with the complicated and ever-changing recommended vaccine schedule for infants and children, vaccines for adults have been straightforward. Adults without compromised immunity who received all their childhood vaccinations are eligible for a tetanus and diphtheria (Td) or tetanus, diphtheria, and pertussis (Tdap) booster every 10 years, recombinant herpes zoster vaccine at age 50, and pneumococcal vaccines at age 65, along with annual influenza and (likely) COVID-19 vaccines. Last year, due to rising rates of acute hepatitis B, the Centers for Disease Control and Prevention first recommended universal hepatitis B vaccination for adults aged 19-59 years without a record of previous hepatitis B infection or vaccination.

An additional routine vaccine for adults is now on the horizon. The U.S. Food and Drug Administration recently approved Arexvy, a vaccine against respiratory syncytial virus (RSV) for adults aged 60 years or older. Two more RSV vaccines are in the final stages of development. Why should family physicians prioritize vaccinating older adults against RSV, and how can we incorporate this new vaccine into our practices and overcome patient hesitancy to receive yet another vaccine?

Clinicians tend to think of RSV as a serious disease in young children – which it is – but data suggest that in 2019, RSV infection led to more than 100,000 hospitalizations and 7,700 deaths in older adults in the United States. In a randomized controlled trial of 25,000 adults aged 60 years or older with a median of 6.7 months of follow-up, Arexvy reduced severe RSV disease by 94% and RSV-related acute respiratory infections by 71%, with similar effectiveness in adults with underlying health conditions. That’s considerably better protection than current influenza vaccines and comparable to COVID-19 mRNA vaccines before variants became widespread. Pain and fatigue were the most common side effects and usually resolved within 1-2 days.

Although the seasonal pattern of RSV shifted during the COVID-19 pandemic, RSV season historically begins in October, peaks in December, and ends in April. If the vaccine is recommended by the CDC and is widely available by fall, as the manufacturer, GSK, expects, it could be administered around the same time as influenza and COVID-19 vaccines.

The challenges of incorporating this new vaccine into practice will feel familiar: Many of our patients won’t have heard about it, may feel that they don’t need it, or may decline it because of concerns about side effects, real or imagined. (Of note, the FDA is requiring GSK to perform a postmarketing study to rule out associations with rare cases of Guillain-Barré syndrome and acute disseminated encephalomyelitis, and the company also plans to monitor the incidence of atrial fibrillation, which was slightly more common in the vaccine group than the placebo group.)

While a strong recommendation from a family physician is often enough to convince patients to accept vaccination, rampant misinformation during the pandemic may have worsened vaccine hesitancy for some. It may feel like a fruitless exercise to try to convince adults who have refused COVID-19 and influenza vaccines to accept a newer vaccine against a respiratory virus that causes less serious illness overall. But with other RSV vaccines and monoclonal antibodies for older adults and infants likely to be approved soon, it’s important for us to start laying the groundwork now by educating colleagues, staff, and patients about preventing serious illness caused by RSV.

Dr. Lin is an associate professor in the Department of Family Medicine at Georgetown University and a staff physician atMedStar Health Center, both in Washington. He has received income from UpToDate, Wiley-Blackwell, and the American Academy of Family Physicians.

A version of this article first appeared on Medscape.com.

Taking a daily flavanol supplement improves hippocampal-dependent memory in older adults who have a relatively poor diet, results of a large new study suggest.

There’s increasing evidence that certain nutrients are important for the aging body and brain, study investigator Scott Small, MD, the Boris and Rose Katz Professor of Neurology, Columbia University Vagelos College of Physicians and Surgeons, New York, told this news organization.

“With this new study, I think we can begin to say flavanols might be the first one that really is a nutrient for the aging brain.”

These findings, said Dr. Small, represent “the beginning of a new era” that will eventually lead to formal recommendations” related to ideal intake of flavanols to reduce cognitive aging.

The findings were published online in the Proceedings of the National Academy of Science.
 

Better cognitive aging

Cognitive aging refers to the decline in cognitive abilities that are not thought to be caused by neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. Cognitive aging targets two areas of the brain: the hippocampus, which is related to memory function, and the prefrontal cortex, which is related to attention and executive function.

Previous research has linked flavanols, which are found in foods like apples, pears, berries, and cocoa beans, to improved cognitive aging. The evidence shows that consuming these nutrients might be associated with the hippocampal-dependent memory component of cognitive aging.

The new study, known as COcoa Supplement and Multivitamin Outcomes Study-Web (COSMOS-Web), included 3,562 generally healthy men and women, mean age 71 years, who were mostly well-educated and non-Hispanic/non-Latinx White individuals.

Participants were randomly assigned to receive oral flavanol-containing cocoa extract (500 mg of cocoa flavanols, including 80 mg of epicatechin) or a placebo daily.

The primary endpoint was hippocampal-dependent memory at year 1 as assessed with the ModRey, a neuropsychological test designed to measure hippocampal function.

Results showed participants in both groups had a typical learning (practice) effect, with similar improvements (d = 0.025; P = .42).

Researchers used other tests to measure cognition: the Color/Directional Flanker Task, a measure of prefrontal cortex function, and the ModBent, a measure that’s sensitive to dentate gyrus function. The flavanol intervention did not affect ModBent results or performance on the Flanker test after 1 year.

However, it was a different story for those with a poor diet at baseline. Researchers stratified participants into tertiles on the basis of diet quality as measured by the Healthy Eating Index (HEI) scores. Those in the lowest tertile had poorer baseline hippocampal-dependent memory performance but not memory related to the prefrontal cortex.

The flavanol intervention improved performance on the ModRey test, compared with placebo in participants in the low HEI tertile (overall effect: d = 0.086; P = .011) but not among those with a medium or high HEI at baseline.

“We confirmed that the flavanol intervention only benefits people who are relatively deficient at baseline,” said Dr. Small.

The correlation with hippocampal-dependent memory was confirmed in a subset of 1,361 study participants who provided a urine sample. Researchers measured urinary 5-(3′,4′-dihydroxyphenyl)-gamma-valerolactone metabolite (gVLM) concentrations, a validated biomarker of flavanol consumption.

After stratifying these results into tertiles, researchers found performance on the ModRey was significantly improved with the dietary flavanol intervention (overall effect: d = 0.141; P = .006) in the lowest gVLM tertile.
 

Memory restored

When participants in the lowest tertile consumed the supplement, “their flavanol levels went back to normal, and when that happened, their memory was restored,” said Dr. Small.

It appears that there is a sort of ceiling effect to the flavanol benefits. “It seems what you need to do is normalize your flavanol levels; if you go above normal, there was no evidence that your memory keeps on getting better,” said Dr. Small.

The study included only older adults, so it’s unclear what the impact of flavanol supplementation is in younger adults. But cognitive aging “begins its slippery side” in the 40s, said Dr. Small. “If this is truly a nutrient that is taken to prevent that slide from happening, it might be beneficial to start in our 40s.”

He recognized that the effect size is not large but said this is “very dependent” on baseline factors and most study participants had a rather healthy diet. “None of our participants were really highly deficient” in flavanols, he said.

“To see a stronger effect size, we need to do another study where we recruit people who are very low, truly deficient, in flavanols, and then see what happens.”

Showing that flavanols are linked to the hippocampal and not to the prefrontal component of cognitive aging “speaks to the mechanism,” said Dr. Small.

Though the exact mechanism linking flavanols with enhanced memory isn’t clear, there are some clues; for example, research suggests cognitive aging affects the dentate gyrus, a subregion of the hippocampus.

The flavanol supplements were well tolerated. “I can say with close to certainty that this is very safe,” said Dr. Small, adding the flavanols have now been used in numerous studies.

The findings suggest flavanol consumption might be part of future dietary guidelines. “I suspect that once there is sufficient evidence, flavanols will be part of the dietary recommendations for healthy aging,” said Dr. Small.
 

A word of caution

Heather M. Snyder, PhD, vice president of medical and scientific relations, Alzheimer’s Association, said that though science suggests a balanced diet is good for overall brain health, no single food, beverage, ingredient, vitamin, or supplement has yet been proven to prevent dementia, treat or cure Alzheimer’s, or benefit cognitive function or brain health.

Experts agree the best source of vitamins and other nutrients is from whole foods as part of a balanced diet. “We recognize that, for a variety of reasons, this may not always be possible,” said Dr. Snyder.

However, she noted, dietary supplements are not subject to the same rigorous review and regulation process as medications.

“The Alzheimer’s Association strongly encourages individuals to have conversations with their physicians about all medications and dietary supplements they are currently taking or interested in starting.” 

COSMOS is supported by an investigator-initiated grant from Mars Edge, a segment of Mars, company engaged in flavanol research and flavanol-related commercial activities, which included infrastructure support and the donation of study pills and packaging. Small reports receiving an unrestricted research grant from Mars.

A version of this article first appeared on Medscape.com.

Taking a daily flavanol supplement improves hippocampal-dependent memory in older adults who have a relatively poor diet, results of a large new study suggest.

There’s increasing evidence that certain nutrients are important for the aging body and brain, study investigator Scott Small, MD, the Boris and Rose Katz Professor of Neurology, Columbia University Vagelos College of Physicians and Surgeons, New York, told this news organization.

“With this new study, I think we can begin to say flavanols might be the first one that really is a nutrient for the aging brain.”

These findings, said Dr. Small, represent “the beginning of a new era” that will eventually lead to formal recommendations” related to ideal intake of flavanols to reduce cognitive aging.

The findings were published online in the Proceedings of the National Academy of Science.
 

Better cognitive aging

Cognitive aging refers to the decline in cognitive abilities that are not thought to be caused by neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. Cognitive aging targets two areas of the brain: the hippocampus, which is related to memory function, and the prefrontal cortex, which is related to attention and executive function.

Previous research has linked flavanols, which are found in foods like apples, pears, berries, and cocoa beans, to improved cognitive aging. The evidence shows that consuming these nutrients might be associated with the hippocampal-dependent memory component of cognitive aging.

The new study, known as COcoa Supplement and Multivitamin Outcomes Study-Web (COSMOS-Web), included 3,562 generally healthy men and women, mean age 71 years, who were mostly well-educated and non-Hispanic/non-Latinx White individuals.

Participants were randomly assigned to receive oral flavanol-containing cocoa extract (500 mg of cocoa flavanols, including 80 mg of epicatechin) or a placebo daily.

The primary endpoint was hippocampal-dependent memory at year 1 as assessed with the ModRey, a neuropsychological test designed to measure hippocampal function.

Results showed participants in both groups had a typical learning (practice) effect, with similar improvements (d = 0.025; P = .42).

Researchers used other tests to measure cognition: the Color/Directional Flanker Task, a measure of prefrontal cortex function, and the ModBent, a measure that’s sensitive to dentate gyrus function. The flavanol intervention did not affect ModBent results or performance on the Flanker test after 1 year.

However, it was a different story for those with a poor diet at baseline. Researchers stratified participants into tertiles on the basis of diet quality as measured by the Healthy Eating Index (HEI) scores. Those in the lowest tertile had poorer baseline hippocampal-dependent memory performance but not memory related to the prefrontal cortex.

The flavanol intervention improved performance on the ModRey test, compared with placebo in participants in the low HEI tertile (overall effect: d = 0.086; P = .011) but not among those with a medium or high HEI at baseline.

“We confirmed that the flavanol intervention only benefits people who are relatively deficient at baseline,” said Dr. Small.

The correlation with hippocampal-dependent memory was confirmed in a subset of 1,361 study participants who provided a urine sample. Researchers measured urinary 5-(3′,4′-dihydroxyphenyl)-gamma-valerolactone metabolite (gVLM) concentrations, a validated biomarker of flavanol consumption.

After stratifying these results into tertiles, researchers found performance on the ModRey was significantly improved with the dietary flavanol intervention (overall effect: d = 0.141; P = .006) in the lowest gVLM tertile.
 

Memory restored

When participants in the lowest tertile consumed the supplement, “their flavanol levels went back to normal, and when that happened, their memory was restored,” said Dr. Small.

It appears that there is a sort of ceiling effect to the flavanol benefits. “It seems what you need to do is normalize your flavanol levels; if you go above normal, there was no evidence that your memory keeps on getting better,” said Dr. Small.

The study included only older adults, so it’s unclear what the impact of flavanol supplementation is in younger adults. But cognitive aging “begins its slippery side” in the 40s, said Dr. Small. “If this is truly a nutrient that is taken to prevent that slide from happening, it might be beneficial to start in our 40s.”

He recognized that the effect size is not large but said this is “very dependent” on baseline factors and most study participants had a rather healthy diet. “None of our participants were really highly deficient” in flavanols, he said.

“To see a stronger effect size, we need to do another study where we recruit people who are very low, truly deficient, in flavanols, and then see what happens.”

Showing that flavanols are linked to the hippocampal and not to the prefrontal component of cognitive aging “speaks to the mechanism,” said Dr. Small.

Though the exact mechanism linking flavanols with enhanced memory isn’t clear, there are some clues; for example, research suggests cognitive aging affects the dentate gyrus, a subregion of the hippocampus.

The flavanol supplements were well tolerated. “I can say with close to certainty that this is very safe,” said Dr. Small, adding the flavanols have now been used in numerous studies.

The findings suggest flavanol consumption might be part of future dietary guidelines. “I suspect that once there is sufficient evidence, flavanols will be part of the dietary recommendations for healthy aging,” said Dr. Small.
 

A word of caution

Heather M. Snyder, PhD, vice president of medical and scientific relations, Alzheimer’s Association, said that though science suggests a balanced diet is good for overall brain health, no single food, beverage, ingredient, vitamin, or supplement has yet been proven to prevent dementia, treat or cure Alzheimer’s, or benefit cognitive function or brain health.

Experts agree the best source of vitamins and other nutrients is from whole foods as part of a balanced diet. “We recognize that, for a variety of reasons, this may not always be possible,” said Dr. Snyder.

However, she noted, dietary supplements are not subject to the same rigorous review and regulation process as medications.

“The Alzheimer’s Association strongly encourages individuals to have conversations with their physicians about all medications and dietary supplements they are currently taking or interested in starting.” 

COSMOS is supported by an investigator-initiated grant from Mars Edge, a segment of Mars, company engaged in flavanol research and flavanol-related commercial activities, which included infrastructure support and the donation of study pills and packaging. Small reports receiving an unrestricted research grant from Mars.

A version of this article first appeared on Medscape.com.

Taking a daily flavanol supplement improves hippocampal-dependent memory in older adults who have a relatively poor diet, results of a large new study suggest.

There’s increasing evidence that certain nutrients are important for the aging body and brain, study investigator Scott Small, MD, the Boris and Rose Katz Professor of Neurology, Columbia University Vagelos College of Physicians and Surgeons, New York, told this news organization.

“With this new study, I think we can begin to say flavanols might be the first one that really is a nutrient for the aging brain.”

These findings, said Dr. Small, represent “the beginning of a new era” that will eventually lead to formal recommendations” related to ideal intake of flavanols to reduce cognitive aging.

The findings were published online in the Proceedings of the National Academy of Science.
 

Better cognitive aging

Cognitive aging refers to the decline in cognitive abilities that are not thought to be caused by neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease. Cognitive aging targets two areas of the brain: the hippocampus, which is related to memory function, and the prefrontal cortex, which is related to attention and executive function.

Previous research has linked flavanols, which are found in foods like apples, pears, berries, and cocoa beans, to improved cognitive aging. The evidence shows that consuming these nutrients might be associated with the hippocampal-dependent memory component of cognitive aging.

The new study, known as COcoa Supplement and Multivitamin Outcomes Study-Web (COSMOS-Web), included 3,562 generally healthy men and women, mean age 71 years, who were mostly well-educated and non-Hispanic/non-Latinx White individuals.

Participants were randomly assigned to receive oral flavanol-containing cocoa extract (500 mg of cocoa flavanols, including 80 mg of epicatechin) or a placebo daily.

The primary endpoint was hippocampal-dependent memory at year 1 as assessed with the ModRey, a neuropsychological test designed to measure hippocampal function.

Results showed participants in both groups had a typical learning (practice) effect, with similar improvements (d = 0.025; P = .42).

Researchers used other tests to measure cognition: the Color/Directional Flanker Task, a measure of prefrontal cortex function, and the ModBent, a measure that’s sensitive to dentate gyrus function. The flavanol intervention did not affect ModBent results or performance on the Flanker test after 1 year.

However, it was a different story for those with a poor diet at baseline. Researchers stratified participants into tertiles on the basis of diet quality as measured by the Healthy Eating Index (HEI) scores. Those in the lowest tertile had poorer baseline hippocampal-dependent memory performance but not memory related to the prefrontal cortex.

The flavanol intervention improved performance on the ModRey test, compared with placebo in participants in the low HEI tertile (overall effect: d = 0.086; P = .011) but not among those with a medium or high HEI at baseline.

“We confirmed that the flavanol intervention only benefits people who are relatively deficient at baseline,” said Dr. Small.

The correlation with hippocampal-dependent memory was confirmed in a subset of 1,361 study participants who provided a urine sample. Researchers measured urinary 5-(3′,4′-dihydroxyphenyl)-gamma-valerolactone metabolite (gVLM) concentrations, a validated biomarker of flavanol consumption.

After stratifying these results into tertiles, researchers found performance on the ModRey was significantly improved with the dietary flavanol intervention (overall effect: d = 0.141; P = .006) in the lowest gVLM tertile.
 

Memory restored

When participants in the lowest tertile consumed the supplement, “their flavanol levels went back to normal, and when that happened, their memory was restored,” said Dr. Small.

It appears that there is a sort of ceiling effect to the flavanol benefits. “It seems what you need to do is normalize your flavanol levels; if you go above normal, there was no evidence that your memory keeps on getting better,” said Dr. Small.

The study included only older adults, so it’s unclear what the impact of flavanol supplementation is in younger adults. But cognitive aging “begins its slippery side” in the 40s, said Dr. Small. “If this is truly a nutrient that is taken to prevent that slide from happening, it might be beneficial to start in our 40s.”

He recognized that the effect size is not large but said this is “very dependent” on baseline factors and most study participants had a rather healthy diet. “None of our participants were really highly deficient” in flavanols, he said.

“To see a stronger effect size, we need to do another study where we recruit people who are very low, truly deficient, in flavanols, and then see what happens.”

Showing that flavanols are linked to the hippocampal and not to the prefrontal component of cognitive aging “speaks to the mechanism,” said Dr. Small.

Though the exact mechanism linking flavanols with enhanced memory isn’t clear, there are some clues; for example, research suggests cognitive aging affects the dentate gyrus, a subregion of the hippocampus.

The flavanol supplements were well tolerated. “I can say with close to certainty that this is very safe,” said Dr. Small, adding the flavanols have now been used in numerous studies.

The findings suggest flavanol consumption might be part of future dietary guidelines. “I suspect that once there is sufficient evidence, flavanols will be part of the dietary recommendations for healthy aging,” said Dr. Small.
 

A word of caution

Heather M. Snyder, PhD, vice president of medical and scientific relations, Alzheimer’s Association, said that though science suggests a balanced diet is good for overall brain health, no single food, beverage, ingredient, vitamin, or supplement has yet been proven to prevent dementia, treat or cure Alzheimer’s, or benefit cognitive function or brain health.

Experts agree the best source of vitamins and other nutrients is from whole foods as part of a balanced diet. “We recognize that, for a variety of reasons, this may not always be possible,” said Dr. Snyder.

However, she noted, dietary supplements are not subject to the same rigorous review and regulation process as medications.

“The Alzheimer’s Association strongly encourages individuals to have conversations with their physicians about all medications and dietary supplements they are currently taking or interested in starting.” 

COSMOS is supported by an investigator-initiated grant from Mars Edge, a segment of Mars, company engaged in flavanol research and flavanol-related commercial activities, which included infrastructure support and the donation of study pills and packaging. Small reports receiving an unrestricted research grant from Mars.

A version of this article first appeared on Medscape.com.

Dual orexin receptor antagonists (DORAs), a class of drugs approved to treat insomnia, may also be effective for rapid eye movement sleep behavior disorder (RBD), a study suggests.

About 3 million people in the United States have RBD, which is often a precursor to Parkinson’s disease. People with the disorder act out their dreams by talking, flailing their arms and legs, punching, kicking, and exhibiting other behaviors while asleep.

Researchers used an animal model for the study, which they say is the first to identify a new form of treatment for RBD.

“REM behavior disorder is difficult to treat, and the treatments are mostly limited to clonazepam and melatonin,” which may have side effects, senior investigator Andrew Varga, MD, PhD, associate professor of pulmonary, critical care, and sleep medicine at the Icahn School of Medicine at Mount Sinai, New York, told this news organization. “We’re using something completely different, which raises the possibility this might be something useful for REM behavior disorders.”

The findings, with Mount Sinai assistant professor Korey Kam, PhD, as lead author, were published online in the Journal of Neuroscience.
 

A new model for RBD?

RBD can signal risk for synucleinopathies, a group of neurological conditions such as Parkinson’s disease that involve the formation of clumps of alpha-synuclein protein in the brain.

Prior research on RBD was done in synucleinopathy mouse models. For this study, however, researchers used a tauopathy mouse model to investigate how the abnormal accumulation of tau protein might affect RBD.

Researchers collected data on biophysical properties when the mice were awake and in REM and non-REM sleep. They examined length of sleep, transitions from waking to sleep, and how some factors are related to age.

Nearly a third of the older animals showed behaviors similar to REM sleep behavior disorder in humans, including chewing and limb extension.

But after researchers administered a DORA medication twice during a 24-hour period, they noted that the medication not only helped the animals fall asleep faster and for longer, it also reduced levels of dream enactment that are a hallmark of RBD.
 

The ‘bigger highlight’

Finding RBD behaviors in a tauopathy animal model was surprising, Dr. Varga said, because RBD has been previously linked to synucleinopathies. There was no known correlation between RBD and abnormal accumulation of tau.

Another unexpected finding was the detection of RBD in some of the younger animals, who had not yet shown evidence of tau accumulation.

“It appears to be a biomarker or a signature of something that’s going on that predicts the impending tauopathy at a time where there is very little, or no, tau pathology going on in the brain,” Dr. Varga said.

If RBD is an early predictor of future tau accumulation, the model could guide future prevention and treatment. However, the more important finding is the potential new treatment for the condition.

“The bigger highlight here is less about what’s causing the RBD [than about] what you can do to make it better,” he said.

The next step in the work is to study whether the effect of DORAs on RBD seen in this tauopathy mouse model is evidenced in other animals and whether it is effective in humans with RBD, Dr. Varga said.

The study was funded by the Alzheimer’s Association and Merck Investigator Studies Program. Dr. Kam, Dr. Varga, and coauthors report no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Dual orexin receptor antagonists (DORAs), a class of drugs approved to treat insomnia, may also be effective for rapid eye movement sleep behavior disorder (RBD), a study suggests.

About 3 million people in the United States have RBD, which is often a precursor to Parkinson’s disease. People with the disorder act out their dreams by talking, flailing their arms and legs, punching, kicking, and exhibiting other behaviors while asleep.

Researchers used an animal model for the study, which they say is the first to identify a new form of treatment for RBD.

“REM behavior disorder is difficult to treat, and the treatments are mostly limited to clonazepam and melatonin,” which may have side effects, senior investigator Andrew Varga, MD, PhD, associate professor of pulmonary, critical care, and sleep medicine at the Icahn School of Medicine at Mount Sinai, New York, told this news organization. “We’re using something completely different, which raises the possibility this might be something useful for REM behavior disorders.”

The findings, with Mount Sinai assistant professor Korey Kam, PhD, as lead author, were published online in the Journal of Neuroscience.
 

A new model for RBD?

RBD can signal risk for synucleinopathies, a group of neurological conditions such as Parkinson’s disease that involve the formation of clumps of alpha-synuclein protein in the brain.

Prior research on RBD was done in synucleinopathy mouse models. For this study, however, researchers used a tauopathy mouse model to investigate how the abnormal accumulation of tau protein might affect RBD.

Researchers collected data on biophysical properties when the mice were awake and in REM and non-REM sleep. They examined length of sleep, transitions from waking to sleep, and how some factors are related to age.

Nearly a third of the older animals showed behaviors similar to REM sleep behavior disorder in humans, including chewing and limb extension.

But after researchers administered a DORA medication twice during a 24-hour period, they noted that the medication not only helped the animals fall asleep faster and for longer, it also reduced levels of dream enactment that are a hallmark of RBD.
 

The ‘bigger highlight’

Finding RBD behaviors in a tauopathy animal model was surprising, Dr. Varga said, because RBD has been previously linked to synucleinopathies. There was no known correlation between RBD and abnormal accumulation of tau.

Another unexpected finding was the detection of RBD in some of the younger animals, who had not yet shown evidence of tau accumulation.

“It appears to be a biomarker or a signature of something that’s going on that predicts the impending tauopathy at a time where there is very little, or no, tau pathology going on in the brain,” Dr. Varga said.

If RBD is an early predictor of future tau accumulation, the model could guide future prevention and treatment. However, the more important finding is the potential new treatment for the condition.

“The bigger highlight here is less about what’s causing the RBD [than about] what you can do to make it better,” he said.

The next step in the work is to study whether the effect of DORAs on RBD seen in this tauopathy mouse model is evidenced in other animals and whether it is effective in humans with RBD, Dr. Varga said.

The study was funded by the Alzheimer’s Association and Merck Investigator Studies Program. Dr. Kam, Dr. Varga, and coauthors report no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Dual orexin receptor antagonists (DORAs), a class of drugs approved to treat insomnia, may also be effective for rapid eye movement sleep behavior disorder (RBD), a study suggests.

About 3 million people in the United States have RBD, which is often a precursor to Parkinson’s disease. People with the disorder act out their dreams by talking, flailing their arms and legs, punching, kicking, and exhibiting other behaviors while asleep.

Researchers used an animal model for the study, which they say is the first to identify a new form of treatment for RBD.

“REM behavior disorder is difficult to treat, and the treatments are mostly limited to clonazepam and melatonin,” which may have side effects, senior investigator Andrew Varga, MD, PhD, associate professor of pulmonary, critical care, and sleep medicine at the Icahn School of Medicine at Mount Sinai, New York, told this news organization. “We’re using something completely different, which raises the possibility this might be something useful for REM behavior disorders.”

The findings, with Mount Sinai assistant professor Korey Kam, PhD, as lead author, were published online in the Journal of Neuroscience.
 

A new model for RBD?

RBD can signal risk for synucleinopathies, a group of neurological conditions such as Parkinson’s disease that involve the formation of clumps of alpha-synuclein protein in the brain.

Prior research on RBD was done in synucleinopathy mouse models. For this study, however, researchers used a tauopathy mouse model to investigate how the abnormal accumulation of tau protein might affect RBD.

Researchers collected data on biophysical properties when the mice were awake and in REM and non-REM sleep. They examined length of sleep, transitions from waking to sleep, and how some factors are related to age.

Nearly a third of the older animals showed behaviors similar to REM sleep behavior disorder in humans, including chewing and limb extension.

But after researchers administered a DORA medication twice during a 24-hour period, they noted that the medication not only helped the animals fall asleep faster and for longer, it also reduced levels of dream enactment that are a hallmark of RBD.
 

The ‘bigger highlight’

Finding RBD behaviors in a tauopathy animal model was surprising, Dr. Varga said, because RBD has been previously linked to synucleinopathies. There was no known correlation between RBD and abnormal accumulation of tau.

Another unexpected finding was the detection of RBD in some of the younger animals, who had not yet shown evidence of tau accumulation.

“It appears to be a biomarker or a signature of something that’s going on that predicts the impending tauopathy at a time where there is very little, or no, tau pathology going on in the brain,” Dr. Varga said.

If RBD is an early predictor of future tau accumulation, the model could guide future prevention and treatment. However, the more important finding is the potential new treatment for the condition.

“The bigger highlight here is less about what’s causing the RBD [than about] what you can do to make it better,” he said.

The next step in the work is to study whether the effect of DORAs on RBD seen in this tauopathy mouse model is evidenced in other animals and whether it is effective in humans with RBD, Dr. Varga said.

The study was funded by the Alzheimer’s Association and Merck Investigator Studies Program. Dr. Kam, Dr. Varga, and coauthors report no relevant financial relationships.

A version of this article first appeared on Medscape.com.

From Vanderbilt University School of Medicine, and Vanderbilt University Medical Center, Nashville, TN.

ABSTRACT

Objective: Severe hypoglycemia can alter consciousness and inhibit oral intake, requiring nonoral rescue glucagon administration to raise blood glucose to safe levels. Thus, current guidelines recommend glucagon kit prescriptions for all patients at risk for hypoglycemia, especially patients with type 1 diabetes mellitus (T1DM). At the diabetes outpatient clinic at a tertiary medical center, glucagon prescription rates for T1DM patients remained suboptimal.

Methods: A quality improvement team analyzed patient flow through the endocrinology clinic and identified the lack of a systematic approach to assessing patients for home glucagon prescriptions as a major barrier. The team implemented 2 successive interventions. First, intake staff indicated whether patients lacked an active glucagon prescription on patients’ face sheets. Second, clinical pharmacists reviewed patient prescriptions prior to scheduled visits and pended glucagon orders for patients without active prescriptions. Of note, when a pharmacy pends an order, the pharmacist enters an order into the electronic health record (EHR) but does not sign it. The order is saved for a provider to later access and sign. A statistical process control p-chart tracked monthly prescription rates.

Results: After 7 months, glucagon prescription rates increased from a baseline of 59% to 72% as the new steady state.

Conclusion: This project demonstrates that a series of interventions can improve glucagon prescription rates for patients at risk for hypoglycemia. The project’s success stemmed from combining an EHR-generated report and interdisciplinary staff members’ involvement. Other endocrinology clinics may incorporate this approach to implement similar processes and improve glucagon prescription rates.

Keywords: diabetes, hypoglycemia, glucagon, quality improvement, prescription rates, medical student.

Hypoglycemia limits the management of blood glucose in patients with type 1 diabetes mellitus (T1DM). Severe hypoglycemia, characterized by altered mental status (AMS) or physical status requiring assistance for recovery, can lead to seizure, coma, or death.¹ Hypoglycemia in diabetes often occurs iatrogenically, primarily from insulin therapy: 30% to 40% of patients with T1DM and 10% to 30% of patients with insulin-treated type 2 diabetes mellitus experience severe hypoglycemia in a given year.² One study estimated that nearly 100,000 emergency department visits for hypoglycemia occur in the United States per year, with almost one-third resulting in hospitalization.³

Most patients self-treat mild hypoglycemia with oral intake of carbohydrates. However, since hypoglycemia-induced nausea and AMS can make oral intake more difficult or prevent it entirely, patients require a treatment that family, friends, or coworkers can administer. Rescue glucagon, prescribed as intramuscular injections or intranasal sprays, raises blood glucose to safe levels in 10 to 15 minutes.⁴ Therefore, the American Diabetes Association (ADA) recommends glucagon for all patients at risk for hypoglycemia, especially patients with T1DM.⁵ Despite the ADA’s recommendation, current evidence suggests suboptimal glucagon prescription rates, particularly in patients with T1DM. One study reported that, although 85% of US adults with T1DM had formerly been prescribed glucagon, only 68% of these patients (57.8% overall) had a current prescription.⁴ Few quality improvement efforts have tackled increasing prescription rates. Prior successful studies have attempted to do so via pharmacist-led educational interventions for providers⁶ and via electronic health record (EHR) notifications for patient risk.⁷ The project described here aimed to expand upon prior studies with a quality improvement project to increase glucagon prescription rates among patients at risk for severe hypoglycemia.

Methods

Setting

This study was conducted at a tertiary medical center’s outpatient diabetes clinic; the clinic treats more than 9500 patients with DM annually, more than 2700 of whom have T1DM. In the clinic’s multidisciplinary care model, patients typically follow up every 3 to 6 months, alternating between appointments with fellowship-trained endocrinologists and advanced practice providers (APPs). In addition to having certified diabetes educators, the clinic employs 2 dedicated clinical pharmacists whose duties include assisting providers in prescription management, helping patients identify the most affordable way to obtain their medications, and educating patients regarding their medications.

Patient flow through the clinic involves close coordination with multiple health professionals. Medical assistants (MAs) and licensed practical nurses (LPNs) perform patient intake, document vital signs, and ask screening questions, including dates of patients’ last hemoglobin A1c tests and diabetic eye examination. After intake, the provider (endocrinologist or APP) sees the patient. Once the appointment concludes, patients proceed to the in-house phlebotomy laboratory as indicated and check out with administrative staff to schedule future appointments.

Project Design

From August 2021 through June 2022, teams of medical students at the tertiary center completed this project as part of a 4-week integrated science course on diabetes. Longitudinal supervision by an endocrinology faculty member ensured project continuity. The project employed the Standards for QUality Improvement Reporting Excellence (SQUIRE 2.0) method for reporting.⁸

Stakeholder analysis took place in August 2021. Surveyed clinic providers identified patients with T1DM as the most appropriate population and the outpatient setting as the most appropriate site for intervention. A fishbone diagram illustrated stakeholders to interview, impacts of the clinical flow, information technology to leverage, and potential holes contributing to glucagon prescription conversations falling through.

Interviews with T1DM patients, clinical pharmacists, APPs, MAs/LPNs, and endocrinologists identified barriers to glucagon prescription. The interviews and a process map analysis revealed several themes. While patients and providers understood the importance of glucagon prescription, barriers included glucagon cost, prescription fill burden, and, most pervasively, providers forgetting to ask patients whether they have a glucagon prescription and failing to consider glucagon prescriptions.For this study, each team of medical students worked on the project for 1 month. The revolving teams of medical students met approximately once per week for the duration of the project to review data and implementation phases. At the end of each month, the current team recorded the steps they had taken and information they had analyzed in a shared document, prepared short videos summarizing the work completed, and proposed next steps for the incoming team to support knowledge generation and continuity. Students from outgoing teams were available to contact if incoming teams had any questions.

Interventions

In the first implementation phase, which was carried out over 4 months (December 2021 to March 2022), the patient care manager trained MAs/LPNs to write a glucagon reminder on patients’ face sheets. At check-in, MAs/LPNs screened for a current glucagon prescription. If the patient lacked an up-to-date prescription, the MAs/LPNs hand-wrote a reminder on the patient’s face sheet, which was given to the provider immediately prior to seeing the patient. The clinical staff received an email explaining the intervention beforehand; the daily intake staff email included project reminders.

In the second implementation phase, which started in April 2022, had been carried out for 3 months at the time of this report, and is ongoing, clinical pharmacists have been pending glucagon prescriptions ahead of patients’ appointments. Each week, the pharmacists generate an EHR report that includes all patients with T1DM who have attended at least 1 appointment at the clinic within the past year (regardless of whether each patient possessed an active and up-to-date glucagon prescription) and the date of each patient’s next appointment. For patients who have an appointment in the upcoming week and lack an active glucagon prescription, the pharmacists run a benefits investigation to determine the insurance-preferred glucagon formulation and then pend the appropriate order in the EHR. During the patient’s next appointment, the EHR prompts the provider to review and sign the pharmacist’s pended order (Figure 1).

Measures

This project used a process measure in its analysis: the percentage of patients with T1DM with an active glucagon prescription at the time of their visit to the clinic. The patient population included all patients with a visit diagnosis of T1DM seen by an APP at the clinic during the time scope of the project. The project’s scope was limited to patients seen by APPs to help standardize appointment comparisons, with the intent to expand to the endocrinologist staff if the interventions proved successful with APPs. Patients seen by APPs were also under the care of endocrinologists and seen by them during this time period. The project excluded no patients.

Each individual patient appointment represented a data point: a time at which an APP could prescribe glucagon for a patient with T1DM. Thus, a single patient who had multiple appointments during the study period would generate multiple data points in this study.

Specific Aims and Analysis

For all T1DM patients at the clinic seen by an APP during the study period, the project aimed to increase the percentage with an active and up-to-date glucagon prescription from 58.8% to 70% over a 6-month period, a relatively modest goal appropriate for the time constraints and that would be similar to the changes seen in previous work in the same clinic.⁹

This project analyzed de-identified data using a statistical process control chart (specifically, a p-chart) and standard rules for assessing special-cause signals and thus statistical significance.

Results

Baseline data were collected from October 2020 to September 2021. During this time, APPs saw 1959 T1DM patients, of whom 1152 (58.8%) had an active glucagon prescription at the time of visit and 41.2% lacked a glucagon prescription (Figure 2). During the 4 months of implementation phase 1, analysis of the statistical process control chart identified no special cause signal. Therefore, the project moved to a second intervention with implementation phase 2 in April 2022 (3 months of postintervention data are reported). During the entire intervention, 731 of 1080 (67.7%) patients had a glucagon prescription. The average for the last 2 months, with phase 2 fully implemented, was 72.3%, surpassing the 70% threshold identified as the study target (Figure 3).

Interviews with clinical pharmacists during implementation phase 2 revealed that generating the EHR report and reviewing patients with glucagon prescription indications resulted in variable daily workload increases ranging from approximately 15 to 45 minutes, depending on the number of patients requiring intervention that day. During the first month of implementation phase 2, the EHR report required repeated modification to fulfill the intervention needs. Staffing changes over the intervention period potentially impacted the pattern of glucagon prescribing. This project excluded the 2 months immediately prior to implementation phase 1, from October 2021 to November 2021, because the staff had begun having discussions about this initiative, which may have influenced glucagon prescription rates.

Discussion

This project evaluated 2 interventions over the course of 7 months to determine their efficacy in increasing the frequency of glucagon prescribing for individuals with T1DM in an endocrinology clinic. These interventions were associated with increased prescribing from a baseline of 58.8% to 72.3% over the last 2 months of the project. In the first intervention, performed over 4 months, MAs/LPNs wrote reminders on the appropriate patients’ face sheets, which were given to providers prior to appointments. This project adapted the approach from a successful previous quality improvement study on increasing microalbuminuria screening rates.⁹ However, glucagon prescription rates did not increase significantly, likely because, unlike with microalbuminuria screenings, MAs/LPNs could not pend glucagon prescriptions.

In the second intervention, performed over 3 months, clinical pharmacists pended glucagon prescriptions for identified eligible patients. Glucagon prescribing rates increased considerably, with rates of 72.3% and 72.4% over May and June 2021, respectively, indicating that the intervention successfully established a new higher steady state of proportion of patient visits with active glucagon prescriptions compared with the baseline rate of 58.8%. Given that the baseline data for this clinic were higher than the baseline glucagon prescription rates reported in other studies (49.3%),¹⁰ this intervention could have a major impact in clinics with a baseline more comparable to conditions in that study.

This project demonstrated how a combination of an EHR-generated report and interdisciplinary involvement provides an actionable process to increase glucagon prescription rates for patients with T1DM. Compared to prior studies that implemented passive interventions, such as a note template that relies on provider adherence,⁷ this project emphasizes the benefit of implementing an active systems-level intervention with a pre-pended order.

Regarding prior studies, 1 large, 2-arm study of clinical pharmacists proactively pending orders for appropriate patients showed a 56% glucagon prescription rate in the intervention group, compared with 0.9% in the control group with no pharmacist intervention.¹¹ Our project had a much higher baseline rate: 58.8% prior to intervention vs 0.9% in the nonintervention group for the previous study—likely due to its chosen location’s status as an endocrinology clinic rather than a general health care setting.

A different study that focused on patient education rather than glucagon prescription rates used similar EHR-generated reports to identify appropriate patients and assessed glucagon prescription needs during check-in. Following the educational interventions in that study, patients reporting self-comfort and education with glucagon administration significantly increased from 66.2% to 83.2%, and household member comfort and education with glucagon administration increased from 50.8% to 79.7%. This suggests the possibility of expanding the use of the EHR-generated report to assist not only with increasing glucagon prescription rates, but also with patient education on glucagon use rates and possibly fill rates.⁷ While novel glucagon products may change uptake rates, no new glucagon products arose or were prescribed at this clinic during the course of data collection.

Of note, our project increased the workload on clinical pharmacists. The pharmacists agreed to participate, despite the increased work, after a collaborative discussion about how to best address the need to increase glucagon prescriptions or patient safety; the pharmacy department had initially agreed to collaborate specifically to identify and attend to unmet needs such as this one. Although this project greatly benefited from the expertise and enthusiasm of the clinical pharmacists involved, this tradeoff requires further study to determine sustainability.

Limitations

This project had several limitations. Because of the structure in which this intervention occurred (a year-long course with rotating groups of medical students), there was a necessary component of time constraint, and this project had just 2 implementation phases, for a total of 7 months of postintervention data. The clinic has permanently implemented these changes into its workflow, but subsequent assessments are needed to monitor the effects and assess sustainability.

The specific clinical site chosen for this study benefited from dedicated onsite clinical pharmacists, who are not available at all comparable clinical sites. Due to feasibility, this project only assessed whether the providers prescribed the glucagon, not whether the patients filled the prescriptions and used the glucagon when necessary. Although prescribing rates increased in our study, it cannot be assumed that fill rates increased identically.

Finally, interventions relying on EHR-generated reports carry inherent limitations, such as the risk of misidentification or omission of patients who had indications for a glucagon prescription. The project attempted to mitigate this limitation through random sampling of the EHR report to ensure accuracy. Additionally, EHR-generated reports encourage sustainability and expansion to all clinic patients, with far less required overhead work compared to manually derived data.

Future investigations may focus on expanding this intervention to all patients at risk for hypoglycemia, as well as to study further interventions into prescription fill rates and glucagon use rates.

Conclusion

This project indicates that a proactive, interdisciplinary quality improvement project can increase glucagon prescription rates for patients with T1DM in the outpatient setting. The most effective intervention mobilized clinical pharmacists to identify patients with indications for a glucagon prescription using an integrated EHR-generated report and subsequently pend a glucagon order for the endocrinology provider to sign during the visit. The strengths of the approach included using a multidisciplinary team, minimizing costs to patients by leveraging the pharmacists’ expertise to ensure insurance coverage of specific formulations, and utilizing automatic EHR reporting to streamline patient identification. Ideally, improvements in glucagon prescription rates should ultimately decrease hospitalizations and improve treatment of severe hypoglycemia for at-risk patients.

Corresponding author: Chase D. Hendrickson, MD, MPH; [email protected]

Disclosures: None reported.

From Vanderbilt University School of Medicine, and Vanderbilt University Medical Center, Nashville, TN.

ABSTRACT

Objective: Severe hypoglycemia can alter consciousness and inhibit oral intake, requiring nonoral rescue glucagon administration to raise blood glucose to safe levels. Thus, current guidelines recommend glucagon kit prescriptions for all patients at risk for hypoglycemia, especially patients with type 1 diabetes mellitus (T1DM). At the diabetes outpatient clinic at a tertiary medical center, glucagon prescription rates for T1DM patients remained suboptimal.

Methods: A quality improvement team analyzed patient flow through the endocrinology clinic and identified the lack of a systematic approach to assessing patients for home glucagon prescriptions as a major barrier. The team implemented 2 successive interventions. First, intake staff indicated whether patients lacked an active glucagon prescription on patients’ face sheets. Second, clinical pharmacists reviewed patient prescriptions prior to scheduled visits and pended glucagon orders for patients without active prescriptions. Of note, when a pharmacy pends an order, the pharmacist enters an order into the electronic health record (EHR) but does not sign it. The order is saved for a provider to later access and sign. A statistical process control p-chart tracked monthly prescription rates.

Results: After 7 months, glucagon prescription rates increased from a baseline of 59% to 72% as the new steady state.

Conclusion: This project demonstrates that a series of interventions can improve glucagon prescription rates for patients at risk for hypoglycemia. The project’s success stemmed from combining an EHR-generated report and interdisciplinary staff members’ involvement. Other endocrinology clinics may incorporate this approach to implement similar processes and improve glucagon prescription rates.

Keywords: diabetes, hypoglycemia, glucagon, quality improvement, prescription rates, medical student.

Hypoglycemia limits the management of blood glucose in patients with type 1 diabetes mellitus (T1DM). Severe hypoglycemia, characterized by altered mental status (AMS) or physical status requiring assistance for recovery, can lead to seizure, coma, or death.¹ Hypoglycemia in diabetes often occurs iatrogenically, primarily from insulin therapy: 30% to 40% of patients with T1DM and 10% to 30% of patients with insulin-treated type 2 diabetes mellitus experience severe hypoglycemia in a given year.² One study estimated that nearly 100,000 emergency department visits for hypoglycemia occur in the United States per year, with almost one-third resulting in hospitalization.³

Most patients self-treat mild hypoglycemia with oral intake of carbohydrates. However, since hypoglycemia-induced nausea and AMS can make oral intake more difficult or prevent it entirely, patients require a treatment that family, friends, or coworkers can administer. Rescue glucagon, prescribed as intramuscular injections or intranasal sprays, raises blood glucose to safe levels in 10 to 15 minutes.⁴ Therefore, the American Diabetes Association (ADA) recommends glucagon for all patients at risk for hypoglycemia, especially patients with T1DM.⁵ Despite the ADA’s recommendation, current evidence suggests suboptimal glucagon prescription rates, particularly in patients with T1DM. One study reported that, although 85% of US adults with T1DM had formerly been prescribed glucagon, only 68% of these patients (57.8% overall) had a current prescription.⁴ Few quality improvement efforts have tackled increasing prescription rates. Prior successful studies have attempted to do so via pharmacist-led educational interventions for providers⁶ and via electronic health record (EHR) notifications for patient risk.⁷ The project described here aimed to expand upon prior studies with a quality improvement project to increase glucagon prescription rates among patients at risk for severe hypoglycemia.

Methods

Setting

This study was conducted at a tertiary medical center’s outpatient diabetes clinic; the clinic treats more than 9500 patients with DM annually, more than 2700 of whom have T1DM. In the clinic’s multidisciplinary care model, patients typically follow up every 3 to 6 months, alternating between appointments with fellowship-trained endocrinologists and advanced practice providers (APPs). In addition to having certified diabetes educators, the clinic employs 2 dedicated clinical pharmacists whose duties include assisting providers in prescription management, helping patients identify the most affordable way to obtain their medications, and educating patients regarding their medications.

Patient flow through the clinic involves close coordination with multiple health professionals. Medical assistants (MAs) and licensed practical nurses (LPNs) perform patient intake, document vital signs, and ask screening questions, including dates of patients’ last hemoglobin A1c tests and diabetic eye examination. After intake, the provider (endocrinologist or APP) sees the patient. Once the appointment concludes, patients proceed to the in-house phlebotomy laboratory as indicated and check out with administrative staff to schedule future appointments.

Project Design

From August 2021 through June 2022, teams of medical students at the tertiary center completed this project as part of a 4-week integrated science course on diabetes. Longitudinal supervision by an endocrinology faculty member ensured project continuity. The project employed the Standards for QUality Improvement Reporting Excellence (SQUIRE 2.0) method for reporting.⁸

Stakeholder analysis took place in August 2021. Surveyed clinic providers identified patients with T1DM as the most appropriate population and the outpatient setting as the most appropriate site for intervention. A fishbone diagram illustrated stakeholders to interview, impacts of the clinical flow, information technology to leverage, and potential holes contributing to glucagon prescription conversations falling through.

Interviews with T1DM patients, clinical pharmacists, APPs, MAs/LPNs, and endocrinologists identified barriers to glucagon prescription. The interviews and a process map analysis revealed several themes. While patients and providers understood the importance of glucagon prescription, barriers included glucagon cost, prescription fill burden, and, most pervasively, providers forgetting to ask patients whether they have a glucagon prescription and failing to consider glucagon prescriptions.For this study, each team of medical students worked on the project for 1 month. The revolving teams of medical students met approximately once per week for the duration of the project to review data and implementation phases. At the end of each month, the current team recorded the steps they had taken and information they had analyzed in a shared document, prepared short videos summarizing the work completed, and proposed next steps for the incoming team to support knowledge generation and continuity. Students from outgoing teams were available to contact if incoming teams had any questions.

Interventions

In the first implementation phase, which was carried out over 4 months (December 2021 to March 2022), the patient care manager trained MAs/LPNs to write a glucagon reminder on patients’ face sheets. At check-in, MAs/LPNs screened for a current glucagon prescription. If the patient lacked an up-to-date prescription, the MAs/LPNs hand-wrote a reminder on the patient’s face sheet, which was given to the provider immediately prior to seeing the patient. The clinical staff received an email explaining the intervention beforehand; the daily intake staff email included project reminders.

In the second implementation phase, which started in April 2022, had been carried out for 3 months at the time of this report, and is ongoing, clinical pharmacists have been pending glucagon prescriptions ahead of patients’ appointments. Each week, the pharmacists generate an EHR report that includes all patients with T1DM who have attended at least 1 appointment at the clinic within the past year (regardless of whether each patient possessed an active and up-to-date glucagon prescription) and the date of each patient’s next appointment. For patients who have an appointment in the upcoming week and lack an active glucagon prescription, the pharmacists run a benefits investigation to determine the insurance-preferred glucagon formulation and then pend the appropriate order in the EHR. During the patient’s next appointment, the EHR prompts the provider to review and sign the pharmacist’s pended order (Figure 1).

Measures

This project used a process measure in its analysis: the percentage of patients with T1DM with an active glucagon prescription at the time of their visit to the clinic. The patient population included all patients with a visit diagnosis of T1DM seen by an APP at the clinic during the time scope of the project. The project’s scope was limited to patients seen by APPs to help standardize appointment comparisons, with the intent to expand to the endocrinologist staff if the interventions proved successful with APPs. Patients seen by APPs were also under the care of endocrinologists and seen by them during this time period. The project excluded no patients.

Each individual patient appointment represented a data point: a time at which an APP could prescribe glucagon for a patient with T1DM. Thus, a single patient who had multiple appointments during the study period would generate multiple data points in this study.

Specific Aims and Analysis

For all T1DM patients at the clinic seen by an APP during the study period, the project aimed to increase the percentage with an active and up-to-date glucagon prescription from 58.8% to 70% over a 6-month period, a relatively modest goal appropriate for the time constraints and that would be similar to the changes seen in previous work in the same clinic.⁹

This project analyzed de-identified data using a statistical process control chart (specifically, a p-chart) and standard rules for assessing special-cause signals and thus statistical significance.

Results

Baseline data were collected from October 2020 to September 2021. During this time, APPs saw 1959 T1DM patients, of whom 1152 (58.8%) had an active glucagon prescription at the time of visit and 41.2% lacked a glucagon prescription (Figure 2). During the 4 months of implementation phase 1, analysis of the statistical process control chart identified no special cause signal. Therefore, the project moved to a second intervention with implementation phase 2 in April 2022 (3 months of postintervention data are reported). During the entire intervention, 731 of 1080 (67.7%) patients had a glucagon prescription. The average for the last 2 months, with phase 2 fully implemented, was 72.3%, surpassing the 70% threshold identified as the study target (Figure 3).

Interviews with clinical pharmacists during implementation phase 2 revealed that generating the EHR report and reviewing patients with glucagon prescription indications resulted in variable daily workload increases ranging from approximately 15 to 45 minutes, depending on the number of patients requiring intervention that day. During the first month of implementation phase 2, the EHR report required repeated modification to fulfill the intervention needs. Staffing changes over the intervention period potentially impacted the pattern of glucagon prescribing. This project excluded the 2 months immediately prior to implementation phase 1, from October 2021 to November 2021, because the staff had begun having discussions about this initiative, which may have influenced glucagon prescription rates.

Discussion

This project evaluated 2 interventions over the course of 7 months to determine their efficacy in increasing the frequency of glucagon prescribing for individuals with T1DM in an endocrinology clinic. These interventions were associated with increased prescribing from a baseline of 58.8% to 72.3% over the last 2 months of the project. In the first intervention, performed over 4 months, MAs/LPNs wrote reminders on the appropriate patients’ face sheets, which were given to providers prior to appointments. This project adapted the approach from a successful previous quality improvement study on increasing microalbuminuria screening rates.⁹ However, glucagon prescription rates did not increase significantly, likely because, unlike with microalbuminuria screenings, MAs/LPNs could not pend glucagon prescriptions.

In the second intervention, performed over 3 months, clinical pharmacists pended glucagon prescriptions for identified eligible patients. Glucagon prescribing rates increased considerably, with rates of 72.3% and 72.4% over May and June 2021, respectively, indicating that the intervention successfully established a new higher steady state of proportion of patient visits with active glucagon prescriptions compared with the baseline rate of 58.8%. Given that the baseline data for this clinic were higher than the baseline glucagon prescription rates reported in other studies (49.3%),¹⁰ this intervention could have a major impact in clinics with a baseline more comparable to conditions in that study.

This project demonstrated how a combination of an EHR-generated report and interdisciplinary involvement provides an actionable process to increase glucagon prescription rates for patients with T1DM. Compared to prior studies that implemented passive interventions, such as a note template that relies on provider adherence,⁷ this project emphasizes the benefit of implementing an active systems-level intervention with a pre-pended order.

Regarding prior studies, 1 large, 2-arm study of clinical pharmacists proactively pending orders for appropriate patients showed a 56% glucagon prescription rate in the intervention group, compared with 0.9% in the control group with no pharmacist intervention.¹¹ Our project had a much higher baseline rate: 58.8% prior to intervention vs 0.9% in the nonintervention group for the previous study—likely due to its chosen location’s status as an endocrinology clinic rather than a general health care setting.

A different study that focused on patient education rather than glucagon prescription rates used similar EHR-generated reports to identify appropriate patients and assessed glucagon prescription needs during check-in. Following the educational interventions in that study, patients reporting self-comfort and education with glucagon administration significantly increased from 66.2% to 83.2%, and household member comfort and education with glucagon administration increased from 50.8% to 79.7%. This suggests the possibility of expanding the use of the EHR-generated report to assist not only with increasing glucagon prescription rates, but also with patient education on glucagon use rates and possibly fill rates.⁷ While novel glucagon products may change uptake rates, no new glucagon products arose or were prescribed at this clinic during the course of data collection.

Of note, our project increased the workload on clinical pharmacists. The pharmacists agreed to participate, despite the increased work, after a collaborative discussion about how to best address the need to increase glucagon prescriptions or patient safety; the pharmacy department had initially agreed to collaborate specifically to identify and attend to unmet needs such as this one. Although this project greatly benefited from the expertise and enthusiasm of the clinical pharmacists involved, this tradeoff requires further study to determine sustainability.

Limitations

This project had several limitations. Because of the structure in which this intervention occurred (a year-long course with rotating groups of medical students), there was a necessary component of time constraint, and this project had just 2 implementation phases, for a total of 7 months of postintervention data. The clinic has permanently implemented these changes into its workflow, but subsequent assessments are needed to monitor the effects and assess sustainability.

The specific clinical site chosen for this study benefited from dedicated onsite clinical pharmacists, who are not available at all comparable clinical sites. Due to feasibility, this project only assessed whether the providers prescribed the glucagon, not whether the patients filled the prescriptions and used the glucagon when necessary. Although prescribing rates increased in our study, it cannot be assumed that fill rates increased identically.

Finally, interventions relying on EHR-generated reports carry inherent limitations, such as the risk of misidentification or omission of patients who had indications for a glucagon prescription. The project attempted to mitigate this limitation through random sampling of the EHR report to ensure accuracy. Additionally, EHR-generated reports encourage sustainability and expansion to all clinic patients, with far less required overhead work compared to manually derived data.

Future investigations may focus on expanding this intervention to all patients at risk for hypoglycemia, as well as to study further interventions into prescription fill rates and glucagon use rates.

Conclusion

This project indicates that a proactive, interdisciplinary quality improvement project can increase glucagon prescription rates for patients with T1DM in the outpatient setting. The most effective intervention mobilized clinical pharmacists to identify patients with indications for a glucagon prescription using an integrated EHR-generated report and subsequently pend a glucagon order for the endocrinology provider to sign during the visit. The strengths of the approach included using a multidisciplinary team, minimizing costs to patients by leveraging the pharmacists’ expertise to ensure insurance coverage of specific formulations, and utilizing automatic EHR reporting to streamline patient identification. Ideally, improvements in glucagon prescription rates should ultimately decrease hospitalizations and improve treatment of severe hypoglycemia for at-risk patients.

Corresponding author: Chase D. Hendrickson, MD, MPH; [email protected]

Disclosures: None reported.

From Vanderbilt University School of Medicine, and Vanderbilt University Medical Center, Nashville, TN.

ABSTRACT

Objective: Severe hypoglycemia can alter consciousness and inhibit oral intake, requiring nonoral rescue glucagon administration to raise blood glucose to safe levels. Thus, current guidelines recommend glucagon kit prescriptions for all patients at risk for hypoglycemia, especially patients with type 1 diabetes mellitus (T1DM). At the diabetes outpatient clinic at a tertiary medical center, glucagon prescription rates for T1DM patients remained suboptimal.

Methods: A quality improvement team analyzed patient flow through the endocrinology clinic and identified the lack of a systematic approach to assessing patients for home glucagon prescriptions as a major barrier. The team implemented 2 successive interventions. First, intake staff indicated whether patients lacked an active glucagon prescription on patients’ face sheets. Second, clinical pharmacists reviewed patient prescriptions prior to scheduled visits and pended glucagon orders for patients without active prescriptions. Of note, when a pharmacy pends an order, the pharmacist enters an order into the electronic health record (EHR) but does not sign it. The order is saved for a provider to later access and sign. A statistical process control p-chart tracked monthly prescription rates.

Results: After 7 months, glucagon prescription rates increased from a baseline of 59% to 72% as the new steady state.

Conclusion: This project demonstrates that a series of interventions can improve glucagon prescription rates for patients at risk for hypoglycemia. The project’s success stemmed from combining an EHR-generated report and interdisciplinary staff members’ involvement. Other endocrinology clinics may incorporate this approach to implement similar processes and improve glucagon prescription rates.

Keywords: diabetes, hypoglycemia, glucagon, quality improvement, prescription rates, medical student.

Hypoglycemia limits the management of blood glucose in patients with type 1 diabetes mellitus (T1DM). Severe hypoglycemia, characterized by altered mental status (AMS) or physical status requiring assistance for recovery, can lead to seizure, coma, or death.¹ Hypoglycemia in diabetes often occurs iatrogenically, primarily from insulin therapy: 30% to 40% of patients with T1DM and 10% to 30% of patients with insulin-treated type 2 diabetes mellitus experience severe hypoglycemia in a given year.² One study estimated that nearly 100,000 emergency department visits for hypoglycemia occur in the United States per year, with almost one-third resulting in hospitalization.³

Most patients self-treat mild hypoglycemia with oral intake of carbohydrates. However, since hypoglycemia-induced nausea and AMS can make oral intake more difficult or prevent it entirely, patients require a treatment that family, friends, or coworkers can administer. Rescue glucagon, prescribed as intramuscular injections or intranasal sprays, raises blood glucose to safe levels in 10 to 15 minutes.⁴ Therefore, the American Diabetes Association (ADA) recommends glucagon for all patients at risk for hypoglycemia, especially patients with T1DM.⁵ Despite the ADA’s recommendation, current evidence suggests suboptimal glucagon prescription rates, particularly in patients with T1DM. One study reported that, although 85% of US adults with T1DM had formerly been prescribed glucagon, only 68% of these patients (57.8% overall) had a current prescription.⁴ Few quality improvement efforts have tackled increasing prescription rates. Prior successful studies have attempted to do so via pharmacist-led educational interventions for providers⁶ and via electronic health record (EHR) notifications for patient risk.⁷ The project described here aimed to expand upon prior studies with a quality improvement project to increase glucagon prescription rates among patients at risk for severe hypoglycemia.

Methods

Setting

This study was conducted at a tertiary medical center’s outpatient diabetes clinic; the clinic treats more than 9500 patients with DM annually, more than 2700 of whom have T1DM. In the clinic’s multidisciplinary care model, patients typically follow up every 3 to 6 months, alternating between appointments with fellowship-trained endocrinologists and advanced practice providers (APPs). In addition to having certified diabetes educators, the clinic employs 2 dedicated clinical pharmacists whose duties include assisting providers in prescription management, helping patients identify the most affordable way to obtain their medications, and educating patients regarding their medications.

Patient flow through the clinic involves close coordination with multiple health professionals. Medical assistants (MAs) and licensed practical nurses (LPNs) perform patient intake, document vital signs, and ask screening questions, including dates of patients’ last hemoglobin A1c tests and diabetic eye examination. After intake, the provider (endocrinologist or APP) sees the patient. Once the appointment concludes, patients proceed to the in-house phlebotomy laboratory as indicated and check out with administrative staff to schedule future appointments.

Project Design

From August 2021 through June 2022, teams of medical students at the tertiary center completed this project as part of a 4-week integrated science course on diabetes. Longitudinal supervision by an endocrinology faculty member ensured project continuity. The project employed the Standards for QUality Improvement Reporting Excellence (SQUIRE 2.0) method for reporting.⁸

Stakeholder analysis took place in August 2021. Surveyed clinic providers identified patients with T1DM as the most appropriate population and the outpatient setting as the most appropriate site for intervention. A fishbone diagram illustrated stakeholders to interview, impacts of the clinical flow, information technology to leverage, and potential holes contributing to glucagon prescription conversations falling through.

Interviews with T1DM patients, clinical pharmacists, APPs, MAs/LPNs, and endocrinologists identified barriers to glucagon prescription. The interviews and a process map analysis revealed several themes. While patients and providers understood the importance of glucagon prescription, barriers included glucagon cost, prescription fill burden, and, most pervasively, providers forgetting to ask patients whether they have a glucagon prescription and failing to consider glucagon prescriptions.For this study, each team of medical students worked on the project for 1 month. The revolving teams of medical students met approximately once per week for the duration of the project to review data and implementation phases. At the end of each month, the current team recorded the steps they had taken and information they had analyzed in a shared document, prepared short videos summarizing the work completed, and proposed next steps for the incoming team to support knowledge generation and continuity. Students from outgoing teams were available to contact if incoming teams had any questions.

Interventions

In the first implementation phase, which was carried out over 4 months (December 2021 to March 2022), the patient care manager trained MAs/LPNs to write a glucagon reminder on patients’ face sheets. At check-in, MAs/LPNs screened for a current glucagon prescription. If the patient lacked an up-to-date prescription, the MAs/LPNs hand-wrote a reminder on the patient’s face sheet, which was given to the provider immediately prior to seeing the patient. The clinical staff received an email explaining the intervention beforehand; the daily intake staff email included project reminders.

In the second implementation phase, which started in April 2022, had been carried out for 3 months at the time of this report, and is ongoing, clinical pharmacists have been pending glucagon prescriptions ahead of patients’ appointments. Each week, the pharmacists generate an EHR report that includes all patients with T1DM who have attended at least 1 appointment at the clinic within the past year (regardless of whether each patient possessed an active and up-to-date glucagon prescription) and the date of each patient’s next appointment. For patients who have an appointment in the upcoming week and lack an active glucagon prescription, the pharmacists run a benefits investigation to determine the insurance-preferred glucagon formulation and then pend the appropriate order in the EHR. During the patient’s next appointment, the EHR prompts the provider to review and sign the pharmacist’s pended order (Figure 1).

Measures

This project used a process measure in its analysis: the percentage of patients with T1DM with an active glucagon prescription at the time of their visit to the clinic. The patient population included all patients with a visit diagnosis of T1DM seen by an APP at the clinic during the time scope of the project. The project’s scope was limited to patients seen by APPs to help standardize appointment comparisons, with the intent to expand to the endocrinologist staff if the interventions proved successful with APPs. Patients seen by APPs were also under the care of endocrinologists and seen by them during this time period. The project excluded no patients.

Each individual patient appointment represented a data point: a time at which an APP could prescribe glucagon for a patient with T1DM. Thus, a single patient who had multiple appointments during the study period would generate multiple data points in this study.

Specific Aims and Analysis

For all T1DM patients at the clinic seen by an APP during the study period, the project aimed to increase the percentage with an active and up-to-date glucagon prescription from 58.8% to 70% over a 6-month period, a relatively modest goal appropriate for the time constraints and that would be similar to the changes seen in previous work in the same clinic.⁹

This project analyzed de-identified data using a statistical process control chart (specifically, a p-chart) and standard rules for assessing special-cause signals and thus statistical significance.

Results

Baseline data were collected from October 2020 to September 2021. During this time, APPs saw 1959 T1DM patients, of whom 1152 (58.8%) had an active glucagon prescription at the time of visit and 41.2% lacked a glucagon prescription (Figure 2). During the 4 months of implementation phase 1, analysis of the statistical process control chart identified no special cause signal. Therefore, the project moved to a second intervention with implementation phase 2 in April 2022 (3 months of postintervention data are reported). During the entire intervention, 731 of 1080 (67.7%) patients had a glucagon prescription. The average for the last 2 months, with phase 2 fully implemented, was 72.3%, surpassing the 70% threshold identified as the study target (Figure 3).

Interviews with clinical pharmacists during implementation phase 2 revealed that generating the EHR report and reviewing patients with glucagon prescription indications resulted in variable daily workload increases ranging from approximately 15 to 45 minutes, depending on the number of patients requiring intervention that day. During the first month of implementation phase 2, the EHR report required repeated modification to fulfill the intervention needs. Staffing changes over the intervention period potentially impacted the pattern of glucagon prescribing. This project excluded the 2 months immediately prior to implementation phase 1, from October 2021 to November 2021, because the staff had begun having discussions about this initiative, which may have influenced glucagon prescription rates.

Discussion

This project evaluated 2 interventions over the course of 7 months to determine their efficacy in increasing the frequency of glucagon prescribing for individuals with T1DM in an endocrinology clinic. These interventions were associated with increased prescribing from a baseline of 58.8% to 72.3% over the last 2 months of the project. In the first intervention, performed over 4 months, MAs/LPNs wrote reminders on the appropriate patients’ face sheets, which were given to providers prior to appointments. This project adapted the approach from a successful previous quality improvement study on increasing microalbuminuria screening rates.⁹ However, glucagon prescription rates did not increase significantly, likely because, unlike with microalbuminuria screenings, MAs/LPNs could not pend glucagon prescriptions.

In the second intervention, performed over 3 months, clinical pharmacists pended glucagon prescriptions for identified eligible patients. Glucagon prescribing rates increased considerably, with rates of 72.3% and 72.4% over May and June 2021, respectively, indicating that the intervention successfully established a new higher steady state of proportion of patient visits with active glucagon prescriptions compared with the baseline rate of 58.8%. Given that the baseline data for this clinic were higher than the baseline glucagon prescription rates reported in other studies (49.3%),¹⁰ this intervention could have a major impact in clinics with a baseline more comparable to conditions in that study.

This project demonstrated how a combination of an EHR-generated report and interdisciplinary involvement provides an actionable process to increase glucagon prescription rates for patients with T1DM. Compared to prior studies that implemented passive interventions, such as a note template that relies on provider adherence,⁷ this project emphasizes the benefit of implementing an active systems-level intervention with a pre-pended order.

Regarding prior studies, 1 large, 2-arm study of clinical pharmacists proactively pending orders for appropriate patients showed a 56% glucagon prescription rate in the intervention group, compared with 0.9% in the control group with no pharmacist intervention.¹¹ Our project had a much higher baseline rate: 58.8% prior to intervention vs 0.9% in the nonintervention group for the previous study—likely due to its chosen location’s status as an endocrinology clinic rather than a general health care setting.

A different study that focused on patient education rather than glucagon prescription rates used similar EHR-generated reports to identify appropriate patients and assessed glucagon prescription needs during check-in. Following the educational interventions in that study, patients reporting self-comfort and education with glucagon administration significantly increased from 66.2% to 83.2%, and household member comfort and education with glucagon administration increased from 50.8% to 79.7%. This suggests the possibility of expanding the use of the EHR-generated report to assist not only with increasing glucagon prescription rates, but also with patient education on glucagon use rates and possibly fill rates.⁷ While novel glucagon products may change uptake rates, no new glucagon products arose or were prescribed at this clinic during the course of data collection.

Of note, our project increased the workload on clinical pharmacists. The pharmacists agreed to participate, despite the increased work, after a collaborative discussion about how to best address the need to increase glucagon prescriptions or patient safety; the pharmacy department had initially agreed to collaborate specifically to identify and attend to unmet needs such as this one. Although this project greatly benefited from the expertise and enthusiasm of the clinical pharmacists involved, this tradeoff requires further study to determine sustainability.

Limitations

This project had several limitations. Because of the structure in which this intervention occurred (a year-long course with rotating groups of medical students), there was a necessary component of time constraint, and this project had just 2 implementation phases, for a total of 7 months of postintervention data. The clinic has permanently implemented these changes into its workflow, but subsequent assessments are needed to monitor the effects and assess sustainability.

The specific clinical site chosen for this study benefited from dedicated onsite clinical pharmacists, who are not available at all comparable clinical sites. Due to feasibility, this project only assessed whether the providers prescribed the glucagon, not whether the patients filled the prescriptions and used the glucagon when necessary. Although prescribing rates increased in our study, it cannot be assumed that fill rates increased identically.

Finally, interventions relying on EHR-generated reports carry inherent limitations, such as the risk of misidentification or omission of patients who had indications for a glucagon prescription. The project attempted to mitigate this limitation through random sampling of the EHR report to ensure accuracy. Additionally, EHR-generated reports encourage sustainability and expansion to all clinic patients, with far less required overhead work compared to manually derived data.

Future investigations may focus on expanding this intervention to all patients at risk for hypoglycemia, as well as to study further interventions into prescription fill rates and glucagon use rates.

Conclusion

This project indicates that a proactive, interdisciplinary quality improvement project can increase glucagon prescription rates for patients with T1DM in the outpatient setting. The most effective intervention mobilized clinical pharmacists to identify patients with indications for a glucagon prescription using an integrated EHR-generated report and subsequently pend a glucagon order for the endocrinology provider to sign during the visit. The strengths of the approach included using a multidisciplinary team, minimizing costs to patients by leveraging the pharmacists’ expertise to ensure insurance coverage of specific formulations, and utilizing automatic EHR reporting to streamline patient identification. Ideally, improvements in glucagon prescription rates should ultimately decrease hospitalizations and improve treatment of severe hypoglycemia for at-risk patients.

Corresponding author: Chase D. Hendrickson, MD, MPH; [email protected]

Disclosures: None reported.

Study 1 Overview (Park et al)

Objective: To compare rates of adverse events and 30-day readmission among patients with dementia who undergo percutaneous coronary intervention (PCI) with those without dementia.

Design: This cohort study used a national database of hospital readmissions developed by the Agency for Healthcare Research and Quality.

Setting and participants: Data from State Inpatient Databases were used to derive this national readmissions database representing 80% of hospitals from 28 states that contribute data. The study included all individuals aged 18 years and older who were identified to have had a PCI procedure in the years 2017 and 2018. International Classification of Diseases, Tenth Revision (ICD-10) codes were used to identify PCI procedures, including drug-eluting stent placement, bare-metal stent placement, and balloon angioplasty, performed in patients who presented with myocardial infarction and unstable angina and those with stable ischemic heart disease. Patients were stratified into those with or without dementia, also defined using ICD-10 codes. A total of 755,406 index hospitalizations were included; 2.3% of the patients had dementia.

Main outcome measures: The primary study outcome was 30-day all-cause readmission, with the cause classified as cardiovascular or noncardiovascular. Secondary outcome measures examined were delirium, in-hospital mortality, cardiac arrest, blood transfusion, acute kidney injury, fall in hospital, length of hospital stay, and other adverse outcomes. Location at discharge was also examined. Other covariates included in the analysis were age, sex, comorbidities, hospital characteristics, primary payer, and median income. For analysis, a propensity score matching algorithm was applied to match patients with and without dementia. Kaplan-Meier curves were used to examine 30-day readmission rates, and a Cox proportional hazards model was used to calculate hazard ratios (HR) for those with and without dementia. For secondary outcomes, logistic regression models were used to calculate odds ratios (OR) of outcomes between those with and without dementia.

Main results: The average age of those with dementia was 78.8 years vs 64.9 years in those without dementia. Women made up 42.8% of those with dementia and 31.3% of those without dementia. Those with dementia also had higher rates of comorbidities, such as heart failure, renal failure, and depression. After propensity score matching, 17,309 and 17,187 patients with and without dementia, respectively, were included. Covariates were balanced between the 2 groups after matching. For the primary outcome, patients with dementia were more likely to be readmitted at 30 days (HR, 1.11; 95% CI, 1.05-1.18; P < .01) when compared to those without dementia. For other adverse outcomes, delirium was significantly more likely to occur for those with dementia (OR, 4.37; 95% CI, 3.69-5.16; P < .01). Patients with dementia were also more likely to die in hospital (OR, 1.15; 95% CI, 1.01-1.30; P = .03), have cardiac arrest (OR, 1.19; 95% CI, 1.01-1.39; P = .04), receive a blood transfusion (OR, 1.17; 95% CI, 1.00-1.36; P = .05), experience acute kidney injury (OR, 1.30; 95% CI, 1.21-1.39; P < .01), and fall in hospital (OR, 2.51; 95% CI, 2.06-3.07; P < .01). Hospital length of stay was higher for those with dementia, with a mean difference of 1.43 days. For discharge location, patients with dementia were more likely to be sent to a skilled nursing facility (30.1% vs 12.2%) and less likely to be discharged home.

Conclusion: Patients with dementia are more likely to experience adverse events, including delirium, mortality, kidney injury, and falls after PCI, and are more likely to be readmitted to the hospital in 30 days compared to those without dementia.

Study 2 Overview (Gilmore-Bykovskyi et al)

Objective: To examine the association between race and 30-day readmissions in Black and non-Hispanic White Medicare beneficiaries with dementia.

Design: This was a retrospective cohort study that used 100% Medicare fee-for service claims data from all hospitalizations between January 1, 2014, and November 30, 2014, for all enrollees with a dementia diagnosis. The claims data were linked to the patient, hospital stay, and hospital factors. Patients with dementia were identified using a validated algorithm that requires an inpatient, skilled nursing facility, home health, or Part B institutional or noninstitutional claim with a qualifying diagnostic code during a 3-year period. Persons enrolled in a health maintenance organization plan were excluded.

Main outcome measures: The primary outcome examined in this study was 30-day all-cause readmission. Self-reported race and ethnic identity was a baseline covariate. Persons who self-reported Black or non-Hispanic White race were included in the study; other categories of race and ethnicity were excluded because of prior evidence suggesting low accuracy of these categories in Medicare claims data. Other covariates included neighborhood disadvantage, measured using the Area Deprivation Index (ADI), and rurality; hospital-level and hospital stay–level characteristics such as for-profit status and number of annual discharges; and individual demographic characteristics and comorbidities. The ADI is constructed using variables of poverty, education, housing, and employment and is represented as a percentile ranking of level of disadvantage. Unadjusted and adjusted analyses of 30-day hospital readmission were conducted. Models using various levels of adjustment were constructed to examine the contributions of the identified covariates to the estimated association between 30-day readmission and race.

Main results: A total of 1,523,142 index hospital stays among 945,481 beneficiaries were included; 215,815 episodes were among Black beneficiaries and 1,307,327 episodes were among non-Hispanic White beneficiaries. Mean age was 81.5 years, and approximately 61% of beneficiaries were female. Black beneficiaries were younger but had higher rates of dual Medicare/Medicaid eligibility and disability; they were also more likely to reside in disadvantaged neighborhoods. Black beneficiaries had a 30-day readmission rate of 24.1% compared with 18.5% in non-Hispanic White beneficiaries (unadjusted OR, 1.37; 95% CI, 1.35-1.39). The differences in outcomes persisted after adjusting for geographic factors, social factors, hospital characteristics, hospital stay factors, demographics, and comorbidities, suggesting that unmeasured underlying racial disparities not included in this model accounted for the differences. The effects of certain variables, such as neighborhood, differed by race; for example, the protective effect of living in a less disadvantaged neighborhood was observed among White beneficiaries but not Black beneficiaries.

Conclusion: Racial and geographic disparities in 30-day readmission rates were observed among Medicare beneficiaries with dementia. Protective effects associated with neighborhood advantage may confer different levels of benefit for people of different race.

Commentary

Adults living with dementia are at higher risk of adverse outcomes across settings. In the first study, by Park et al, among adults who underwent a cardiac procedure (PCI), those with dementia were more likely to experience adverse events compared to those without dementia. These outcomes include increased rates of 30-day readmissions, delirium, cardiac arrest, and falls. These findings are consistent with other studies that found a similar association among patients who underwent other cardiac procedures, such as transcatheter aortic valve replacement.¹ Because dementia is a strong predisposing factor for delirium, it is not surprising that delirium is observed across patients who underwent different procedures or hospitalization episodes.² Because of the potential hazards for inpatients with dementia, hospitals have developed risk-reduction programs, such as those that promote recognition of dementia, and management strategies that reduce the risk of delirium.³ Delirium prevention may also impact other adverse outcomes, such as falls, discharge to institutional care, and readmissions.

Racial disparities in care outcomes have been documented across settings, including hospital⁴ and hospice care settings.⁵ In study 2, by Gilmore-Bykovskyi et al, the findings of higher rates of hospital readmission among Black patients when compared to non-Hispanic White patients were not surprising. The central finding of this study is that even when accounting for various levels of factors, including hospital-level, hospital stay–level, individual (demographics, comorbidities), and neighborhood characteristics (disadvantage), the observed disparity diminished but persisted, suggesting that while these various levels of factors contributed to the observed disparity, other unmeasured factors also contributed. Another key finding is that the effect of the various factors examined in this study may affect different subgroups in different ways, suggesting underlying factors, and thus potential solutions to reduce disparities in care outcomes, could differ among subgroups.

Applications for Clinical Practice and System Implementation

These 2 studies add to the literature on factors that can affect 30-day hospital readmission rates in patients with dementia. These data could allow for more robust discussions of what to anticipate when adults with dementia undergo specific procedures, and also further build the case that improvements in care, such as delirium prevention programs, could offer benefits. The observation about racial and ethnic disparities in care outcomes among patients with dementia highlights the continued need to better understand the drivers of these disparities so that hospital systems and policy makers can consider and test possible solutions. Future studies should further disentangle the relationships among the various levels of factors and observed disparities in outcomes, especially for this vulnerable population of adults living with dementia.

Practice Points

• Clinicians should be aware of the additional risks for poor outcomes that dementia confers.
• Awareness of this increased risk will inform discussions of risks and benefits for older adults considered for procedures.

–William W. Hung, MD, MPH

Study 1 Overview (Park et al)

Objective: To compare rates of adverse events and 30-day readmission among patients with dementia who undergo percutaneous coronary intervention (PCI) with those without dementia.

Design: This cohort study used a national database of hospital readmissions developed by the Agency for Healthcare Research and Quality.

Setting and participants: Data from State Inpatient Databases were used to derive this national readmissions database representing 80% of hospitals from 28 states that contribute data. The study included all individuals aged 18 years and older who were identified to have had a PCI procedure in the years 2017 and 2018. International Classification of Diseases, Tenth Revision (ICD-10) codes were used to identify PCI procedures, including drug-eluting stent placement, bare-metal stent placement, and balloon angioplasty, performed in patients who presented with myocardial infarction and unstable angina and those with stable ischemic heart disease. Patients were stratified into those with or without dementia, also defined using ICD-10 codes. A total of 755,406 index hospitalizations were included; 2.3% of the patients had dementia.

Main outcome measures: The primary study outcome was 30-day all-cause readmission, with the cause classified as cardiovascular or noncardiovascular. Secondary outcome measures examined were delirium, in-hospital mortality, cardiac arrest, blood transfusion, acute kidney injury, fall in hospital, length of hospital stay, and other adverse outcomes. Location at discharge was also examined. Other covariates included in the analysis were age, sex, comorbidities, hospital characteristics, primary payer, and median income. For analysis, a propensity score matching algorithm was applied to match patients with and without dementia. Kaplan-Meier curves were used to examine 30-day readmission rates, and a Cox proportional hazards model was used to calculate hazard ratios (HR) for those with and without dementia. For secondary outcomes, logistic regression models were used to calculate odds ratios (OR) of outcomes between those with and without dementia.

Main results: The average age of those with dementia was 78.8 years vs 64.9 years in those without dementia. Women made up 42.8% of those with dementia and 31.3% of those without dementia. Those with dementia also had higher rates of comorbidities, such as heart failure, renal failure, and depression. After propensity score matching, 17,309 and 17,187 patients with and without dementia, respectively, were included. Covariates were balanced between the 2 groups after matching. For the primary outcome, patients with dementia were more likely to be readmitted at 30 days (HR, 1.11; 95% CI, 1.05-1.18; P < .01) when compared to those without dementia. For other adverse outcomes, delirium was significantly more likely to occur for those with dementia (OR, 4.37; 95% CI, 3.69-5.16; P < .01). Patients with dementia were also more likely to die in hospital (OR, 1.15; 95% CI, 1.01-1.30; P = .03), have cardiac arrest (OR, 1.19; 95% CI, 1.01-1.39; P = .04), receive a blood transfusion (OR, 1.17; 95% CI, 1.00-1.36; P = .05), experience acute kidney injury (OR, 1.30; 95% CI, 1.21-1.39; P < .01), and fall in hospital (OR, 2.51; 95% CI, 2.06-3.07; P < .01). Hospital length of stay was higher for those with dementia, with a mean difference of 1.43 days. For discharge location, patients with dementia were more likely to be sent to a skilled nursing facility (30.1% vs 12.2%) and less likely to be discharged home.

Conclusion: Patients with dementia are more likely to experience adverse events, including delirium, mortality, kidney injury, and falls after PCI, and are more likely to be readmitted to the hospital in 30 days compared to those without dementia.

Study 2 Overview (Gilmore-Bykovskyi et al)

Objective: To examine the association between race and 30-day readmissions in Black and non-Hispanic White Medicare beneficiaries with dementia.

Design: This was a retrospective cohort study that used 100% Medicare fee-for service claims data from all hospitalizations between January 1, 2014, and November 30, 2014, for all enrollees with a dementia diagnosis. The claims data were linked to the patient, hospital stay, and hospital factors. Patients with dementia were identified using a validated algorithm that requires an inpatient, skilled nursing facility, home health, or Part B institutional or noninstitutional claim with a qualifying diagnostic code during a 3-year period. Persons enrolled in a health maintenance organization plan were excluded.

Main outcome measures: The primary outcome examined in this study was 30-day all-cause readmission. Self-reported race and ethnic identity was a baseline covariate. Persons who self-reported Black or non-Hispanic White race were included in the study; other categories of race and ethnicity were excluded because of prior evidence suggesting low accuracy of these categories in Medicare claims data. Other covariates included neighborhood disadvantage, measured using the Area Deprivation Index (ADI), and rurality; hospital-level and hospital stay–level characteristics such as for-profit status and number of annual discharges; and individual demographic characteristics and comorbidities. The ADI is constructed using variables of poverty, education, housing, and employment and is represented as a percentile ranking of level of disadvantage. Unadjusted and adjusted analyses of 30-day hospital readmission were conducted. Models using various levels of adjustment were constructed to examine the contributions of the identified covariates to the estimated association between 30-day readmission and race.

Main results: A total of 1,523,142 index hospital stays among 945,481 beneficiaries were included; 215,815 episodes were among Black beneficiaries and 1,307,327 episodes were among non-Hispanic White beneficiaries. Mean age was 81.5 years, and approximately 61% of beneficiaries were female. Black beneficiaries were younger but had higher rates of dual Medicare/Medicaid eligibility and disability; they were also more likely to reside in disadvantaged neighborhoods. Black beneficiaries had a 30-day readmission rate of 24.1% compared with 18.5% in non-Hispanic White beneficiaries (unadjusted OR, 1.37; 95% CI, 1.35-1.39). The differences in outcomes persisted after adjusting for geographic factors, social factors, hospital characteristics, hospital stay factors, demographics, and comorbidities, suggesting that unmeasured underlying racial disparities not included in this model accounted for the differences. The effects of certain variables, such as neighborhood, differed by race; for example, the protective effect of living in a less disadvantaged neighborhood was observed among White beneficiaries but not Black beneficiaries.

Conclusion: Racial and geographic disparities in 30-day readmission rates were observed among Medicare beneficiaries with dementia. Protective effects associated with neighborhood advantage may confer different levels of benefit for people of different race.

Commentary

Adults living with dementia are at higher risk of adverse outcomes across settings. In the first study, by Park et al, among adults who underwent a cardiac procedure (PCI), those with dementia were more likely to experience adverse events compared to those without dementia. These outcomes include increased rates of 30-day readmissions, delirium, cardiac arrest, and falls. These findings are consistent with other studies that found a similar association among patients who underwent other cardiac procedures, such as transcatheter aortic valve replacement.¹ Because dementia is a strong predisposing factor for delirium, it is not surprising that delirium is observed across patients who underwent different procedures or hospitalization episodes.² Because of the potential hazards for inpatients with dementia, hospitals have developed risk-reduction programs, such as those that promote recognition of dementia, and management strategies that reduce the risk of delirium.³ Delirium prevention may also impact other adverse outcomes, such as falls, discharge to institutional care, and readmissions.

Racial disparities in care outcomes have been documented across settings, including hospital⁴ and hospice care settings.⁵ In study 2, by Gilmore-Bykovskyi et al, the findings of higher rates of hospital readmission among Black patients when compared to non-Hispanic White patients were not surprising. The central finding of this study is that even when accounting for various levels of factors, including hospital-level, hospital stay–level, individual (demographics, comorbidities), and neighborhood characteristics (disadvantage), the observed disparity diminished but persisted, suggesting that while these various levels of factors contributed to the observed disparity, other unmeasured factors also contributed. Another key finding is that the effect of the various factors examined in this study may affect different subgroups in different ways, suggesting underlying factors, and thus potential solutions to reduce disparities in care outcomes, could differ among subgroups.

Applications for Clinical Practice and System Implementation

These 2 studies add to the literature on factors that can affect 30-day hospital readmission rates in patients with dementia. These data could allow for more robust discussions of what to anticipate when adults with dementia undergo specific procedures, and also further build the case that improvements in care, such as delirium prevention programs, could offer benefits. The observation about racial and ethnic disparities in care outcomes among patients with dementia highlights the continued need to better understand the drivers of these disparities so that hospital systems and policy makers can consider and test possible solutions. Future studies should further disentangle the relationships among the various levels of factors and observed disparities in outcomes, especially for this vulnerable population of adults living with dementia.

Practice Points

• Clinicians should be aware of the additional risks for poor outcomes that dementia confers.
• Awareness of this increased risk will inform discussions of risks and benefits for older adults considered for procedures.

–William W. Hung, MD, MPH

Study 1 Overview (Park et al)

Objective: To compare rates of adverse events and 30-day readmission among patients with dementia who undergo percutaneous coronary intervention (PCI) with those without dementia.

Design: This cohort study used a national database of hospital readmissions developed by the Agency for Healthcare Research and Quality.

Setting and participants: Data from State Inpatient Databases were used to derive this national readmissions database representing 80% of hospitals from 28 states that contribute data. The study included all individuals aged 18 years and older who were identified to have had a PCI procedure in the years 2017 and 2018. International Classification of Diseases, Tenth Revision (ICD-10) codes were used to identify PCI procedures, including drug-eluting stent placement, bare-metal stent placement, and balloon angioplasty, performed in patients who presented with myocardial infarction and unstable angina and those with stable ischemic heart disease. Patients were stratified into those with or without dementia, also defined using ICD-10 codes. A total of 755,406 index hospitalizations were included; 2.3% of the patients had dementia.

Main outcome measures: The primary study outcome was 30-day all-cause readmission, with the cause classified as cardiovascular or noncardiovascular. Secondary outcome measures examined were delirium, in-hospital mortality, cardiac arrest, blood transfusion, acute kidney injury, fall in hospital, length of hospital stay, and other adverse outcomes. Location at discharge was also examined. Other covariates included in the analysis were age, sex, comorbidities, hospital characteristics, primary payer, and median income. For analysis, a propensity score matching algorithm was applied to match patients with and without dementia. Kaplan-Meier curves were used to examine 30-day readmission rates, and a Cox proportional hazards model was used to calculate hazard ratios (HR) for those with and without dementia. For secondary outcomes, logistic regression models were used to calculate odds ratios (OR) of outcomes between those with and without dementia.

Main results: The average age of those with dementia was 78.8 years vs 64.9 years in those without dementia. Women made up 42.8% of those with dementia and 31.3% of those without dementia. Those with dementia also had higher rates of comorbidities, such as heart failure, renal failure, and depression. After propensity score matching, 17,309 and 17,187 patients with and without dementia, respectively, were included. Covariates were balanced between the 2 groups after matching. For the primary outcome, patients with dementia were more likely to be readmitted at 30 days (HR, 1.11; 95% CI, 1.05-1.18; P < .01) when compared to those without dementia. For other adverse outcomes, delirium was significantly more likely to occur for those with dementia (OR, 4.37; 95% CI, 3.69-5.16; P < .01). Patients with dementia were also more likely to die in hospital (OR, 1.15; 95% CI, 1.01-1.30; P = .03), have cardiac arrest (OR, 1.19; 95% CI, 1.01-1.39; P = .04), receive a blood transfusion (OR, 1.17; 95% CI, 1.00-1.36; P = .05), experience acute kidney injury (OR, 1.30; 95% CI, 1.21-1.39; P < .01), and fall in hospital (OR, 2.51; 95% CI, 2.06-3.07; P < .01). Hospital length of stay was higher for those with dementia, with a mean difference of 1.43 days. For discharge location, patients with dementia were more likely to be sent to a skilled nursing facility (30.1% vs 12.2%) and less likely to be discharged home.

Conclusion: Patients with dementia are more likely to experience adverse events, including delirium, mortality, kidney injury, and falls after PCI, and are more likely to be readmitted to the hospital in 30 days compared to those without dementia.

Study 2 Overview (Gilmore-Bykovskyi et al)

Objective: To examine the association between race and 30-day readmissions in Black and non-Hispanic White Medicare beneficiaries with dementia.

Design: This was a retrospective cohort study that used 100% Medicare fee-for service claims data from all hospitalizations between January 1, 2014, and November 30, 2014, for all enrollees with a dementia diagnosis. The claims data were linked to the patient, hospital stay, and hospital factors. Patients with dementia were identified using a validated algorithm that requires an inpatient, skilled nursing facility, home health, or Part B institutional or noninstitutional claim with a qualifying diagnostic code during a 3-year period. Persons enrolled in a health maintenance organization plan were excluded.

Main outcome measures: The primary outcome examined in this study was 30-day all-cause readmission. Self-reported race and ethnic identity was a baseline covariate. Persons who self-reported Black or non-Hispanic White race were included in the study; other categories of race and ethnicity were excluded because of prior evidence suggesting low accuracy of these categories in Medicare claims data. Other covariates included neighborhood disadvantage, measured using the Area Deprivation Index (ADI), and rurality; hospital-level and hospital stay–level characteristics such as for-profit status and number of annual discharges; and individual demographic characteristics and comorbidities. The ADI is constructed using variables of poverty, education, housing, and employment and is represented as a percentile ranking of level of disadvantage. Unadjusted and adjusted analyses of 30-day hospital readmission were conducted. Models using various levels of adjustment were constructed to examine the contributions of the identified covariates to the estimated association between 30-day readmission and race.

Main results: A total of 1,523,142 index hospital stays among 945,481 beneficiaries were included; 215,815 episodes were among Black beneficiaries and 1,307,327 episodes were among non-Hispanic White beneficiaries. Mean age was 81.5 years, and approximately 61% of beneficiaries were female. Black beneficiaries were younger but had higher rates of dual Medicare/Medicaid eligibility and disability; they were also more likely to reside in disadvantaged neighborhoods. Black beneficiaries had a 30-day readmission rate of 24.1% compared with 18.5% in non-Hispanic White beneficiaries (unadjusted OR, 1.37; 95% CI, 1.35-1.39). The differences in outcomes persisted after adjusting for geographic factors, social factors, hospital characteristics, hospital stay factors, demographics, and comorbidities, suggesting that unmeasured underlying racial disparities not included in this model accounted for the differences. The effects of certain variables, such as neighborhood, differed by race; for example, the protective effect of living in a less disadvantaged neighborhood was observed among White beneficiaries but not Black beneficiaries.

Conclusion: Racial and geographic disparities in 30-day readmission rates were observed among Medicare beneficiaries with dementia. Protective effects associated with neighborhood advantage may confer different levels of benefit for people of different race.

Commentary

Adults living with dementia are at higher risk of adverse outcomes across settings. In the first study, by Park et al, among adults who underwent a cardiac procedure (PCI), those with dementia were more likely to experience adverse events compared to those without dementia. These outcomes include increased rates of 30-day readmissions, delirium, cardiac arrest, and falls. These findings are consistent with other studies that found a similar association among patients who underwent other cardiac procedures, such as transcatheter aortic valve replacement.¹ Because dementia is a strong predisposing factor for delirium, it is not surprising that delirium is observed across patients who underwent different procedures or hospitalization episodes.² Because of the potential hazards for inpatients with dementia, hospitals have developed risk-reduction programs, such as those that promote recognition of dementia, and management strategies that reduce the risk of delirium.³ Delirium prevention may also impact other adverse outcomes, such as falls, discharge to institutional care, and readmissions.

Racial disparities in care outcomes have been documented across settings, including hospital⁴ and hospice care settings.⁵ In study 2, by Gilmore-Bykovskyi et al, the findings of higher rates of hospital readmission among Black patients when compared to non-Hispanic White patients were not surprising. The central finding of this study is that even when accounting for various levels of factors, including hospital-level, hospital stay–level, individual (demographics, comorbidities), and neighborhood characteristics (disadvantage), the observed disparity diminished but persisted, suggesting that while these various levels of factors contributed to the observed disparity, other unmeasured factors also contributed. Another key finding is that the effect of the various factors examined in this study may affect different subgroups in different ways, suggesting underlying factors, and thus potential solutions to reduce disparities in care outcomes, could differ among subgroups.

Applications for Clinical Practice and System Implementation

These 2 studies add to the literature on factors that can affect 30-day hospital readmission rates in patients with dementia. These data could allow for more robust discussions of what to anticipate when adults with dementia undergo specific procedures, and also further build the case that improvements in care, such as delirium prevention programs, could offer benefits. The observation about racial and ethnic disparities in care outcomes among patients with dementia highlights the continued need to better understand the drivers of these disparities so that hospital systems and policy makers can consider and test possible solutions. Future studies should further disentangle the relationships among the various levels of factors and observed disparities in outcomes, especially for this vulnerable population of adults living with dementia.

Practice Points

• Clinicians should be aware of the additional risks for poor outcomes that dementia confers.
• Awareness of this increased risk will inform discussions of risks and benefits for older adults considered for procedures.

–William W. Hung, MD, MPH