Lana Sargent1,2,3, Mike Nalls1,4, Elaine J Amella3, Martina Mueller3, Sarah K Lageman5, Stefania Bandinelli6, Marco Colpo6, Patricia W Slattum7, Andrew Singleton1, Luigi Ferrucci8. 1. Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland. 2. Virginia Commonwealth University School of Nursing, Richmond, Virginia. 3. Medical University of South Carolina School of Nursing, Charleston, South Carolina. 4. Department of Neurology, Virginia Commonwealth School of Medicine, Richmond, Virginia. 5. Laboratory of Clinical Epidemiology, InCHIANTI Study Group, Local Health Unit Tuscany Center, Florence, Italy. 6. Data Tecnica International, Glen Echo, Maryland. 7. Department of Pharmacotherapy & Outcome Science, Virginia Commonwealth School of Pharmacy, Richmond, Virginia. 8. Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, Maryland.
Abstract
BACKGROUND: The aims of this study were to evaluate the relationship between anticholinergic drug burden (ACB) cognitive impairment, physical frailty, and cognitive frailty, and to determine if ACB is predictive of these phenotypes when modeled with biological and genomic biomarkers. METHODS: In a retrospective cohort study, a total of 1,453 adults aged 20-102 years were used to examine ACB as a predictor for cognitive impairment, physical frailty, and cognitive frailty. Anticholinergic burden is examined as a predictor for all phenotypes in a cross-sectional analysis using logistic, ordinal regression models, and Extreme Gradient Boosting for population predictive modeling. RESULTS: A significant association was found between ACB and cognitive decline (p = .02), frailty (p < .001), and cognitive frailty (p < .001). The odds of cognitive impairment increased by 1.21 (95% confidence interval [CI] = 1.06-1.37, p < .001), odds of being frail increased by 1.33 (95% CI = 1.18-1.50, p < .001), and odds of having cognitive frailty increased by 1.36 (95% CI = 1.21-1.54, p < .001). Population modeling results indicated ACB score as one of the stronger predictors for cognitive impairment, physical frailty, and cognitive frailty with area under the curves ranging from 0.81 to 0.88. CONCLUSIONS: Anticholinergic medications are a potentially modifiable risk factor for the prevention of cognitive and physical decline. Identification of reversible causes for cognitive and physical impairment is critical for the aging population. These findings encourage new research that may lead to effective interventions for deprescribing programs for the prevention of cognitive and physical decline in older adults.
BACKGROUND: The aims of this study were to evaluate the relationship between anticholinergic drug burden (ACB) cognitive impairment, physical frailty, and cognitive frailty, and to determine if ACB is predictive of these phenotypes when modeled with biological and genomic biomarkers. METHODS: In a retrospective cohort study, a total of 1,453 adults aged 20-102 years were used to examine ACB as a predictor for cognitive impairment, physical frailty, and cognitive frailty. Anticholinergic burden is examined as a predictor for all phenotypes in a cross-sectional analysis using logistic, ordinal regression models, and Extreme Gradient Boosting for population predictive modeling. RESULTS: A significant association was found between ACB and cognitive decline (p = .02), frailty (p < .001), and cognitive frailty (p < .001). The odds of cognitive impairment increased by 1.21 (95% confidence interval [CI] = 1.06-1.37, p < .001), odds of being frail increased by 1.33 (95% CI = 1.18-1.50, p < .001), and odds of having cognitive frailty increased by 1.36 (95% CI = 1.21-1.54, p < .001). Population modeling results indicated ACB score as one of the stronger predictors for cognitive impairment, physical frailty, and cognitive frailty with area under the curves ranging from 0.81 to 0.88. CONCLUSIONS: Anticholinergic medications are a potentially modifiable risk factor for the prevention of cognitive and physical decline. Identification of reversible causes for cognitive and physical impairment is critical for the aging population. These findings encourage new research that may lead to effective interventions for deprescribing programs for the prevention of cognitive and physical decline in older adults.
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