OBJECTIVES: To investigate whether anticholinergic burden scores from nine published anticholinergic scales are associated with adverse health outcomes, including hospital admissions, hospitalizations for falls, hospital length of stay (LOS), and more visits to general practitioners (GPs). DESIGN: Pharmacoepidemiological population-based study. SETTING: New Zealand. PARTICIPANTS: Population aged 65 and older (n = 537,387). MEASUREMENTS: Data were analyzed for 537,387 individuals from the Pharmaceutical Claims Data Mart data set (2011). Anticholinergic medication exposure was calculated using nine published scales. Events information (2012) was extracted from the National Minimum Datasets using International Classification of Diseases, Tenth Revision, codes. Predictors of hospital admissions, hospitalizations for falls, LOS, and GP visits were examined using regression models adjusting for age, sex, ethnicity, comorbidities, and polypharmacy. RESULTS: Prevalence of exposure to anticholinergic medicines ranged from 22.8% to 55.9% according to the different scales. Multivariate regression analysis showed that anticholinergic burden scores quantified according to all nine scales were significantly associated with hospital admissions, hospitalizations for falls, LOS, and GP visits (P < .001). The strongest predictors of these outcomes were the Drug Burden Index-Anticholinergic component scores, aged 85 and older, female sex, and polypharmacy. CONCLUSION: There are substantial differences in the estimation of anticholinergic burden exposure between the nine scales. Anticholinergic burden scores obtained from each of the scales were associated with adverse clinical outcomes of interest.
OBJECTIVES: To investigate whether anticholinergic burden scores from nine published anticholinergic scales are associated with adverse health outcomes, including hospital admissions, hospitalizations for falls, hospital length of stay (LOS), and more visits to general practitioners (GPs). DESIGN: Pharmacoepidemiological population-based study. SETTING: New Zealand. PARTICIPANTS: Population aged 65 and older (n = 537,387). MEASUREMENTS: Data were analyzed for 537,387 individuals from the Pharmaceutical Claims Data Mart data set (2011). Anticholinergic medication exposure was calculated using nine published scales. Events information (2012) was extracted from the National Minimum Datasets using International Classification of Diseases, Tenth Revision, codes. Predictors of hospital admissions, hospitalizations for falls, LOS, and GP visits were examined using regression models adjusting for age, sex, ethnicity, comorbidities, and polypharmacy. RESULTS: Prevalence of exposure to anticholinergic medicines ranged from 22.8% to 55.9% according to the different scales. Multivariate regression analysis showed that anticholinergic burden scores quantified according to all nine scales were significantly associated with hospital admissions, hospitalizations for falls, LOS, and GP visits (P < .001). The strongest predictors of these outcomes were the Drug Burden Index-Anticholinergic component scores, aged 85 and older, female sex, and polypharmacy. CONCLUSION: There are substantial differences in the estimation of anticholinergic burden exposure between the nine scales. Anticholinergic burden scores obtained from each of the scales were associated with adverse clinical outcomes of interest.
Authors: Jennifer G Naples; Zachary A Marcum; Subashan Perera; Shelly L Gray; Anne B Newman; Eleanor M Simonsick; Kristine Yaffe; Ronald I Shorr; Joseph T Hanlon Journal: J Am Geriatr Soc Date: 2015-10 Impact factor: 5.562
Authors: Birgit Böhmdorfer; Sonja Rohleder; Martin Wawruch; T J M van der Cammen; Thomas Frühwald; Christian Jagsch; Susanne Melitta Maria Janowitz; Marietta Nagano; Mirko Petrovic; Ulrike Sommeregger; Bernhard Iglseder Journal: Z Gerontol Geriatr Date: 2015-08-19 Impact factor: 1.281
Authors: Peter Hanlon; Terence J Quinn; Katie I Gallacher; Phyo K Myint; Bhautesh Dinesh Jani; Barbara I Nicholl; Richard Lowrie; Roy L Soiza; Samuel R Neal; Duncan Lee; Frances S Mair Journal: Ann Fam Med Date: 2020-03 Impact factor: 5.166