TY - JOUR
T1 - Anticholinergic burden measures, symptoms, and fall-associated risk in older adults with polypharmacy
T2 - Development and validation of a prognostic model
AU - Dinh, Truc Sophia
AU - Meid, Andreas D
AU - Rudolf, Henrik
AU - Brueckle, Maria-Sophie
AU - González-González, Ana I
AU - Bencheva, Veronika
AU - Gogolin, Matthias
AU - Snell, Kym I E
AU - Elders, Petra J M
AU - Thuermann, Petra A
AU - Donner-Banzhoff, Norbert
AU - Blom, Jeanet W
AU - van den Akker, Marjan
AU - Gerlach, Ferdinand M
AU - Harder, Sebastian
AU - Thiem, Ulrich
AU - Glasziou, Paul P
AU - Haefeli, Walter E
AU - Muth, Christiane
N1 - Copyright: © 2023 Dinh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding Information:
Funding: PROPER med was funded by the German Innovation Fund (grant number 01VSF16018). RIME was funded by the German Federal Ministry of Education and Research(grant number 01ET1005A).PRIMUM was funded by the German Federal Ministry of Education and Research (grant number 01GK0702). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Funding Information:
PROPERmed was funded by the German Innovation Fund (grant number 01VSF16018). RIME was funded by the German Federal Ministry of Education and Research (grant number 01ET1005A). PRIMUM was funded by the German Federal Ministry of Education and Research (grant number 01GK0702). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors would like to thank Kiran Chapidi for support in data management. The authors are also grateful to all members of the PROPERmed, PRIMUM, and RIME study groups and Phillip Elliott for conducting a language review.
Publisher Copyright:
© 2023 Dinh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2023/1/23
Y1 - 2023/1/23
N2 - BACKGROUND: Anticholinergic burden has been associated with adverse outcomes such as falls. To date, no gold standard measure has been identified to assess anticholinergic burden, and no conclusion has been drawn on which of the different measure algorithms best predicts falls in older patients from general practice. This study compared the ability of five measures of anticholinergic burden to predict falls. To account for patients' individual susceptibility to medications, the added predictive value of typical anticholinergic symptoms was further quantified in this context.METHODS AND FINDINGS: To predict falls, models were developed and validated based on logistic regression models created using data from two German cluster-randomized controlled trials. The outcome was defined as "≥ 1 fall" vs. "no fall" within a 6-month follow-up period. Data from the RIME study (n = 1,197) were used in model development, and from PRIMUM (n = 502) for external validation. The models were developed step-wise in order to quantify the predictive ability of anticholinergic burden measures, and anticholinergic symptoms. In the development set, 1,015 patients had complete data and 188 (18.5%) experienced ≥ 1 fall within the 6-month follow-up period. The overall predictive value of the five anticholinergic measures was limited, with neither the employed anticholinergic variable (binary / count / burden), nor dose-dependent or dose-independent measures differing significantly in their ability to predict falls. The highest c-statistic was obtained using the German Anticholinergic Burden Score (0.73), whereby the optimism-corrected c-statistic was 0.71 after interval validation using bootstrapping and 0.63 in the external validation. Previous falls and dizziness / vertigo had the strongest prognostic value in all models.CONCLUSIONS: The ability of anticholinergic burden measures to predict falls does not appear to differ significantly, and the added value they contribute to risk classification in fall-prediction models is limited. Previous falls and dizziness / vertigo contributed most to model performance.
AB - BACKGROUND: Anticholinergic burden has been associated with adverse outcomes such as falls. To date, no gold standard measure has been identified to assess anticholinergic burden, and no conclusion has been drawn on which of the different measure algorithms best predicts falls in older patients from general practice. This study compared the ability of five measures of anticholinergic burden to predict falls. To account for patients' individual susceptibility to medications, the added predictive value of typical anticholinergic symptoms was further quantified in this context.METHODS AND FINDINGS: To predict falls, models were developed and validated based on logistic regression models created using data from two German cluster-randomized controlled trials. The outcome was defined as "≥ 1 fall" vs. "no fall" within a 6-month follow-up period. Data from the RIME study (n = 1,197) were used in model development, and from PRIMUM (n = 502) for external validation. The models were developed step-wise in order to quantify the predictive ability of anticholinergic burden measures, and anticholinergic symptoms. In the development set, 1,015 patients had complete data and 188 (18.5%) experienced ≥ 1 fall within the 6-month follow-up period. The overall predictive value of the five anticholinergic measures was limited, with neither the employed anticholinergic variable (binary / count / burden), nor dose-dependent or dose-independent measures differing significantly in their ability to predict falls. The highest c-statistic was obtained using the German Anticholinergic Burden Score (0.73), whereby the optimism-corrected c-statistic was 0.71 after interval validation using bootstrapping and 0.63 in the external validation. Previous falls and dizziness / vertigo had the strongest prognostic value in all models.CONCLUSIONS: The ability of anticholinergic burden measures to predict falls does not appear to differ significantly, and the added value they contribute to risk classification in fall-prediction models is limited. Previous falls and dizziness / vertigo contributed most to model performance.
UR - http://www.scopus.com/inward/record.url?scp=85147046510&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0280907
DO - 10.1371/journal.pone.0280907
M3 - Article
C2 - 36689445
SN - 1932-6203
VL - 18
JO - PLoS One
JF - PLoS One
IS - 1 January
M1 - e0280907
ER -