Association entre la charge anticholinergique et sédative et la fonction physique chez les adultes d’âge moyen et les aînés canadiens
Bibliographic record
Abstract
Background: Anticholinergic and sedative medications, frequently prescribed to older adults, are associated with impaired physical function. Physical function is multidimensional and assessed through various tests, some subject to ceiling effects, which limits comparability and has led most studies to adopt a partial rather than an integrated approach. There remains a need to better identify the dimensions of physical function most affected in relation to anticholinergic and sedative drug burden. Objective: To evaluate the association between anticholinergic and sedative drug burden, latent physical function profiles, and functional limitation groups, as well as to describe the prevalence of exposure to different medication classes across profiles and groups. Methods: This cross-sectional study was based on data from the comprehensive cohort of the Canadian Longitudinal Study on Aging (n = 30,097). Physical function was assessed using five standardized tests, with performances converted into age- and sex-adjusted percentiles and then grouped into profiles through latent profile analysis. Anticholinergic and sedative drug burden was estimated using the Drug Burden Index (DBI), dichotomized as < 1 or ≥ 1. Associations were examined using adjusted multinomial logistic regression. The prevalence of exposure to medication classes was calculated across physical function profiles and functional limitation groups. Results: Six distinct profiles were identified. A DBI ≥ 1 was associated with a higher probability of belonging to profiles 4 and 1 (lower performance) and a reduced probability of belonging to profile 2 (higher performance). These associations remained significant after adjustment, except for profile 1 in adults aged ≥ 65 years. All functional limitation groups were associated with a DBI ≥ 1. Antidepressants, benzodiazepines, and opioids were more frequently observed in the most vulnerable profiles. Conclusion: High exposure (DBI ≥ 1) was associated with an increased likelihood of belonging to profiles characterized by poor performance on balance, gait speed, Timed Up and Go, chair stand, and grip strength tests (profile 4), as well as to functional limitation groups, independently of multimorbidity. Antidepressants, benzodiazepines, and z-drugs were more frequent among profiles with low physical function and among functional limitation groups. These findings underscore the importance of minimizing anticholinergic and sedative drug burden and considering deprescribing strategies to optimize physical function in older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".