Effect of polypharmacy, potentially inappropriate medications and anticholinergic burden on clinical outcomes: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Polypharmacy, potentially inappropriate medications and anticholinergic burden (as assessed by the anticholinergic risk scale) are commonly used as quality indicators of pharmacotherapy in older adults. However, their role in clinical practice is undefined. We sought to investigate longitudinal changes in these indicators and their effects on clinical outcomes. METHODS: We used Taiwan's Longitudinal Health Insurance Database to retrieve quarterly information about drug use for people aged 65 years and older over a 10-year period. We analyzed the association between indicators and all-cause admission to hospital, fracture-specific admission to hospital and death using generalized estimating equations. RESULTS: The study cohort comprised 59,042 older adults (65-74 yr: 39,358 [66.7%], 75-84 yr: 16,903 [28.6%], and ≥ 85 yr: 2781 [4.7%]). The mean changes in polypharmacy over the course of the study were greatest among patients aged 65-74 years (absolute difference +2.14, 95% confidence interval [CI] 2.10-2.19), then among those aged 75-84 yr (+1.79, 95% CI 1.70-1.88), and finally those aged 85 years and older (+0.71, 95% CI 0.36-1.05). The number of potentially inappropriate medications increased among patients aged 65-74 years (+0.16 [0.15-0.18]) and 75-84 years (+0.09 [0.06-0.08]), but decreased in those aged 85 years and older (-0.15 [-0.26 to -0.04]). Polypharmacy, potentially inappropriate medications and anticholinergic risk scale were each associated with an increased risk of admission to hospital, but not with death. In addition, both polypharmacy (5-9 drugs: odds ratio [OR] 1.18, 95% CI 1.12-1.24; ≥ 10 drugs: OR 1.54, 95% CI 1.42-1.66) and anticholinergic burden (score 1-2: 1.39, 95% CI 1.31-1.48; ≥ 3: 1.53, 95% CI 1.41-1.66) showed dose-response relations with fracture-specific admission to hospital. INTERPRETATION: The total number of drugs taken (polypharmacy), number of potentially inappropriate medications and anticholinergic risk changed during follow-up and varied across age groups in this cohort of older adult patients. These indicators showed dose-response relations with admission to hospital, but not with death.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".