Consequences of polypharmacy among the people living with dementia: a systematic review and meta-analysis
Bibliographic record
Abstract
Objectives The aim of this systematic review and meta-analysis was to analyse and summarize studies on the effects of polypharmacy on people living with dementia (PwD). The study aimed to categorize these effects, evaluate the quality of the studies, and estimate the pooled effect sizes of these consequences using meta-analysis.Method A systematic literature review was conducted following the PRISMA guideline. Covidence software was used for screening, study selection, and data extraction. The quality assessment was conducted using the Newcastle-Ottawa Scale (NOS) scale. Random effect models were used to perform the meta-analyses and the heterogeneity was reported with I2 statistics.Results This review of 19 studies found that polypharmacy is significantly associated with potentially inappropriate medication (PIM), hospitalisation, adverse drug reactions, and mortality. The quality of the studies was fair to good. Meta-analysis revealed that the odds of having PIM among the PwD exposed to polypharmacy was 2.93 times (95% CI: 2.24–3.82; I2 = 95.6%). The studies showed heterogeneity in design, sample size, follow-up duration, confounder adjustment, polypharmacy definitions, and inconsistent tools for dementia diagnosis.Conclusion Polypharmacy in PwD is associated with increased potentially inappropriate medication, adverse drug reactions, and hospitalisation. Regular management of polypharmacy is recommended in clinical practice.
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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 | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.048 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".