Prevalence of polypharmacy among older adults with diabetes: A systematic review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: Polypharmacy, the concurrent use of five or more medications, is prevalent among older adults with Diabetes, a population at elevated risk for medication-related complications. Complex treatment regimens for Diabetes and its comorbidities exacerbate challenges such as medication non-adherence, drug interactions, adverse events, and increased hospitalization risk. This review aimed to estimate the prevalence of polypharmacy among older adults with Diabetes. METHOD: Following PRISMA 2020 guidelines, we performed a systematic search of PubMed, Embase, and Web of Science. Screened articles using Nested Knowledge software. Eligible studies included those aged 60 years or older with Diabetes, reporting on the prevalence of polypharmacy. Study quality was assessed using a modified Newcastle-Ottawa Scale, and meta-analysis was performed using random-effects models in R software version 4.4.1. Publication bias was indicated by a Doi plot with an LFK index. RESULTS: The pooled prevalence of polypharmacy was 59% (95% CI, 48%-70%). Subgroup analyses showed a prevalence of 55% in retrospective studies and 62% in cross-sectional studies. Sensitivity analyses confirmed the stability of the results. Significant geographic variability was noted, with lower prevalence in high-income countries compared to regions in Southern Europe and Asia. CONCLUSIONS: Polypharmacy is highly prevalent among older adults with Diabetes, with significant variability across study designs and geographic regions. Targeted interventions and further research are essential to address its associated risks and optimize medication management.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".