Polypharmacy and risk of fractures in older adults: A systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Fractures have serious health consequences in older adults. While some medications are individually associated with increased risk of falls and fractures, it is not clear if this holds true for the use of many medications (polypharmacy). We aimed to identify what is known about the association between polypharmacy and the risk of fractures in adults aged ≥65 and to examine the methods used to study this association. METHODS: We conducted a systematic review with narrative synthesis of studies published up to October 2023 in PubMed, Embase, CINAHL, PsychINFO, Cochrane Library, Web of Science, and the grey literature. Two independent reviewers screened titles, abstracts, and full texts, then performed data extraction and quality assessment. RESULTS: Among the 31 studies included, 11 different definitions of polypharmacy were used and were based on three medication counting methods (concurrent use 15/31, cumulative use over a period 6/31, daily average 3/31, and indeterminate 7/31). Overall, polypharmacy was frequent and associated with higher fracture risk. A dose-response relationship between increasing number of medications and increased risk of fractures was observed. However, only seven studies adjusted for major confounders (age, sex, and chronic disease). The quality of the studies ranged from poor to high. CONCLUSIONS: Polypharmacy appears to be a relevant modifiable risk factor for fractures in older individuals that can easily be used to identify those at risk. The diversity of medication calculation methods and definitions of polypharmacy highlights the importance of a detailed methodology to understand and compare results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it