Pain Is Associated with Recurrent Falls in Community-Dwelling Older Adults: Evidence from a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Pain and recurrent falls are highly problematic in community-dwelling older adults, yet the association remains elusive. OBJECTIVE: The objective of this study was to investigate the association between pain and recurrent falls in community-dwelling older adults. DESIGN: Two independent reviewers conducted searches of major electronic databases, completed methodological assessment, and extracted the data of all included articles. Articles that were included are those that (1) involved community-dwelling older adults; (2) recorded recurrent falls; and (3) assessed pain. Articles that were excluded are those that included participants with dementia, any neurological conditions, or those with orthopedic trauma/surgery in the past 6 months. RESULTS: Out of a potential of 71 articles, 11 met the inclusion criteria and 7 (N = 9,581) were eligible for the meta-analysis. The annual prevalence of recurrent falls in those reporting pain (12.9%) was higher than the pain-free control group (7.2%, P < 0.001). A global meta-analysis established that pain was associated with recurrent falls (odds ratio [OR]: 2.04, confidence interval [CI]: 1.75-2.39; N = 3,950 with pain and N = 5,631 controls), and this was decreased in a subgroup meta-analysis utilizing prospective studies only (OR: 1.79, CI: 1.44-2.21, P < 0.001, I2 = 0%; N = 3, N = 2,646). A subgroup analysis comparing recurrent fallers vs. non-fallers only (OR: 2.18, CI: 1.82-2.60, N = 6,320, I2 = 0%) established the odds were particularly higher than single fallers vs. non-fallers (OR:1.44, CI: 1.26-1.64, N = 6,903, (I2) = 0%). CONCLUSION: Older adults with pain are at particularly increased risk of recurrent falls. Clinicians working with recurrent fallers should routinely assess pain while pain specialists should inquire about older adults' falls history.
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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 | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.036 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".