Osteoarthritis year in review 2025: Rehabilitation and outcomes including sex and gender reporting
Bibliographic record
Abstract
This year in review (1) narratively synthesises the effect of, or patient experience with, non-pharmacological or non-surgical rehabilitation treatments for osteoarthritis at any joint; and (2) describes how sex and/or gender are defined, reported, and analysed. We searched three databases (Medline, Embase, CINAHL) for studies that met predefined criteria and selected those of perceived moderate-to-high quality and importance published between 12th March 2024 and 1st March 2025. Studies were grouped according to predominant treatment topic areas (e.g. core [exercise, diet]; adjunct [electrotherapy, manual therapy]; multimodal [different rehabilitation treatments]). Two authors independently screened records. One author extracted data, and another checked 10% of the accuracy. Full-text screening identified 158 eligible studies, reduced to 39 for synthesis. We identified eight themes: i) Exercise is effective for knee osteoarthritis and comorbidities, but has varied effects for hip osteoarthritis; ii) Diet plus exercise is effective for weight loss, but may not reduce pain; iii) Digital rehabilitation is a viable alternative to in-person care; iv) No added benefit of mind/behavioural treatments; v) Effects of electrotherapy modalities on pain were inconsistent and region-specific; vi) Orthoses may relieve pain, but should be individualised to patient preferences; vii) Acupuncture and blood flow restriction treatment show effectiveness in single clinical trials; viii) Treatment packages for osteoarthritis have varied benefits. Sex and gender were reported in 23 and 11 studies, respectively. For gender, most studies used female/male/woman/man interchangeably. No study defined sex or gender, 5% reported results disaggregated by sex or gender, no study justified why results were not, and 5% summarised key sex or gender findings.
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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 | 0.095 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.017 | 0.023 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".