Land-based Exercise for Osteoarthritis of the Knee: A Metaanalysis of Randomized Controlled Trials
Bibliographic record
Abstract
OBJECTIVE: To determine if clinical guidelines recommending therapeutic exercise for people with knee osteoarthritis (OA) are supported by rigorous scientific evidence. To explore whether the magnitude of treatment benefit reported in randomized controlled trials (RCT) is associated with exercise dosage or study methodology. METHODS: We conducted a metaanalysis of RCT comparing some form of land-based therapeutic exercise with a nonexercise group using pain and self-reported physical function outcomes. RESULTS: The 32 included studies provided data on almost 3800 participants. Metaanalysis revealed a beneficial treatment effect: standardized mean difference (SMD) 0.40 [95% confidence interval (CI) 0.30 to 0.50] for knee pain; SMD 0.37 (95% CI 0.25 to 0.49) for physical function. While the pooled beneficial effects of the 9 RCT evaluating exercise programs providing fewer than 12 direct supervision occasions or the 9 RCT judged to have a low risk of bias remained significant and clinically relevant, the magnitude of treatment benefit pooled from these RCT was significantly smaller than the comparator group (12 or more supervision occasions, moderate to high risk of bias, respectively). The mode of treatment delivery (individual treatments, exercise classes, home program) was not significantly associated with the magnitude of treatment benefit. CONCLUSION: There is evidence that land-based therapeutic exercise has at least short-term benefit in terms of reduced knee pain and physical disability for people with knee OA. The magnitude of the treatment effect was significantly associated with the number of direct supervision occasions provided and study methodology (assessor blinding, adequate allocation concealment).
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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 | 0.040 | 0.073 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.050 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".