The efficacy and safety of pilates exercise in patients with knee osteoarthritis: a systematic review with meta-analysis of randomized controlled trials
Bibliographic record
Abstract
Evidence on the effects of Pilates exercise in patients with knee osteoarthritis (KOA) remains limited. This meta-analysis aimed to evaluate its efficacy and safety. We searched PubMed, Web of Science, EMBASE, Cochrane Library, and Google Scholar up to May 21, 2024, for randomized controlled trials (RCTs). Outcomes included Visual Analogue Scale (VAS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), knee range of motion (ROM), and adverse events. Risk of bias and evidence certainty were assessed; subgroup, sensitivity, and publication bias analyses were performed. Eight RCTs involving 322 participants were included. Risk of bias ranged from low to high, mainly due to lack of blinding. Compared to blank controls, Pilates significantly reduced WOMAC scores (SMD = −1.70; 95% CI: −3.14 to −0.25). One study comparing Pilates to health education reported significant reductions in VAS (MD = −1.74; 95% CI: −2.51 to −0.97) and WOMAC (SMD = −1.42; 95% CI: −2.39 to −0.45), but no significant ROM improvement. Compared to other exercises, Pilates showed no significant effects on VAS, WOMAC, or ROM. Funnel plots showed asymmetry for VAS and WOMAC; Egger’s test indicated possible publication bias (p = 0.0039 and 0.0154, respectively). No adverse events were reported, but active monitoring was limited. GRADE rated evidence as “very low” for VAS and WOMAC, and “low” for ROM. Pilates may relieve pain and improve physical function, but has limited effects on ROM. Due to insufficient adverse event reporting, safety remains unclear. Given the low study quality, high heterogeneity, and possible bias, results should be interpreted cautiously. Future studies should use standardized protocols, report long-term adherence, and assess mental health benefits.
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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 | 0.021 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.038 |
| Bibliometrics | 0.009 | 0.007 |
| 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) | 0.004 | 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".