Are aquatic exercises efficacious in postmenopausal women with knee osteoarthritis? A meta-analysis of randomized controlled trials
Bibliographic record
Abstract
INTRODUCTION: To assess the effects of aquatic exercise in postmenopausal women with knee osteoarthritis using an up-to-date meta-analysis. EVIDENCE ACQUISITION: PubMed, Cochrane Library, Embase, Scopus, Web of Science, Google Scholar, the China National Knowledge Infrastructure (CNKI), the Chinese Biomedical Database (CBM), VIP and Wanfang database were searched systematically for randomized controlled trials (RCTs) published until July 2018. The RCTs included comparing the efficacy of aquatic exercise vs. control in postmenopausal women with knee osteoarthritis, the primary outcomes were assessed by the Western Ontario McMaster University Osteoarthritis Index (WOMAC) and the Knee injury and Osteoarthritis Outcome Score (KOOS). EVIDENCE SYNTHESIS: Six RCTs comprising 432 participants. This meta-analysis revealed that aquatic exercise could significantly relieve the symptom of postmenopausal women with knee osteoarthritis. But there was no significant difference between aquatic exercise program and control group for the improvement of pain, stiffness, function outcomes, sport, activities of daily living and quality of life. CONCLUSIONS: Contrary to prior reviews, our analysis demonstrated that aquatic exercise has no positive impact on pain physical function, stiffness, activities of daily living, sport and quality of life in elderly women with knee osteoarthritis. However, aquatic exercise could improve the symptoms of knee osteoarthritis. Further investigation is needed because of limited available data.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.027 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".