Effectiveness of curcuminoids in the treatment of knee osteoarthritis: a systematic review and meta‐analysis of randomized clinical trials
Bibliographic record
Abstract
Abstract Aim To critically appraise and evaluate the evidence for effectiveness of curcuminoids in the treatment of osteoarthritis (OA) in adults. Methods We conducted electronic searches in Medline, Embase,AMED, Cinahl and the Cochrane library. We included randomized controlled trials (RCTs) that investigated the effectiveness of orally‐administered curcuminoids inOAin adults, and assessed risk of bias using the Cochrane risk of bias criteria. We used a random‐effect model for meta‐analysis. Results We included seven studies with a total of 797 participants with primarily kneeOA. All studies were conducted in Asia. The overall risk of bias was moderate. Compared with placebo, curcuminoids significantly reduced knee pain (visual analogue scale): (standardized mean difference: −3.45; 95%CI: −5.52 to −1.38;I2 = 95%P = 0.001), and improved quality of life (Lequesne pain‐function index): (mean difference: −2.69; 95%CI: −3.48 to −1.90;I2 = 0%P < 0.00001). There were significantly fewer effects on pain relief, knee stiffness and physical function with curcuminoids compared with ibuprofen. Significant improvements in Western Ontario and McMaster Universities Arthritis Index total scores, with significant reductions in the use of rescue medication were also observed with curcuminoids. No serious adverse events were reported. Conclusions Curcuminoids may have some beneficial effects on knee pain and quality of life in patients with kneeOA. However, they are less effective at relieving pain compared with ibuprofen. Curcuminoids appear safe on the short‐term, and may reduce the need for rescue medication. PublishedRCTs vary in reporting quality, are characterized by small sample sizes, and have all been conducted in Asia. Further clinical trials are therefore warranted.
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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 | 0.031 | 0.073 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.031 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 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".