Mesenchymal stem cells for chronic knee pain secondary to osteoarthritis: A systematic review and meta-analysis of randomized trials
Bibliographic record
Abstract
OBJECTIVE: To assess the effectiveness of mesenchymal stem cells (MSCs) for chronic knee pain secondary to osteoarthritis (OA). METHODS: We searched MEDLINE, EMBASE, CINAHL, and Cochrane Central to September 2023 for trials that (1) enrolled patients with chronic pain associated with knee OA, and (2) randomized them to MSC therapy vs. placebo or usual care. We performed random-effects meta-analysis and used Grading of Recommendations, Assessment, Development, and Evaluation to assess the certainty of evidence. RESULTS: We included 16 trials (807 participants). At 3-6 months, MSC therapy probably results in little to no difference in pain relief (weighted mean difference [WMD] -0.74 cm on a 10 cm visual analog scale [VAS], 95% confidence interval [95%CI] -1.16 to -0.33; minimally important difference [MID] 1.5 cm) or physical functioning (WMD 2.23 points on 100-point 36-item Short Form Survey (SF-36) physical functioning subscale, 95%CI -0.97 to 5.43; MID 10-points; both moderate certainty). At 12 months, injection of MSCs probably results in little to no difference in pain (WMD -0.73 cm on a 10 cm VAS, 95%CI -1.69 to 0.24; moderate certainty) and may improve physical functioning (WMD 19.36 points on 100-point SF-36 PF subscale, 95%CI -0.19 to 38.9; low certainty). MSC therapy may increase risk of any adverse events (risk ratio [RR] 2.67, 95%CI 1.19 to 5.99; low certainty) and pain and swelling of the knee joint (RR 1.58, 95%CI 1.04 to 2.38; low certainty). CONCLUSIONS: Intra-articular injection of MSCs for chronic knee pain associated with OA probably provides little to no improvement in pain or physical function.
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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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.031 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".