Efficacy of different platelet‐rich plasma injections in the treatment of mild‐moderate knee osteoarthritis: A systematic review and meta‐analysis
Bibliographic record
Abstract
AIMS: This study aimed to compare the efficacy of different numbered sets of injections of platelet-rich plasma (PRP) in the treatment of mild-moderate knee osteoarthritis (OA). METHODS: A comprehensive search in three databases of Cochrane Library, Embase, and PubMed was conducted to find relevant articles that investigated the efficacy of PRP injection therapies in the treatment of mild-moderate knee OA through August 2020. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function scores were the primary outcomes and visual analogue scale (VAS) was the secondary outcome. The pooled improvements amongst different injection therapies were compared. RESULTS: No significant differences in the improvement of WOMAC pain were observed amongst 1-, 2-, and 3-injection therapies at 3- (P = .26) and 6-month (P = .13) follow-ups. For a 12-month follow-up, the difference amongst different therapies reached borderline significance (P = .05) in which 3-injection therapy had a significantly better improvement than 2-injection therapy (P = .02) and reached borderline significance compared with 1-injection (P = .07). However, no significant differences in the improvement of VAS scores were observed amongst three injection therapies for all the follow-up visits (P > .05). For WOMAC function score, 3-injection therapy performed significantly better than 1-injection (P < .00001) or 2-injection therapy (P < .0001) only at 12-month follow-up visit. CONCLUSIONS: Our results demonstrated that 3-injection therapy of PRP in the treatment of mild-moderate knee OA had the best efficacy in pain relief and function improvement compared with 1- and 2-injection therapies.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.026 |
| 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) | 0.003 | 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".