Meta‐analysis of the efficacy and safety of arthroscopic surgery associated with platelet‐rich plasma infusion when treating knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy and safety of arthroscopic surgery associated with platelet-rich plasma (PRP) infusion in treating knee osteoarthritis (KOA). METHODS: PubMed, EMBASE, ScienceDirect, Cochrane Library, China Knowledge Network Database, China VIP Database, Wanfang Database, and China Biomedical Literature Database online database were searched for the case-control trial of arthroscopic surgery associated with PRP infusion in patients with KOA. During the search period of January 2010 through May 2022, two researchers independently extracted the data. With RevMan5.3, we performed a meta-analysis on the collected data. RESULTS: A total of six clinical controlled studies were included, including 333 individuals. Compared with the control group treated only by arthroscopic surgery, the results showed that the visual analogue scores of patients in the arthroscopic surgery and PRP infusion group were significantly lower at 3, 6 and 12 months after operation, and the Western Ontario and McMaster Universities Osteoarthritis Index were significantly lower at 3, 6 and 12 months after operation (p < .05). The meta-analysis of Hospital for Special Surgery (HSS) knee score and Lisum knee score (LKSS) showed that postoperative HSS score, LKSS score at 3, 6, and 12 months after operation, and SF-36 quality of life score at 6 and 12 months after operation were higher (p < .05). CONCLUSION: Arthroscopic debridement associated with PRP is more successful in relieving knee pain and enhancing knee joint function than arthroscopic debridement in treating KOA. The treatment scheme deserves to be popularized in clinical practice, but further research and longer interventions will be needed to validate it, using high-quality methods.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.043 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".