Platelet-Rich Plasma Is More Effective Than Hyaluronic Acid Injections for Osteoarthritis of the Knee: A Meta-analysis Based on Randomized, Double-Blinded, Controlled Clinical Trials
Bibliographic record
Abstract
PURPOSE: To evaluate the difference in clinical efficacy of platelet-rich plasma (PRP) versus hyaluronic acid (HA) in the treatment of knee osteoarthritis (KOA). METHODS: This study conducted a comprehensive search of the Cochrane Library, Web of Science, PubMed, CNKI, Wanfang Data, and VIP databases. Eligible studies underwent rigorous quality assessment using the Cochrane Handbook 8.2 Risk of Bias 2 criteria. A meta-analysis of efficacy-related indicators was performed using RevMan 5.4 software. RESULTS: Fifteen double-blind randomized controlled trials comprising 1,632 patients with KOA ranging from I to III on the Kellgren-Lawrence grading scale were included. Meta-analysis revealed that the PRP group exhibited significantly lower Western Ontario and McMaster Universities Osteoarthritis Index pain scores and total scores from baseline compared to the HA group at 12 months (MD = -1.14; 95% CI, -2.09 to -0.20; P = .02; MD = -7.33; 95% CI, -12.81 to -1.85; P = .009, respectively), both of which reached the minimal clinically important difference. Visual analog scale scores were also significantly reduced in the PRP group at 12 months (mean difference [MD] = -0.35; 95% CI, -0.59 to -0.10; P = .005, respectively). Improved International Knee Documentation Committee scores were observed in the PRP group at 1 month (MD = 3.13; 95% CI, 1.34-4.93; P = .0006, respectively). CONCLUSIONS: After 12 months, there were statistically significant differences in Western Ontario and McMaster Universities Osteoarthritis Index pain and total scores, as well as minimal clinically important differences, with PRP being superior to HA in the treatment of KOA. LEVEL OF EVIDENCE: Level Ⅱ, meta-analysis of Level Ⅰ and Ⅱ studies.
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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 | 0.027 | 0.034 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.050 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| 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".