Efficacy of Platelet-Rich Plasma Injections in Knee Osteoarthritis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
The study was conducted to evaluate the safety and effectiveness of platelet-rich plasma (PRP) injections for knee osteoarthritis. A systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Searches were performed in PubMed, Scopus, Web of Science, and the Cochrane Database for studies published between January 2015 and June 2025. Only randomized controlled trials (RCTs) published in the English language were included, while reviews, case reports, and non-randomized studies were excluded. Six high-quality RCTs were identified, including a total of 1,162 patients with mild-to-moderate knee osteoarthritis. PRP injections were compared with hyaluronic acid, corticosteroid injections, or placebo. Pain and function were assessed using standardized tools such as the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), the International Knee Documentation Committee (IKDC) score, the Knee Injury and Osteoarthritis Outcome Score, and the Visual Analog Scale. Significant improvements with PRP were observed at 6 and 12 months. The WOMAC pain score was reduced by an average of -8.5 points, and the IKDC score increased by +6.2 points. Both results were statistically significant. Moderate variability was found between studies, but sensitivity analyses confirmed stability of the results. Subgroup analysis did not show consistent differences between leukocyte-rich PRP and leukocyte-poor PRP. Reported side effects were minor and self-limiting. Overall, PRP demonstrated significant improvements at 6 and 12 months. Pooled analysis indicated moderate pain reduction (standardized mean difference (SMD) = -0.32, 95% confidence interval (CI) = -0.48 to -0.15; I² = 46%) and functional improvement (SMD = -0.28, 95% CI = -0.44 to -0.12; I² = 52%) compared with control groups. However, long-term structural improvement was not demonstrated. Larger trials are still needed to confirm benefits, optimize preparation methods, and assess cost-effectiveness.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.041 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".