Platelet rich plasma compared to viscosupplementation in the treatment of knee osteoarthritis: A systematic review and meta‐analysis of randomised controlled trials with 6 month and 12 month follow‐up
Bibliographic record
Abstract
Purpose: Platelet rich plasma (PRP) and hyaluronic acid (HA) have been utilised in the last few decades as a conservative treatment for knee osteoarthritis (OA). We sought to evaluate the patient reported outcomes at specific intermediate term endpoints comparing PRP to HA through a systematic review and meta-analysis of randomised controlled trials (RCTs). We also sought to determine the effect of platelet concentration on the relative outcomes between PRP and HA. Methods: The Embase, PubMed, Scopus and Cochrane databases were searched for terms related to PRP and osteoarthritis. RCTs comparing PRP and HA in the treatment of knee OA were selected. A total of 26 trials with 1650 knees were included. The two treatments were compared based on the Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) and visual analogue scale (VAS) at specific time points of baseline, 6 months, and 12 months. Results: PRP had a significant benefit over HA based on the WOMAC at 6 months and at 12 months. It also had a significant benefit over HA on the VAS at 6 months and at 12 months. When limiting the analysis to 6 month follow-up and separating the studies by platelet count, PRP had a statistically significant benefit over HA for platelet counts corresponding to 'greater than baseline to 1,250,000 platelets/μL' for the WOMAC score and platelet counts corresponding to 'between 750,000 and 1,250,000 platelets/μL' for the VAS score. Conclusions: When taken as a whole, PRP demonstrates a significantly superior clinical result compared to HA at 6 months and 12 months. These findings must be considered in light of the numerous preparation protocols and PRP classifications detailed in this report for the included studies. Level of Evidence: Level 1, systematic review of Level-1 randomised controlled 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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.026 | 0.034 |
| Bibliometrics | 0.005 | 0.006 |
| 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) | 0.004 | 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".