Meta-analysis Comparing Platelet-Rich Plasma vs Hyaluronic Acid Injection in Patients with Knee Osteoarthritis
Bibliographic record
Abstract
PURPOSE: The purpose of this meta-analysis was to compare platelet-rich plasma (PRP) and hyaluronic acid (HA) in patients with knee osteoarthritis (KOA). METHODS: Randomized controlled trials (RCTs) comparing the use of PRP and HA in KOA patients were retrieved from each database from the establishment date to April 2018. Outcome measurements were the Western Ontario and McMaster Universities Arthritis Index (WOMAC), visual analog scale (VAS), International Knee Documentation Committee, and Lequesne Index scores and adverse events. The pooled data were evaluated with Review Manager 5.3.5. RESULTS: Fifteen RCTs (N = 1,314) were included in our meta-analysis. The present meta-analysis indicated that PRP injections reduced pain more effectively than HA injections in patients with KOA at six and 12 months of follow-up, as evaluated by the WOMAC pain score; the VAS pain score showed a significant difference at 12 months. Moreover, better functional improvement was observed in the PRP group, as demonstrated by the WOMAC function score at three, six, and 12 months. Additionally, PRP injections did not display different adverse event rates compared with HA injections. CONCLUSION: In terms of long-term pain relief and functional improvement, PRP injections might be more effective than HA injections as a treatment for KOA. The optimal dosage, the timing interval and frequency of injections, and the ideal treatment for different stages of KOA remain areas of concern for future investigations.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.050 |
| Bibliometrics | 0.004 | 0.005 |
| 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".