Intraarticular leukocyte-poor platelet-rich plasma injection is more effective than intraarticular hyaluronic acid injection in the treatment of knee osteoarthritis: a systematic review and meta-analysis of 12 randomized controlled trials
Bibliographic record
Abstract
PURPOSE: We aim to compare the clinical effects of intraarticular leukocyte-poor platelet-rich plasma (LP-PRP) injection with those of intraarticular hyaluronic acid (HA) injection in adult patients with knee osteoarthritis. METHODS: Two authors independently reviewed databases, including PubMed, Web of Science, and the Cochrane Library. Only randomized controlled trials (RCTs) were included in our meta-analysis. Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores (WOMAC total, pain, stiffness, and physical function scores), visual analog scale (VAS) scores, EQ-VAS scores, International Knee Documentation Committee (IKDC) scores, and adverse events were used as outcome measurements to evaluate the efficacy of LP-PRP and HA treatment. RESULTS: After screening 377 potential articles, 12 RCTs were included in this systemic review and meta-analysis. The WOMAC total scores and WOMAC physical function scores of the LP-PRP group were better than those of the HA group at 6 and 12 months. VAS scores of the LP-PRP group were better than those of the HA group at 3, 6, and 12 months. The LP-PRP group showed a better outcome of IKDC scores than the HA group at 6 months. There was no significant difference in adverse events between the LP-PRP and HA groups. CONCLUSION: Intraarticular injections of LP-PRP showed better overall outcomes, such as WOMAC total scores, WOMAC physical function scores, VAS scores, and IKDC scores, compared with HA for adult patients with knee osteoarthritis at 6- and 12-month follow-up periods. Also, LP-PRP showed better pain relief compared with HA at 3-, 6-, and 12-month follow-up periods. Intraarticular LP-PRP improves pain relief and overall outcomes in patients with knee osteoarthritis.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.039 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".