How to Choose Platelet-Rich Plasma or Hyaluronic Acid for the Treatment of Knee Osteoarthritis in Overweight or Obese Patients: A Meta-Analysis
Bibliographic record
Abstract
Objective . The purpose of this meta-analysis was to determine whether platelet-rich plasma (PRP) was better than hyaluronic acid (HA) for the treatment of knee osteoarthritis (OA) in overweight or obese patients. Design . Two reviewers independently used the keywords combined with free words to search English-based electronic databases according to Cochrane Collaboration guidelines, such as PubMed, Embase, ScienceDirect, and Cochrane library. The pooled data were analyzed using RevMan 5.3. Results . Ten randomized controlled trials (RCTs) with 1096 patients were included. During the first two months of follow-up, there was no significant difference between the two groups. At the 3rd, 6th, and 12th months of follow-up, the pooled analysis showed that PRP was better than HA for the treatment of knee OA in overweight or obese patients. There were significant differences between the two groups at Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score (3 months: MD = −1.35, [95% CI: −2.19 to −0.50],<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mi>P</mml:mi><mml:mo>=</mml:mo><mml:mn>0.002</mml:mn></mml:mrow></mml:math>, I 2 = 0%; 6 months: MD = −7.62, [95% CI: −13.51 to −1.72],<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:mi>P</mml:mi><mml:mo>=</mml:mo><mml:mn>0.01</mml:mn></mml:mrow></mml:math>, I 2 = 88%; 12 months: MD = −12.11, [95% CI: −20.21 to −4.01],<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mrow><mml:mi>P</mml:mi><mml:mo>=</mml:mo><mml:mn>0.003</mml:mn></mml:mrow></mml:math>, I 2 = 94%). Conclusions . For overweight or obese patients with knee OA, intra-articular injection of PRP in a short time was not necessarily superior to HA, but long-term use was better than HA in pain and functional relief.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".