Clinical efficacy of single intra-articular platelet-rich plasma injections in mild to moderate knee osteoarthritis: a prospective study
Bibliographic record
Abstract
Background: Knee osteoarthritis (OA) is a degenerative joint disease that significantly impacts mobility and quality of life, particularly in older adults. Conventional treatments often provide limited relief, leading to interest in regenerative therapies like platelet-rich plasma (PRP) injections. This study aims to evaluate the clinical effects of a single intra-articular PRP injection in patients with mild to moderate knee OA. Methods: A prospective, randomized study was conducted with 56 patients aged 40 to 70 years diagnosed with primary knee OA (Kellgren-Lawrence grades 1 and 2). Participants were treated with a single intra-articular PRP injection, prepared using the double-spin technique. Pain intensity was assessed using the Visual Analog Scale (VAS), and functional status was evaluated with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) at baseline, and follow-up assessments were performed at 1 week, 4 weeks, 8 weeks, 12 weeks, and 6 months post-injection. Results: Significant improvements in both pain and function were observed. The mean VAS score decreased from 7 at baseline to 4 at 12 weeks, and to 3 at 6 months. The mean WOMAC score improved from 53 at baseline to 30 at 12 weeks, and 24 at 6 months. These changes were statistically significant (p <0.05). No major adverse events were reported during the study period. Conclusion: A single intra-articular PRP injection significantly reduces pain and improves function in patients with mild to moderate knee OA. PRP therapy is a promising treatment option for managing knee OA, offering an alternative to more invasive procedures. Further studies are needed to explore the long-term effects and optimal treatment protocols.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".