THE EFFECTIVENESS OF PLATELET-RICH PLASMA THERAPY IN TREATING KNEE OSTEOARTHRITIS
Bibliographic record
Abstract
Background: Knee osteoarthritis (KOA) is a prevalent degenerative joint disorder characterized by cartilage deterioration, pain, and functional impairment. Platelet-rich plasma (PRP) therapy has emerged as a promising regenerative treatment due to its potential to modulate inflammation and promote tissue repair. This study aimed to evaluate the clinical efficacy of PRP in patients with KOA, focusing on pain reduction, functional improvement, and structural changes over a six-month period. Methods: A prospective clinical trial was conducted with 133 patients diagnosed with KOA (Kellgren-Lawrence grades 1–3). Participants received three weekly intra-articular PRP injections. Outcomes were assessed at baseline, 1, 3, and 6 months’ post-treatment using the Visual Analog Scale (VAS) for pain, the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the Knee Society Score (KSS). Magnetic resonance imaging (MRI) was performed at baseline and 6 months to evaluate cartilage thickness. Statistical analysis was performed using non-parametric tests. Results: Significant improvements were observed in all outcome measures. VAS scores decreased from 7.8 ± 1.1 at baseline to 2.0 ± 1.0 at 6 months (p < 0.05) WOMAC scores improved from 65.7 ± 11.4 to 28.6 ± 7.3, and KSS scores increased from 52.6 ± 9.3 to 79.3 ± 8.9 (p < 0.05). MRI revealed modest increases in cartilage thickness, particularly in the medial compartments (0.3 mm in the femoral condyle and 0.2 mm in the tibial plateau). Conclusion: PRP therapy significantly reduced pain, improved joint function, and enhanced quality of life in KOA patients over six months. While structural changes were modest, the clinical outcomes support PRP as an effective conservative treatment for early to moderate KOA. Further research with longer follow-up and control groups is warranted to validate these findings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".