Comparative Effect between Infiltration of Platelet-rich Plasma and the Use of Corticosteroids in the Treatment of Knee Osteoarthritis: A Prospective and Randomized Clinical Trial
Bibliographic record
Abstract
Abstract Objectives This study aimed to analyze the efficacy of platelet-rich plasma obtained from the peripheral, autologous blood of the patients in pain complaints reduction and functional improvement of knee osteoarthritis compared with the standard treatment with injectable corticosteroid, such as triamcinolone. Methods The patients were followed-up clinically at the preinfiltrative visit, with quantitative evaluation using the Knee Society Score (KSS), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, and the Kellgren and Lawrence scales. In addition, they were reevaluated with the same scales after 1 month and 6 months of intervention with 2.5 mL of triamcinolone acetate or 5 mL of platelet-rich plasma. The study was performed on 50 patients with knee osteoarthritis treated at the Medical Specialty Center and randomly divided into equivalent samples for each therapy. Results The present study verified the reduction of pain scores, such as the WOMAC score, and elevations of functional scales, such as the KSS, evidenced in 180 days when using platelet-rich plasma, a therapy that uses the autologous blood of the patient and has fewer side effects. Conclusion Although both platelet-rich plasma and corticosteroid therapies have been shown to be effective in the reduction pain complaints and functional recovery, there was a statistically significant difference between them at 180 days. According to the results obtained, platelet-rich plasma presented longer-lasting effects within 180 days in the treatment of 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".