Efficacy of Intra-Articular Platelet-Rich Plasma Injections in Knee Osteoarthritis
Bibliographic record
Abstract
Introduction: Platelet-rich plasma (PRP) has been widely studied as a potential nonsurgical treatment for knee osteoarthritis. The current study was done to assess the effectiveness of PRP injections in terms of pain reduction and functional outcomes. Materials and Methods: In this prospective randomized clinical study, 50 patients with early osteoarthritis knees who met the inclusion criteria received two intra-articular pure PRP injections. Follow-up assessments were performed at 6 weeks, 3 months, 6 months, and 1 year for pain reduction measured on the Visual Analog Scale (VAS) and functional improvement assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire. The pre and post injection WOMAC and VAS scores were compared. A p value < 0.05 was considered significant. Results: Two intra-articular injections of PRP were administered to 50 patients. Female patients were 27(54%) and male 23(46%). Majority (60.%,n=30) of knees had grade II Osteoarthritis while 20(40%) knees had grade I Osteoarthritis. Each follow-up visit resulted in a significant improvement in pain reduction (VAS) and functional outcome (WOMAC), which maintained until the final follow-up appointment at one year. No complications were reported. Conclusion: Two intra-articular PRP injections in an early osteoarthritis knee resulted in a significant reduction in pain and improved functional results.
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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".