COMPARISON OF CORTICOSTEROID AND PLATELET-RICH PLASMA (PRP) INJECTIONS FOR SYMPTOMATIC RELIEF IN KNEE OSTEOARTHRITIS: A RANDOMIZED CONTROLLED STUDY
Bibliographic record
Abstract
Background: Osteoarthritis (OA) of the knee is a prevalent and disabling condition with limited long-term treatment options. This study evaluates the effectiveness of corticosteroid versus platelet-rich plasma (PRP) injections in alleviating pain and improving function in patients with knee OA. Methods: This randomized controlled trial included patients diagnosed with knee OA, divided into two treatment groups: corticosteroid injections and PRP injections. Visual Analog Scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores were measured at baseline, 1 month, 3 months, 6 months, and 12 months post-treatment to assess pain and functional improvement. Incidence of adverse effects was also recorded. The PRP group demonstrated significantly lower VAS scores than the corticos Results: teroid group at each time interval (p<0.05). WOMAC scores were also improved in the PRP group, particularly by 6 and 12 months. Adverse effects were more frequent and severe in the corticosteroid group, with PRP showing a safer profile and more sustainable symptom relief. PRP i Conclusion: njections appear to offer superior, longer-term symptom relief for knee OA compared to corticosteroids, particularly for early-stage OA. Further research is recommended to optimize PRP administration and confirm long-term outcomes.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".