Role of Platelet-Rich Plasma (PRP) in Early Stages of Knee Osteoarthritis
Bibliographic record
Abstract
Background: Osteoarthritis (OA) is the most prevalent chronic joint disorder worldwide and is associated with significant pain and disability. The primary objective in knee OA treatment focus on pain reduction, joint mobility improvement, as well as the reduction of disease progression and to preserve patients’ independence and quality of life. The aim of the present study was to evaluate the effectiveness of Platelet-rich plasma (PRP) for the management of early knee OA.Methods: This experimental study was conducted in NITOR from February 2021 to June 2021. Total 30 patients were purposively selected. Pain and functional improvement were measured using the Visual Analogue Scale (VAS) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) respectively. All patients were followed up for 3 months.Results: Almost 63% of the patients were female and their mean age was 59±7.58 years. Among them, 86.7% were in Kellgren-Lawrence grade 2. The mean duration of the disease was 16.3±9.1 months. Both VAS and WOMAC score has improved significantly in every follow up from baseline (VAS score 7.52±0.68 at baseline, 5.6±1.03 after 1 month of intervention and 4.24±1.27 after 3 months, p-value <0.05; WOMAC score 73.02±4.22 at baseline, 59.64±3.42 after 1 month of intervention and 53.26±4.65 after 3 months, p-value is <0.05).Conclusion: Intra-articular platelet-rich plasma improves pain and function of the knee in patients with 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".