An evaluation of a low‐cost platelet‐rich plasma for osteoarthritis of the knee: A pilot study
Bibliographic record
Abstract
Abstract Purpose To assess the characteristics and effectiveness of low‐cost platelet‐rich plasma (LC‐PRP) for knee osteoarthritis (OA) by evaluating its composition and effect on pain, function, satisfaction, safety and cost‐effectiveness. Methods Level IV evidence single‐arm prospective cohort pilot study of 20 subjects (30 knees total) with mild‐to‐moderate knee OA. Two LC‐PRP injections were performed, 3 weeks apart. Platelet extraction/yield, patient‐reported outcomes and incidence of adverse events were assessed with a primary endpoint of 6 months. A cost‐effectiveness analysis of LC‐PRP compared to corticosteroid injection was conducted. Results On average, this LC‐PRP preparation method allowed for recovery of 85% of platelets. Significant mean differences in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores (total, pain and function) and global assessment score were observed at all follow‐up points compared to baseline ( p < 0.05 for 1, 3, 6 and 12 months). Satisfaction was noted in 90% of patients at 6 months and 75% of patients at 12 months. No significant adverse events were reported. LC‐PRP was less costly ($654 vs. $1308) and yielded more QALYs (0.846 vs. 0.708) than corticosteroid injections. Per injection costs were estimated to be $10 for corticosteroid and $11 for LC‐PRP. Conclusions This pilot study demonstrates that LC‐PRP ($11) may significantly benefit patients with knee OA. LC‐PRP appears to be a safe, cost‐effective means for improving pain and function in knee OA. Level of Evidence Level IV.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".