Do Platelet-Rich Plasma Injections for Knee Osteoarthritis Work?
Bibliographic record
Abstract
BACKGROUND: Recent evidence suggests a benefit in platelet-rich plasma injections (PRP) for the knee in the management of mild to moderate osteoarthritis (OA). There is a reported reduction in pain, stiffness, and improved function. However, there is very little level-one literature available that supports this practice and conclusively proves a benefit gained throughout the course. Three main randomized control trials (RCTs) conducted in North America are often referenced and cited to prove their efficacy. This study aimed to look at the outcomes of patients having undergone this treatment to determine if there was any benefit. AIMS: This study aimed to determine if PRP injections administered in patients with knee OA over a six to eight-week time period demonstrated any benefit. METHODS: The Western Ontario and McMaster Universities arthritis index (WOMAC) tool was used before each of the three PRP injections over the six to eight-week period, and six weeks after the final injection in 31 patients. Each injection was given spaced two to three weeks apart. The outcomes observed were pain, stiffness, and physical function, and the total WOMAC score was calculated. RESULTS: The third injection showed a reduction in total WOMAC score, pain, stiffness, and physical function by 16.36%, 16.37%, 5.12%, and 18.03%, respectively. However, all scores returned close to baseline at the sixth-week follow-up post treatment. CONCLUSION: Results showed a trend of reduction in the WOMAC score. However, they are overall indicative of a placebo effect from the injections. Further studies are needed to explore whether the grade of OA and patients' weight have a significant impact on the 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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".