Intra-articular platelet-rich plasma (PRP) injections for treating knee pain associated with osteoarthritis of the knee in the Japanese population: a phase I and IIa clinical trial.
Bibliographic record
Abstract
Intra-articular platelet-rich plasma (PRP) injection has been found to be effective for treating osteoarthritis in patients from Western countries; however, the safety and efficacy of PRP have not been sufficiently investigated in Japanese patients. The present study aimed to evaluate the safety and feasibility of intra-articular PRP injection in Japanese patients with knee osteoarthritis. PRP without white blood cells was prepared using a single-spin centrifuge (PRGF-Endoret; BTI Biotechnology Institute, Vitoria, Spain). A 6-mL PRP volume was injected in the knee joint three times at 1 week intervals. All patients were prospectively evaluated before intervention and at 1, 3, and 6 months after the treatment. Adverse events, the Visual Analog Scale (VAS) pain score, Japanese Knee Osteoarthritis Measure (JKOM) score and Japanese Orthopedic Association score were evaluated. Ten patients (all women; average age, 60.6 years) were treated. Only minor adverse events after injection were noted, and symptoms resolved within 48 hours after the injection. The average VAS pain scores were 71.6 mm and 18.4 mm at baseline and the 6-month follow-up, respectively (P < 0.05). At the 6-month follow-up, 80% of patients had a decrease in the VAS pain score of 50% or more. The average JKOM scores were 35.2 and 14.3 at baseline and at the 1-month follow-up, respectively (P < 0.05). Intra-articular PRP injection likely represents a safe treatment option for Japanese patients with mild-to-moderate knee osteoarthritis, and has the potential to relieve pain for up to 6 months, but further study is needed to verify the efficacy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".