The Effectiveness of Single Injection of Platelet-Rich Plasma for Knee Osteoarthritis Combined with Meniscus Injury: A Randomized Trial
Bibliographic record
Abstract
Objectives : To explore the effectiveness of single injection of platelet-rich plasma with rehabilitation therapy for knee osteoarthritis combined with meniscus injury. Methods : Forty patients who met the inclusion criteria were randomly assigned to a rehabilitation group (REH group, 20 cases) receiving rehabilitation training, and a platelet-rich plasma group (PRP group, 20 cases) receiving an ultrasound-guided single injection of PRP in combination with rehabilitation training. Rehabilitation training in the two groups lasted for 2 weeks, and the patients were evaluated using the short-form McGill pain questionnaire (SF-MPQ), Western Ontario McMaster Universities index (WOMAC score), and infrared thermography (knee-joint mean temperature) before treatment, at 1 week, 1 month and 6 months after treatment. Results : Two patients were lost to follow-up in both the PRP group and the REH group. Significant reductions in pain scores, WOMAC scores and knee temperature were observed at 1 week and 1 month after treatment in both groups (p < 0.05). Significant lower SF-MPQ scores were observed in the PRP group than in the REH group at 6 months followup (p < 0.01). Similarly, the mean knee temperature was significantly lower in the PRP group than in the REH group at 6 months follow-up (p < 0.01). No severe complications occurred in either group. Conclusions: Compared to rehabilitation therapy alone, single injection of platelet-rich plasma in combination with rehabilitation therapy has beneficial effect on pain, knee function and mean knee temperature in patients with KOA combined with meniscus injury. Single injection of platelet-rich plasma combined with rehabilitation therapy has a good short-term effectiveness.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".