MRI-based cartilage changes and clinical effectiveness of autologous intra-articular platelet-rich plasma injections in symptomatic patients with moderate osteoarthritis of the knee
Bibliographic record
Abstract
Abstract Background An autologous blood product containing a high percentage of various growth factors, cytokines, and modulating factors such as platelet-rich plasma (PRP) is thought to play a role in chondral remodeling by promoting the production of cartilage matrix molecules and repairing and regenerating articular cartilage. In symptomatic patients with moderate osteoarthritis (OA) of the knee, we aimed to investigate MRI-based cartilage changes and the clinical efficacy of autologous intra-articular PRP injections. Results Thirty-three patients with grades 2 and 3 OA of knees as per Kellgren and Lawrence OA classification underwent three consecutive PRP injections at monthly intervals. These patients were followed up monthly for the first 3 months, and then after every 3 months at 6 months, 9 months, and 12 months. There was statistically significant improvement in joint pain and functionality with the visual analogue scale (VAS) scores showing a reduction from 7 ± 2 at baseline to 2.76 ± 1.34 at 12 months and Western Ontario and McMaster Universities Osteoarthritis Index Score (WOMAC) scores declining from 77.91 ± 1 1.6 at baseline to 23.61 ± 19.1 at 12 months (p < 0.05). The reduction in VAS and WOMAC scores was maximum during the first 3 months after PRP therapy. MRI showed a statistically insignificant improvement in cartilage thickness [Whole Organ Magnetic Resonance Imaging Score (WORMS) 3.15 ± 1.41 to 3.3 ± 0.84) (p > 0.05)]. Conclusions PRP had a positive effect on pain alleviation and patient functioning, but there was no significant change in articular cartilage as measured by MRI.
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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 | 0.000 | 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".