Tibiofemoral chondromalacia treated with platelet-rich plasma and hyaluronic acid
Bibliographic record
Abstract
Background: The objective of the present study was to determine if platelet rich plasma (PRP) can increase tibiofemoral cartilage regeneration and improve knee function. Methods: Fourty consecutive and strictly selected patients affected by grade II or III chondromalacia underwent 1 yr of treatment (nine injections) with autologous PRP in a liquid form with 2.0 to 2.5-fold platelet concentration (20 cases) or with hyaluronic acid (HA) (20 patients). Outcome measures included the Lysholm, Tegner, International Knee Documentation Committee (IKDC), Western Ontario and McMaster (WOMAC) Osteoarthritis Index, and Short Form (SF)-36 scores. MRI arthroscopic and histologic assessment were used to evaluate cartilage thickness and degree of degeneration before and after treatment (1 yr after the primary arthroscopy). Results: The study demonstrated significant improvement in Lysholm, Tegner, IKDC, WOMAC, and SF-36 scores in both groups. Cartilage assessment revealed no significant macroscopic or microscopic structural regeneration as well as no cartilage height increase in either group. Higher content of chondrocytes and proteoglycans in cartilage was proven in both groups after treatment without a statistically significant difference between the groups. There were no adverse events observed. Conclusions: PRP and HA significantly reduced pain and improved quality of life in patients with a low degree of cartilage degeneration. MRI and arthroscopic assessment did not confirm any significant cartilage structural improvement. The content of chondrocytes and proteoglycans in cartilage was higher in the PRP group than in the HA group after the treatment but did not reach statistical significance.
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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) | 0.001 | 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".