Comparison of the intraarticular injection of platelet rich plasma (PRGF®) and hyaluronic acid (Hyalone®) in the treatment of chondral lesions: a randomized, prospective clinical study
Bibliographic record
Abstract
Objective: To compare the effect of the intraarticular injection of platelet rich plasma (PRGF®) and hyaluronic acid (Hyalone®) in the treatment of degenerative cartilage lesions of the knee. Methods: A randomized, prospective open-label study was made to compare the clinical effect of treatment with platelet rich plasma (PRP) (PRGF®) and hyaluronic acid (Hyalone®) in patients with degenerative (not traumatic) chondral lesions of the knee. A total of 80 patients were randomized to two groups of 40 patients each. Clinical assessment was made initially and 6 months after treatment using the Knee Injury and Osteoarthritis Outcome Score (KOOS), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and a visual analogue scale (VAS). Results: Both groups showed significant improvements with respect to the baseline values. The patients treated with PRP showed greater pain reduction than those treated with hyaluronic acid, according to the VAS, with improvements of 2.08 (1.5) and 0.47 (1.7), respectively (PRGF® versus Hyalone®; p = 0.001). However, neither the WOMAC nor the KOOS showed differences between the two groups (p > 0.05). Conclusions: The intraarticular injection of PRP did not result in consistent greater clinical improvement versus hyaluronic acid after 6 months of follow-up. Although differences favourable to PRP were recorded with the VAS, they were not confirmed by the rest of the scales used. Level of evidence: IV.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".