Knee chondral lesions treated with autologous chondrocyte transplantation in a tridimensional matrix: clinical evaluation at 1-year follow-up
Bibliographic record
Abstract
BACKGROUND: Despite the many studies on chondral injury repair, no outcomes have been evaluated with the Western Ontario and McMaster (WOMAC) Universities osteoarthritis index, the Knee Injury and Osteoarthritis Outcome Score (KOOS), and the Oxford Knee Score, all of which are specific for evaluating the presence of osteoarthritis. MATERIALS AND METHODS: We evaluated the clinical progress of patients following autologous chondrocyte implantation (ACI) performed by our Bone and Tissue Bank using a technique in which cells, instead of being introduced to the articular defect in a liquid form, are implanted into a tridimensional matrix of semisolid collagen (Condrograft((R))). A total of 22 patients underwent the procedure, 15 of whom were available for a 1-year follow-up that included clinical evaluation by WOMAC score before and after surgery and KOOS and the Oxford Knee Score after surgery. RESULTS: The results were improved WOMAC score from 56.4 before surgery to 16.2 after surgery (P < 0.002), average KOOS score of 83.6, and average Oxford Knee Score of 18.8. CONCLUSIONS: These results indicate that our tridimensional matrix technique effectively improved patients' quality of life, at least in the short term, and delayed any subsequent procedure. Long-term assessment is necessary to determine the true value of this technique.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".