The location‐specific healing response of damaged articular cartilage after ACL reconstruction: short‐term follow‐up
Bibliographic record
Abstract
Although many different interventions have been proposed for treating cartilage lesions at the time of ACL reconstruction, the normal healing response of these injuries has not been well documented. To address this point, we compared the arthroscopic status of chondral lesions at the time of ACL reconstruction with that obtained at second-look arthroscopy. We hypothesized that there might be a location-specific difference in the healing response of damaged articular cartilage. Between September 1998 and March 2000, 383 patients underwent arthroscopically-assisted hamstring ACL reconstruction without any intervention to the articular cartilage. Among these patients, 84 patients underwent second-look arthroscopy (ranging from 6 to 52 months following initial surgery) and make up the population of the present study. Chondral injuries, left untreated at ACL reconstruction, were arthroscopically evaluated using the Outerbridge classification, and were again evaluated at second-look arthroscopy. At second-look arthroscopy, there was significant recovery of chondral lesions by Outerbridge grading on both the medial and lateral femoral condyles. Among the recovered chondral lesions, 69% of cases of the medial femoral condyle, 88% of cases of the lateral femoral condyle were partial thickness injuries (grade I and II). Conversely, there was no significant recovery of chondral lesions observed at the patello-femoral joint or tibial plateaus. Our study revealed that there was a location-specific difference in the natural healing response of chondral injury. Untreated cartilage lesions on the femoral condlyes had a superior healing response compared to those on the tibial plateaus, and in the patello-femoral joint.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".