Effects of Calcified Cartilage on Healing of Chondral Defects Treated with Microfracture in Horses
Bibliographic record
Abstract
BACKGROUND: Microfracture of full-thickness articular defects has been shown to significantly enhance the amount of repair tissue. However, there is a suggestion that leaving calcified cartilage inhibits this repair response. HYPOTHESIS: Removal of the calcified cartilage with retention of subchondral bone enhances the amount of attachment of the repair tissue compared with retention of the calcified cartilage layer. STUDY DESIGN: Controlled laboratory study. METHODS: There were 1-cm(2) articular cartilage defects made in 12 skeletally mature horses on the axial weightbearing portion of both medial femoral condyles. Using a custom measuring device and direct arthroscopic observation of the subchondral bone beneath the calcified cartilage layer, the authors removed the calcified cartilage from 1 defect of each horse. The repair was assessed with arthroscopy, clinical examination, radiographic and magnetic resonance imaging examinations, biopsy at 4 months, gross and histopathologic examinations at 12 months, as well as mRNA and immunohistochemical evaluations. RESULTS: Removal of calcified cartilage with retention of the subchondral bone plate increased the overall repair tissue as assessed by arthroscopic (4 months) and gross evaluation (12 months). An increase in the level of the subchondral bone was also observed with removal of the calcified cartilage layer. The clinical pain, radiographic examinations, magnetic resonance imaging evaluations, histologic character, matrix proteins, or mRNA expression do not appear to differ based on level of defect debridement. CLINICAL RELEVANCE: Removal of the calcified cartilage layer appears to provide optimal amount and attachment of repair tissue. Therefore, close arthroscopic visualization is recommended for debridement of clinical lesions to ensure removal of the calcified cartilage layer.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".