Radiographic and Arthroscopic Findings in the Elbow Joints of 263 Dogs with Medial Coronoid Disease
Bibliographic record
Abstract
OBJECTIVE: To report clinical, radiographic, and arthroscopic findings in dogs with thoracic limb lameness attributed solely to disease of the medial aspect of the coronoid process (MCP). STUDY DESIGN: Case series. ANIMALS: Dogs (n=263) with MCP disease (MCD; 437 elbows). METHODS: Clinical records (January 2000-July 2006) and radiographs were reviewed and pertinent data recorded. Radiographic interpretation included measures of periarticular osteophytosis, gross assessment of MCP integrity, and measurement of ulnar subtrochlear sclerosis (STS). Statistical analysis was performed to evaluate associations between data; confidence interval was set at 95%. RESULTS: Labrador Retrievers were 50.2% of all dogs with MCD. Mean age at diagnosis was 32 months and duration of lameness was 14.5 weeks. Thirteen elbows (3%) were considered radiographically normal. Osteophytosis was identified on the anconeal process (70.2%), radial head (37.3%), and lateral epicondyle (56.5%), and STS was identified in 86.7% of elbows. Median osteophytosis score was 1; mean absolute osteophytosis score was 1.7. Arthroscopic findings included: fissuring (18.3%) and fragmentation (64.1%) of the MCP and kissing lesions (49.0%) of elbows. Median-modified Outerbridge score of the MCP was 2 and the humeral condyle, 0. Weak or moderate correlations were found between osteophytosis and modified Outerbridge scores and weak correlation between modified Outerbridge scores of the MCP and medial humeral condyle. CONCLUSIONS: Wide ranges in clinical, radiographic, and arthroscopic findings are recognized in dogs with MCD but correlations between such factors are generally weak. Radiographic and arthroscopic findings do not correlate with owner-reported duration of lameness. CLINICAL RELEVANCE: Radiographic measures of osteophytosis are poor predictors of severity of arthroscopic pathology for MCD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".