Risk factors for medial meniscal injury in association with cranial cruciate ligament rupture
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To determine the significant risk factors for medial meniscal injury in naturally occurring cranial cruciate ligament rupture and to quantify the risk using multivariate analysis. METHODS: A retrospective case control study was performed of dogs that had undergone surgery for cranial cruciate ligament rupture. Data recorded included patient signalment (age, breed and sex), the duration of the lameness, the extent of the cranial cruciate ligament rupture (complete or partial) and the condition of the medial meniscus. Logistic regression was used to analyse the relationship between these variables and tears in the medial meniscus. RESULTS: One hundred and sixty-one of 443 stifles (36·3%) in 366 dogs had a medial meniscal tear. The risk of a medial meniscal tear was increased by 12·9 times in association with complete cranial cruciate ligament rupture (OR 12·9; 95% CI 6·8 to 24·2), by approximately 2·6% for each additional week of lameness (OR 1·026; 95% CI 1·009 to 1·043) and by approximately 1·4% for each additional kilogram of bodyweight (OR 1·014; 95% CI 1·000 to 1·028). Golden retrievers and Rottweilers were at increased risk and West Highland white terriers were at reduced risk of medial meniscal tears compared with Labrador retrievers. CLINICAL SIGNIFICANCE: To minimise the risk of medial meniscal tears, surgical stabilisation should not be unnecessarily delayed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it