Distraction index as a risk factor for osteoarthritis associated with hip dysplasia in four large dog breeds<sup>*</sup>
Bibliographic record
Abstract
OBJECTIVE: To determine if age, breed, gender, weight or distraction index (DI) influenced the risk of radiographic osteoarthritis (OA) of canine hip dysplasia (CHD) in four common dog breeds; the American bulldog, Bernese mountain dog, Newfoundland and standard poodle. MATERIALS AND METHODS: This was a cross sectional prevalence study with 4349 dogs. Canine hips were evaluated using 3 radiographic projections: the hip-extended view, the compression view and the distraction view. The hip-extended view was examined for the presence of OA. The PennHIP distraction view was utilized to calculate the DI. For all breeds, a multiple logistic regression model incorporating age, weight, gender, and DI was created. For each breed, disease-susceptibility curves grouping dogs on the basis of age were constructed. Receiver-operating characteristic (ROC) curves were developed for each breed regardless of age. RESULTS: For all breeds, DI was the most significant risk factor for the development of OA associated with CHD. Weight and age were also significant risk factors in all four breeds, but gender was not. CLINICAL SIGNIFICANCE: Results from this study support previous findings, that irrespective of breed, the probability of radiographic OA increases with hip joint laxity as measured by the DI. Breed-specific differences in this relationship, however, warrant investigation of all breeds affected by CHD to determine inherent dependency of hip OA on joint laxity. Such findings guide veterinarians in helping dog breeders to make evidence-based breeding decisions and in informing dog owners to implement preventative treatments for CHD for dogs found to be at risk.
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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 | 0.000 |
| 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".