Long-term assessment of pancarpal arthrodesis performed on working dogs in New Zealand
Bibliographic record
Abstract
AIM: To determine the outcomes following unilateral pancarpal arthrodesis (PCA) in working dogs in New Zealand, in terms of return to work and ability, as assessed by the owner. METHODS: Working dogs treated using unilateral PCA were identified by searching the medical records of the Massey University Veterinary Teaching Hospital (MUVTH) by diagnosis and breed code. Eight Heading dogs (working Collies) and four New Zealand Huntaways were identified with carpal pathology that had been treated by dorsal-plate application, bone-grafting, and casting. All dogs were actively in work on sheep or cattle farms at the time of injury. Case files and radiographs were retrospectively analysed, and the ability of the dog to work after surgery and owner satisfaction with the outcome were assessed using a questionnaire conducted at a mean follow-up interval of 5 years. RESULTS: Following arthrodesis, 6/12 (50%) dogs could perform duties as before surgery. A further four (33%) dogs could perform most former duties. Ten of the twelve owners were satisfied or very satisfied with resultant mobility and work performance of their dogs. Post-operative complications occurred in 50% of dogs, but in only one case affected the eventual outcome. Eleven owners felt surgical repair was worthwhile in a trained working dog. CONCLUSIONS: Unilateral PCA carries a good prognosis for working dogs in New Zealand to return to work, even on hill-country properties. CLINICAL RELEVANCE: This study may allow veterinarians to provide a more accurate prognosis for working dogs requiring PCA. Working dogs that have sustained severe carpal injury including hyper-extension injury, luxation and fracture, or dogs with crippling carpal osteoarthrosis (OA) can return to work after PCA.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".