Incidence of Bandage-Associated Complications in Cats following Clean Orthopaedic Procedures: A Retrospective Study of 152 Cases
Bibliographic record
Abstract
To report the incidence of bandage-associated complications in cats following clean orthopaedic injury.Multi-institutional retrospective case series of 152 client-owned cats. Medical records were searched for cats that had a bandage placed after a clean orthopaedic injury. Data collected included: signalment, diagnosis, anatomical region, orthopaedic procedure, professional role of the person applying the bandage (specialist/resident/nurse), bandage duration, complications, and outcomes.A total of 152 cats had bandages placed after clean orthopaedic injuries. Complications were reported in 104 cats (68.4%). Bandage-related complications were mild in 64.4% cases, moderate in 32.7% cases, and severe 2.9% of cases. If a cat had a splint placed, it was 3.4 times more likely to have a more severe complication compared with a cat which did not require a splint.Bandage complications occur frequently in cats, and the use of splints was a significant predictor of increased complication severity. Clinicians should be particularly vigilant when bandaging limbs in cats, as complications secondary to bandaging occur frequently. These findings underscore the importance of appropriate case selection for bandage application and monitoring strategies to minimize the risk of complications.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".