Limb amputation for feline appendicular bone tumors results in excellent recovery outcomes and high owner satisfaction with a low incidence of complications
Bibliographic record
Abstract
Objective: To evaluate the recovery outcomes of cats following limb amputation for appendicular bone tumors. Methods: This retrospective, multi-institutional study included cats that underwent thoracic or pelvic limb amputation to treat primary appendicular bone tumors (2006 to 2019). Short- and long-term postoperative complications were investigated. Owners were surveyed to evaluate their perceptions and satisfaction regarding postoperative adaptation and recovery outcomes. Fisher exact tests were used to compare the results between different levels of amputation performed. Results: A total of 68 client-owned cats were included. Mild short-term (≤ 14 days) and long-term (> 14 days) postoperative complications were reported in 5 (7.4%) and 3 (4.4%) cats, respectively. Overall, time to return to walking without support was < 3 days in 69.7% of cats and 3 to 7 days in 16.7%. Activity level changes were reported as no change in 75.8% of cats. There were no behavioral changes in 92.3% of cats. Quality of life following amputation was recorded as excellent in 82.4% of cats. Owner satisfaction was reported as very satisfied, moderately satisfied, or satisfied in 98.5% of cats. There was no significant difference between thoracic limb and pelvic limb amputation in owner satisfaction or postoperative complications (short-term, OR = 0.39 [95% CI, 0.035 to 2.39]; long-term, OR = 0.41 [95% CI, 0.0074 to 5.39]). Conclusions: Most cats showed prompt and complete recovery following thoracic or pelvic limb amputation, with a high level of owner satisfaction and low incidence of postoperative complications. Clinical Relevance: Thoracic or pelvic limb amputation in cats can result in excellent recovery outcomes.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".