A retrospective study of perianesthetic and sedation deaths in dogs and cats submitted to Canadian veterinary diagnostic laboratories.
Bibliographic record
Abstract
Background: Perianesthetic death or sedation death in companion animals is an infrequent but devastating complication. Few studies have investigated the pathology associated with these deaths. Objective: To determine clinical features and postmortem findings for submissions to multiple Canadian diagnostic laboratories from perianesthetic/sedation deaths in dogs and cats. Animals and procedure: Laboratory Information Management Systems were retrospectively reviewed for cases of perianesthetic/sedation death in dogs and cats. Inclusion criteria were: i) whole-body submissions and ii) death within 7 d after the procedure. Results: = 111, 58%). The American Society of Anesthesiologists physical status in these animals was low (ASA status I or II) in 94% of dogs (68/72) and 93% of cats (103/111). Clinical history was considered incomplete in 60.3% of cases (242/401). Conclusion and clinical relevance: These results had similar trends to those in previous studies that identified an important proportion of submissions for perianesthetic/sedation deaths lacked significant lesions to explain the cause of death. This study also identified spay/neuter procedures were involved in the largest proportion of submissions, despite their low pre-anesthetic/sedation 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".