Trends in feline perianesthetic death postmortem submissions from a referral teaching hospital and general practices in Saskatchewan (Canada) and a proposed postmortem checklist
Bibliographic record
Abstract
Lesions associated with perianesthetic death (PAD) postmortem submissions are infrequently reported in the literature, with no studies comparing findings between general and referral practices (RPs). This study compared PAD postmortem submissions in cats from a referral teaching hospital (referral practice, RP) and general practices (GP) in Saskatchewan. In the RP, death was most commonly due to euthanasia (15/23, 65%), with most cases having severe underlying disease. In GP, most deaths were unassisted (37/45, 82%), and most animals (33/37, 89%) had an undiagnosed condition or an unknown cause of death. The American Society of Anesthesiologists (ASA) physical status classification was high (ASA III-V) in 16/23 (70%) of RP cases and low (ASA I-II) in 38/45 (85%) of GP cases. Cats with limited medical history accounted for 5/23 (22%) of the RP submissions and 17/45 (38%) of the GP submissions. Reporting of gross examination findings and tissues collected for histologic examination were inconsistent. For example, although the presence of negative pressure within the thoracic cavity is evaluated routinely during a complete postmortem examination, its presence (or absence) was only reported in 4/45 (9%) of cases where the animal died unassisted. No significant difference was found in determining the cause of death between RP and GP when euthanized cases were excluded ( P = .445). A standardized perianesthetic postmortem checklist is proposed to enhance reporting and improve diagnostic consistency.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".