Clinical findings and prognostic factors for immediate survival in 33 dogs undergoing surgery for biliary peritonitis
Bibliographic record
Abstract
OBJECTIVE: To report demographics, clinical signs, physical examination, diagnostic test results, surgical findings, and prognostic factors for in-hospital postoperative mortality following biliary peritonitis surgery in dogs. STUDY DESIGN: Retrospective, multi-institutional cohort study. ANIMALS: Thirty-three client-owned dogs. METHODS: The medical records of dogs that underwent surgery for biliary peritonitis between 2015 and 2021 were reviewed. Dogs were included if they had a definitive diagnosis of biliary peritonitis and a surgery report. Information on demographics, clinical signs and duration, physical examination findings, laboratory and diagnostic imaging results, surgery, perioperative medical treatment, and complications for each patient was obtained. Statistical analyses were performed to identify risk factors that affected survival. RESULTS: Cholecystectomy was the procedure most frequently performed (31/33, 94%). The overall mortality rate was 36% (12/33). Survival was affected negatively by hyperbilirubinemia (p = .049), administration of vasopressors (p = .002), renal dysfunction (p = .008), and number of postoperative complications (p = .005). A mortality rate of 50% was observed in dogs with a total bilirubin level greater than 60.5 μmol/L. There was no difference in mortality rate between septic and nonseptic biliary effusions. CONCLUSION: New prognostic factors associated with in-hospital postoperative mortality in dogs treated surgically for biliary peritonitis were identified, while others that had been reported previously were confirmed. A preoperative bilirubin threshold value associated with a 50% mortality was identified. CLINICAL SIGNIFICANCE: Additional information that could help to predict survival in dogs with biliary peritonitis has been provided. However, further research is warranted.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".