Journal of the American Veterinary Medical Association · 2026
Development of a predictive model for estimation of postoperative risk following brachycephalic obstructive airway syndrome surgery.
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Ruzics Eva A, Reynolds Penny S, Morse Zechariah, Shipman Julia, Ham Kathleen M
Аннотация
OBJECTIVE: To identify risk factors for postoperative death and complications in dogs undergoing brachycephalic obstructive airway syndrome (BOAS) surgery and utilize this information to develop a predictive model for risk estimation.
METHODS: Records of dogs undergoing BOAS surgery at a veterinary teaching hospital between 2012 and 2023 were reviewed. Predictor variables were categorized into domains, including signalment, history, clinical signs, underlying pathology, acuity status, and surgeries performed. Outcomes were categorized as death, major complications, or minor complications. The association between outcomes and predictors was modeled by logistic regression. Results were reported as ORs and regression coefficients with 95% CIs. A predictive model was created to estimate risk of mortality and complications following BOAS surgery.
RESULTS: 297 cases were included. Twelve dogs (4%) died prior to discharge. Major complications (airway interventions and pneumonia) were reported for 29 dogs (10%). Major complications were strongly associated with emergent presentation (OR, 7.45; 95% CI, 2.70 to 20.59), female sex (OR, 2.78; 95% CI, 1.11 to 6.67), high-grade laryngeal collapse (OR, 4.28; 95% CI, 1.56 to 11.79), and history of regurgitation/vomiting (OR, 2.16; 95% CI, 0.87 to 5.38).
CONCLUSIONS: Risk factors for postoperative death and complications were identified. A predictive model was developed, allowing estimation of postoperative risk based on individual patient factors.
CLINICAL RELEVANCE: A multivariable predictive model may be useful in clinical practice to obtain individualized postoperative risk predictions to contribute to prognostication, decision-making, and triage. However, as this model has not been externally validated, calculated risk should be utilized with caution and consideration for the clinical picture of each patient.
METHODS: Records of dogs undergoing BOAS surgery at a veterinary teaching hospital between 2012 and 2023 were reviewed. Predictor variables were categorized into domains, including signalment, history, clinical signs, underlying pathology, acuity status, and surgeries performed. Outcomes were categorized as death, major complications, or minor complications. The association between outcomes and predictors was modeled by logistic regression. Results were reported as ORs and regression coefficients with 95% CIs. A predictive model was created to estimate risk of mortality and complications following BOAS surgery.
RESULTS: 297 cases were included. Twelve dogs (4%) died prior to discharge. Major complications (airway interventions and pneumonia) were reported for 29 dogs (10%). Major complications were strongly associated with emergent presentation (OR, 7.45; 95% CI, 2.70 to 20.59), female sex (OR, 2.78; 95% CI, 1.11 to 6.67), high-grade laryngeal collapse (OR, 4.28; 95% CI, 1.56 to 11.79), and history of regurgitation/vomiting (OR, 2.16; 95% CI, 0.87 to 5.38).
CONCLUSIONS: Risk factors for postoperative death and complications were identified. A predictive model was developed, allowing estimation of postoperative risk based on individual patient factors.
CLINICAL RELEVANCE: A multivariable predictive model may be useful in clinical practice to obtain individualized postoperative risk predictions to contribute to prognostication, decision-making, and triage. However, as this model has not been externally validated, calculated risk should be utilized with caution and consideration for the clinical picture of each patient.