Survival outcomes and prognostic indicators in canine pancreatitis: A retrospective cohort study of acute kidney injury and concurrent diseases

Abstract

Background and Aim: Canine pancreatitis is often complicated by acute kidney injury (AKI) and systemic comorbidities, both of which may worsen clinical outcomes. This study aimed to evaluate survival rates in dogs with pancreatitis, stratified by the presence of AKI and other concurrent diseases, and to identify prognostic indicators for mortality. Materials and Methods: A retrospective cohort study was conducted at Prasu Arthorn Veterinary Teaching Hospital, Mahidol University, Thailand, from February 2021 to February 2023. Medical records of 146 dogs diagnosed with pancreatitis (serum canine pancreatic lipase ≥400 µg/L and clinical signs) were reviewed. Dogs were categorized into four groups: Pancreatitis alone (n = 24), pancreatitis with AKI (n = 28), pancreatitis with concurrent diseases (n = 57), and pancreatitis with both AKI and concurrent diseases (n = 34). Survival was analyzed using Kaplan–Meier curves and log-rank tests, while prognostic factors were assessed using Cox proportional hazards regression. Results: The overall mortality rate was 39.72% (58/146), with the highest mortality in dogs with AKI (Groups 2 and 4). Median survival was 4 days (95% confidence interval [CI]: 0.0–11.7) in Group 2 and 7 days (95% CI: 2.7–11.2) in Group 4, while median survival was not reached in Groups 1 and 3 due to high survival. Hematocrit (HCT) and blood urea nitrogen-to-creatinine ratio (BCR) were identified as independent predictors of mortality. Lower HCT (Hazard ratio [HR] = 0.967, 95% CI: 0.941–0.994, p = 0.019) and higher BCR (HR = 1.024, 95% CI: 1.007–1.041, p = 0.006) were significantly associated with increased risk of death. Conclusion: AKI is a major negative prognostic factor in canine pancreatitis, markedly reducing survival irrespective of concurrent systemic diseases. Readily available markers, such as HCT and BCR, provide practical tools for early triage and prognostic stratification. Incorporating these parameters into clinical decision-making may enhance outcomes by guiding intensive monitoring and targeted interventions.