Development and internal validation of a practical model to predict 30 days mortality of severe acute pancreatitis patients

BACKGROUND: Severe acute pancreatitis (SAP) is a common disease in the intensive care unit (ICU) accompanied by high mortality, the purpose of this study was to build a prediction model for the 30 days mortality of SAP. METHODS: We retrospectively reviewed 149 patients with SAP after admission in 48 h to the ICU of the First Affiliated Hospital of Nanjing Medical University between January 2015 and December 2019. Clinical variables including gender, age, blood routine, and biochemical indicators were collected. On the basis of these variables, stepwise regression analysis was carried out to establish the model. A bootstrapping technique was applied for internal validation. RESULTS: Age, aspartate aminotransferase (AST), alkaline phosphatase (ALP), triglycerides (TG), and creatinine (CREA) were differences between survivors and nonsurvivors groups (all p < 0.1). Multivariate analysis suggested that age, AST, ALP, TG, and CREA were independent variables. Then, a model was established. The area-under-the curve (AUC) of the model was 0.875 (95% confidence interval (CI): 0.811–0.924). After internal validation, the C-index was 0.859 (95% CI: 0.786–0.932). CONCLUSION: Our study has built a refined model with easily acquired biochemical parameters to predict 30 days mortality of SAP admitted to ICU. This model will require external and prospective validation prior to translate into clinical management.