A prognostic model based on metabolic indicators for recurrent acute pancreatitis in hypertriglyceridemia patients: a retrospective cohort study

BACKGROUND: Hypertriglyceridemic acute pancreatitis (HTG-AP) is associated with a high risk of recurrence. This study aimed to identify risk factors for HTG-AP recurrence and to develop a predictive model integrating metabolic and clinical indicators. METHODS: We retrospectively enrolled patients with HTG-AP treated at Weifang People's Hospital between January 2019 and October 2023. Independent predictors of recurrence were identified using univariate and multivariate Cox regression analyses, and a predictive model was constructed based on significant variables. A nomogram was developed to visualize the model. Kaplan-Meier analysis was used to assess recurrence risk across different risk strata. Model performance was evaluated using the C-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Internal validation was performed using bootstrap resampling and repeated cross-validation. RESULTS: = 0.007) as independent predictors of recurrence. A prediction model was established based on these variables. Kaplan-Meier curves showed good discrimination between risk groups. The model achieved an area under the ROC curve of 0.927, which was significantly higher than that of any individual predictor. Calibration analysis showed good agreement, and DCA demonstrated favorable clinical utility. CONCLUSION: This prediction model showed high accuracy for early risk stratification of HTG-AP recurrence and may support individualized follow-up and intervention strategies.