Construction and validation of a nomogram for predicting survival in diabetic patients with severe acute pancreatitis: A retrospective study from a tertiary center

Abstract

Background:
There is currently a lack of nomograms specifically designed for predicting the risk of death in diabetic patients with severe acute pancreatitis (SAP). The objective of this study was to develop a nomogram tailored to diabetic patients with SAP to predict overall survival.


Methods:
Diabetic patients diagnosed with SAP between January 1, 2018 and December 31, 2023 were included in the study. Risk factors were identified through least absolute shrinkage and selection operator regression analysis. Subsequently, a novel nomogram model was developed through multivariable logistic regression analysis. The predictive performance of the nomogram was evaluated using metrics such as the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA).


Results:
A total of 206 patients were included in the analysis, with 171 in the survival group and 35 in the deceased group. Multivariate logistic regression indicated that age, platelet, total bilirubin, and potassium were independent prognostic factors for the survival of diabetic patients with SAP. The nomogram demonstrated a performance comparable to sequential organ failure assessment (P = 0.570). Additionally, the calibration curve showed satisfactory predictive accuracy, and the DCA highlighted the clinical application value of the nomogram.


Conclusion:
We have identified key demographic and laboratory parameters that are associated with the survival of diabetic patients with SAP. These parameters have been utilized to create a precise and user-friendly nomogram, which could be an effective and valuable clinical tool for clinicians.