Risk factor analysis and nomogram development for survival prediction in obese patients with severe acute pancreatitis: a retrospective study.

Background: Currently, there is a lack of nomograms specifically designed to predict mortality risk in obese patients with severe acute pancreatitis (SAP). The aim of our study is to develop a predictive model tailored to this population, enabling more accurate anticipation of overall survival.

Methods: The study included obese patients diagnosed with SAP between January 1, 2016, and December 31, 2023. 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. An independent cohort was used for external validation. 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 394 patients were included in the study, with 341 in the survival group and 53 in the deceased group. The results of the multivariate logistic analysis revealed that age, total bilirubin, blood urea nitrogen, potassium, activated partial thromboplastin time, and malignancy were independent predictors for the survival of obese patients with SAP. The nomogram exhibited superior performance compared to the Sequential Organ Failure Assessment (SOFA) score (P = 0.011). In the external validation cohort, the nomogram maintained good discrimination and showed improved reclassification over SOFA. Additionally, the calibration curve demonstrated satisfactory predictive accuracy, while DCA highlighted the clinical utility of the nomogram.

Conclusion: Key demographic and laboratory parameters associated with the survival of obese SAP patients have been identified. These parameters were used to develop an accurate, user-friendly nomogram, potentially serving as an effective and valuable clinical tool for clinicians.