Development and Evaluation of a Nomogram to Predict the Eventual Severity of the First Episode of Acute Pancreatitis.

Abstract

The aim of this research was to establish a nomogram for early prediction of the severity of acute pancreatitis (AP). A total of 1860 AP patients from 2013 to 2020 were included in this study. According to the 2012 revised Atlanta classification, patients were divided into nonsevere AP group and severe AP (SAP) group. The baseline characteristics and first laboratory indicators after admission between the 2 groups were analyzed using univariate and multivariate logistic regression analysis in training set. R language was used for establishing a predictive nomogram and further verified in validation set. Univariate and multivariate logistic regression analysis in the training set showed red blood cell distribution width, d -dimer, apolipoprotein A1, and albumin were independent factors for SAP. A predictive nomogram was accordingly established based on the 4 indicators. Validation on this predictive nomogram showed high internal validation concordance index of 0.940 (95% confidence interval, 0.922-0.958) and high external validation concordance index of 0.943 (95% confidence interval, 0.920-0.966). The calibration curve, receiver operating characteristic curve, and decision curve analysis all showed that the nomogram had good predictive ability. This nomogram may be an effective clinical tool for predicting the first episode of SAP.