A Mobile Terminal-based Nomogram for Early Predicting Severity of Acute Pancreatitis

Abstract

Background: Early prediction of the severity of acute pancreatitis (AP) is important but there is no preferred method in China. We aimed to develop and validate a simple-to-use predictive nomogram for persistent organ failure (POF) on admission in patients with AP. Methods: Data from 816 consecutive patients was obtained from internal (Chengdu) retrospective datasets and formed the training cohort for nomogram development. Data from 398 and 880 consecutive patients from internal (Chengdu) and external (Nanchang) prospective datasets formed the validation cohorts (all admitted < 48 hours of symptom onset). Univariate and multivariate logistic regressions were used to identify independent prognostic factors to establish the nomogram for POF. The calibration curves, concordance index (C-index), decision curve analysis (DCA), and clinical impact curve (CIC) were used to evaluate the performance of the nomogram and its clinical utility. The area under the receiver-operating characteristic curve (AUC) with 95% CI and likelihood ratio as well as post-test probability were applied. Measurements and main results: Age, respiratory rate, albumin, lactate dehydrogenase, oxygen support, and pleural effusion were identified as independent prognostic factors for POF and were included in the nomogram model (web-based calculator: https://shina.shinyapps.io/DynNomapp/). This predictive nomogram had good predictive ability for POF (C-indexes of 0.88, 0.91 and 0.81 for the training and two validation cohorts) and promising clinical utility (DCA: better or equivalent than prognostic scores; CIC: high clinical net benefit). The AUC of (0.91 [0.88-0.94] and 0.81 [0.79-0.84]), negative likelihood ratio (NLR 0.11 and 0.29), post-test probability of negative (0.9% and 6.7%) of the nomogram were superior in predicting POF than all other routinely used clinical prognostic scoring systems in both validation cohorts. Similar findings were observed for predicting major infection (superior to other prognostic scores) and mortality (superior or equally to others). Conclusions: The validated nomogram comprises 6 independent prognostic factors to predict major clinical outcomes of patients with AP in two distinct Chinese centers. This mobile terminal-based nomogram should be validated in other settings and considered for clinical practice and trial allocation, until more accurate biomarkers are discovered.