Development and validation of a computed tomography index for assessing outcomes in patients with acute pancreatitis: "SMART-CT" index.

Abstract

The existing CT indices do not allow quantitative prediction of clinical outcomes in acute pancreatitis (AP). The aim of this study was to develop and validate a revised CT index using a nomogram-based approach. This retrospective study comprised consecutive patients with AP who underwent contrast-enhanced CT between June 2017 and March 2019. 123 CT scans were randomly divided into training (n = 103) and validation groups (n = 20). Two radiologists analyzed CT scans for findings described in modified CT severity index and additional exploratory items (13 items). Seven items (pancreatic necrosis, number of collections, size of collections, ascites, pleural effusion, celiac artery involvement, and liver steatosis) found to be statistically significant were used for development of index. Synthetic minority oversampling technique (SMOTE) was employed to balance representation of minority classes and hence this index was named "SMOTE Application for Reading CT in AcuTe Pancreatitis (SMART-CT index)". Binomial logistic regression was used for development of prediction algorithm. Nomograms were then created and validated for each outcome. The new CT index had area under the curve (AUC) of 0.79 [95% CI 0.65-0.93], 0.66 (95% CI 0.54-0.77), 0.75 (95% CI 0.65-0.85), 0.83 (95% CI 0.69-0.96), 0.70 (95% CI 0.60-0.81), and 0.64 (95% CI 0.53-0.75) for mortality, intensive care unit (ICU) stay, length of hospitalization, length of ICU stay, number of admissions, and severity, respectively. The AUC of validation cohort was comparable to the training cohort. The novel nomogram-based index predicts occurrence of clinical outcome with moderate accuracy.