Development and validation of a composite score to predict severe forms of ischemic colitis.

<bold>Objective: </bold>To develop a simple scoring system in order to predict the risk of severe (death and/or surgery) ischemic colitis METHODS: In this retrospective study, 205 patients diagnosed with ischemic colitis in a tertiary hospital were consecutively included over a 6-year period. The study sample was sequentially divided into a training cohort (n = 103) and a validation cohort (n = 102). In the training cohort, multivariable analysis was used to identify clinical, biological, and CT variables associated with poor outcome and to build a risk scoring system. The discriminative ability of the score (sensitivity, specificity, positive predictive value, negative predictive value) was estimated in the two cohorts to externally validate the score, and a receiver operating characteristic curve was established to estimate the area under the curve of the score. Bootstrapping was used to validate the score internally.<bold>Results: </bold>In the training cohort, four independent variables were associated with unfavorable outcome: hemodynamic instability (2 pts), involvement of the small bowel (1 pt), paper-thin wall pattern (3 pts), no stratified enhancement pattern (1 pt). The score was used to categorize patients into low risk (score: 0, 1), high risk (score: 2-3), and very high risk (score: 4-7) groups with sensitivity and specificity of 97% and 67%, respectively, and a good discriminating capability, with a C-statistic of 0.94. Internal and external validation showed good discrimination capability (C-statistics of 0.9 and 0.84, respectively).<bold>Conclusion: </bold>A simple risk score can stratify patients into three distinct prognosis groups, which can optimize patient management.<bold>Clinical Trial Number: </bold>NCT04662268 KEY POINTS: • Simple scoring system predicting the risk of severe ischemic colitis • First study to include CT findings to the clinical and biological data used to determine a severity score. [ABSTRACT FROM AUTHOR]