Assessing the severity of ischemic colitis: validation of a CT scan severity score in 174 consecutive patients.
retrospective_cohort · Level III
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- Also identified by DOI 10.1007/s00330-026-12417-7.
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Abstract
To validate a previously published CT-based severity score of ischemic colitis and to propose a potential improvement by assessing severity using clinical, biological, and CT criteria. This retrospective single-center study included 174 patients (mean age, 73 ± 12 years; 85 men) with ischemic colitis diagnosed between 2014 and 2023. All underwent contrast-enhanced CT. Severe ischemic colitis was defined by death within 1 month, necrosis at colonoscopy, surgery, or superior mesenteric artery stenting. Clinical, biological, and CT features were compared between severe and non-severe cases. The Montpellier CT severity score was applied to the cohort. Logistic regression was used to test additional CT predictors and to propose a modified score. Among 174 patients, 97 (56%) had non-severe and 77 (44%) had severe ischemic colitis. The Montpellier score showed 68% sensitivity, 81% specificity, and an AUC of 0.78 (95% CI: 0.71-0.85). Multivariate analysis identified decreased wall enhancement, right colon involvement, and peritoneal effusion as additional severity predictors. A modified score including decreased wall enhancement achieved 71% sensitivity, 80% specificity, and an AUC of 0.80 (95% CI: 0.73-0.86). CT-based severity scoring was useful in predicting severe ischemic colitis. Montpellier score and modified Montpellier score (adding the decreased wall enhancement criterion) appeared to be reliable tools in practice. Question Severe ischemic colitis remains difficult to diagnose, and CT imaging provides objective criteria to differentiate between mild and life-threatening forms. Findings A validated CT-based severity score accurately stratifies patients and improves diagnostic performance in clinical practice. Clinical relevance CT-based severity scoring helps identify patients with ischemic colitis who are at high risk of adverse outcomes, supporting timely surgical decision-making and improving clinical management.