Assessment of Sigmoidal Artery and Vein Diameters as Predictive Markers for Complications in Acute Sigmoid Diverticulitis: A Retrospective Observational Analysis

Background Acute sigmoid diverticulitis is a common inflammatory condition that can progress to severe complications such as abscess formation, fistulas, and perforation. While computed tomography (CT) is the gold standard for diagnosis, it offers limited prognostic information. Emerging evidence suggests that vascular changes in the sigmoidal arteries and veins may correlate with disease severity and serve as predictive markers for complications. Material/Methods This retrospective study analyzed 160 patients with confirmed acute sigmoid diverticulitis between May 2018 and May 2023. Patients were divided into two groups based on the presence of complications using the modified Hinchey classification: Group 1 (uncomplicated diverticulitis) and Group 2 (complicated diverticulitis). Vascular diameters were measured using contrast-enhanced CT scans, focusing on the sigmoidal arteries and veins. The study assessed the relationship between vascular diameters and disease severity using multivariate logistic regression, with receiver operating characteristic (ROC) curve analysis to determine diagnostic cut-off values. Results Patients with complicated diverticulitis exhibited significantly larger sigmoidal artery and vein diameters compared to those with uncomplicated disease (p < 0.001). The optimal cut-off values for predicting complications were 3.15 mm for the sigmoidal artery and 3.85 mm for the sigmoidal vein, with sensitivities of 78% and 82%, and specificities of 76% and 81%, respectively. Multivariate analysis confirmed that increased vascular diameters and elevated neutrophil-to-lymphocyte ratio (NLR) were independent predictors of complicated diverticulitis (p < 0.05). Conclusions Vascular measurements of the sigmoidal arteries and veins, along with inflammatory markers, can enhance the prediction of complications in acute sigmoid diverticulitis. These measurements may serve as valuable tools for guiding treatment decisions, potentially improving patient outcomes through early identification of high-risk cases.