Predictive Value of Imaging-Based Classifications for Conservative Management Failure in Isolated Superior Mesenteric Artery Dissection.

BACKGROUND

Isolated superior mesenteric artery dissection (ISMAD) is a relatively uncommon vascular disease with uncertain optimal management. Multiple imaging-based classifications have been developed, but their ability to predict conservative management failure remains unclear.

OBJECTIVES

This study aimed to compare the predictive performance of 8 ISMAD classification systems for conservative management failure.

METHODS

This multicenter retrospective study included 156 patients with ISMAD from 3 centers in China (October 2009 to February 2023). The median computed tomography angiography follow-up time was 7.9 months (IQR: 3.7-24.3). Patients were classified using 8 systems and grouped as successful (108 of 156, 69.2%) or failed (48 of 156, 30.8%) conservative management. Performance was evaluated by model fit (Akaike Information Criterion, Bayesian Information Criterion), discrimination (C-statistic), net reclassification improvement, calibration, and decision curve analysis.

RESULTS

Compared with the successful group, patients who failed conservative management had a longer duration of abdominal pain before admission (8 [IQR: 3-30] days vs 4 [IQR: 1-11] days; P = 0.0214) and more severe superior mesenteric artery degree of stenosis (0.83 [IQR: 0.69-1.00] vs 0.64 [IQR: 0.52-1.00]; P = 0.00544). Among all classifications, Tan's classification showed good model fit (Akaike Information Criterion = 186; Bayesian Information Criterion = 226), the highest discrimination (C-statistic = 0.750; 95% CI: 0.670-0.830), and the greatest improvement (net reclassification improvement = 0.593; 95% CI: 0.244-0.903). It also demonstrated good calibration and yielded the highest net benefit across clinically relevant threshold probabilities in decision curve analysis.

CONCLUSIONS

Tan's classification showed the best overall performance in predicting conservative management failure and may help guide timely interventions.