Abstract
OBJECTIVES: Acute mesenteric ischemia (AMI) is a rare disease with a relatively high mortality rate. We aimed to investigate the factors influencing in-hospital mortality in AMI patients and develop a nomogram for early risk stratification. METHODS: Clinical data of AMI patients hospitalized from January 2013 to October 2025 were retrospectively analyzed. Univariate and multivariate logistic regression identified independent pre-treatment risk factors, and a nomogram was constructed. Discrimination, calibration, and clinical utility were evaluated using receiver operating characteristic curve analysis, Hosmer-Lemeshow test, calibration curves, and decision curve analysis (DCA), with Bootstrap internal validation. Subgroup validation was performed by age, sex, and other subgroups. A further adjusted multivariate model examined associations of early clinical characteristics and treatments with mortality. RESULTS: Among 235 patients, 44 died in hospital (18.7%). Advanced age, heart failure, higher white blood cell (WBC), and creatinine were independent predictors. The model showed good discrimination (Bootstrap area under the curve: 0.849, 95% CI: 0.780-0.909) and fit (Hosmer-Lemeshow: χ² = 10.111, P = 0.257), with good calibration and net benefit on DCA. Performance remained stable across subgroups. Further analysis that incorporated early clinical characteristics and treatment measures found that age, heart failure, WBC, aspartate aminotransferase, anticoagulation therapy, and vasopressor use were associated with mortality. Anticoagulation therapy was negatively correlated with mortality risk, whereas vasopressor use was positively correlated with mortality risk. CONCLUSIONS: This study identified risk factors for in-hospital mortality in AMI patients and developed a predictive nomogram model. This aids in early high-risk patient identification, timely intervention, optimized treatment decisions, and improved patient outcomes.