Development and Validation of the Systemic Inflammatory Response Index-Based Nomogram for Predicting Short-Term Adverse Events in Patients With Acute Uncomplicated Type B Aortic Intramural Hematoma

Abstract

Yasong Wang,1,2 Xuan Wu,2 Yue Wang,2 Zhiqiang Zhang,2 Xuanze Liu,2 Dongyuan Sun,2 Xue Liu,2 Tienan Zhou,2 Xiaozeng Wang2 1Graduate School of Dalian Medical University, Dalian Medical University, Dalian, 116044, People’s Republic of China; 2State Key Laboratory of Frigid Zone Cardiovascular Diseases, Cardiovascular Research Institute and Department of Cardiology, General Hospital of Northern Theater Command, Shenyang, 110016, People’s Republic of ChinaCorrespondence: Xiaozeng Wang, Department of Cardiology, Institute of Cardiovascular Research, General Hospital of Northern Theater Command, Shenhe District, Shenyang, Liaoning, 110016, People’s Republic of China, Tel [phone], Email [email protected]: This study aims to develop and validate a nomogram based on the Systemic Inflammatory Response Index (SIRI) to predict short-term aortic-related adverse events (ARAEs) in patients with acute uncomplicated Type B intramural hematoma (IMH).Patients and methods: We retrospectively analyzed 332 patients diagnosed with acute uncomplicated Type B IMH between April 2018 and April 2024. Patients were categorized into the stable group (N=225) and the exacerbation group (N=107) based on the occurrence of ARAEs within 30-day observation period. SIRI was calculated using neutrophil, monocyte, and lymphocyte counts. ARAEs were defined as death related to aortic disease, and the progression of IMH to aortic dissection or penetrating aortic ulcer. The nomogram was developed incorporating SIRI and other significant clinical variables. The model’s performance was evaluated using the area under the curve (AUC), calibration curves, decision curve analysis (DCA), and net reclassification index (NRI).Results: Among the 332 patients, 217 were male (65.4%), with a mean age of 64.3± 9.4 years. Multivariate logistic regression and LASSO regression analyses identified SIRI, anemia, diabetes, maximum diameter of aortic diameter (MDAD), and ulcer like projection (ULP) as independent predictors of ARAEs. Two nomogram models were developed: the Clinical model, including anemia, diabetes, MDAD, and ULP; and the Clinical-SIRI model, incorporating SIRI to the Clinical model. The Clinical-SIRI model demonstrated higher predictive accuracy, with an AUC of 0.788 (95% CI: 0.740– 0.831), compared to the Clinical model’s AUC of 0.742 (95% CI: 0.691– 0.788, P = 0.012). SIRI improved predictive accuracy, as shown by a continuous NRI of 0.521 (95% CI: 0.301– 0.743). Calibration curves and DCA further supported the clinical utility of the Clinical-SIRI model.Conclusion: The SIRI-based nomogram is a valuable prognostic tool for predicting short-term ARAEs in patients with acute uncomplicated Type B IMH.Plain Language Summary: This study introduces a novel nomogram that integrates the Systemic Inflammatory Response Index with clinical variables to enhance the prediction of adverse events in patients with Type B aortic intramural hematoma, a condition marked by highly variable clinical outcomes. The inclusion of this biomarker not only optimizes patient management but also aligns with the growing emphasis on precision in medical interventions.Keywords: Systemic inflammatory response Index, Type B aortic intramural hematoma, biomarkers, nomogram, prognosis

Keywords

• systemic inflammatory response index
• type b aortic intramural hematoma
• biomarkers
• nomogram
• prognosis.