Wang Yasong, Wu Xuan, Wang Yue, Zhang Zhiqiang, Liu Xuanze, Sun Dongyuan, Liu Xue, Zhou Tienan, Wang Xiaozeng
Graduate School of Dalian Medical University, Dalian Medical University, Dalian, 116044, People's Republic of China.
State 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 China.
J Inflamm Res. 2025 Jan 28;18:1303-1316. doi: 10.2147/JIR.S496007. eCollection 2025.
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).
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).
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.
The SIRI-based nomogram is a valuable prognostic tool for predicting short-term ARAEs in patients with acute uncomplicated Type B IMH.
本研究旨在开发并验证一种基于全身炎症反应指数（SIRI）的列线图，以预测急性单纯性B型壁内血肿（IMH）患者的短期主动脉相关不良事件（ARAEs）。
我们回顾性分析了2018年4月至2024年4月期间诊断为急性单纯性B型IMH的332例患者。根据30天观察期内ARAEs的发生情况，将患者分为稳定组（N = 225）和恶化组（N = 107）。使用中性粒细胞、单核细胞和淋巴细胞计数计算SIRI。ARAEs定义为与主动脉疾病相关的死亡，以及IMH进展为主动脉夹层或穿透性主动脉溃疡。纳入SIRI和其他重要临床变量开发列线图。使用曲线下面积（AUC）、校准曲线、决策曲线分析（DCA）和净重新分类指数（NRI）评估模型的性能。
在332例患者中，217例为男性（65.4%），平均年龄为64.3±9.4岁。多因素逻辑回归和LASSO回归分析确定SIRI、贫血、糖尿病、主动脉最大直径（MDAD）和溃疡样突出（ULP）为ARAEs的独立预测因素。开发了两个列线图模型：临床模型，包括贫血、糖尿病、MDAD和ULP；以及临床 - SIRI模型，将SIRI纳入临床模型。临床 - SIRI模型显示出更高的预测准确性，AUC为0.788（95%CI：0.740 - 0.831），而临床模型的AUC为0.742（95%CI：0.691 - 0.788，P = 0.012）。如连续NRI为0.521（95%CI：0.301 - 0.743）所示，SIRI提高了预测准确性。校准曲线和DCA进一步支持了临床 - SIRI模型的临床实用性。
基于SIRI的列线图是预测急性单纯性B型IMH患者短期ARAEs的有价值的预后工具。
