Li Zhennan, Chen Yuan, Guo Junxia, Zhang Yan, Hou Zhihui, An Yunqiang, Gao Yang, Lu Bin
Heart Center of Henan Provincial People's Hospital, Central China Fuwai Hospital, Central China Fuwai Hospital of Zhengzhou University, Zhengzhou, Henan 450003, People's Republic of China; Department of Radiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, People's Republic of China.
Department of Radiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, People's Republic of China.
Int J Cardiol. 2020 Aug 15;313:114-120. doi: 10.1016/j.ijcard.2020.03.041. Epub 2020 Mar 19.
Prior studies provided limited data regarding natural history of initially medically treated type A intramural hematoma (IMH).
To develop predictive models for adverse aorta-related events in patients with type A IMH.
We performed a retrospective pooled analysis of individual patient data, including baseline clinical and CT characteristics. All patients enrolled were followed up for adverse aorta-related events, defined as a composite of aortic disease-related death and the presence of aortic complications that required aortic invasive treatment.
A total of 172 patients (52.9% men) were included, with a mean age of 61.1 ± 11.2 years. During a median follow-up time of 770.5 (45.3-1695.8) days, 60 patients (34.9%) experienced adverse aorta-related events. In Cox regression model for predicting adverse aorta-related events, hypertension (HR = 3.78, p = .067), MAD (HR = 1.05, p = .018), presence of ULP (HR = 2.43, p = .002) and pericardial effusion (HR = 1.65, p = .061) were independently associated with adverse aorta-related events. A majority of the adverse aorta-related events (n = 46, 76.7%) occurred within acute and subacute phase (90 days) of IMH. In predictive model for 90 days aortic events, MAD≥50.7 mm (OR = 2.79, p = .006) and presence of ULP (OR = 3.20, p = .002) were independent predictors. C statistic of the predictive model were 0.71 (p < .001).
Predictive models including baseline clinical and CT characteristics as predictors allow for accurate estimation of risk of adverse aorta-related events in patients with type A IMH. The proposed predictive models are helpful for risk estimates and decision making.
先前的研究提供了关于初始接受药物治疗的A型壁内血肿（IMH）自然史的有限数据。
建立A型IMH患者主动脉相关不良事件的预测模型。
我们对个体患者数据进行了回顾性汇总分析，包括基线临床和CT特征。所有纳入的患者均随访主动脉相关不良事件，该事件定义为主动脉疾病相关死亡与需要主动脉侵入性治疗的主动脉并发症的综合。
共纳入172例患者（52.9%为男性），平均年龄61.1±11.2岁。在中位随访时间770.5（45.3 - 1695.8）天期间，60例患者（34.9%）发生主动脉相关不良事件。在预测主动脉相关不良事件的Cox回归模型中，高血压（HR = 3.78，p = 0.067）、最大主动脉直径（MAD）（HR = 1.05，p = 0.018）、存在破口（ULP）（HR = 2.43，p = 0.002）和心包积液（HR =
