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Prediction of adverse events in patients with initially medically treated type A intramural hematoma.
International Journal of Cardiology ( IF 3.2 ) Pub Date : 2020-03-19 , DOI: 10.1016/j.ijcard.2020.03.041
Zhennan Li 1 , Yuan Chen 2 , Junxia Guo 3 , Yan Zhang 4 , Zhihui Hou 2 , Yunqiang An 2 , Yang Gao 2 , Bin Lu 2
Affiliation  

Background

Prior studies provided limited data regarding natural history of initially medically treated type A intramural hematoma (IMH).

Objectives

To develop predictive models for adverse aorta-related events in patients with type A IMH.

Methods

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.

Results

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).

Conclusions

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.



中文翻译:

最初接受药物治疗的A型壁内血肿患者的不良事件预测。

背景

先前的研究提供了有关最初药物治疗的A型壁内血肿(IMH)的自然史的有限数据。

目标

为A型IMH患者的不良主动脉相关事件建立预测模型。

方法

我们对单个患者的数据进行了回顾性汇总分析,包括基线临床和CT特征。所有入组患者均接受了与主动脉相关的不良事件的随访,这些事件定义为与主动脉疾病相关的死亡和需要主动脉侵入性治疗的主动脉并发症的综合。

结果

包括172名患者(男性占52.9%),平均年龄为61.1±11.2岁。在770.5(45.3–1695.8)天的中位随访时间内,有60名患者(34.9%)经历了与主动脉相关的不良事件。在用于预测不良主动脉相关事件的Cox回归模型中,高血压(HR = 3.78,p  = .067),MAD(HR = 1.05,p  = .018),存在ULP(HR = 2.43,p  = .002)和心包积液(HR = 1.65,p  = .061)与不良的主动脉相关事件独立相关。大多数不良主动脉相关事件(n  = 46,76.7%)发生在IMH的急性和亚急性阶段(90天)内。在90天主动脉事件的预测模型中,MAD≥50.7mm(OR = 2.79,p = .006)和ULP的存在(OR = 3.20,p  = .002)是独立的预测因子。预测模型的C统计量为0.71(p  <.001)。

结论

包括基线临床和CT特征作为预测因子的预测模型可以准确估算A型IMH患者的不良主动脉相关事件的风险。所提出的预测模型有助于风险估计和决策。

更新日期:2020-03-19
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