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非缺血性扩张型心肌病风险分层的新兴技术:JACC 本周综述专题。

Emerging Techniques for Risk Stratification in Nonischemic Dilated Cardiomyopathy: JACC Review Topic of the Week.

机构信息

Department of Cardiovascular Sciences, University of Leicester and the National Institute for Health Research (NIHR) Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom.

Department of Cardiovascular Medicine, National Heart & Lung Institute, Imperial College, London, United Kingdom; Department of Cardiology, National Heart Centre Singapore, Singapore.

出版信息

J Am Coll Cardiol. 2020 Mar 17;75(10):1196-1207. doi: 10.1016/j.jacc.2019.12.058.

Abstract

Dilated cardiomyopathy (DCM) is a common condition, which carries significant mortality from sudden cardiac death and pump failure. Left ventricular ejection fraction has conventionally been used as a risk marker for sudden cardiac death, but has performed poorly in trials. There have been significant advances in the areas of cardiac magnetic resonance imaging and genetics, which are able to provide useful rick prediction in DCM. Biomarkers and cardiopulmonary exercise testing are well validated in the prediction of risk in heart failure; however, they have been tested less specifically in the DCM setting. This review will discuss these methods with a view toward multiparametric risk assessment in DCM with the hope of creating parametric risk models to predict sudden cardiac death and pump failure in the DCM population.

摘要

扩张型心肌病(DCM)是一种常见疾病,其导致的心脏性猝死和泵衰竭的死亡率较高。左心室射血分数一直以来都被用作心脏性猝死的风险标志物,但在临床试验中的表现不佳。在心脏磁共振成像和遗传学领域已经取得了重大进展,这些进展能够为 DCM 提供有用的风险预测。生物标志物和心肺运动试验在心力衰竭风险预测方面得到了很好的验证;然而,它们在 DCM 环境中的测试并不那么具体。本综述将讨论这些方法,以期对 DCM 进行多参数风险评估,希望建立参数风险模型来预测 DCM 人群中的心脏性猝死和泵衰竭。

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