Cardiac Electrophysiology Unit, Cardiovascular Analytics Group, Hong Kong, China.
Second Department of Cardiology, Evangelismos General Hospital of Athens, Athens, Greece.
J Electrocardiol. 2022 May-Jun;72:28-34. doi: 10.1016/j.jelectrocard.2022.02.009. Epub 2022 Mar 2.
Brugada syndrome (BrS) is a rare disorder characterized by coved or saddle-shaped ST-segment elevation in the right precordial leads on the electrocardiogram. Risk stratification in BrS remains challenging. A number of clinical, electrocardiographic, programmed ventricular stimulation and genetic risk factors have been identified as important predictors of future major arrhythmic events. There is a positive association between the number of risk factors and arrhythmic events. Hence, a multi-parametric approach would provide comprehensive risk assessment and more accurate risk stratification, assisting in therapeutic decisions making, including implantable cardioverter-defibrillator placement or identification of low-risk individuals. However, the extent to which each variable influences the risk and non-linear interactions between the different risk variables make risk stratification challenging. This paper aims to provide a focused review of the multi-parametric risk models for BrS risk stratification published in the literature.
Brugada 综合征（BrS）是一种罕见的疾病，其特征是心电图上右胸前导联出现穹窿或马鞍形 ST 段抬高。BrS 的风险分层仍然具有挑战性。已经确定了许多临床、心电图、程控心室刺激和遗传危险因素，它们是未来发生主要心律失常事件的重要预测因素。危险因素的数量与心律失常事件之间存在正相关关系。因此，多参数方法可以提供全面的风险评估和更准确的风险分层，有助于治疗决策，包括植入式心脏复律除颤器的放置或识别低风险个体。然而，每个变量对风险的影响程度以及不同风险变量之间的非线性相互作用使得风险分层具有挑战性。本文旨在对文献中发表的 Brugada 综合征风险分层的多参数风险模型进行重点综述。
