心脏MRI预测扩张性心肌病中心脏猝死风险的临床研究

Study on Predicting the Risk of Sudden Cardiac Death in Dilated Cardiomyopathy Using Cardiac MRI

目的本研究旨在确定心脏MRI心肌组织特征预测心源性猝死(sudden cardiac death,SCD)的相关因素,并探讨非缺血性扩张型心肌病(dilated cardiomyopathy,DCM)的SCD分层算法。方法纳入了在2020年1月至2021年12月期间接受心脏MRI检查的非缺血型扩张型心肌病成人患者。与SCD相关的事件包括SCD、适当的植入性心律转复除颤器休克和心脏骤停后的复苏。竞争风险回归分析和Kaplan-Meier分析用于确定心肌组织特征与预后的关系。结果858名参与者中,70名(8%)参与者在中位数33.0个月的随访中经历了SCD相关事件。在多变量竞争风险分析中,晚期Gd增强(LGE)(危险比[HR],1.87;95%CI:1.07,3.27;P=0.03)、自然T1(每10毫秒增加一次:HR,1.07;95%CI:1.04,1.11;P<0.001)和细胞外体积分数(每增加3%:HR,1.26;95%CI:1.11,1.44;P<0.001)是调整收缩压、房颤和左心室射血分数后SCD相关事件的独立预测因素。结合本地T1和LGE制定了SCD风险分层类别。自然T1值高于平均值(1382毫秒)4或以上的参与者每年SCD相关事件的发生率最高,为9.3%,而天然T1值为2,低于平均值(1292毫秒)且LGE为负值的参与者的SCD相关事件发生率最低,为0.6%。这一类别具有良好的预测能力(C=0.74),可用于区分SCD风险和竞争性心力衰竭风险。结论来自心脏MRI的心肌组织特征是非缺血性扩张型心肌病患者心源性猝死(SCD)相关事件的独立预测因子,可用于根据不同的SCD风险类别对参与者进行分层。

Objective This study aims to determine whether cardiac MRI myocardial tissue characterization can be used to predict sudden cardiac death(SCD)events,and to explore the SCD stratification algorithm for non ischemic dilated cardiomyopathy(DCM).Methods Adult patients with non ischemic dilated cardiomyopathy who underwent cardiac MRI examination between January 2020 and December 2021 were included.Events related to SCD include SCD,appropriate implantable cardioverter defibrillator shock,and resuscitation after cardiac arrest.Competitive risk regression analysis and Kaplan Meier analysis were used to determine the relationship between myocardial tissue characteristics and prognosis.Results Out of 858 participants,70(8%)experienced SCD related events during a median follow-up of 33.0 months.In multivariate competitive risk analysis,late Gd enhancement(LGE)(hazard ratio[HR],1.87;95%CI:1.07,3.27;P=0.03),natural T1(increase every 10 milliseconds:HR,1.07;95%CI:1.04,1.11;P<0.001),and extracellular volume fraction(increase every 3%:HR,1.26;95%CI:1.11,1.44;P<0.001)were independent predictors of SCD related events after adjusting for systolic blood pressure,atrial fibrillation,and left ventricular ejection fraction.SCD risk stratification categories have been developed based on local T1 and LGE.Participants with a natural T1 value higher than the average(1382 milliseconds)of 4 or more had the highest incidence of SCD related events per year,at 9.3%,while participants with a natural T1 value of 2,lower than the average(1292 milliseconds),and a negative LGE had the lowest incidence of SCD related events,at 0.6%.This category has good predictive power(C=0.74)and can be used to distinguish between SCD risk and competitive heart failure risk.Conclusion Myocardial tissue features from cardiac MRI are independent predictors of sudden cardiac death(SCD)related events in patients with non ischemic dilated cardiomyopathy,and can be used to stratify participants based on different SCD risk categories.