[Predictive value of left ventricular ejection fraction reserve assessed by SPECT G-MPI for major adverse cardiovascular event in patients with coronary artery disease].

狼牙棒 射血分数 心脏病学 内科学 医学 冠状动脉疾病 SSS公司* 接收机工作特性 心肌灌注成像 冲程容积 心肌梗塞 心力衰竭 经皮冠状动脉介入治疗
作者
Yi‐Hua Zhou,Yao Lu,Jianfeng Meng,Tiantian Mou,Yingjie Bai,Shutian Zhang,Yiqing Zheng,Qiuju Deng,Jian Jiao,Chang Zhao,X F Xie,M K Yun,Haiyi Mi,Xiaolin Li,X L Zhang
出处
期刊:PubMed [National Institutes of Health]
卷期号:51 (6): 626-632 被引量:1
标识
DOI:10.3760/cma.j.cn112148-20220919-00730
摘要

Objective: To evaluate the prognostic value of left ventricular ejection fraction (LVEF) reserve assessed by gated SPECT myocardial perfusion imaging (SPECT G-MPI) for major adverse cardiovascular event (MACE) in patients with coronary artery disease. Methods: This is a retrospective cohort study. From January 2017 to December 2019, patients with coronary artery disease and confirmed myocardial ischemia by stress and rest SPECT G-MPI, and underwent coronary angiography within 3 months were enrolled. The sum stress score (SSS) and sum resting score (SRS) were analyzed by the standard 17-segment model, and the sum difference score (SDS, SDS=SSS-SRS) was calculated. The LVEF at stress and rest were analyzed by 4DM software. The LVEF reserve (ΔLVEF) was calculated (ΔLVEF=stress LVEF-rest LVEF). The primary endpoint was MACE, which was obtained by reviewing the medical record system or by telephone follow-up once every twelve months. Patients were divided into MACE-free and MACE groups. Spearman correlation analysis was used to analyze the correlation between ΔLVEF and all MPI parameters. Cox regression analysis was used to analyze the independent factors of MACE, and the optimal SDS cutoff value for predicting MACE was determined by receiver operating characteristic curve (ROC). Kaplan-Meier survival curves were plotted to compare the difference in the incidence of MACE between different SDS groups and different ΔLVEF groups. Results: A total of 164 patients with coronary artery disease [120 male; age (58.6±10.7) years] were included. The average follow-up time was (26.5±10.4) months, and a total of 30 MACE were recorded during follow-up. Multivariate Cox regression analysis showed that SDS (HR=1.069, 95%CI: 1.005-1.137, P=0.035) and ΔLVEF (HR=0.935, 95%CI: 0.878-0.995, P=0.034) were independent predictors of MACE. According to ROC curve analysis, the optimal cut-off to predict MACE was a SDS of 5.5 with an area under the curve of 0.63 (P=0.022). Survival analysis showed that the incidence of MACE was significantly higher in the SDS≥5.5 group than in the SDS<5.5 group (27.6% vs. 13.2%, P=0.019), but the incidence of MACE was significantly lower in the ΔLVEF≥0 group than in theΔLVEF<0 group (11.0% vs. 25.6%, P=0.022). Conclusions: LVEF reserve (ΔLVEF) assessed by SPECT G-MPI serves as an independent protective factor for MACE, while SDS is an independent risk predictor in patients with coronary artery disease. SPECT G-MPI is valuable for risk stratification by assessing myocardial ischemia and LVEF.目的: 探讨门控单光子发射计算机断层成像心肌灌注显像(SPECT G-MPI)评估的左心室射血分数(LVEF)储备对冠心病患者主要不良心血管事件(MACE)的预测价值。 方法: 本研究为回顾性队列研究。纳入2017年1月至2019年12月诊断为冠心病,行负荷+静息SPECT G-MPI提示有心肌缺血,且在3个月内行冠状动脉造影的住院患者。以17节段5分法,获得负荷总积分(SSS)和静息总积分(SRS),计算总差值分(SDS,SDS=SSS-SRS)。采用4DM软件获得负荷和静息状态下LVEF,计算LVEF储备(ΔLVEF,ΔLVEF=负荷LVEF-静息LVEF)。记录病历系统中再住院MACE情况或每12个月随访1次,随访终点为患者发生MACE。根据是否发生MACE将患者分为无MACE组和MACE组。采用Spearman相关性分析探讨ΔLVEF与所有MPI参数的相关性。采用Cox回归分析预测MACE的独立影响因素,并通过受试者工作特征(ROC)曲线确定预测MACE的最佳SDS截断值。绘制Kaplan-Meier生存曲线,比较不同SDS组和不同ΔLVEF组MACE发生率的差异。 结果: 最终纳入164例冠心病患者,年龄为(58.6±10.7)岁,其中男性120例。随访(26.5±10.4)个月,共30例发生MACE。Cox多因素回归分析示SDS(HR=1.069,95%CI:1.005~1.137,P=0.035)和ΔLVEF(HR=0.935,95%CI:0.878~0.995,P=0.034)为预测MACE的独立影响因素。根据受试者工作特征ROC曲线分析,SDS预测MACE的最佳截断值为5.5,曲线下面积为0.63(P=0.022)。生存分析示,SDS≥5.5组MACE发生率高于SDS<5.5组(27.6%比13.2%,P=0.019),ΔLVEF<0组MACE发生率高于ΔLVEF≥0组(25.6%比11.0%,P=0.022)。 结论: SPECT G-MPI评估的LVEF储备为预测MACE的独立保护因素,而SDS为独立危险因素。SPECT G-MPI可以通过评估心肌缺血和LVEF储备预测冠心病患者的预后。.

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