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心脏再同步治疗短期临床反应的预测因素。

Predictors of short-term clinical response to cardiac resynchronization therapy.

机构信息

Department of Cardiology, Karolinska University Hospital, Stockholm, Sweden.

Division of Cardiovascular Medicine and the Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, USA.

出版信息

Eur J Heart Fail. 2017 Aug;19(8):1056-1063. doi: 10.1002/ejhf.795. Epub 2017 Mar 14.

DOI:10.1002/ejhf.795
PMID:28295869
Abstract

AIMS

Cardiac resynchronization therapy (CRT) reduces morbidity and mortality in patients with symptomatic heart failure and QRS prolongation but there is uncertainty about which patient characteristics predict short-term clinical response.

METHODS AND RESULTS

In an individual patient meta-analysis of three double-blind, randomized trials, clinical composite score (CCS) at 6 months was compared in patients assigned to CRT programmed on or off. Treatment-covariate interactions were assessed to measure likelihood of improved CCS at 6 months. MIRACLE, MIRACLE ICD, and REVERSE trials contributed data for this analysis (n = 1591). Multivariable modelling identified QRS duration and left ventricular ejection fraction (LVEF) as predictors of CRT clinical response (P < 0.05). The odds ratio for a better CCS at 6 months increased by 3.7% for every 1% decrease in LVEF for patients assigned to CRT-on compared to CRT-off, and was greatest when QRS duration was between 160 and 180 ms.

CONCLUSIONS

In symptomatic chronic heart failure patients (NYHA class II-IV), longer QRS duration and lower LVEF independently predict early clinical response to CRT.

摘要

目的

心脏再同步治疗(CRT)可降低有症状心力衰竭和 QRS 延长患者的发病率和死亡率,但对于哪些患者特征可预测短期临床反应尚不确定。

方法和结果

在三项双盲、随机试验的个体患者荟萃分析中,比较了 CRT 程控开启或关闭的患者在 6 个月时的临床综合评分(CCS)。评估了治疗协变量的相互作用,以衡量 6 个月时 CCS 改善的可能性。MIRACLE、MIRACLE ICD 和 REVERSE 试验为该分析提供了数据(n=1591)。多变量模型确定 QRS 持续时间和左心室射血分数(LVEF)是 CRT 临床反应的预测因素(P<0.05)。与 CRT 关闭相比,对于 CRT 开启的患者,LVEF 每降低 1%,6 个月时 CCS 更好的可能性增加 3.7%,而当 QRS 持续时间在 160 至 180ms 之间时,效果最大。

结论

在有症状的慢性心力衰竭患者(NYHA 分级 II-IV)中,较长的 QRS 持续时间和较低的 LVEF 独立预测 CRT 的早期临床反应。

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