A combination of anatomical and functional evaluations improves the prediction of cardiac event in patients with coronary artery bypass

结合解剖学和功能性评估可以提高对冠状动脉旁路移植术患者心脏事件的预测准确性。

阅读:1

Abstract

OBJECTIVE: To study the usefulness of combined risk stratification of coronary CT angiography (CTA) and myocardial perfusion imaging (MPI) in patients with previous coronary-artery-bypass grafting (CABG). DESIGN: A retrospective, observational, single centre study. SETTING AND PATIENTS: 204 patients (84.3% men, mean age 68.7±7.6) undergoing CTA and MPI. MAIN OUTCOME MEASURES: CTA defined unprotected coronary territories (UCT; 0, 1, 2 or 3) by evaluating the number of significant stenoses which were defined as the left main trunk ≥50% diameter stenosis, other native vessel stenosis ≥70% or graft stenosis ≥70%. Using a cut-off value with receiver-operating characteristics analysis, all patients were divided into four groups: group A (UCT=0, summed stress score (SSS)<4), group B (UCT≥1, SSS<4), group C (UCT=0, SSS≥4) and group D (UCT≥1, SSS≥4). RESULTS: Cardiac events, as a composite end point including cardiac death, non-fatal myocardial infarction, unstable angina requiring revascularisation and heart-failure hospitalisation, were observed in 27 patients for a median follow-up of 27.5 months. The annual event rates were 1.1%, 2%, 5.7% and 12.9% of patients in groups A, B, C and D, respectively (log rank p value <0.0001). Adding UCT or SSS to a model with significant clinical factors including left ventricular ejection fraction, time since CABG and Euro SCORE II improved the prediction of events, while adding UCT and SSS to the model improved it greatly with increasing C-index, net reclassification improvement and integrated discrimination improvement. CONCLUSIONS: The combination of anatomical and functional evaluations non-invasively enhances the predictive accuracy of cardiac events in patients with CABG.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。