Suppr超能文献

多排螺旋冠状动脉 CT 血管造影与运动心电图在疑似冠心病患者中的预测价值。

Prognostic value of multidetector coronary computed tomography angiography in relation to exercise electrocardiogram in patients with suspected coronary artery disease.

机构信息

Division of Cardiology Severance Cardiovascular Hospital, Yonsei University College of Medicine, Yonsei University Health System, Seoul, South Korea.

出版信息

J Am Coll Cardiol. 2012 Nov 20;60(21):2205-15. doi: 10.1016/j.jacc.2012.08.981. Epub 2012 Oct 24.

Abstract

OBJECTIVES

This study was designed to determine the prognostic value of multidetector coronary computed tomography angiography (CTA) in relation to exercise electrocardiography (XECG) findings.

BACKGROUND

The prognostic usefulness of coronary CTA findings of coronary artery disease in relation to XECG findings has not been explored systematically.

METHODS

Patients with suspected coronary artery disease who had undergone both coronary CTA and XECG (<90 days between tests) from 2003 through 2009 were enrolled retrospectively. Coronary CTA results were classified according to the severity of maximal stenosis (normal, mild: <40% of luminal stenosis, moderate: 40% to 69%, severe: ≥70%), XECG results were categorized as positive and negative, and Duke XECG score was calculated. Clinical follow-up data were collected for major adverse cardiac events (MACE): cardiac death, nonfatal myocardial infarction, unstable angina requiring hospitalization, and revascularization after 90 days from index coronary CTA. C-statistics were calculated to compare discriminatory values of each test.

RESULTS

Among the 2,977 (58 ± 10 years) study patients, 12% demonstrated positive XECG results. By coronary CTA, patients were categorized as normal (56%) or having mild (26%), moderate (13%), or severe (5%) disease. During a median follow-up of 3.3 years (interquartile range: 2.3 to 4.6), 97 MACE were observed and the 5-year cumulative event rate was 3.6% (95% confidence interval: 3.0 to 4.3). Although both XECG (C-statistic: 0.790) and coronary CTA (C-statistic: 0.908) improved risk stratification beyond clinical risk factors (C-statistic: 0.746, p < 0.05 for all), XECG in addition to coronary CTA (C-statistic: 0.907) did not provide better discrimination than coronary CTA alone (p = 0.389). In subgroup analyses, coronary CTA stratified risk of MACE in groups with both positive and negative XECG results (all p < 0.001 for trend). However, positive XECG results predicted risk of MACE on coronary CTA only in the moderate stenosis group (hazard ratio: 2.58, 95% confidence interval: 1.29 to 5.19, p = 0.008) and severe stenosis group (hazard ratio: 2.28, 95% confidence interval: 1.19 to 4.38, p = 0.013).

CONCLUSIONS

In patients with suspected coronary artery disease, coronary CTA discriminates future risk of MACE in patients independent of XECG results. Compared with coronary CTA, XECG has an additive prognostic value only in patients with moderate to severe stenosis on coronary CTA.

摘要

目的

本研究旨在确定多排冠状动脉计算机断层血管造影(CTA)与运动心电图(XECG)检查结果的相关性对预后的评估价值。

背景

冠状动脉 CTA 对冠状动脉疾病的发现与 XECG 检查结果的相关性的预后价值尚未被系统地研究过。

方法

回顾性纳入了 2003 年至 2009 年间接受过冠状动脉 CTA 和 XECG(两次检查之间<90 天)检查的疑似冠状动脉疾病患者。根据最大狭窄程度的严重程度对冠状动脉 CTA 结果进行分类(正常、轻度:管腔狭窄<40%、中度:40%至 69%、重度:≥70%),将 XECG 结果分为阳性和阴性,并计算 Duke XECG 评分。收集主要不良心脏事件(MACE)的临床随访数据:心脏死亡、非致死性心肌梗死、需要住院的不稳定型心绞痛和指数冠状动脉 CTA 后 90 天内的血运重建。计算 C 统计量以比较各检测方法的判别值。

结果

在 2977 名(58±10 岁)研究患者中,12%的患者 XECG 结果为阳性。根据冠状动脉 CTA,患者被分为正常(56%)或轻度(26%)、中度(13%)或重度(5%)疾病。在中位数为 3.3 年(四分位间距:2.3 至 4.6)的随访期间,观察到 97 例 MACE,5 年累积事件发生率为 3.6%(95%置信区间:3.0 至 4.3)。尽管 XECG(C 统计量:0.790)和冠状动脉 CTA(C 统计量:0.908)均提高了临床危险因素之外的风险分层(C 统计量:0.746,p<0.05),但 XECG 加上冠状动脉 CTA(C 统计量:0.907)并不能提供比冠状动脉 CTA 单独更好的判别能力(p=0.389)。在亚组分析中,冠状动脉 CTA 在 XECG 结果阳性和阴性的两组中均分层了 MACE 的风险(所有趋势的 p<0.001)。然而,在中度和重度狭窄组,阳性 XECG 结果仅能预测冠状动脉 CTA 上的 MACE 风险(危险比:2.58,95%置信区间:1.29 至 5.19,p=0.008)和严重狭窄组(危险比:2.28,95%置信区间:1.19 至 4.38,p=0.013)。

结论

在疑似冠状动脉疾病患者中,冠状动脉 CTA 独立于 XECG 结果对未来 MACE 风险进行了区分。与冠状动脉 CTA 相比,XECG 仅在冠状动脉 CTA 中度至重度狭窄的患者中具有附加的预后价值。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验