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非阻塞性冠状动脉疾病患者应用冠状动脉计算机断层扫描血管造影术进行风险分层。

Risk Stratification With the Use of Coronary Computed Tomographic Angiography in Patients With Nonobstructive Coronary Artery Disease.

机构信息

Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA; Department of Radiology, University Hospital Freiburg, Freiburg, Germany.

Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.

出版信息

JACC Cardiovasc Imaging. 2021 Nov;14(11):2186-2195. doi: 10.1016/j.jcmg.2021.03.019. Epub 2021 Apr 14.

Abstract

OBJECTIVES

The purpose of this study was to develop a risk prediction model for patients with nonobstructive CAD.

BACKGROUND

Among stable chest pain patients, most cardiovascular (CV) events occur in those with nonobstructive coronary artery disease (CAD). Thus, developing tailored risk prediction approaches in this group of patients, including CV risk factors and CAD characteristics, is needed.

METHODS

In PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) computed tomographic angiography patients, a core laboratory assessed prevalence of CAD (nonobstructive 1% to 49% left main or 1% to 69% stenosis any coronary artery), degree of stenosis (minimal: 1% to 29%; mild: 30% to 49%; or moderate: 50% to 69%), high-risk plaque (HRP) features (positive remodeling, low-attenuation plaque, and napkin-ring sign), segment involvement score (SIS), and coronary artery calcium (CAC). The primary end point was an adjudicated composite of unstable angina pectoris, nonfatal myocardial infarction, and death. Cox regression analysis determined independent predictors in nonobstructive CAD.

RESULTS

Of 2,890 patients (age 61.7 years, 46% women) with any CAD, 90.4% (n = 2,614) had nonobstructive CAD (mean age 61.6 yrs, 46% women, atherosclerotic cardiovascular disease [ASCVD] risk 16.2%). Composite events were independently predicted by ASCVD risk (hazard ratio [HR]: 1.03; p = 0.001), degree of stenosis (30% to 69%; HR: 1.91; p = 0.011), and presence of ≥2 HRP features (HR: 2.40; p = 0.008). Addition of ≥2 HRP features to: 1) ASCVD and CAC; 2) ASCVD and SIS; or 3) ASCVD and degree of stenosis resulted in a statistically significant improvement in model fit (p = 0.0036; p = 0.0176; and p = 0.0318; respectively). Patients with ASCVD ≥7.5%, any HRP, and mild/moderate stenosis had significantly higher event rates than those who did not meet those criteria (3.0% vs. 6.2%; p = 0.007).

CONCLUSIONS

Advanced coronary plaque features have incremental value over total plaque burden for the discrimination of clinical events in low-risk stable chest pain patients with nonobstructive CAD. This may be a first step to improve prevention in this cohort with the highest absolute risk for CV events.

摘要

目的

本研究旨在为非阻塞性 CAD 患者建立风险预测模型。

背景

在稳定型胸痛患者中,大多数心血管 (CV) 事件发生在非阻塞性冠状动脉疾病 (CAD) 患者中。因此,需要为这群患者制定量身定制的风险预测方法,包括 CV 危险因素和 CAD 特征。

方法

在 PROMISE(前瞻性多中心成像研究评估胸痛)计算机断层血管造影患者中,核心实验室评估了 CAD 的患病率(非阻塞性 1%至 49%左主干或 1%至 69%狭窄任何冠状动脉)、狭窄程度(最小:1%至 29%;轻度:30%至 49%;或中度:50%至 69%)、高危斑块(HRP)特征(正性重构、低衰减斑块和餐巾环征)、节段受累评分(SIS)和冠状动脉钙化(CAC)。主要终点是不稳定型心绞痛、非致命性心肌梗死和死亡的综合终点。Cox 回归分析确定了非阻塞性 CAD 中的独立预测因子。

结果

在 2890 名患有任何 CAD 的患者(年龄 61.7 岁,46%为女性)中,90.4%(n=2614)患有非阻塞性 CAD(平均年龄 61.6 岁,46%为女性,动脉粥样硬化性心血管疾病 [ASCVD] 风险 16.2%)。复合事件独立预测因子为 ASCVD 风险(危险比 [HR]:1.03;p=0.001)、狭窄程度(30%至 69%;HR:1.91;p=0.011)和存在≥2 个 HRP 特征(HR:2.40;p=0.008)。将≥2 个 HRP 特征添加到:1)ASCVD 和 CAC;2)ASCVD 和 SIS;或 3)ASCVD 和狭窄程度,模型拟合度有统计学显著改善(p=0.0036;p=0.0176;和 p=0.0318;分别)。患有 ASCVD≥7.5%、任何 HRP 和轻度/中度狭窄的患者的事件发生率明显高于不符合这些标准的患者(3.0%比 6.2%;p=0.007)。

结论

在低危稳定型胸痛患者中,与非阻塞性 CAD 患者相比,高级冠状动脉斑块特征对临床事件的鉴别具有比总斑块负担更高的增量价值。这可能是提高该队列 CV 事件绝对风险预防的第一步。

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