Ahmad Ali, Shelly-Cohen Michal, Corban Michel T, Murphree Dennis H, Toya Takumi, Sara Jaskanwal D, Ozcan Ilke, Lerman Lilach O, Friedman Paul A, Attia Zachi I, Lerman Amir
Department of Cardiovascular Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55902, USA.
Department of Medicine, Division of Cardiology, National Defense Medical College, Tokorozawa, Saitama, Japan.
Eur Heart J Digit Health. 2021 Oct 14;2(4):597-605. doi: 10.1093/ehjdh/ztab084. eCollection 2021 Dec.
The current gold standard comprehensive assessment of coronary microvascular dysfunction (CMD) is through a limited-access invasive catheterization lab procedure. We aimed to develop a point-of-care tool to assist clinical guidance in patients presenting with chest pain and/or an abnormal cardiac functional stress test and with non-obstructive coronary artery disease (NOCAD).
This study included 1893 NOCAD patients (<50% angiographic stenosis) who underwent CMD evaluation as well as an electrocardiogram (ECG) up to 1-year prior. Endothelial-independent CMD was defined by coronary flow reserve (CFR) ≤2.5 in response to intracoronary adenosine. Endothelial-dependent CMD was defined by a maximal percent increase in coronary blood flow (%ΔCBF) ≤50% in response to intracoronary acetylcholine infusion. We trained algorithms to distinguish between the following outcomes: CFR ≤2.5, %ΔCBF ≤50, and the combination of both. Two classes of algorithms were trained, one depending on ECG waveforms as input, and another using tabular clinical data. Mean age was 51 ± 12 years and 66% were females ( = 1257). Area under the curve values ranged from 0.49 to 0.67 for all the outcomes. The best performance in our analysis was for the outcome CFR ≤2.5 with clinical variables. Area under the curve and accuracy were 0.67% and 60%. When decreasing the threshold of positivity, sensitivity and negative predictive value increased to 92% and 90%, respectively, while specificity and positive predictive value decreased to 25% and 29%, respectively.
An artificial intelligence-enabled algorithm may be able to assist clinical guidance by ruling out CMD in patients presenting with chest pain and/or an abnormal functional stress test. This algorithm needs to be prospectively validated in different cohorts.
目前评估冠状动脉微血管功能障碍（CMD）的金标准是通过有限介入的有创导管实验室检查。我们旨在开发一种即时护理工具，以协助对出现胸痛和/或心脏功能应激试验异常且患有非阻塞性冠状动脉疾病（NOCAD）的患者进行临床指导。
本研究纳入了1893例NOCAD患者（血管造影狭窄<50%），这些患者在1年之前接受了CMD评估以及心电图（ECG）检查。内皮非依赖性CMD通过冠状动脉内注射腺苷后冠状动脉血流储备（CFR）≤2.5来定义。内皮依赖性CMD通过冠状动脉内注入乙酰胆碱后冠状动脉血流最大百分比增加（%ΔCBF）≤50%来定义。我们训练算法以区分以下结果：CFR≤2.5、%ΔCBF≤50以及两者的组合。训练了两类算法，一类以ECG波形作为输入，另一类使用表格形式的临床数据。平均年龄为51±12岁，66%为女性（n = 1257）。所有结果的曲线下面积值在0.49至0.67之间。在我们的分析中，对于CFR≤2.5这一结果，使用临床变量时表现最佳。曲线下面积和准确率分别为0.67%和60%。当降低阳性阈值时，敏感性和阴性预测值分别增至92%和90%，而特异性和阳性预测值分别降至25%和29%。
一种基于人工智能的算法或许能够通过排除出现胸痛和/或功能应激试验异常的患者的CMD来协助临床指导。该算法需要在不同队列中进行前瞻性验证。
