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28 June 2016 : Clinical Research  

Noninvasive Cardiac Quantum Spectrum Technology Effectively Detects Myocardial Ischemia

Ke LiABCDEF, Qiao XueBCDE, Mohan LiuBCDE, Xiaoqin ZhengBCDE, Rui ChenBCDE, Yufeng LiABCE, Qing DanBCE, Danqun FangBCE

DOI: 10.12659/MSM.895480

Med Sci Monit 2016; 22:2235-2242

Abstract

BACKGROUND: A standard resting electrocardiogram (ECG) shows limited sensitivity and specificity for the detection of coronary artery disease (CAD). Several analytic methods exist to enhance the sensitivity and specificity of resting ECG for diagnosis of CAD. We compared a new computer-enhanced, resting ECG analysis device, the cardiac quantum spectrum (CQS) technique, with coronary angiography in the detection of CAD.

MATERIAL AND METHODS: A consecutive sample of 93 patients with a history of suspected CAD scheduled for coronary angiography was evaluated with CQS before coronary angiography. The sensitivity and specificity of CQS and standard 12-lead ECG for detecting hemodynamically relevant coronary stenosis were compared, using coronary angiography as the reference standard. Kappa analysis was performed to assess the agreement between CQS severity scores and the level of stenosis determined by coronary angiography.

RESULTS: The CQS system identified 78 of 82 patients with hemodynamically relevant stenosis (sensitivity, 95.1%; specificity, 63.6%; accuracy, 91.4%; positive predictive value, 95.1%; negative predictive value, 63.6%). Sensitivity and accuracy were much higher for CQS analysis than for the standard ECG. The Kappa value, assessing the level of agreement between CQS and coronary angiography, was 0.376 (P<0.001).

CONCLUSIONS: CQS analysis of resting ECG data detects hemodynamically relevant CAD with high sensitivity and specificity.

Keywords: Coronary Angiography - methods, Coronary Stenosis - diagnosis, Electrocardiography - methods, Heart - physiopathology, Hemodynamics - physiology, Image Processing, Computer-Assisted - methods, Myocardial Ischemia - physiopathology, Prospective Studies

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750