Int J Med Sci 2007; 4(5):249-263. doi:10.7150/ijms.4.249 This issue

Research Paper

Computerized two-lead resting ECG analysis for the detection of coronary artery stenosis

Eberhard Grube 1, Andreas Bootsveld 2, Seyrani Yuecel 1, Joseph T. Shen 3, Michael Imhoff 4

1. Department of Cardiology and Angiology, Heart Center Siegburg, Klinikum Siegburg, Ringstrasse 49, D-53721 Siegburg, Germany
2. Department of Cardiology, Evangelisches Stift St. Martin, Johannes-Mueller-Strasse 7, D-56068 Koblenz, Germany
3. Premier Heart, LLC, 14 Vanderventer Street, Port Washington, NY 11050, USA
4. Department for Medical Informatics, Biometrics and Epidemiology, Ruhr-University Bochum, Postbox, D-44780 Bochum, Germany

This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) License. See for full terms and conditions.
Grube E, Bootsveld A, Yuecel S, Shen JT, Imhoff M. Computerized two-lead resting ECG analysis for the detection of coronary artery stenosis. Int J Med Sci 2007; 4(5):249-263. doi:10.7150/ijms.4.249. Available from

File import instruction


Background: Resting electrocardiogram (ECG) shows limited sensitivity and specificity for the detection of coronary artery disease (CAD). Several methods exist to enhance sensitivity and specificity of resting ECG for diagnosis of CAD, but such methods are not better than a specialist's judgement. We compared a new computer-enhanced, resting ECG analysis device, 3DMP, to coronary angiography to evaluate the device's accuracy in detecting hemodynamically relevant CAD.

Methods: A convenience sample of 423 patients without prior coronary revascularization was evaluated with 3DMP before coronary angiography. 3DMP's sensitivity and specificity in detecting hemodynamically relevant coronary stenosis as diagnosed with coronary angiography were calculated as well as odds ratios for the 3DMP severity score and coronary artery disease risk factors.

Results: 3DMP identified 179 of 201 patients with hemodynamically relevant stenosis (sensitivity 89.1%, specificity 81.1%). The positive and negative predictive values for identification of coronary stenosis as diagnosed in coronary angiograms were 79% and 90% respectively. CAD risk factors in a logistic regression model had markedly lower predictive power for the presence of coronary stenosis in patients than did 3DMP severity score (odds ratio 3.35 [2.24-5.01] vs. 34.87 [20.00-60.79]). Logistic regression combining severity score with risk factors did not add significantly to the prediction quality (odds ratio 36.73 [20.92-64.51]).

Conclusions: 3DMP's computer-based, mathematically derived analysis of resting two-lead ECG data provides detection of hemodynamically relevant CAD with high sensitivity and specificity that appears to be at least as good as those reported for other resting and/or stress ECG methods currently used in clinical practice.

Keywords: coronary artery disease, electrocardiography, computer-enhanced, coronary imaging: angiography, sensitivity, specificity.