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Comparison of Cardiogoniometry and ECG at Rest Versus Myocardial Perfusion Scintigraphy

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Date 2014 Mar 12
PMID 24612044
Citations 2
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Abstract

Background: Cardiogoniometry (CGM) is a novel resting electrocardiac method based on computer-generated three-dimensional data derived from cardiac potentials. The purpose of this study was to determine CGM's and electrocardiography's (ECG) accuracy for detecting myocardial ischemia and/or lesions in comparison with stress/rest myocardial perfusion scintigraphy (single photon emission computer tomography [SPECT]).

Method: A cohort of consecutively enrolled patients (n = 100) with suspected or known coronary artery disease (mean age 67.8 years, 52% female) were examined by CGM and resting ECG before stress/rest myocardial scintigraphy.

Results: Pathological scintigraphy findings at adenosine stress perfusion (ASP) and/or rest were conclusively identified in 21 patients. Diagnostic sensitivity was 71% for CGM and 24% for ECG, specificity was 70% for CGM and 95% for ECG. Reversible ischemia was diagnosed in 16 of 21 patients with pathological scintigraphy results. In this subgroup, sensitivity was 67% for CGM and 25% for ECG.

Conclusions: At rest, the sensitivity of a CGM significantly surmounts that of a standard 12-lead ECG for detection of isolated myocardial ischemia or myocardial lesions revealed by scintigraphy/SPECT; specificity is in a reasonable range. CGM's ease of use and its considerable agreement with the results of myocardial scintigraphy, suggests a possible role for patient screening in the primary care setting.

Citing Articles

Reliable Detection of Myocardial Ischemia Using Machine Learning Based on Temporal-Spatial Characteristics of Electrocardiogram and Vectorcardiogram.

Zhao X, Zhang J, Gong Y, Xu L, Liu H, Wei S Front Physiol. 2022; 13:854191.

PMID: 35707012 PMC: 9192098. DOI: 10.3389/fphys.2022.854191.


Cardiogoniometry Compared to Fractional Flow Reserve at Identifying Physiologically Significant Coronary Stenosis: The CARDIOFLOW Study.

Brown O, Clark A, Chelliah R, Davison B, Mather A, Cunnington M Cardiovasc Eng Technol. 2018; 9(3):439-446.

PMID: 29651685 PMC: 6096643. DOI: 10.1007/s13239-018-0354-1.

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