Nonlinear transformation of the resting electrocardiogram in the diagnosis of coronary artery disease

Abstract

Despite the common use of the standard 12-lead ECG, its reliability as an indicator of coronary artery disease (CAD) is poor. The normal ECG is falsely negative in more than 50% of angiographically proven CAD. The waveform of the standard ECG, however, can be transformed mathematically by nonlinear signal transformation to enhance its interpretation by computer. Using such a process it is possible that abnormalities can be identified in "normal" ECGs that can be correlated with CAD, thus identifying high-risk patients. A computer template that represents grouped data of normal ECGs for patients who also have normal coronary angiography was developed. Unblinded, preliminary testing of the template on normal ECGs of 107 white patients who had normal or abnormal coronary angiograms was performed. The process identified presence or absence of CAD with 82% specificity and 71% sensitivity for 53 women, and with 82% specificity and 86% sensitivity for 54 men. These preliminary results are promising, but further refinement of the templates is required and blinded studies with larger numbers and varieties of patients are needed.