Accurate detection of coronary artery disease by integrated analysis of the ST-segment depression/heart rate patterns during the exercise and recovery phases of the exercise electrocardiography test

In this comparative cross-sectional study, we evaluated whether a novel computerized diagnostic variable, ST-segment depression/heart rate (STHR) hysteresis, which integrates the efficient STHR analysis during both the exercise and postexercise recovery phases of the exercise electrocardiography (ECG) test, can detect coronary artery disease more accurately than methods using either exercise or recovery phase alone. The study population comprised 347 clinical patients referred for a routine bicycle exercise ECG test at Tampere University Hospital, Finland. Of these, 127 had angiographically proven coronary artery disease, whereas 13 had no coronary artery disease according to angiography, 18 had no perfusion defect according to technetium-99m sestamibi single-photon emission computed tomography, and 189 were clinically normal with respect to cardiac diseases. For each patient, the maximum values of the STHR hysteresis, STHR index, end-exercise ST depression, and recovery ST depression were determined from the Mason-Likar modification of the standard 12-lead exercise electrocardiogram (aVL, aVR, and V1 excluded). The diagnostic performance of these continuous diagnostic variables was compared by means of receiver-operating characteristic analysis. The area under the receiver-operating characteristic curve of the STHR hysteresis was 89%, which was significantly larger than that of the end-exercise ST depression (76%, p < 0.0001), recovery ST depression (84%, p = 0.0063), or STHR index (83%, p = 0.0023), indicating superior diagnostic performance of the STHR hysteresis independent of the partition value selection. In conclusion, computerized analysis of the HR-adjusted ST depression pattern during the exercise phase, integrated with the HR-adjusted ST depression pattern during the recovery phase after exercise, can significantly improve the diagnostic performance and clinical utility of the exercise ECG test for the detection of coronary artery disease.