Comparison of QT interval variability of coronary patients without myocardial infarction with that of patients with old myocardial infarction.

BACKGROUND: The significant association of myocardial ischemia with elevated QT interval variability (QTV) has been reported in myocardial infarction (MI) patients. However, the influence of the time course of MI on QTV has not been investigated systematically. METHOD: Short-term QT and RR interval time series were constructed from the 5 min electrocardiograms of 49 coronary patients without MI and 26 patients with old MI (OMI). The QTV, heart rate variability (HRV), and QT-RR coupling of the two groups were analyzed using various time series analysis tools in the time- and frequency-domains, as well as nonlinear dynamics. RESULTS: Nearly all of the tested QTV indices for coronary patients with OMI were higher than those for patients without MI. However, no significant differences were found between the two groups in any of the variables employed to assess the HRV and QT-RR coupling. All of the markers that showed statistical significances in univariate analyses still possessed the capabilities of distinguishing between the two groups even after adjusting for studied baseline characteristics, including the coronary atherosclerotic burden. CONCLUSIONS: The results suggested that the QTV increased in coronary patients with OMI compared to those without MI, which might reflect the influence of post-MI remodeling on the beat-to-beat temporal variability of ventricular repolarization. The non-significant differences in the HRV and QT-RR couplings could indicate that there were no differences in the modulation of the autonomic nervous system and interaction of QT with the RR intervals between the two groups.

Effect of a multi-lead PCA approach on modified moving average method for T-wave alternans detection.

T-wave alternans, a beat-to-beat re-polarization pattern variation phenomenon, plays an important role in sudden cardiac death prediction. The proposed method modifies the currently available Modified Moving Average Method (MMAM) by a multi-lead principal component analysis (PCA) approach. Application of PCA will concentrate the alternans effect, which is supposed to be distributed on multiple leads in a single derived lead. MMAM is applied to the derived lead and alternans magnitude is measured. Results are compared with MMAM, implemented by the authors and by an open source tool, TWAnalyser. The TWA Physionet/CinC 2008 Challenge Database is used for testing. Performances are measured in terms of root mean square error (rmse) and correlation coefficients. The rmse is highest for TWAnalyser results and lowest for the proposed method. While the correlation coefficient is highest for the proposed method, 0.88, that for normal MMAM is 0.73 and for TWAnalyser is 0.75. The proposed multi-lead PCA approach provides improved performance of current MMAM.