Abstract
R-wave singularity (RWS) measures the intermittence or discontinuousness of R waves. It has been broadly used in QRS (QRS complex of electrocardiogram) detection, electrocardiogram (ECG) beats classification, etc. In this article, we novelly developed RWS to the analysis of QRS morphology as the measurement of ventricular dyssynchrony and tested the hypothesis that RWS could enhance the discrimination between control and acute myocardial infarction (AMI) patients. Holter ECG recordings were obtained from the Telemetric and Holter ECG Warehouse database, among which database Normal was extracted as normal controls (n = 202) and database AMI (n = 93) as typical subjects of autonomic nervous system dysfunction and cardiac electrical dyssynchrony with high risk for cardiac arrhythmias and sudden cardiac death. Experimental results demonstrate that RWS measured by Lipschitz exponent calculated from 5-min Holter recordings was significantly less negative in early AMI and late AMI than that in Normal subjects for overall, elderly, and elderly male groups, which suggested the heterogeneous depolarization of the ventricular myocardium during AMI. Receiver operating characteristic curve analyses show that combined with heart rate variability parameters, Lipschitz exponent provides higher accuracy in distinguishing between the patients with AMI and healthy control subjects for overall, elderly, elderly male, and elderly female groups. In summary, our study demonstrates the significance of using RWS to probe the cardiac electrical dyssynchrony for AMI. Lipschitz exponent may be valuable and complementary for existing cardiac resynchronization therapy and autonomic nervous system assessment.
Highlights
Holter electrocardiogram (ECG) is currently the only noninvasive cardiac electrophysiological monitoring tool that can provide insights into the dynamics of cardiac electrical activity during 24 h recording
For AMIearly group, there was a significant increase in the mean values of RR intervals (RRI) and Lipschitz exponent (LE), a significant decrease in SDNN, RMSSD, pNN50, LF, HF, and LF/HF compared with Normal group
For AMIlate group, there was a significant increase in the mean values of RRI and LE, a significant decrease in SDNN, RMSSD, pNN50, LF, and HF, a trend for a decrease in LF/HF compared with Normal group
Summary
Holter electrocardiogram (ECG) is currently the only noninvasive cardiac electrophysiological monitoring tool that can provide insights into the dynamics of cardiac electrical activity during 24 h recording. Researches based on Holter ECG can be divided into two main categories: time series analysis and morphology analysis. Time series such as RR intervals (RRI) and QT intervals extracted from ECG waveform are significant data sources for the analysis of autonomic nervous system (ANS) activity. The clinical application of Holter ECG recordings has been largely limited to detecting arrhythmic episodes and/or ectopic beats and assessing heart rate variability (HRV) (Immanuel et al, 2016). With the increasing popularity of Holter ECG examination, it is of great clinical significance to further improve the application value of this technology so as to expand the diagnosis scope
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