| Title: | Novel ECG measures of electrophysiological substrate |
| Lead Institution: | Cleveland Clinic Foundation |
| Principal investigator: | Dr Larisa Tereshchenko |
Application 42021
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About
A sudden cardiac arrest is a tragic event, impacting relatives and community at large. With our long-term goal to reduce the rate of sudden cardiac arrest, we initiated a study of its mechanisms. We use a widely available, inexpensive, and non-invasive tool (12-lead ECG) to describe the underlying abnormalities in the electrical system of the heart. The specific objectives of our proposal are to study an electrical system of the heart, considering sex- and racial/ethnic differences, and to investigate whether and which genetic factors determine a function of the electrical system of the heart, and how it can affect the risk of sudden death. In this application, we build on our prior work. In Specific Aim 1 we will determine the associations between novel ECG phenotypes and incident cardiovascular disease, and describe sex- and racial/ethnic differences in novel ECG phenotypes in populations of men and women. We will analyze resting 12-lead ECG and will measure global electrical heterogeneity (sum absolute QRST integral, spatial ventricular gradient elevation, magnitude, and azimuth, and spatial QRS-T angle). On the exercise ECG, we will analyze heart rate variability, QT variability, and ectopic beats. In Specific Aim 2, we will determine cross-sectional and longitudinal associations of ECG phenotypes with left ventricular function and cardiovascular disease, and with body habitus, body composition, impedance, and physical activity. In Specific Aim 3, we will identify genetic factors associated with the ECG phenotypes and will assess effect modification by sex. This research, building on large previous data collection, will uncover how the cardiac electrical system function, and will improve our understanding of underlying mechanisms that may explain why some people die suddenly and will inform future research that will help to prevent sudden death and reduce its risk.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 17013 | Automated detection of non-physiological artifacts on ECG signal: UK Biobank and CRIC | Hassaan A. Bukhari (+23) | 2025 | Computers in Biology and Medicine |
Enabling scientific discoveries that improve human health