Demographic and Methodological Heterogeneity in Electrocardiogram Signals From Guinea Pigs
Electrocardiograms (ECG) are universally used to measure the electrical activity of the heart; however, variations in recording techniques and/or subject demographics can affect ECG interpretation. In this study, we investigated variables that are likely to influence ECG metric measurements in cardi...
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Published in | Frontiers in physiology Vol. 13; p. 925042 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
02.06.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Electrocardiograms (ECG) are universally used to measure the electrical activity of the heart; however, variations in recording techniques and/or subject demographics can affect ECG interpretation. In this study, we investigated variables that are likely to influence ECG metric measurements in cardiovascular research, including recording technique, use of anesthesia, and animal model characteristics. Awake limb lead ECG recordings were collected
in vivo
from adult guinea pigs using a platform ECG system, while recordings in anesthetized animals were performed using both a platform and needle ECG system. We report significant heterogeneities in ECG metric values that are attributed to methodological differences (e.g., ECG lead configuration, ECG recording platform, presence or absence of anesthesia) that persist even within the same cohort of animals. Further, we report that variability in animal demographics is preserved in
vivo
ECG recordings—with animal age serving as a significant contributor, while sex-specific influences were less pronounced. Methodological approaches and subject demographics should be fully considered when interpreting ECG values in animal models, comparing datasets between studies, or developing artificial intelligence algorithms that utilize an ECG database. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Rafael Jaimes, Massachusetts Institute of Technology, United States This article was submitted to Physio-logging, a section of the journal Frontiers in Physiology Rasheda Chowdhury, Imperial College London, United Kingdom Reviewed by: Bradley Barth, Duke University, United States |
ISSN: | 1664-042X 1664-042X |
DOI: | 10.3389/fphys.2022.925042 |