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Relationship Between Electrical Instability and Pumping Performance During Ventricular Tachyarrhythmia: Computational Study

There are representative electrical parameters for understanding the mechanism of reentrant waves in studies on tachyarrhythmia, namely the action potential duration (APD), dominant frequency, phase singularity, and filament. However, there are no studies that have directly identified the correlatio...

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Autores principales: Jeong, Da Un, Lim, Ki Moo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105731/
https://www.ncbi.nlm.nih.gov/pubmed/32265731
http://dx.doi.org/10.3389/fphys.2020.00220
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author Jeong, Da Un
Lim, Ki Moo
author_facet Jeong, Da Un
Lim, Ki Moo
author_sort Jeong, Da Un
collection PubMed
description There are representative electrical parameters for understanding the mechanism of reentrant waves in studies on tachyarrhythmia, namely the action potential duration (APD), dominant frequency, phase singularity, and filament. However, there are no studies that have directly identified the correlation between these electrophysiological parameters and cardiac contractility. Therefore, we have identified individual and integrative correlations between these electrical phenomena and contractility during tachyarrhythmia by deriving regression equations and also investigated the electrophysiological parameters affecting cardiac contractility during tachyarrhythmia. We simulated ventricular tachyarrhythmia with 48 types of electrical patterns by applying four reentry generation methods and changing the electrical conductivity of the potassium channel, which has the greatest effect on ventricular tissue. The mechanical responses reflecting electrical complexity were obtained through deterministic simulations of excitation–contraction coupling. We used the stroke volume and amplitude of myocardial tension (ampTens) as the variables representing contractility. We derived stochastic models through single- and multivariable regression analyses to identify the electrical parameters affecting contractility during tachyarrhythmia. In single-variable regression analysis, the APD, dominant frequency, and filament, excluding phase singularity, have statistically significant correlations with the stroke volume and ampTens. Among them, the APD has the maximum influence on these two mechanical parameters (standard beta coefficient: 0.859 for stroke volume, 0.930 for ampTens). The stochastic model using all four electrical parameters fails to accurately predict contractility owing to the multicollinearity between the APD and dominant frequency. We have rederived the multi-variable stochastic model using three electrical parameters without the APD. The filament has the greatest effect on the stroke volume stochastically (standard beta coefficient: 0.853 and 0.752). The dominant frequency has the greatest effect on ampTens statistically (standard beta coefficient: −0.813). We conclude that among the electrical parameters, the APD has the highest individual influence on mechanical contraction, and the filament has the highest integrative influence in both statistical terms.
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spelling pubmed-71057312020-04-07 Relationship Between Electrical Instability and Pumping Performance During Ventricular Tachyarrhythmia: Computational Study Jeong, Da Un Lim, Ki Moo Front Physiol Physiology There are representative electrical parameters for understanding the mechanism of reentrant waves in studies on tachyarrhythmia, namely the action potential duration (APD), dominant frequency, phase singularity, and filament. However, there are no studies that have directly identified the correlation between these electrophysiological parameters and cardiac contractility. Therefore, we have identified individual and integrative correlations between these electrical phenomena and contractility during tachyarrhythmia by deriving regression equations and also investigated the electrophysiological parameters affecting cardiac contractility during tachyarrhythmia. We simulated ventricular tachyarrhythmia with 48 types of electrical patterns by applying four reentry generation methods and changing the electrical conductivity of the potassium channel, which has the greatest effect on ventricular tissue. The mechanical responses reflecting electrical complexity were obtained through deterministic simulations of excitation–contraction coupling. We used the stroke volume and amplitude of myocardial tension (ampTens) as the variables representing contractility. We derived stochastic models through single- and multivariable regression analyses to identify the electrical parameters affecting contractility during tachyarrhythmia. In single-variable regression analysis, the APD, dominant frequency, and filament, excluding phase singularity, have statistically significant correlations with the stroke volume and ampTens. Among them, the APD has the maximum influence on these two mechanical parameters (standard beta coefficient: 0.859 for stroke volume, 0.930 for ampTens). The stochastic model using all four electrical parameters fails to accurately predict contractility owing to the multicollinearity between the APD and dominant frequency. We have rederived the multi-variable stochastic model using three electrical parameters without the APD. The filament has the greatest effect on the stroke volume stochastically (standard beta coefficient: 0.853 and 0.752). The dominant frequency has the greatest effect on ampTens statistically (standard beta coefficient: −0.813). We conclude that among the electrical parameters, the APD has the highest individual influence on mechanical contraction, and the filament has the highest integrative influence in both statistical terms. Frontiers Media S.A. 2020-03-24 /pmc/articles/PMC7105731/ /pubmed/32265731 http://dx.doi.org/10.3389/fphys.2020.00220 Text en Copyright © 2020 Jeong and Lim. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Jeong, Da Un
Lim, Ki Moo
Relationship Between Electrical Instability and Pumping Performance During Ventricular Tachyarrhythmia: Computational Study
title Relationship Between Electrical Instability and Pumping Performance During Ventricular Tachyarrhythmia: Computational Study
title_full Relationship Between Electrical Instability and Pumping Performance During Ventricular Tachyarrhythmia: Computational Study
title_fullStr Relationship Between Electrical Instability and Pumping Performance During Ventricular Tachyarrhythmia: Computational Study
title_full_unstemmed Relationship Between Electrical Instability and Pumping Performance During Ventricular Tachyarrhythmia: Computational Study
title_short Relationship Between Electrical Instability and Pumping Performance During Ventricular Tachyarrhythmia: Computational Study
title_sort relationship between electrical instability and pumping performance during ventricular tachyarrhythmia: computational study
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105731/
https://www.ncbi.nlm.nih.gov/pubmed/32265731
http://dx.doi.org/10.3389/fphys.2020.00220
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