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室性快速心律失常期间电不稳定性与泵血性能之间的关系:计算研究

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

作者信息

Jeong Da Un, Lim Ki Moo

机构信息

Computational Medicine Lab, Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, South Korea.

出版信息

Front Physiol. 2020 Mar 24;11:220. doi: 10.3389/fphys.2020.00220. eCollection 2020.

Abstract

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.

摘要

在快速性心律失常研究中,存在一些用于理解折返波机制的代表性电参数,即动作电位时程(APD)、主导频率、相位奇点和细丝。然而,尚无研究直接确定这些电生理参数与心脏收缩性之间的相关性。因此,我们通过推导回归方程,确定了快速性心律失常期间这些电现象与收缩性之间的个体和综合相关性,并研究了影响快速性心律失常期间心脏收缩性的电生理参数。我们通过应用四种折返产生方法并改变对心室组织影响最大的钾通道电导率,用48种电模式模拟了室性快速性心律失常。通过兴奋 - 收缩偶联的确定性模拟获得反映电复杂性的机械反应。我们将每搏输出量和心肌张力幅度(ampTens)用作代表收缩性的变量。我们通过单变量和多变量回归分析推导随机模型,以确定快速性心律失常期间影响收缩性的电参数。在单变量回归分析中,除相位奇点外,APD、主导频率和细丝与每搏输出量和ampTens具有统计学显著相关性。其中,APD对这两个机械参数的影响最大(标准β系数:每搏输出量为0.859,ampTens为0.930)。由于APD和主导频率之间的多重共线性,使用所有四个电参数的随机模型无法准确预测收缩性。我们使用不包括APD的三个电参数重新推导了多变量随机模型。细丝对每搏输出量的随机影响最大(标准β系数:0.853和0.752)。主导频率对ampTens的统计学影响最大(标准β系数: - 0.813)。我们得出结论,在电参数中,APD对机械收缩的个体影响最大,而细丝在统计方面具有最高的综合影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d85/7105731/bd64c3329a70/fphys-11-00220-g001.jpg

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