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

Action potential duration (APD), which is commonly used in the study of tachyarrhythmia, can predict the contraction of myocardial filaments; however, it cannot predict cardiac contractility during tachyarrhythmia. This is because APD does not reflect the electrical complexity occurring throughout the heart, whereas dominant frequency, phase singularity, and filaments provide information regarding the position and distribution of reentry rotors. Accordingly, they can be used as alternatives to APD. However, there are no studies that have directly identified the correlation between these electrophysiological parameters and cardiac contractility. Therefore, we have identified the individual and integrative correlations between these electrical phenomena and contractility during tachyarrhythmia by deriving regression equations, and we have 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 by 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 the amplitude of myocardial tension (ampTens) as the variables representing the contractility. We derived stochastic models through single- and multiple-regression analyses to identify the electrical parameters affecting the contractility during tachyarrhythmia. In single-regression analysis, APD, dominant frequency, and filaments, excluding phase singularity, had statistically significant correlations with stroke volume and ampTens. Among them, APD was the most influential on two dependent variables indicating contractility (standard beta coefficient: 0.859 of stroke volume, 0.930 of ampTens). The stochastic model using all four electrical parameters failed to accurately predict the contractility owing to the multicollinearity between APD and dominant frequency. Therefore, we re-derived the multi-variable stochastic model using three electrical parameters without APD. Among these, the filament had the greatest effect on the stroke volume (standard beta coefficient: 0.853), and the dominant frequency had the greatest effect on ampTens (standard beta coefficient: -0.813). In conclusion, we have suggested that the influence of certain electrical parameters on the contractility can vary depending on the presence of absence of other electrophysiological phenomena during ventricular tachyarrhythmia.