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ORIGINAL RESEARCH article
Front. Physiol.
Sec. Cardiac Electrophysiology
Volume 15 - 2024 |
doi: 10.3389/fphys.2024.1529426
Atrioventricular nodal reentrant tachycardia onset, sustainability, and spontaneous termination in rabbit atrioventricular node model with autonomic nervous system control
Provisionally accepted- 1 University of Aizu, Aizuwakamatsu, Japan
- 2 Fukushima Medical University, Fukushima, Fukushima, Japan
Atrioventricular nodal reentrant tachycardia (AVNRT) is one of the most common types of paroxysmal supraventricular tachycardia. The activity of the autonomic nervous system (ANS) is known to influence episodes of AVNRT, yet the precise mechanisms underlying this effect remain incompletely understood. In this study, we update our compact multifunctional model of the rabbit atrioventricular (AV) node with ANS control to simulate AVNRT. The refractoriness of the model cells is adjusted by a specific ANS coefficient, which impacts the effective refractory periods, conduction delays, and intrinsic frequency of pacemaker cells. Using this model, we investigate the onset, sustainability, and spontaneous termination of typical slow-fast and atypical fast-slow forms of AVNRT under ANS modulation. The conditions for the onset and sustainability of AVNRT can exist independently in various combinations. Differences in the effective refractory periods of the slow and fast pathways of the AV node during anterograde and retrograde conduction determine the specific form of AVNRT. For the first time, a computer model reveals the potential to identify hidden processes within the AV node, thereby bringing us closer to understanding the role of ANS control in AVNRT. The results obtained are consistent with clinical and experimental data and represent a novel tool for studying the electrophysiological mechanisms behind this type of arrhythmia.
Keywords: Atrioventricular Node, rabbit heart model, Aliev-Panfilov model, Dual pathway, Autonomic Nervous System, AVNRT, Effective Refractory Period, Computer Simulation
Received: 16 Nov 2024; Accepted: 30 Dec 2024.
Copyright: © 2024 Ryzhii and Ryzhii. 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) or licensor 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.
* Correspondence:
Maxim Ryzhii, University of Aizu, Aizuwakamatsu, Japan
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