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bioRxiv · 10.1101/2025.11.27.690941

Assessment of atrioventricular nodal reentrant tachycardia inducibility with alternative pacing methods: Computer simulation

Abstract

Background and objectiveIn clinical and experimental electrophysiology, the standard S1S2 stimulation protocol is widely used to assess the inducibility of reciprocal tachycardias. However, this method may lead to over- or under-estimation of atrioventricular nodal reentrant tachycardia (AVNRT) susceptibility. Computational modeling enables a detailed examination of these limitations and the design of more physiologically accurate stimulation approaches. This study evaluates alternative stimulation methods using a compact, multifunctional rabbit AV node model with autonomic nervous system (ANS) control. MethodsThe model, based on experimental data, incorporates dual (fast and slow) pathway conduction and simulates the propagation of nodal electrical excitation. Alternative stimulation protocols were implemented and compared with the standard S1S2 approach at both atrial and His bundle stimulation sites. ResultsSimulations yielded AV node ladder diagrams, effective refractory periods, and echo response zones across the full range of ANS modulation. The proposed methods enabled accurate characterization of nodal pathway refractory periods during retrograde conduction and identified physiological conditions leading to intranodal reentry. Compared with the S1S2 protocol, the alternative approaches reduced misestimation of AVNRT inducibility and provided clearer separation between echo beats and sustained reentry. ConclusionsThe proposed stimulation methods, particularly during His bundle pacing, offer a more accurate and physiologically grounded assessment of AVNRT inducibility than the conventional S1S2 protocol, improving the understanding of nodal conduction dynamics and arrhythmia mechanisms.

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BibTeXRIS

Ryzhii, M., Ryzhii, E.. 2025-12-01. Assessment of atrioventricular nodal reentrant tachycardia inducibility with alternative pacing methods: Computer simulation. https://doi.org/10.1101/2025.11.27.690941

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