ECG-based Assessment and Therapeutic Implications of AV Nodal Conduction Dynamics During Atrial Fibrillation

Mattias Karlsson, Mikael Wallman, Pyotr G. Platonov, Sara R. Ulimoen, Frida Sandberg

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

The conduction properties of the atrioventricular (AV) node have a significant impact on heart rate during permanent atrial fibrillation (AF), and can be modulated through the use of β-blockers or calcium channel blockers. These drugs have different physiological effects and are often selected empirically. Hence, an improved understanding of how these drugs affect the AV node conduction properties may contribute to personalized treatment of AF. We propose a novel methodology for estimating the refractory period and conduction delay dynamics of the fast and slow pathways of the AV node from 24-hour ambulatory ECG recordings. Our approach comprises a network model of the AV node, a problem-specific genetic algorithm, and an approximate Bayesian computation algorithm for estimating the posterior distribution of the AV node properties. We analyzed 24-hour ambulatory ECG recordings at baseline from 51 patients with permanent AF. Interestingly, a moderate correlation between the short-term variability in the refractory period for the fast pathway and reduction in heart rate during treatment with metoprolol (ρ = 0.48, p < 0.005) was found. Thus, the proposed methodology enables individualized characterization of the AV node and can potentially assist in treatment selection.

Original languageEnglish
Title of host publicationComputing in Cardiology, CinC 2023
PublisherIEEE Computer Society
Volume50
ISBN (Electronic)9798350382525
DOIs
Publication statusPublished - 2023
Event50th Computing in Cardiology, CinC 2023 - Atlanta, United States
Duration: 2023 Oct 12023 Oct 4

Publication series

NameComputing in Cardiology
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Conference

Conference50th Computing in Cardiology, CinC 2023
Country/TerritoryUnited States
CityAtlanta
Period2023/10/012023/10/04

Bibliographical note

Publisher Copyright:
© 2023 CinC.

Subject classification (UKÄ)

  • Biomedical Laboratory Science/Technology

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