Evidence map›Paper›PMID 40821943›Full record

ArticleFrontiers in physiology2025

ECG-based beat-to-beat assessment of AV node conduction properties during AF.

Mattias Karlsson, Felix Plappert, Pyotr G Platonov, Sten Östenson, Mikael Wallman, Frida Sandberg

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Article in Frontiers in physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Mattias KarlssonDepartment of Systems and Data Analysis, Fraunhofer-Chalmers Centre, Gothenburg, Sweden.
Felix PlappertDepartment of Biomedical Engineering, Lund University, Lund, Sweden.
Pyotr G PlatonovDepartment of Cardiology, Clinical Sciences, Lund University, Lund, Sweden.
Sten ÖstensonDepartment of Internal Medicine and Department of Clinical Physiology, Central Hospital Kristianstad, Kristianstad, Sweden.
Mikael Wallman *Department of Systems and Data Analysis, Fraunhofer-Chalmers Centre, Gothenburg, Sweden.
Frida Sandberg *Department of Biomedical Engineering, Lund University, Lund, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The refractory period and conduction delay of the atrioventricular (AV) node play a crucial role in regulating the heart rate during atrial fibrillation (AF). Beat-to-beat variations in these properties are known to be induced by the autonomic nervous system (ANS) but have previously not been assessable during AF. Assessing these could provide novel information for improved diagnosis, prognosis, and treatment on an individual basis. Methods: To estimate AV nodal conduction properties with beat-to-beat resolution, we propose a methodology comprising a network model of the AV node, a particle filter, and a smoothing algorithm. The methodology was evaluated using simulated data and using synchronized electrogram (EGM) and ECG recordings from five patients in the intracardiac atrial fibrillation database. The methodology's ability to quantify ANS-induced changes in AV node conduction properties was evaluated by analyzing ECG data from 21 patients in AF undergoing a tilt test protocol. Results: The estimated refractory period and conduction delay matched the simulated ground truth based on ECG recordings with a mean absolute error ( Discussion: These results suggest that beat-to-beat estimation of AV nodal conduction properties during AF from ECG is feasible, with different levels of uncertainty, and that the estimated properties agree with expected AV nodal modulation.

Indexed as

atrial fibrillationatrioventricular node modelautonomic nervous systemmathematical modelingparticle filtersmoothing algorithm

Identifiers

PMID40821943
PMCPMC12354475

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