ECG based assessment of circadian variation in AV-nodal conduction during AF—Influence of rate control drugs

Karlsson, Mattias; Wallman, Mikael; Platonov, Pyotr G.; Ulimoen, Sara R., et al. (2022-10-04). ECG based assessment of circadian variation in AV-nodal conduction during AF—Influence of rate control drugs. Frontiers in Physiology, 13,
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DOI:
| Published | English
Authors:
Karlsson, Mattias ; Wallman, Mikael ; Platonov, Pyotr G. ; Ulimoen, Sara R. , et al.
Department:
Department of Biomedical Engineering
LTH Profile Area: Engineering Health
Cardiology
Project:
Ph.D. project: Non-invasive analysis of ANS activity in atrial fibrillation
Diagnostic Biomarkers in Atrial Fibrillation - Autonomic Nervous System Response as a Sign of Disease Progression
Abstract:

The heart rate during atrial fibrillation (AF) is highly dependent on the conduction properties of the atrioventricular (AV) node. These properties can be affected using β-blockers or calcium channel blockers, mainly chosen empirically. Characterization of individual AV-nodal conduction could assist in personalized treatment selection during AF. Individual AV nodal refractory periods and conduction delays were characterized based on 24-hour ambulatory ECGs from 60 patients with permanent AF. This was done by estimating model parameters from a previously created mathematical network model of the AV node using a problem-specific genetic algorithm. Based on the estimated model parameters, the circadian variation and its drug-dependent difference between treatment with two β-blockers and two calcium channel blockers were quantified on a population level by means of cosinor analysis using a linear mixed-effect approach. The mixed-effects analysis indicated increased refractoriness relative to baseline for all drugs. An additional decrease in circadian variation for parameters representing conduction delay was observed for the β-blockers. This indicates that the two drug types have quantifiable differences in their effects on AV-nodal conduction properties. These differences could be important in treatment outcome, and thus quantifying them could assist in treatment selection.

Keywords:
atrial fibrillation ; atrioventricular node ; circadian variation ; ECG ; genetic algorithm ; mathematical modeling ; mixed effect modeling ; rate control drugs
ISSN:
1664-042X
LUP-ID:
2f5b9448-5cc0-4370-a142-1c3268876496 | Link: https://lup.lub.lu.se/record/2f5b9448-5cc0-4370-a142-1c3268876496 | Statistics

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