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ECG based assessment of circadian variation in AV-nodal conduction during AF—Influence of rate control drugs
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577140/ https://www.ncbi.nlm.nih.gov/pubmed/36267586 http://dx.doi.org/10.3389/fphys.2022.976526 |
Sumario: | 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. |
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