The effect of clinically relevant changes in extracellular electrolyte concentrations on human atrial arrhythmias
File(s)
Published version
Author(s)
Corrado, Cesare
Roney, Caroline
Narayan, Sanjiv
Giles, Wayne
Niederer, Steven
Type
Journal Article
Abstract
Background
Patients with recent-onset atrial fibrillation (AF) frequently present with plasma electrolyte imbalances. Low plasma concentrations of potassium (hypokalaemia), and more recently low plasma concentrations of sodium (hyponatremia), have both been shown to contribute to a pro-arrhythmic substrate and may affect the success of restoring the normal rhythm (cardioversion). However, the mechanistic effects of these electrolyte alterations on atrial electrophysiology remain incompletely understood. This study aims to investigate how clinically relevant variations in extracellular electrolyte concentrations influence human atrial electrical activity and arrhythmia initiation.
Methods
We applied our cardiac digital twin methodology to a cohort of 100 atrial fibrillation patients (43 paroxysmal, 41 persistent, 16 long-standing persistent). For each patient-specific model, we simulated sinus rhythm and AF induction under baseline and 30 distinct combinations of extracellular potassium, sodium and calcium concentrations. Global sensitivity analysis and machine learning were used to quantify how these electrolyte alterations affect key electrophysiological markers, including action potential duration, resting membrane potential (RMP), and conduction velocity (CV), and the induction and maintenance of AF.
Results
Here we show that our computational framework accurately replicates the experimentally observed sensitivity of human atrial electrophysiology to electrolyte variations. Hyponatremia significantly modifies the action potential waveform, thereby promoting AF sustainability, while hypokalaemia predominantly alters the RMP and thus CV, and only moderately increases AF inducibility.
Conclusions
The combination of clinical data sets and multiscale computational analyses yields insights into cellular and tissue-level mechanisms for AF as well as suggesting personalised approaches for management and treatment.
Patients with recent-onset atrial fibrillation (AF) frequently present with plasma electrolyte imbalances. Low plasma concentrations of potassium (hypokalaemia), and more recently low plasma concentrations of sodium (hyponatremia), have both been shown to contribute to a pro-arrhythmic substrate and may affect the success of restoring the normal rhythm (cardioversion). However, the mechanistic effects of these electrolyte alterations on atrial electrophysiology remain incompletely understood. This study aims to investigate how clinically relevant variations in extracellular electrolyte concentrations influence human atrial electrical activity and arrhythmia initiation.
Methods
We applied our cardiac digital twin methodology to a cohort of 100 atrial fibrillation patients (43 paroxysmal, 41 persistent, 16 long-standing persistent). For each patient-specific model, we simulated sinus rhythm and AF induction under baseline and 30 distinct combinations of extracellular potassium, sodium and calcium concentrations. Global sensitivity analysis and machine learning were used to quantify how these electrolyte alterations affect key electrophysiological markers, including action potential duration, resting membrane potential (RMP), and conduction velocity (CV), and the induction and maintenance of AF.
Results
Here we show that our computational framework accurately replicates the experimentally observed sensitivity of human atrial electrophysiology to electrolyte variations. Hyponatremia significantly modifies the action potential waveform, thereby promoting AF sustainability, while hypokalaemia predominantly alters the RMP and thus CV, and only moderately increases AF inducibility.
Conclusions
The combination of clinical data sets and multiscale computational analyses yields insights into cellular and tissue-level mechanisms for AF as well as suggesting personalised approaches for management and treatment.
Date Issued
2026-01-05
Date Acceptance
2025-11-12
Citation
Communications Medicine, 2026, 6
ISSN
2730-664X
Publisher
Nature Portfolio
Journal / Book Title
Communications Medicine
Volume
6
Copyright Statement
© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Identifier
10.1038/s43856-025-01260-4
Publication Status
Published
Article Number
7
Date Publish Online
2025-12-02