Exploring Refractoriness as an Adjunctive Electrical Biomarker for Staging of Atrial Fibrillation

Patients diagnosed with the same subtype of atrial fibrillation according to our current classification system may differ in symptom severity, severity of the arrhythmogenic substrate, and response to antiarrhythmic therapy. Hence, there is a need for an electrical biomarker as an indicator of the a...

Full description

Saved in:
Bibliographic Details
Published in:Journal of the American Heart Association 2020-12, Vol.9 (23), p.e018427-e018427
Main Authors: van Staveren, Lianne N, de Groot, Natasja M S
Format: Article
Language:English
Subjects:
Anti-Arrhythmia Agents - therapeutic use
atrial fibrillation
Atrial Fibrillation - diagnosis
Atrial Fibrillation - drug therapy
Atrial Fibrillation - physiopathology
Atrial Function - physiology
biomarker
Contemporary Review
Electrocardiography
electrophysiology
Humans
refractory period
Refractory Period, Electrophysiological - physiology
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Patients diagnosed with the same subtype of atrial fibrillation according to our current classification system may differ in symptom severity, severity of the arrhythmogenic substrate, and response to antiarrhythmic therapy. Hence, there is a need for an electrical biomarker as an indicator of the arrhythmogenic substrate underlying atrial fibrillation enabling patient-tailored therapy. The aim of this review is to investigate whether atrial refractoriness, a well-known electrophysiological parameter that is affected by electrical remodeling, can be used as an electrical biomarker of the arrhythmogenic substrate underlying atrial fibrillation. We discuss methodologies of atrial effective refractory period assessment, identify which changes in refractoriness-related parameters reflect different degrees of electrical remodeling, and explore whether these parameters can be used to predict clinical outcomes.
ISSN:2047-9980
2047-9980
DOI:10.1161/JAHA.120.018427