In search of a driver for atrial fibrillation

Journal Article (2025)
Author(s)

Lianne N. van Staveren (Erasmus MC)

Yannick J.H.J. Taverne (Erasmus MC)

Richard Hendriks (TU Delft - Signal Processing Systems)

Natasja M.S. de Groot (TU Delft - Signal Processing Systems, TU Delft - Biomechanical Engineering, Erasmus MC)

Research Group
Signal Processing Systems
DOI related publication
https://doi.org/10.1016/j.hrthm.2025.05.024
More Info
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Publication Year
2025
Language
English
Research Group
Signal Processing Systems
Issue number
10
Volume number
22
Pages (from-to)
e978-e989
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Abstract

Background: Short atrial fibrillation cycle lengths (AFCLs) and regular activation patterns are associated with drivers of atrial fibrillation, although the relation with underlying patterns of activation is incompletely understood. Previous studies used automated assessment of electrograms to determine fast and regular fibrillatory rates. Objective: We investigated the relation among AFCL, temporal variation in AFCL, and the occurrence of driver-like patterns of activation using high-density local activation time mapping. Methods: High-density epicardial mapping of the right atrium and left atrial ventricular groove including Bachmann's bundle was performed in 71 patients admitted for elective cardiac surgery. Recording sites with the shortest median AFCL or the smallest standard deviation of AFCL were identified. Patterns of activation included focal or rotational activation, smooth propagation, propagation with conduction block (CB), collision, and remnant activity. Results: There was a higher number of fibrillation waves with CB (81% [interquartile range (IQR) 76%–85%] vs 74% [68%–76%]; P < .001) and fractionated potentials (22% [12%–37%] vs 12% [9%–15%]; P < .001) at shortest median AFCL than at other recording sites. Smallest standard deviation sites harbored more smoothly propagating waves (33% [24%–54%] vs 17% [11%–25%]; P < .001) and a higher proportion of single potentials (76% [60%–89%] vs 59% [54%–65%]; P < .001). Both highly regular and fastest reactivated sites did not correspond to the origin of (repetitive) focal fibrillation waves. Conclusion: During extensive mapping, the fastest or most regularly activated areas are characterized by CB and smoothly propagating fibrillation waves instead of repetitive occurrence of focal or rotational activation patterns. This study rejects the concept of detecting drivers by identifying the fastest or most regularly activated recording sites.