Model-Based Characterization of Atrial Fibrillation Episodes and its Clinical Association

Martin-Yebra, Alba; Henriksson, Mikael; Butkuviene, Monika; Marozas, Vaidotas, et al. (2020). Model-Based Characterization of Atrial Fibrillation Episodes and its Clinical Association 2020 Computing in Cardiology, CinC 2020, 2020-September,. 2020 Computing in Cardiology, CinC 2020. Rimini, Italy: IEEE Computer Society
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Conference Proceeding/Paper | Published | English
Authors:
Martin-Yebra, Alba ; Henriksson, Mikael ; Butkuviene, Monika ; Marozas, Vaidotas , et al.
Department:
Department of Biomedical Engineering
Department of Biomedical Engineering
Abstract:

Studies investigating risk factors associated with atrial fibrillation (AF) have mostly focused on AF presence and burden, disregarding the temporal distribution of AF episodes although such information can be relevant. In the present study, the alternating, bivariate Hawkes model was used to characterize paroxysmal AF episode patterns. Two parameters: the intensity ratio µ, describing the dominating rhythm (AF or non-AF) and the exponential decay ß 1, providing information on clustering, were investigated in relation to AF burden and atrial echocardiographic measurements. Both µ and ß1were weakly correlated with atrial volume (r=0.19 and r=0.34, respectively), whereas µ was correlated with atrial strain (r=-0.74, p=0.1) and AF burden (r=0.68, p=0.05). Weak correlation between ß1 and AF burden was found (r=0.29). Atrial structural remodeling is associated with changes in AF characteristics, often manifested as episodes of increasing duration, thus µ may reflect the degree of atrial electrical and structural remodeling. Moreover, clustering information (ß1) is complementary information to AF burden, which may be useful for understanding arrhythmia progression and risk assessment of ischemic stroke.

ISBN:
9781728173825
ISSN:
2325-887X
LUP-ID:
cdabf6f8-5bab-4a43-97fd-88227a5b97ae | Link: https://lup.lub.lu.se/record/cdabf6f8-5bab-4a43-97fd-88227a5b97ae | Statistics

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