Model-Based Characterization of Atrial Fibrillation Episodes and its Clinical Association
(2020) 2020 Computing in Cardiology, CinC 2020 In Computing in Cardiology 2020-September.- 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... (More)
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.
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- author
- Martin-Yebra, Alba LU ; Henriksson, Mikael LU ; Butkuviene, Monika ; Marozas, Vaidotas ; Petrenas, Andrius ; Savelev, Aleksei ; Platonov, Pyotr G. LU and Sornmo, Leif LU
- organization
- publishing date
- 2020
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2020 Computing in Cardiology, CinC 2020
- series title
- Computing in Cardiology
- volume
- 2020-September
- article number
- 9344171
- publisher
- IEEE Computer Society
- conference name
- 2020 Computing in Cardiology, CinC 2020
- conference location
- Rimini, Italy
- conference dates
- 2020-09-13 - 2020-09-16
- external identifiers
-
- scopus:85100920355
- ISSN
- 2325-887X
- 2325-8861
- ISBN
- 9781728173825
- DOI
- 10.22489/CinC.2020.232
- language
- English
- LU publication?
- yes
- id
- cdabf6f8-5bab-4a43-97fd-88227a5b97ae
- date added to LUP
- 2021-03-05 11:02:21
- date last changed
- 2024-10-03 21:14:18
@inproceedings{cdabf6f8-5bab-4a43-97fd-88227a5b97ae, abstract = {{<p>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.</p>}}, author = {{Martin-Yebra, Alba and Henriksson, Mikael and Butkuviene, Monika and Marozas, Vaidotas and Petrenas, Andrius and Savelev, Aleksei and Platonov, Pyotr G. and Sornmo, Leif}}, booktitle = {{2020 Computing in Cardiology, CinC 2020}}, isbn = {{9781728173825}}, issn = {{2325-887X}}, language = {{eng}}, publisher = {{IEEE Computer Society}}, series = {{Computing in Cardiology}}, title = {{Model-Based Characterization of Atrial Fibrillation Episodes and its Clinical Association}}, url = {{http://dx.doi.org/10.22489/CinC.2020.232}}, doi = {{10.22489/CinC.2020.232}}, volume = {{2020-September}}, year = {{2020}}, }