| Title |
Model-based characterization of atrial fibrillation episodes and its clinical association / |
| Authors |
Martín-Yebra, Alba ; Henriksson, Mikael ; Butkuvienė, Monika ; Marozas, Vaidotas ; Petrėnas, Andrius ; Savelev, Aleksei ; Platonov, Pyotr G ; Sörnmo, Leif |
| DOI |
10.22489/CinC.2020.232 |
| ISBN |
9781728111056 |
| eISBN |
9781728173825 |
| Full Text |
|
| Is Part of |
Computing in cardiology (CinC): September 13-16, 2020, Rimini, Italy / Ch. Pickett, C. Corsi, R. MacLeod (eds.).. Piscataway, NJ : IEEE, 2020. vol. 47, p. 1-4.. ISSN 2325-8861. eISSN 2325-887X. ISBN 9781728111056. eISBN 9781728173825 |
| Keywords [eng] |
model-based characterization ; atrial fibrillation episodes ; clinical association |
| Abstract [eng] |
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 β1, providing information on clustering, were investigated in relation to AF burden and atrial echocardiographic measurements. Both µ and β1 were 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 β1 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 (β1) is complementary information to AF burden, which may be useful for understanding arrhythmia progression and risk assessment of ischemic stroke. |
| Published |
Piscataway, NJ : IEEE, 2020 |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2020 |
| CC license |
|
