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Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation

Methods for characterization of atrial fibrillation (AF) episode patterns have been introduced without establishing clinical significance. This study investigates, for the first time, whether post-ablation recurrence of AF can be predicted by evaluating episode patterns. The dataset comprises of 54...

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Autores principales: Saiz-Vivó, Javier, Corino, Valentina D. A., Martín-Yebra, Alba, Mainardi, Luca T., Hatala, Robert, Sörnmo, Leif
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9852159/
https://www.ncbi.nlm.nih.gov/pubmed/36409405
http://dx.doi.org/10.1007/s11517-022-02713-x
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author Saiz-Vivó, Javier
Corino, Valentina D. A.
Martín-Yebra, Alba
Mainardi, Luca T.
Hatala, Robert
Sörnmo, Leif
author_facet Saiz-Vivó, Javier
Corino, Valentina D. A.
Martín-Yebra, Alba
Mainardi, Luca T.
Hatala, Robert
Sörnmo, Leif
author_sort Saiz-Vivó, Javier
collection PubMed
description Methods for characterization of atrial fibrillation (AF) episode patterns have been introduced without establishing clinical significance. This study investigates, for the first time, whether post-ablation recurrence of AF can be predicted by evaluating episode patterns. The dataset comprises of 54 patients (age 56 ± 11 years; 67% men), with an implantable cardiac monitor, before undergoing the first AF catheter ablation. Two parameters of the alternating bivariate Hawkes model were used to characterize the pattern: AF dominance during the monitoring period (log(mu)) and temporal aggregation of episodes (beta1). Moreover, AF burden and AF density, a parameter characterizing aggregation of AF burden, were studied. The four parameters were computed from an average of 29 AF episodes before ablation. The risk of AF recurrence after catheter ablation using the Hawkes parameters log(mu) and beta1, AF burden, and AF density was evaluated. While the combination of AF burden and AF density is related to a non-significant hazard ratio, the combination of log(mu) and beta1 is related to a hazard ratio of 1.95 (1.03–3.70; p < 0.05). The Hawkes parameters showed increased risk of AF recurrence within 1 year after the procedure for patients with high AF dominance and high episode aggregation and may be used for pre-ablation risk assessment. GRAPHICAL ABSTRACT: [Image: see text]
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spelling pubmed-98521592023-01-21 Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation Saiz-Vivó, Javier Corino, Valentina D. A. Martín-Yebra, Alba Mainardi, Luca T. Hatala, Robert Sörnmo, Leif Med Biol Eng Comput Original Article Methods for characterization of atrial fibrillation (AF) episode patterns have been introduced without establishing clinical significance. This study investigates, for the first time, whether post-ablation recurrence of AF can be predicted by evaluating episode patterns. The dataset comprises of 54 patients (age 56 ± 11 years; 67% men), with an implantable cardiac monitor, before undergoing the first AF catheter ablation. Two parameters of the alternating bivariate Hawkes model were used to characterize the pattern: AF dominance during the monitoring period (log(mu)) and temporal aggregation of episodes (beta1). Moreover, AF burden and AF density, a parameter characterizing aggregation of AF burden, were studied. The four parameters were computed from an average of 29 AF episodes before ablation. The risk of AF recurrence after catheter ablation using the Hawkes parameters log(mu) and beta1, AF burden, and AF density was evaluated. While the combination of AF burden and AF density is related to a non-significant hazard ratio, the combination of log(mu) and beta1 is related to a hazard ratio of 1.95 (1.03–3.70; p < 0.05). The Hawkes parameters showed increased risk of AF recurrence within 1 year after the procedure for patients with high AF dominance and high episode aggregation and may be used for pre-ablation risk assessment. GRAPHICAL ABSTRACT: [Image: see text] Springer Berlin Heidelberg 2022-11-21 2023 /pmc/articles/PMC9852159/ /pubmed/36409405 http://dx.doi.org/10.1007/s11517-022-02713-x Text en © The Author(s) 2022, corrected publication 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Saiz-Vivó, Javier
Corino, Valentina D. A.
Martín-Yebra, Alba
Mainardi, Luca T.
Hatala, Robert
Sörnmo, Leif
Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation
title Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation
title_full Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation
title_fullStr Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation
title_full_unstemmed Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation
title_short Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation
title_sort atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9852159/
https://www.ncbi.nlm.nih.gov/pubmed/36409405
http://dx.doi.org/10.1007/s11517-022-02713-x
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