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Incidence and Predictors of Atrial Fibrillation Progression
BACKGROUND: The incidence and predictors of atrial fibrillation (AF) progression are currently not well defined, and clinical AF progression partly overlaps with rhythm control interventions (RCIs). METHODS AND RESULTS: We assessed AF type and intercurrent RCIs during yearly follow‐ups in 2869 prosp...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6818023/ https://www.ncbi.nlm.nih.gov/pubmed/31590581 http://dx.doi.org/10.1161/JAHA.119.012554 |
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author | Blum, Steffen Aeschbacher, Stefanie Meyre, Pascal Zwimpfer, Leon Reichlin, Tobias Beer, Jürg H. Ammann, Peter Auricchio, Angelo Kobza, Richard Erne, Paul Moschovitis, Giorgio Di Valentino, Marcello Shah, Dipen Schläpfer, Jürg Henz, Selina Meyer‐Zürn, Christine Roten, Laurent Schwenkglenks, Matthias Sticherling, Christian Kühne, Michael Osswald, Stefan Conen, David |
author_facet | Blum, Steffen Aeschbacher, Stefanie Meyre, Pascal Zwimpfer, Leon Reichlin, Tobias Beer, Jürg H. Ammann, Peter Auricchio, Angelo Kobza, Richard Erne, Paul Moschovitis, Giorgio Di Valentino, Marcello Shah, Dipen Schläpfer, Jürg Henz, Selina Meyer‐Zürn, Christine Roten, Laurent Schwenkglenks, Matthias Sticherling, Christian Kühne, Michael Osswald, Stefan Conen, David |
author_sort | Blum, Steffen |
collection | PubMed |
description | BACKGROUND: The incidence and predictors of atrial fibrillation (AF) progression are currently not well defined, and clinical AF progression partly overlaps with rhythm control interventions (RCIs). METHODS AND RESULTS: We assessed AF type and intercurrent RCIs during yearly follow‐ups in 2869 prospectively followed patients with paroxysmal or persistent AF. Clinical AF progression was defined as progression from paroxysmal to nonparoxysmal or from persistent to permanent AF. An RCI was defined as pulmonary vein isolation, electrical cardioversion, or new treatment with amiodarone. During a median follow‐up of 3 years, the incidence of clinical AF progression was 5.2 per 100 patient‐years, and 10.9 per 100 patient‐years for any RCI. Significant predictors for AF progression were body mass index (hazard ratio [HR], 1.03; 95% CI, 1.01–1.05), heart rate (HR per 5 beats/min increase, 1.05; 95% CI, 1.02–1.08), age (HR per 5‐year increase 1.19; 95% CI, 1.13–1.27), systolic blood pressure (HR per 5 mm Hg increase, 1.03; 95% CI, 1.00–1.05), history of hyperthyroidism (HR, 1.71; 95% CI, 1.16–2.52), stroke (HR, 1.50; 95% CI, 1.19–1.88), and heart failure (HR, 1.69; 95% CI, 1.34–2.13). Regular physical activity (HR, 0.80; 95% CI, 0.66–0.98) and previous pulmonary vein isolation (HR, 0.69; 95% CI, 0.53–0.90) showed an inverse association. Significant predictive factors for RCIs were physical activity (HR, 1.42; 95% CI, 1.20–1.68), AF‐related symptoms (HR, 1.84; 95% CI, 1.47–2.30), age (HR per 5‐year increase, 0.88; 95% CI, 0.85–0.92), and paroxysmal AF (HR, 0.61; 95% CI, 0.51–0.73). CONCLUSIONS: Cardiovascular risk factors and comorbidities were key predictors of clinical AF progression. A healthy lifestyle may therefore reduce the risk of AF progression. |
format | Online Article Text |
id | pubmed-6818023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68180232019-11-04 Incidence and Predictors of Atrial Fibrillation Progression Blum, Steffen Aeschbacher, Stefanie Meyre, Pascal Zwimpfer, Leon Reichlin, Tobias Beer, Jürg H. Ammann, Peter Auricchio, Angelo Kobza, Richard Erne, Paul Moschovitis, Giorgio Di Valentino, Marcello Shah, Dipen Schläpfer, Jürg Henz, Selina Meyer‐Zürn, Christine Roten, Laurent Schwenkglenks, Matthias Sticherling, Christian Kühne, Michael Osswald, Stefan Conen, David J Am Heart Assoc Original Research BACKGROUND: The incidence and predictors of atrial fibrillation (AF) progression are currently not well defined, and clinical AF progression partly overlaps with rhythm control interventions (RCIs). METHODS AND RESULTS: We assessed AF type and intercurrent RCIs during yearly follow‐ups in 2869 prospectively followed patients with paroxysmal or persistent AF. Clinical AF progression was defined as progression from paroxysmal to nonparoxysmal or from persistent to permanent AF. An RCI was defined as pulmonary vein isolation, electrical cardioversion, or new treatment with amiodarone. During a median follow‐up of 3 years, the incidence of clinical AF progression was 5.2 per 100 patient‐years, and 10.9 per 100 patient‐years for any RCI. Significant predictors for AF progression were body mass index (hazard ratio [HR], 1.03; 95% CI, 1.01–1.05), heart rate (HR per 5 beats/min increase, 1.05; 95% CI, 1.02–1.08), age (HR per 5‐year increase 1.19; 95% CI, 1.13–1.27), systolic blood pressure (HR per 5 mm Hg increase, 1.03; 95% CI, 1.00–1.05), history of hyperthyroidism (HR, 1.71; 95% CI, 1.16–2.52), stroke (HR, 1.50; 95% CI, 1.19–1.88), and heart failure (HR, 1.69; 95% CI, 1.34–2.13). Regular physical activity (HR, 0.80; 95% CI, 0.66–0.98) and previous pulmonary vein isolation (HR, 0.69; 95% CI, 0.53–0.90) showed an inverse association. Significant predictive factors for RCIs were physical activity (HR, 1.42; 95% CI, 1.20–1.68), AF‐related symptoms (HR, 1.84; 95% CI, 1.47–2.30), age (HR per 5‐year increase, 0.88; 95% CI, 0.85–0.92), and paroxysmal AF (HR, 0.61; 95% CI, 0.51–0.73). CONCLUSIONS: Cardiovascular risk factors and comorbidities were key predictors of clinical AF progression. A healthy lifestyle may therefore reduce the risk of AF progression. John Wiley and Sons Inc. 2019-10-08 /pmc/articles/PMC6818023/ /pubmed/31590581 http://dx.doi.org/10.1161/JAHA.119.012554 Text en © 2019 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Research Blum, Steffen Aeschbacher, Stefanie Meyre, Pascal Zwimpfer, Leon Reichlin, Tobias Beer, Jürg H. Ammann, Peter Auricchio, Angelo Kobza, Richard Erne, Paul Moschovitis, Giorgio Di Valentino, Marcello Shah, Dipen Schläpfer, Jürg Henz, Selina Meyer‐Zürn, Christine Roten, Laurent Schwenkglenks, Matthias Sticherling, Christian Kühne, Michael Osswald, Stefan Conen, David Incidence and Predictors of Atrial Fibrillation Progression |
title | Incidence and Predictors of Atrial Fibrillation Progression |
title_full | Incidence and Predictors of Atrial Fibrillation Progression |
title_fullStr | Incidence and Predictors of Atrial Fibrillation Progression |
title_full_unstemmed | Incidence and Predictors of Atrial Fibrillation Progression |
title_short | Incidence and Predictors of Atrial Fibrillation Progression |
title_sort | incidence and predictors of atrial fibrillation progression |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6818023/ https://www.ncbi.nlm.nih.gov/pubmed/31590581 http://dx.doi.org/10.1161/JAHA.119.012554 |
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