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Automated left atrial strain analysis for predicting atrial fibrillation in severe COVID-19 pneumonia: a prospective study

BACKGROUND: Atrial fibrillation (AF) is the most documented arrhythmia in COVID-19 pneumonia. Left atrial (LA) strain (LAS) analysis, a marker of LA contractility, have been associated with the development of AF in several clinical situations. We aimed to assess the diagnostic ability of LA strain p...

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Autores principales: Beyls, Christophe, Hermida, Alexis, Bohbot, Yohann, Martin, Nicolas, Viart, Christophe, Boisgard, Solenne, Daumin, Camille, Huette, Pierre, Dupont, Hervé, Abou-Arab, Osama, Mahjoub, Yazine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8649321/
https://www.ncbi.nlm.nih.gov/pubmed/34874509
http://dx.doi.org/10.1186/s13613-021-00955-w
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author Beyls, Christophe
Hermida, Alexis
Bohbot, Yohann
Martin, Nicolas
Viart, Christophe
Boisgard, Solenne
Daumin, Camille
Huette, Pierre
Dupont, Hervé
Abou-Arab, Osama
Mahjoub, Yazine
author_facet Beyls, Christophe
Hermida, Alexis
Bohbot, Yohann
Martin, Nicolas
Viart, Christophe
Boisgard, Solenne
Daumin, Camille
Huette, Pierre
Dupont, Hervé
Abou-Arab, Osama
Mahjoub, Yazine
author_sort Beyls, Christophe
collection PubMed
description BACKGROUND: Atrial fibrillation (AF) is the most documented arrhythmia in COVID-19 pneumonia. Left atrial (LA) strain (LAS) analysis, a marker of LA contractility, have been associated with the development of AF in several clinical situations. We aimed to assess the diagnostic ability of LA strain parameters to predict AF in patients with severe hypoxemic COVID-19 pneumonia. We conducted a prospective single center study in Amiens University Hospital intensive care unit (ICU) (France). Adult patients with severe or critical COVID-19 pneumonia according to the World Health Organization definition and in sinus rhythm were included. Transthoracic echocardiography was performed within 48 h of ICU admission. LA strain analysis was performed by an automated software. The following LA strain parameters were recorded: LA strain during reservoir phase (LASr), LA strain during conduit phase (LAScd) and LA strain during contraction phase (LASct). The primary endpoint was the occurrence of AF during ICU stay. RESULTS: From March 2020 to February of 2021, 79 patients were included. Sixteen patients (20%) developed AF in ICU. Patients of the AF group were significantly older with a higher SAPS II score than those without AF. LAScd and LASr were significantly more impaired in the AF group compared to the other group (− 8.1 [− 6.3; − 10.9] vs. − 17.2 [− 5.0; − 10.2] %; P < 0.001 and 20.2 [12.3;27.3] % vs. 30.5 [23.8;36.2] %; P = 0.002, respectively), while LASct did not significantly differ between groups (p = 0.31). In a multivariate model, LAScd and SOFA cv were significantly associated with the occurrence of AF. A LAScd cutoff value of − 11% had a sensitivity of 76% and a specificity of 75% to identify patients with AF. The 30-day cumulative risk of AF was 42 ± 9% with LAScd > − 11% and 8 ± 4% with LAScd ≤ − 11% (log rank test P value < 0.0001). CONCLUSION: For patients with severe COVID-19 pneumonia, development of AF during ICU stay is common (20%). LAS parameters seem useful in predicting AF within the first 48 h of ICU admission. Trial registration: NCT04354558.
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spelling pubmed-86493212021-12-07 Automated left atrial strain analysis for predicting atrial fibrillation in severe COVID-19 pneumonia: a prospective study Beyls, Christophe Hermida, Alexis Bohbot, Yohann Martin, Nicolas Viart, Christophe Boisgard, Solenne Daumin, Camille Huette, Pierre Dupont, Hervé Abou-Arab, Osama Mahjoub, Yazine Ann Intensive Care Research BACKGROUND: Atrial fibrillation (AF) is the most documented arrhythmia in COVID-19 pneumonia. Left atrial (LA) strain (LAS) analysis, a marker of LA contractility, have been associated with the development of AF in several clinical situations. We aimed to assess the diagnostic ability of LA strain parameters to predict AF in patients with severe hypoxemic COVID-19 pneumonia. We conducted a prospective single center study in Amiens University Hospital intensive care unit (ICU) (France). Adult patients with severe or critical COVID-19 pneumonia according to the World Health Organization definition and in sinus rhythm were included. Transthoracic echocardiography was performed within 48 h of ICU admission. LA strain analysis was performed by an automated software. The following LA strain parameters were recorded: LA strain during reservoir phase (LASr), LA strain during conduit phase (LAScd) and LA strain during contraction phase (LASct). The primary endpoint was the occurrence of AF during ICU stay. RESULTS: From March 2020 to February of 2021, 79 patients were included. Sixteen patients (20%) developed AF in ICU. Patients of the AF group were significantly older with a higher SAPS II score than those without AF. LAScd and LASr were significantly more impaired in the AF group compared to the other group (− 8.1 [− 6.3; − 10.9] vs. − 17.2 [− 5.0; − 10.2] %; P < 0.001 and 20.2 [12.3;27.3] % vs. 30.5 [23.8;36.2] %; P = 0.002, respectively), while LASct did not significantly differ between groups (p = 0.31). In a multivariate model, LAScd and SOFA cv were significantly associated with the occurrence of AF. A LAScd cutoff value of − 11% had a sensitivity of 76% and a specificity of 75% to identify patients with AF. The 30-day cumulative risk of AF was 42 ± 9% with LAScd > − 11% and 8 ± 4% with LAScd ≤ − 11% (log rank test P value < 0.0001). CONCLUSION: For patients with severe COVID-19 pneumonia, development of AF during ICU stay is common (20%). LAS parameters seem useful in predicting AF within the first 48 h of ICU admission. Trial registration: NCT04354558. Springer International Publishing 2021-12-07 /pmc/articles/PMC8649321/ /pubmed/34874509 http://dx.doi.org/10.1186/s13613-021-00955-w Text en © The Author(s) 2021 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 Research
Beyls, Christophe
Hermida, Alexis
Bohbot, Yohann
Martin, Nicolas
Viart, Christophe
Boisgard, Solenne
Daumin, Camille
Huette, Pierre
Dupont, Hervé
Abou-Arab, Osama
Mahjoub, Yazine
Automated left atrial strain analysis for predicting atrial fibrillation in severe COVID-19 pneumonia: a prospective study
title Automated left atrial strain analysis for predicting atrial fibrillation in severe COVID-19 pneumonia: a prospective study
title_full Automated left atrial strain analysis for predicting atrial fibrillation in severe COVID-19 pneumonia: a prospective study
title_fullStr Automated left atrial strain analysis for predicting atrial fibrillation in severe COVID-19 pneumonia: a prospective study
title_full_unstemmed Automated left atrial strain analysis for predicting atrial fibrillation in severe COVID-19 pneumonia: a prospective study
title_short Automated left atrial strain analysis for predicting atrial fibrillation in severe COVID-19 pneumonia: a prospective study
title_sort automated left atrial strain analysis for predicting atrial fibrillation in severe covid-19 pneumonia: a prospective study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8649321/
https://www.ncbi.nlm.nih.gov/pubmed/34874509
http://dx.doi.org/10.1186/s13613-021-00955-w
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