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Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a common cause of death. Early circulatory failure is the most common reason for death within the first 48 h. This study in intensive care unit (ICU) patients with OHCA was designed to identify and characterize clusters based on clinical features...

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Autores principales: Binois, Yannick, Renaudier, Marie, Dumas, Florence, Youssfi, Younès, Beganton, Frankie, Jost, Daniel, Lamhaut, Lionel, Marijon, Eloi, Jouven, Xavier, Cariou, Alain, Bougouin, Wulfran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256665/
https://www.ncbi.nlm.nih.gov/pubmed/37294400
http://dx.doi.org/10.1186/s13613-023-01143-8
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author Binois, Yannick
Renaudier, Marie
Dumas, Florence
Youssfi, Younès
Beganton, Frankie
Jost, Daniel
Lamhaut, Lionel
Marijon, Eloi
Jouven, Xavier
Cariou, Alain
Bougouin, Wulfran
author_facet Binois, Yannick
Renaudier, Marie
Dumas, Florence
Youssfi, Younès
Beganton, Frankie
Jost, Daniel
Lamhaut, Lionel
Marijon, Eloi
Jouven, Xavier
Cariou, Alain
Bougouin, Wulfran
author_sort Binois, Yannick
collection PubMed
description BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a common cause of death. Early circulatory failure is the most common reason for death within the first 48 h. This study in intensive care unit (ICU) patients with OHCA was designed to identify and characterize clusters based on clinical features and to determine the frequency of death from refractory postresuscitation shock (RPRS) in each cluster. METHODS: We retrospectively identified adults admitted alive to ICUs after OHCA in 2011–2018 and recorded in a prospective registry for the Paris region (France). We identified patient clusters by performing an unsupervised hierarchical cluster analysis (without mode of death among the variables) based on Utstein clinical and laboratory variables. For each cluster, we estimated the hazard ratio (HRs) for RPRS. RESULTS: Of the 4445 included patients, 1468 (33%) were discharged alive from the ICU and 2977 (67%) died in the ICU. We identified four clusters: initial shockable rhythm with short low-flow time (cluster 1), initial non-shockable rhythm with usual absence of ST-segment elevation (cluster 2), initial non-shockable rhythm with long no-flow time (cluster 3), and long low-flow time with high epinephrine dose (cluster 4). RPRS was significantly associated with this last cluster (HR, 5.51; 95% confidence interval 4.51–6.74). CONCLUSIONS: We identified patient clusters based on Utstein criteria, and one cluster was strongly associated with RPRS. This result may help to make decisions about using specific treatments after OHCA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13613-023-01143-8.
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spelling pubmed-102566652023-06-11 Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis Binois, Yannick Renaudier, Marie Dumas, Florence Youssfi, Younès Beganton, Frankie Jost, Daniel Lamhaut, Lionel Marijon, Eloi Jouven, Xavier Cariou, Alain Bougouin, Wulfran Ann Intensive Care Research BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a common cause of death. Early circulatory failure is the most common reason for death within the first 48 h. This study in intensive care unit (ICU) patients with OHCA was designed to identify and characterize clusters based on clinical features and to determine the frequency of death from refractory postresuscitation shock (RPRS) in each cluster. METHODS: We retrospectively identified adults admitted alive to ICUs after OHCA in 2011–2018 and recorded in a prospective registry for the Paris region (France). We identified patient clusters by performing an unsupervised hierarchical cluster analysis (without mode of death among the variables) based on Utstein clinical and laboratory variables. For each cluster, we estimated the hazard ratio (HRs) for RPRS. RESULTS: Of the 4445 included patients, 1468 (33%) were discharged alive from the ICU and 2977 (67%) died in the ICU. We identified four clusters: initial shockable rhythm with short low-flow time (cluster 1), initial non-shockable rhythm with usual absence of ST-segment elevation (cluster 2), initial non-shockable rhythm with long no-flow time (cluster 3), and long low-flow time with high epinephrine dose (cluster 4). RPRS was significantly associated with this last cluster (HR, 5.51; 95% confidence interval 4.51–6.74). CONCLUSIONS: We identified patient clusters based on Utstein criteria, and one cluster was strongly associated with RPRS. This result may help to make decisions about using specific treatments after OHCA. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13613-023-01143-8. Springer International Publishing 2023-06-09 /pmc/articles/PMC10256665/ /pubmed/37294400 http://dx.doi.org/10.1186/s13613-023-01143-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Binois, Yannick
Renaudier, Marie
Dumas, Florence
Youssfi, Younès
Beganton, Frankie
Jost, Daniel
Lamhaut, Lionel
Marijon, Eloi
Jouven, Xavier
Cariou, Alain
Bougouin, Wulfran
Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis
title Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis
title_full Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis
title_fullStr Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis
title_full_unstemmed Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis
title_short Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis
title_sort factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256665/
https://www.ncbi.nlm.nih.gov/pubmed/37294400
http://dx.doi.org/10.1186/s13613-023-01143-8
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