Latent transition analysis of cardiac arrest patients treated in the intensive care unit.

<h4>Background and objective</h4>Post-cardiac arrest (CA) syndrome is heterogenous in their clinical presentations and outcomes. This study aimed to explore the transition and stability of subphenotypes (profiles) of CA treated in the intensive care unit (ICU).<h4>Patients and meth...

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Autores principales:	Lifeng Xing, Min Yao, Hemant Goyal, Yucai Hong, Zhongheng Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a9252927ef174c558526713cb9517b66
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spelling	oai:doaj.org-article:a9252927ef174c558526713cb9517b662021-11-25T06:23:41ZLatent transition analysis of cardiac arrest patients treated in the intensive care unit.1932-620310.1371/journal.pone.0252318https://doaj.org/article/a9252927ef174c558526713cb9517b662021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0252318https://doaj.org/toc/1932-6203<h4>Background and objective</h4>Post-cardiac arrest (CA) syndrome is heterogenous in their clinical presentations and outcomes. This study aimed to explore the transition and stability of subphenotypes (profiles) of CA treated in the intensive care unit (ICU).<h4>Patients and methods</h4>Clinical features of CA patients on day 1 and 3 after ICU admission were modeled by latent transition analysis (LTA) to explore the transition between subphenotypes over time. The association between different transition patterns and mortality outcome was explored using multivariable logistic regression.<h4>Results</h4>We identified 848 eligible patients from the database. The LPA identified three distinct subphenotypes: Profile 1 accounted for the largest proportion (73%) and was considered as the baseline subphenotype. Profile 2 (13%) was characterized by brain injury and profile 3 (14%) was characterized by multiple organ dysfunctions. The same three subphenotypes were identified on day 3. The LTA showed consistent subphenotypes. A majority of patients in profile 2 (72%) and 3 (82%) on day 1 switched to profile 1 on day 3. In the logistic regression model, patients in profile 1 on day 1 transitioned to profile 3 had worse survival outcome than those continue to remain in profile 1 (OR: 20.64; 95% CI: 6.01 to 70.94; p < 0.001) and transitioned to profile 2 (OR: 8.42; 95% CI: 2.22 to 31.97; p = 0.002) on day 3.<h4>Conclusion</h4>The study identified three subphenotypes of CA, which was consistent on day 1 and 3 after ICU admission. Patients who transitioned to profile 3 on day 3 had significantly worse survival outcome than those remained in profile 1 or 2.Lifeng XingMin YaoHemant GoyalYucai HongZhongheng ZhangPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 5, p e0252318 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lifeng Xing Min Yao Hemant Goyal Yucai Hong Zhongheng Zhang Latent transition analysis of cardiac arrest patients treated in the intensive care unit.
description	<h4>Background and objective</h4>Post-cardiac arrest (CA) syndrome is heterogenous in their clinical presentations and outcomes. This study aimed to explore the transition and stability of subphenotypes (profiles) of CA treated in the intensive care unit (ICU).<h4>Patients and methods</h4>Clinical features of CA patients on day 1 and 3 after ICU admission were modeled by latent transition analysis (LTA) to explore the transition between subphenotypes over time. The association between different transition patterns and mortality outcome was explored using multivariable logistic regression.<h4>Results</h4>We identified 848 eligible patients from the database. The LPA identified three distinct subphenotypes: Profile 1 accounted for the largest proportion (73%) and was considered as the baseline subphenotype. Profile 2 (13%) was characterized by brain injury and profile 3 (14%) was characterized by multiple organ dysfunctions. The same three subphenotypes were identified on day 3. The LTA showed consistent subphenotypes. A majority of patients in profile 2 (72%) and 3 (82%) on day 1 switched to profile 1 on day 3. In the logistic regression model, patients in profile 1 on day 1 transitioned to profile 3 had worse survival outcome than those continue to remain in profile 1 (OR: 20.64; 95% CI: 6.01 to 70.94; p < 0.001) and transitioned to profile 2 (OR: 8.42; 95% CI: 2.22 to 31.97; p = 0.002) on day 3.<h4>Conclusion</h4>The study identified three subphenotypes of CA, which was consistent on day 1 and 3 after ICU admission. Patients who transitioned to profile 3 on day 3 had significantly worse survival outcome than those remained in profile 1 or 2.
format	article
author	Lifeng Xing Min Yao Hemant Goyal Yucai Hong Zhongheng Zhang
author_facet	Lifeng Xing Min Yao Hemant Goyal Yucai Hong Zhongheng Zhang
author_sort	Lifeng Xing
title	Latent transition analysis of cardiac arrest patients treated in the intensive care unit.
title_short	Latent transition analysis of cardiac arrest patients treated in the intensive care unit.
title_full	Latent transition analysis of cardiac arrest patients treated in the intensive care unit.
title_fullStr	Latent transition analysis of cardiac arrest patients treated in the intensive care unit.
title_full_unstemmed	Latent transition analysis of cardiac arrest patients treated in the intensive care unit.
title_sort	latent transition analysis of cardiac arrest patients treated in the intensive care unit.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/a9252927ef174c558526713cb9517b66
work_keys_str_mv	AT lifengxing latenttransitionanalysisofcardiacarrestpatientstreatedintheintensivecareunit AT minyao latenttransitionanalysisofcardiacarrestpatientstreatedintheintensivecareunit AT hemantgoyal latenttransitionanalysisofcardiacarrestpatientstreatedintheintensivecareunit AT yucaihong latenttransitionanalysisofcardiacarrestpatientstreatedintheintensivecareunit AT zhonghengzhang latenttransitionanalysisofcardiacarrestpatientstreatedintheintensivecareunit
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Latent transition analysis of cardiac arrest patients treated in the intensive care unit.

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