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Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database
Cardiac arrest (CA) may occur due to a variety of causes with heterogeneity in their clinical presentation and outcomes. This study aimed to identify clinical patterns or subphenotypes of CA patients admitted to the intensive care unit (ICU). The clinical and laboratory data of CA patients in a larg...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754393/ https://www.ncbi.nlm.nih.gov/pubmed/31541172 http://dx.doi.org/10.1038/s41598-019-50178-0 |
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author | Zhang, Zhongheng Yao, Min Ho, Kwok M. Hong, Yucai |
author_facet | Zhang, Zhongheng Yao, Min Ho, Kwok M. Hong, Yucai |
author_sort | Zhang, Zhongheng |
collection | PubMed |
description | Cardiac arrest (CA) may occur due to a variety of causes with heterogeneity in their clinical presentation and outcomes. This study aimed to identify clinical patterns or subphenotypes of CA patients admitted to the intensive care unit (ICU). The clinical and laboratory data of CA patients in a large electronic healthcare database were analyzed by latent profile analysis (LPA) to identify whether subphenotypes existed. Multivariable Logistic regression was used to assess whether mortality outcome was different between subphenotypes. A total of 1,352 CA patients fulfilled the eligibility criteria were included. The LPA identified three distinct subphenotypes: Profile 1 (13%) was characterized by evidence of significant neurological injury (low GCS). Profile 2 (15%) was characterized by multiple organ dysfunction with evidence of coagulopathy (prolonged aPTT and INR, decreased platelet count), hepatic injury (high bilirubin), circulatory shock (low mean blood pressure and elevated serum lactate); Profile 3 was the largest proportion (72%) of all CA patients without substantial derangement in major organ function. Profile 2 was associated with a significantly higher risk of death (OR: 2.09; 95% CI: 1.30 to 3.38) whilst the mortality rates of Profiles 3 was not significantly different from Profile 1 in multivariable model. LPA using routinely collected clinical data could identify three distinct subphenotypes of CA; those with multiple organ failure were associated with a significantly higher risk of mortality than other subphenotypes. LPA profiling may help researchers to identify the most appropriate subphenotypes of CA patients for testing effectiveness of a new intervention in a clinical trial. |
format | Online Article Text |
id | pubmed-6754393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-67543932019-10-02 Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database Zhang, Zhongheng Yao, Min Ho, Kwok M. Hong, Yucai Sci Rep Article Cardiac arrest (CA) may occur due to a variety of causes with heterogeneity in their clinical presentation and outcomes. This study aimed to identify clinical patterns or subphenotypes of CA patients admitted to the intensive care unit (ICU). The clinical and laboratory data of CA patients in a large electronic healthcare database were analyzed by latent profile analysis (LPA) to identify whether subphenotypes existed. Multivariable Logistic regression was used to assess whether mortality outcome was different between subphenotypes. A total of 1,352 CA patients fulfilled the eligibility criteria were included. The LPA identified three distinct subphenotypes: Profile 1 (13%) was characterized by evidence of significant neurological injury (low GCS). Profile 2 (15%) was characterized by multiple organ dysfunction with evidence of coagulopathy (prolonged aPTT and INR, decreased platelet count), hepatic injury (high bilirubin), circulatory shock (low mean blood pressure and elevated serum lactate); Profile 3 was the largest proportion (72%) of all CA patients without substantial derangement in major organ function. Profile 2 was associated with a significantly higher risk of death (OR: 2.09; 95% CI: 1.30 to 3.38) whilst the mortality rates of Profiles 3 was not significantly different from Profile 1 in multivariable model. LPA using routinely collected clinical data could identify three distinct subphenotypes of CA; those with multiple organ failure were associated with a significantly higher risk of mortality than other subphenotypes. LPA profiling may help researchers to identify the most appropriate subphenotypes of CA patients for testing effectiveness of a new intervention in a clinical trial. Nature Publishing Group UK 2019-09-20 /pmc/articles/PMC6754393/ /pubmed/31541172 http://dx.doi.org/10.1038/s41598-019-50178-0 Text en © The Author(s) 2019 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Zhang, Zhongheng Yao, Min Ho, Kwok M. Hong, Yucai Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database |
title | Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database |
title_full | Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database |
title_fullStr | Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database |
title_full_unstemmed | Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database |
title_short | Subphenotypes of Cardiac Arrest Patients Admitted to Intensive Care Unit: a latent profile analysis of a large critical care database |
title_sort | subphenotypes of cardiac arrest patients admitted to intensive care unit: a latent profile analysis of a large critical care database |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6754393/ https://www.ncbi.nlm.nih.gov/pubmed/31541172 http://dx.doi.org/10.1038/s41598-019-50178-0 |
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