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Identification of three classes of acute respiratory distress syndrome using latent class analysis

Acute respiratory distress syndrome (ARDS) is a highly heterogeneous syndrome that can exhibit significant differences in the underlying causes, leading to different responses to treatment. It is required to identify subtypes of ARDS to guideline clinical treatment and trial design. The study aimed...

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Autor principal: Zhang, Zhongheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5880177/
https://www.ncbi.nlm.nih.gov/pubmed/29610712
http://dx.doi.org/10.7717/peerj.4592
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author Zhang, Zhongheng
author_facet Zhang, Zhongheng
author_sort Zhang, Zhongheng
collection PubMed
description Acute respiratory distress syndrome (ARDS) is a highly heterogeneous syndrome that can exhibit significant differences in the underlying causes, leading to different responses to treatment. It is required to identify subtypes of ARDS to guideline clinical treatment and trial design. The study aimed to identify subtypes of ARDS using latent class analysis (LCA). The study was a secondary analysis of the EDEN study, which was a randomized, controlled, multicenter trial conducted from January 2, 2008 to April 12, 2011. The primary study endpoint was death through 90-day follow up. LCA was performed incorporating variables on day 0 before randomization. The number of classes was chosen by a bootstrapped likelihood ratio test, Bayesian information criterion and the number of patients in each class. A total of 943 patients were enrolled in the study, including 219 (23.2%) non-survivors and 724 (76.8%) survivors. The LCA identified three classes of ARDS. Class 1 (hemodynamically unstable type) had significantly higher mortality rate (p = 0.003) than class 2 (intermediate type) and 3 (stable type) through 90 days follow up. There was significant interaction between cumulative fluid balance and the class (p = 0.02). While more fluid balance was beneficial for class 1, it was harmful for class 2 and 3. In conclusion, the study identified three classes of ARDS, which showed different clinical presentations, responses to fluid therapy and prognosis. The classification system used simple clinical variables and could help to design ARDS trials in the future.
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spelling pubmed-58801772018-04-02 Identification of three classes of acute respiratory distress syndrome using latent class analysis Zhang, Zhongheng PeerJ Clinical Trials Acute respiratory distress syndrome (ARDS) is a highly heterogeneous syndrome that can exhibit significant differences in the underlying causes, leading to different responses to treatment. It is required to identify subtypes of ARDS to guideline clinical treatment and trial design. The study aimed to identify subtypes of ARDS using latent class analysis (LCA). The study was a secondary analysis of the EDEN study, which was a randomized, controlled, multicenter trial conducted from January 2, 2008 to April 12, 2011. The primary study endpoint was death through 90-day follow up. LCA was performed incorporating variables on day 0 before randomization. The number of classes was chosen by a bootstrapped likelihood ratio test, Bayesian information criterion and the number of patients in each class. A total of 943 patients were enrolled in the study, including 219 (23.2%) non-survivors and 724 (76.8%) survivors. The LCA identified three classes of ARDS. Class 1 (hemodynamically unstable type) had significantly higher mortality rate (p = 0.003) than class 2 (intermediate type) and 3 (stable type) through 90 days follow up. There was significant interaction between cumulative fluid balance and the class (p = 0.02). While more fluid balance was beneficial for class 1, it was harmful for class 2 and 3. In conclusion, the study identified three classes of ARDS, which showed different clinical presentations, responses to fluid therapy and prognosis. The classification system used simple clinical variables and could help to design ARDS trials in the future. PeerJ Inc. 2018-03-30 /pmc/articles/PMC5880177/ /pubmed/29610712 http://dx.doi.org/10.7717/peerj.4592 Text en © 2018 Zhang http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Clinical Trials
Zhang, Zhongheng
Identification of three classes of acute respiratory distress syndrome using latent class analysis
title Identification of three classes of acute respiratory distress syndrome using latent class analysis
title_full Identification of three classes of acute respiratory distress syndrome using latent class analysis
title_fullStr Identification of three classes of acute respiratory distress syndrome using latent class analysis
title_full_unstemmed Identification of three classes of acute respiratory distress syndrome using latent class analysis
title_short Identification of three classes of acute respiratory distress syndrome using latent class analysis
title_sort identification of three classes of acute respiratory distress syndrome using latent class analysis
topic Clinical Trials
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5880177/
https://www.ncbi.nlm.nih.gov/pubmed/29610712
http://dx.doi.org/10.7717/peerj.4592
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