Subphenotypes in acute respiratory distress syndrome: Latent class analysis of data from two randomised controlled trials

Abstract

Background: Subphenotypes have been identified within heterogeneous diseases such as asthma and breast cancer, with important therapeutic implications. We assessed whether subphenotypes exist within acute respiratory distress syndrome, another heterogeneous disorder. Methods: We used data from two ARDS randomised controlled trials, sponsored by the National Heart, Lung, and Blood Institute. We applied latent class modelling to identify subphenotypes using clinical and biological data. We modelled data from both studies independently. We then tested the association of subphenotypes with clinical outcomes in both cohorts and with the response to positive end-expiratory pressure in the ALVEOLI cohort. Findings: We analysed data for 1022 patients: 473 in the ARMA cohort and 549 in the ALVEOLI cohort. Independent latent class models indicated that a two-class model was the best fit for both cohorts. In both cohorts, we identified a hyperinflammatory subphenotype that was characterised by higher plasma concentrations of inflammatory biomarkers, a higher prevalence of vasopressor use, lower serum bicarbonate concentrations, and a higher prevalence of sepsis than phenotype 1. Participants in phenotype 2 had higher mortality and fewer ventilator-free days and organ failure-free days in both cohorts than did those in phenotype 1. In the ALVEOLI cohort, the effects of ventilation strategy on mortality, ventilator-free days and organ failure-free days differed by phenotype. Interpretation: We have identified two subphenotypes within ARDS, one of which is categorised by more severe inflammation, shock, and metabolic acidosis and by worse clinical outcomes. Response to treatment in a randomised trial of PEEP strategies differed on the basis of subphenotype. Identification of ARDS subphenotypes might be useful in selecting patients for future clinical trials. Funding: National Institutes of Health. © 2014 Elsevier Ltd.

Other Versions

No versions found

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 103,486

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

  • Only published works are available at libraries.

Similar books and articles

Analytics

Added to PP
2017-03-08

Downloads
13 (#1,379,444)

6 months
1 (#1,580,527)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

B. Thompson
Concordia University

References found in this work

No references found.

Add more references