The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials
Open accessAbstract
Background Subphenotypes have been identified within heterogeneous syndromes such as asthma and breast cancer, with important therapeutic implications. Whether subphenotypes exist within the acute respiratory distress syndrome (ARDS), another heterogeneous syndrome, is unknown. Methods We applied latent class modeling to identify subphenotypes using clinical and biological data from two NHLBI ARDS randomized controlled trials; modeling was conducted independently in each cohort. We then tested the association of subphenotypes with clinical outcomes in both cohorts and with the response to positive end-expiratory pressure (PEEP) in the second cohort. Findings Independent latent class models indicated that a two-class (i.e. two subphenotype) model was optimal for both cohorts. In both cohorts, we identified a hyperinflammatory subphenotype (Phenotype 2) that was characterized by higher plasma levels of inflammatory biomarkers, a higher prevalence of vasopressor use, lower serum bicarbonate, and a higher prevalence of sepsis, compared to Phenotype 1. Subjects in Phenotype 2 had higher mortality and fewer ventilator-free and organ failure-free days in both cohorts. In the second cohort, the effects of ventilation strategy on mortality, ventilator and organ failure-free days differed significantly by phenotype (p=0.003–0.049 for interactions). Interpretation Latent class models identify two subphenotypes within ARDS, one of which is characterized by more severe inflammation, shock, and metabolic acidosis and by significantly worse clinical outcomes. Response to treatment in a randomized trial of PEEP strategies differed based on subphenotype. Identification of ARDS subphenotypes may be useful in selecting patients for clinical trials. Funding National Institutes of Health
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Acute respiratory distress syndrome
Matthay, M. A., Zemans, R. L., Zimmerman, G. A., Arabi, Y. M., Beitler, J. R., Mercat, A., Herridge, M., Randolph, A. G., & Calfee, C. S. (2019) · Nature Reviews Disease Primers · doi:10.1038/s41572-019-0069-0 · Cited by 2,387
Self-citationAcute respiratory distress syndrome
Thompson, B. T., Chambers, R. C., & Liu, K. D. (2017) · New England Journal of Medicine · doi:10.1056/nejmra1608077 · Cited by 1,807
Self-citationDerivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis
Seymour, C. W., Kennedy, J. N., Wang, S., Chang, C.-C. H., Elliott, C. F., Xu, Z., Berry, S., Clermont, G., Cooper, G., Gomez, H., et al. (2019) · JAMA · doi:10.1001/jama.2019.5791 · Cited by 1,567
Practitioner’s guide to latent class analysis: Methodological considerations and common pitfalls
Sinha, P., Calfee, C. S., & Delucchi, K. L. (2021) · Critical Care Medicine · doi:10.1097/ccm.0000000000004710 · Cited by 1,204
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Metadata
- Authors
- Calfee, C. S., Delucchi, K., Parsons, P. E., Thompson, B. T., Ware, L. B., & Matthay, M. A.
- Venue
- The Lancet Respiratory Medicine
- Publisher
- Elsevier BV
- Published
- 2014-08
- Volume
- 2
- Issue
- 8
- Pages
- 611-620
- ISSN
- 2213-2600 (ISSN-L)
- OpenAlex
- W2124519382
- Cited by
- 1,544
- References
- 42
- FWCI
- 33.68
- Type
- journal article
- Language
- en
- Open access
- green
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