1. Identification of phenotypes in paediatric patients with acute respiratory distress syndrome: a latent class analysis
- Author
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Dahmer, Mary K, Yang, Guangyu, Zhang, Min, Quasney, Michael W, Sapru, Anil, Weeks, Heidi M, Sinha, Pratik, Curley, Martha AQ, Delucchi, Kevin L, Calfee, Carolyn S, Flori, Heidi, investigators, RESTORE and BALI study, Matthay, Michael A, Bateman, Scot T, Berg, Marc D, Borasino, Santiago, Bysani, Gokul K, Cowl, Allison S, Bowens, Cindy D, Faustino, Vincent S, Fineman, Lori D, Godshall, Aaron J, Hirshberg, Eliotte L, Kirby, Aileen L, McLaughlin, Gwenn E, Medar, Shivanand S, Oren, Phineas P, Schneider, James B, Schwarz, Adam J, Shanley, Thomas P, Source, Lauren R, Truemper, Edward J, Heyden, Michele A Vender, Wittmayer, Kimberly, Zuppa, Athena F, Wypij, David, and Network, Pediatric Acute Lung Injury and Sepsis Investigators
- Subjects
Biomedical and Clinical Sciences ,Clinical Sciences ,Orphan Drug ,Clinical Research ,Rare Diseases ,Acute Respiratory Distress Syndrome ,Lung ,2.1 Biological and endogenous factors ,Aetiology ,Respiratory ,Area Under Curve ,Child ,Humans ,Latent Class Analysis ,Phenotype ,Respiration ,Artificial ,Respiratory Distress Syndrome ,RESTORE and BALI study investigators ,Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) Network ,Public Health and Health Services ,Other Medical and Health Sciences ,Cardiovascular medicine and haematology ,Clinical sciences - Abstract
BackgroundPrevious latent class analysis of adults with acute respiratory distress syndrome (ARDS) identified two phenotypes, distinguished by the degree of inflammation. We aimed to identify phenotypes in children with ARDS in whom developmental differences might be important, using a latent class analysis approach similar to that used in adults.MethodsThis study was a secondary analysis of data aggregated from the Randomized Evaluation of Sedation Titration for Respiratory Failure (RESTORE) clinical trial and the Genetic Variation and Biomarkers in Children with Acute Lung Injury (BALI) ancillary study. We used latent class analysis, which included demographic, clinical, and plasma biomarker variables, to identify paediatric ARDS (PARDS) phenotypes within a cohort of children included in the RESTORE and BALI studies. The association of phenotypes with clinically relevant outcomes and the performance of paediatric data in adult ARDS classification algorithms were also assessed.Findings304 children with PARDS were included in this secondary analysis. Using latent class analysis, a two-class model was a better fit for the cohort than a one-class model (p
- Published
- 2022