Longitudinal phenotypes in patients with acute respiratory distress syndrome: a multi-database study.

ABSTRACT:

Background

Previously identified phenotypes of acute respiratory distress syndrome (ARDS) have been limited by a disregard for temporal dynamics. We aimed to identify longitudinal phenotypes in ARDS to test the prognostic and predictive enrichment of longitudinal phenotypes, and to develop simplified models for phenotype identification.

Methods

We conducted a multi-database study based on the Chinese Database in Intensive Care (CDIC) and four ARDS randomized clinical trials (RCTs). We employed latent class analysis (LCA) to identify longitudinal phenotypes using 24-hourly data from the first four days of invasive ventilation. We used the Cox regression model to explore the association between time-varying respiratory parameters and 28-day mortality across phenotypes. Phenoty

SUBMITTER: Chen H 

PROVIDER: S-EPMC9635207 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature