Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study.

ABSTRACT:

Background

COVID-19 is a multi-system disorder with high variability in clinical outcomes among patients who are admitted to hospital. Although some cytokines such as interleukin (IL)-6 are believed to be associated with severity, there are no early biomarkers that can reliably predict patients who are more likely to have adverse outcomes. Thus, it is crucial to discover predictive markers of serious complications.

Methods

In this retrospective cohort study, we analysed samples from 455 participants with COVID-19 who had had a positive SARS-CoV-2 RT-PCR result between April 14, 2020, and Dec 1, 2020 and who had visited one of three Mayo Clinic sites in the USA (Minnesota, Arizona, or Florida) in the same period. These participants were assigned to three subgroups depending o

SUBMITTER: Byeon SK 

PROVIDER: S-EPMC9273185 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature