Predicting sepsis severity at first clinical presentation: The role of endotypes and mechanistic signatures.

ABSTRACT:

Background

Inter-individual variability during sepsis limits appropriate triage of patients. Identifying, at first clinical presentation, gene expression signatures that predict subsequent severity will allow clinicians to identify the most at-risk groups of patients and enable appropriate antibiotic use.

Methods

Blood RNA-Seq and clinical data were collected from 348 patients in four emergency rooms (ER) and one intensive-care-unit (ICU), and 44 healthy controls. Gene expression profiles were analyzed using machine learning and data mining to identify clinically relevant gene signatures reflecting disease severity, organ dysfunction, mortality, and specific endotypes/mechanisms.

Findings

Gene expression signatures were obtained that predicted severity/organ dysfuncti

SUBMITTER: Baghela A 

PROVIDER: S-EPMC8808161 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature