Plasma metabolomics signatures predict COVID-19 patient outcome at ICU admission comparable to clinical scores.

ABSTRACT: SARS-CoV-2 significantly impacts the human metabolome. This study aims to evaluate the predictive capability of a comprehensive module clustering approach in plasma metabolomics for identifying the risk of critical complications in COVID-19 patients admitted to intensive care units (ICUs). We conducted a prospective monocenter study, gathering blood samples within 24 h of ICU admission, alongside clinical, biological, and demographic patient characteristics. Subsequently, we quantified patients' plasma metabolome using a comprehensive untargeted metabolomics approach. First, we stratified patients based on a composite outcome score indicating critical status. Analysis of potential predictors revealed that older patients with higher severity scores and pronounced alterations in key biologic

SUBMITTER: Karvelsson ST 

PROVIDER: S-EPMC12049461 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature