Non-invasive urinary proteomic biomarkers for prognostic assessment in sepsis.

ABSTRACT: Early identification of the death risk of sepsis may improve short-term prognosis. The objective of this study was to identify urinary proteomic biomarkers and create a model to predict short-term outcomes in sepsis patients. A total of 46 sepsis patients selected from the intensive care unit of a comprehensive tertiary hospital were enrolled in this study. We used data-independent acquisition (DIA) proteomics to detect proteins in the urinary of death patients (n = 14) and survivals (n = 32). KEGG and GO analyses were conducted to investigate the possible functions of these proteins. Feature variables were selected from the differentially expressed proteins using the Least Absolute Shrinkage and Selection Operator (LASSO) and the random forest algorithms and by determining whether their p

SUBMITTER: Zeng Q 

PROVIDER: S-EPMC12255687 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature