Use of machine learning-based integration to develop a monocyte differentiation-related signature for improving prognosis in patients with sepsis.

ABSTRACT:

Background

Although significant advances have been made in intensive care medicine and antibacterial treatment, sepsis is still a common disease with high mortality. The condition of sepsis patients changes rapidly, and each hour of delay in the administration of appropriate antibiotic treatment can lead to a 4-7% increase in fatality. Therefore, early diagnosis and intervention may help improve the prognosis of patients with sepsis.

Methods

We obtained single-cell sequencing data from 12 patients. This included 14,622 cells from four patients with bacterial infectious sepsis and eight patients with sepsis admitted to the ICU for other various reasons. Monocyte differentiation trajectories were analyzed using the "monocle" software, and differentiation-related genes were ide

SUBMITTER: Ning J 

PROVIDER: S-EPMC10029317 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature