Immune cell profiling supports early prediction of sepsis-associated acute kidney disease using a decision tree algorithm.

ABSTRACT: Sepsis is a major cause of acute kidney injury, progressing to sepsis-associated acute kidney disease (SA-AKD). This study explores SA-AKD prediction by combining immune cell profiling. Peripheral immune cell expression and phenotypes were analyzed in sepsis patients without (n = 97) and with (n = 41) SA-AKD, admitted to a hospital (2020-2022). Blood urea nitrogen and creatinine levels were measured, and a decision tree (DT)-based model was used to evaluate their predictive power in the training (n = 106) and validation (n = 32) cohorts. The DT model, incorporating naïve Treg and CD56^dim NK cells along with clinical parameters, showed high accuracy in predicting SA-AKD. The model using blood urea nitrogen as the first node reached 89.62% accuracy (sensitivity: 94.4% and specific

SUBMITTER: Wu MY 

PROVIDER: S-EPMC12754851 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature