학술논문

Increased percentage of PD-L1+ natural killer cells predicts poor prognosis in sepsis patients: a prospective observational cohort study
Document Type
article
Source
Critical Care, Vol 24, Iss 1, Pp 1-10 (2020)
Subject
Sepsis
NK cells
PD-L1
Biomarker
Mortality
Prognosis
Medical emergencies. Critical care. Intensive care. First aid
RC86-88.9
Language
English
ISSN
1364-8535
Abstract
Abstract Background Natural killer (NK) cells play a major role in immune tolerance after sepsis, and the programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) system mediates evasion of host immunity. The correlation between PD-L1 levels in NK cells and the prognosis of patients with sepsis, however, has not been elucidated. Thus, it was hypothesized that PD-L1 in NK cells could be a novel biomarker of the mortality for sepsis patients. Methods A prospective, observational, cohort study in a general intensive care unit had earlier enrolled patients according to the sepsis-3 criteria, and peripheral blood samples were collected within 24 h post-recruitment. The expression of four co-signaling molecules (PD-1, CD28, PD-L1, and CD86) in NK cells was assayed, and the sequential organ failure assessment (SOFA) scores were recorded on day 1. Patients were followed up until 28 days. Multivariate regression analysis assessed the independent risk factors for 28-day mortality. The association between biomarkers and 28-day mortality was assessed by Cox regression survival analysis. The accuracy of biomarkers for mortality was determined by the area under the receiver operating characteristic (ROC) curve (AUC) analysis. Results A total of 269 patients were recruited, and 114 patients were finally included for final analysis. Of these, 30 (26.3%) patients died during 28 days. The percentage of PD-L1+ NK cells (OR 1.022; 95% CI 1.002–1.043) and SOFA scores (OR 1.247; 95% CI 1.092–1.424) were independent risk factors for 28-day mortality. The AUC of the percentage of PD-L1+ NK cells, SOFA scores, and their combination model were 0.655 (0.559–0.742), 0.727 (0.635–0.807) and 0.808 (0.723–0.876), respectively. The combination model was the indicator with the best AUC to predict mortality in 28 days (all p