Evaluation of presepsin dynamics in septic patients with and without liver cirrhosis

Abstract

Background

Sepsis is associated with high short-term mortality, particularly in patients with decompensated liver cirrhosis. Conventional inflammatory biomarkers have limited prognostic accuracy in this population. Presepsin has emerged as a promising biomarker; however, its dynamic behavior in early sepsis remains insufficiently characterized.

Objectives

To evaluate the prognostic value of presepsin dynamics in sepsis, with and without underlying liver cirrhosis, and to compare it with established inflammatory markers.

Methods

We conducted an observational cohort study including two patient groups: patients with sepsis and decompensated liver cirrhosis (Group A) and patients with sepsis without cirrhosis (Group B). Presepsin levels were measured at admission and after 48 hours, and delta presepsin was calculated. Prognostic performance was assessed using receiver operating characteristic (ROC) analysis and Cox proportional hazards regression. The primary endpoint was 28-day mortality.

Results

In Group A, presepsin measured at 48 hours demonstrated superior prognostic performance compared with baseline levels (AUROC 0.91 vs. 0.78). Changes in presepsin further enhanced risk stratification, with a negative delta associated with improved survival, whereas an increase of ≥500 pg/mL was independently associated with higher mortality. (HR 5, 95% CI:1.64-15.26). In Group B presepsin showed moderate prognostic performance at baseline and 48 hours, whereas delta presepsin demonstrated limited overall accuracy, except in patients with positive delta values. Established biomarkers, including C-reactive protein and procalcitonin, showed inferior prognostic performance compared with presepsin in both cohorts.

Conclusions

Dynamic assessment of presepsin provides clinically relevant prognostic information in sepsis, particularly in patients with decompensated liver cirrhosis. Early changes in presepsin levels may enhance risk stratification beyond conventional inflammatory biomarkers.