# The endothelial activation and stress index as a predictor of 28-day mortality in pulmonary sepsis: a retrospective two-cohort analysis

## TL;DR

The EASIX biomarker effectively predicts 28-day mortality in pulmonary sepsis patients and improves risk stratification when used in a prognostic model.

## Contribution

EASIX is shown to be an independent and potent predictor of mortality in pulmonary sepsis, outperforming traditional severity scores.

## Key findings

- Each unit increase in EASIX was associated with a 7% higher risk of 28-day ICU death.
- Patients in the highest EASIX quartile had nearly twice the mortality risk compared to the lowest quartile.
- A prognostic model integrating EASIX showed superior discriminative ability (AUC 0.67–0.73) compared to traditional scores.

## Abstract

The Endothelial Activation and Stress Index (EASIX) is an emerging biomarker that serves as a straightforward and objective measure of systemic endothelial dysfunction and critical illness severity. This study aims to evaluate the prognostic value of EASIX for 28-day mortality in patients with pulmonary sepsis.

This retrospective study utilised a two-cohort design. The internal cohort was derived from MIMIC-IV; an external cohort was derived from a tertiary hospital (2022–2025). The association between the EASIX and 28-day mortality was evaluated using multivariable Cox regression, restricted cubic spline (RCS) analysis, and Kaplan–Meier survival curves. An ensemble machine-learning approach (Boruta, LASSO-COX, XGBoost, and SVM) was employed for feature selection. Significant predictors were incorporated into a multivariate Cox model to construct a prognostic nomogram. The model’s discriminative performance was assessed using receiver operating characteristic (ROC) curves and the area under the curve (AUC), and compared against conventional severity scores.

A total of 5,416 patients were analyzed. In multivariable adjusted models, the EASIX emerged as an independent predictor of short term mortality. Each unit increase in EASIX was associated with a 7% higher risk of 28-day ICU death (HR 1.07, 95% CI 1.05–1.11, p < 0.001). A clear dose–response relationship was observed across EASIX quartiles, with mortality rising from 13.29% (Q1) to 27.92% (Q4); patients in Q4 had nearly twice the mortality risk of those in Q1 (HR 1.99, 95% CI 1.60–2.46). RCS analysis revealed a nonlinear relationship. Machine-learning feature selection consistently identified EASIX as a core variable. The final prognostic model, integrating EASIX with five other clinical features, demonstrated stable and superior discriminative ability (AUC 0.67–0.73) compared to traditional severity scores in both internal and external validation.

EASIX is a potent and independent predictor of short-term mortality in pulmonary sepsis. Its integration into a pragmatic prognostic model enhances early risk stratification, highlighting its potential as a readily available clinical tool.