Related Experiment Video
Updated: Jul 15, 2026
A Reproducible Intensive Care Unit-Oriented Endotoxin Model in Rats
Published on: February 20, 2021
A blood gas parameter-based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the
Xiao Chen1,2, Huichang Zhuo1,2, Yunpiao Wang3
1Department of Intensive Care Unit, The First Affliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Background:
Blood gas parameters are associated with sepsis prognosis. This study aimed to develop an assessment model based on blood gas parameters for predicting patient outcomes.
Methods:
Data were retrospectively extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and electronic Intensive Care Unit Collaborative Research Database (eICU-CRD). A sepsis assessment model was developed using the MIMIC-IV cohort, followed by internal validation in patients with septic shock from the same database and external validation in patients with sepsis from the eICU-CRD. Bioinformatics and machine learning clarified the relationship between the model and the primary outcome of 28-day mortality in patients with sepsis and septic shock.
Results:
The sepsis assessment blood gas 3 (SABG-3), an assessment model incorporating PO2, base excess (BE), and lactate, was developed and validated as an independent predictor of 28-day mortality in patients with MIMIC-IV sepsis (odds ratio: 1.559; 95% confidence interval: 1.464-1.659; P < 0.001). Its prognostic performance was internally validated in patients with MIMIC-IV sepsis and externally validated in patients with eICU-CRD sepsis. High-risk patients identified by SABG-3 exhibited greater illness severity than low-risk ones. Sensitivity analyses across five methods confirmed the prognostic value of SABG-3 for intensive care unit patients with sepsis and septic shock. A SABG-3-derived nomogram proved superior to existing scales.
Conclusion:
We developed and validated a novel assessment model and nomogram to evaluate sepsis prognosis rapidly and to identify patients who may benefit from intensified treatment.
