A blood gas parameter–based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the MIMIC-IV and eICU-CRD - Xiao Chen; Huichang Zhuo; Yunpiao Wang; Daxuan Wang; Xiaoqin Li; Jiandong Lin; Xiuyu Liao; Xian Lin; Xiao Lin (PLoS ONE, 2026)
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 PO 2 , 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.