基于血气参数的评估模型用于预测败血症预后不良：MIMIC-IV和eICU CRD的回顾性分析
A blood gas parameter-based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the MIMIC-IV and eICU-CRD.
摘要(中文译文)
血气参数与脓毒症预后相关。本研究旨在建立基于血气参数的评估模型以预测患者结局。数据从重症监护医学信息库IV（MIMIC-IV）和电子重症监护病房协作研究数据库（eICU-CRD）中回顾性提取。利用MIMIC-IV队列建立脓毒症评估模型，随后在同一数据库的脓毒性休克患者中进行内部验证，并在eICU-CRD的脓毒症患者中进行外部验证。生物信息学和机器学习阐明了该模型与脓毒症及脓毒性休克患者28天死亡率主要结局之间的关系。脓毒症评估血气3（SABG-3）是一种纳入PO2、碱剩余（BE）和乳酸的评估模型，已被开发并验证为MIMIC-IV脓毒症患者28天死亡率的独立预测因子（比值比：1.559；95%置信区间：1.464-1.659；P < 0.001）。其预后性能在MIMIC-IV脓毒症患者中进行了内部验证，并在eICU-CRD脓毒症患者中进行了外部验证。经SABG-3识别的高风险患者比低风险患者表现出更高的疾病严重程度。五种方法的敏感性分析证实了SABG-3对重症监护病房脓毒症和脓毒性休克患者的预后价值。基于SABG-3的列线图被证明优于现有量表。我们开发并验证了一种新的评估模型和列线图，用于快速评估脓毒症预后并识别可能从强化治疗中获益的患者。
Abstract
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. 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. 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. 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.
如何引用
AMA
Xiao Chen, Huichang Zhuo, Yunpiao Wang, Daxuan Wang, Xiaoqin Li, Jiandong Lin, et al. A blood gas parameter-based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the MIMIC-IV and eICU-CRD.. PloS one. 2026; doi:10.1371/journal.pone.0346532.
APA
Xiao Chen, Huichang Zhuo, Yunpiao Wang, Daxuan Wang, Xiaoqin Li, Jiandong Lin, et al (2026). A blood gas parameter-based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the MIMIC-IV and eICU-CRD.. PloS one. https://doi.org/10.1371/journal.pone.0346532
GB/T 7714
Xiao Chen, Huichang Zhuo, Yunpiao Wang, Daxuan Wang, Xiaoqin Li, Jiandong Lin, et al. A blood gas parameter-based assessment model for predicting poor prognosis in sepsis: A retrospective analysis of the MIMIC-IV and eICU-CRD.[J]. PloS one, 2026 doi:10.1371/journal.pone.0346532.
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