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营养炎症指数与败血症患者死亡率之间的关联:传统方法和基于机器学习的死亡率预测方法的见解

Yuanshuo Ge^1,2, Ding Hu¹, Zhe Wang³

¹Department of General Surgery, General Hospital of Northern Theater Command (Formerly Called General Hospital of Shenyang Military Area), Shenyang, China.

BMC infectious diseases

|August 14, 2025

概括

专蛋白与中性细胞淋巴细胞比率 (ANLR) 是败血症死亡率的强有力的预测指标,在较高的比率下显示出更好的生存率. 这种新型生物标志物在评估败血症风险方面表现优于传统标志物.

科学领域:

关键护理医学关键护理医学
生物标志物发现发现
计算生物学计算生物学

背景情况:

败血症涉及免疫失调和代谢问题.
专蛋白与中性粒细胞淋巴细胞比率 (ANLR) 结合了营养和炎症标志物.
在败血症中ANLR的预后价值需要进一步调查.

研究的目的:

评估ANLR和败血症死亡率之间的关联.
将ANLR的预测性能与已确定的败血症生物标志物进行比较.
用传统和机器学习方法来评估ANLR.

主要方法:

来自MIMIC-IV数据库的6288名败血症患者的回顾性分析.
根据ANLR水平分为四分之一的分层.
使用了生存分析 (卡普兰-梅尔,考克斯回归,RCS) 和机器学习 (SHAP).

主要成果:

更高的ANLR独立地与30天和90天死亡率的降低有关.
升高的ANLR显著降低了死亡风险 (30天HR0.68,90天HR0.85).
机器学习确定ANLR是第二个最重要的预测因子,表现优于SOFA,NLR和白蛋白 (AUC0.66).

结论:

ANLR是败血症死亡率的可靠和独立预测指标.
与传统生物标志物相比,ANLR显示出更高的预后能力.
将ANLR整合到临床实践中可能会增强败血症风险分层和个性化治疗.

关键词:

炎症炎症是一种炎症.预测死亡率的预测.营养营养营养营养营养追溯研究是一项回顾性研究.败血症这是一种败血症.

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