相关实验视频

Updated: Jul 6, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Published on: April 18, 2025

在败血症中SIRI的预后价值:回顾性研究和基于机器学习的模型开发

Yilin Zhu¹, Zhiyang Wang², Shifeng Li³

¹Department of Critical Care Medicine, Zhangjiagang Hospital Affiliated to Soochow University/The First People's Hospital of Zhangjiagang City, Zhangjiagang, 215600, People's Republic of China.

Journal of inflammation research

|October 7, 2025

概括

系统性炎症反应指数 (SIRI) 有效预测败血症患者的28天死亡率. 结合SIRI的新预后模型显示出对败血症结局的高准确性.

科学领域:

关键护理医学关键护理医学
败血症病理生理学病理生理学
预测生物标志物预测生物标志物

背景情况:

败血症是一个重大的全球健康挑战,死亡率高.
准确的预后工具对于在败血症管理中及时做出临床决策至关重要.
系统性炎症反应指数 (SIRI) 已成为评估败血症预后的有希望的生物标志物.

研究的目的:

调查SIRI对败血症患者28天结局的预测价值.
开发和验证一种预后模型,用于预测败血症28天死亡率.
将SIRI的预测性能与APACHE II和SOFA等既有评分系统进行比较.

主要方法:

来自两个医疗中心的成人败血症患者的回顾性分析.
利用受限立方线和ROC曲线分析来评估SIRI的预测能力.
采用考克斯回归,卡普兰-梅尔曲线,博鲁塔算法,LASSO和后勤回归来构建和验证预后模型.
外部验证使用来自另一个医院的数据进行.

主要成果:

与APACHE II和SOFA分数相比,SIRI显示出非线性上升趋势,死亡风险和更高的预测能力.
较高的SIRI水平与较差的28天预后显著相关 (p<0.001).
开发的预后模型,包括SIRI和其他因素 (BUN,年龄,P,Lac,MV),在训练和验证集中显示出高预测性能 (AUC:0.851-0.908).

结论:

SIRI是一种有价值和独立的预测器,可预测毒症患者28天的预后.
开发的结合SIRI的预后模型为预测败血症死亡率提供了高准确性和临床实用性.
这个模型可以帮助临床医生在风险分层和败血症患者的管理.

关键词:

这个名字是名ogramogram.预测模型预测模型预后预后预后这是一种血症.系统性炎症反应指数

更多相关视频

A Data-Driven Approach to Quantifying Immune States in Sepsis

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

相关概念视频

Cancer Survival Analysis

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...