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基于血标记的机器学习模型用于肺结核病患者的生存预测:构建和外部验证

Qiuxiang Huang¹, Mei Feng², Ziwei Chen¹

¹Department of Respiratory Medicine, Guangzhou Twelfth People's Hospital, Guangzhou, 510620, People's Republic of China.

Journal of inflammation research

|March 4, 2026

概括

这项研究发现,C-反应蛋白 (CRP) 和白蛋白-6 (IL-6) 水平,以及临床因素,可以预测短期肺炎症的预后. 这有助于识别高风险患者进行早期干预.

科学领域:

肺部医学肺部医学
职业健康职业健康职业健康
生物标志物生物标志物

背景情况:

肺结核病对健康构成重大风险,特别是在职业环境中.
有效的短期预后预测对于及时的患者管理至关重要.
炎症标志物越来越被认为是呼吸道疾病的潜在预后指标.

研究的目的:

调查血液炎症标志物 (CRP,IL-6) 与短期肺炎症预后之间的关联.
开发和验证用于肺结核病预后的多因素预测模型.
确定肺炎患者不良结果的关键临床和炎症预测因素.

主要方法:

追溯收集了813名肺结核病患者的临床数据.
使用LASSO回归用于变量选和物流回归用于模型构建.
使用考克斯回归,卡普兰-梅尔曲线,ROC分析和决策曲线分析验证了模型.

主要成果:

年龄,暴露于尘埃的持续时间,呼吸不良,SPO2,中性粒细胞数量,CRP和IL-6被确定为预测因素.
CRP和IL-6是短期预后不佳的独立风险因素 (P<0.001).
预测模型显示了高的区别 (AUC 0.905-0.920) 和临床效用.

结论:

结合CRP,IL-6和临床因素的预测模型可以有效地识别高风险肺结核病患者.
该模型为早期干预策略提供了可靠的基础.
高CRP和IL-6水平与肺结核病的短期存活率降低有显著关联.

关键词:

在C-反应性蛋白质中.这是一种炎症炎症炎症炎症.互乐金-6是其中的一种.肺炎症是肺炎的疾病之一.预测模型预测模型

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