在接受免疫抑制药物治疗的患者中,开发和验证用于预测肺部感染的诺米克图
Chuxuan Luo1, Yue Zhang2, Jiajie Zhang3
1Department of Nephrology, Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Taizhou, Zhejiang, China.
Frontiers in pharmacology
|January 31, 2024
概括
这项研究为接受免疫抑制药物的患者开发了一种肺部感染预测 (PIP) 模型. 该模型准确预测肺部感染的风险,有助于个性化临床决策.
科学领域:
- 医学研究 医学研究
- 临床信息学是一种临床信息学.
- 免疫学 免疫学 免疫学
背景情况:
- 肺部感染 (PI) 是免疫抑制疗法的严重并发症.
- 预测PI风险对于改善那些接受免疫抑制药物 (ISD) 患者的治疗结果至关重要.
研究的目的:
- 为接受免疫抑制治疗的患者构建和验证肺感染预测 (PIP) 模型.
- 在接受ISD的患者中确定PI的关键预测因子.
主要方法:
- 使用了7,977名接受ISD的患者的大队列,随机分为开发 (n=5,583) 和验证 (n=2,394) 数据集.
- 使用最少绝对收缩和选择运算符 (LASSO) 和多变量COX回归分析来构建预测名图.
- 模型的性能使用一致性指数 (C指数) 和校准曲线进行评估.
主要成果:
- 肺部感染发生在6.9%的患者中,治疗开始后的中位数为123天.
- 确定了13个独立的预测因素,包括人口因素,并发病症和特定药物使用 (例如甲基prednisolone,口服葡萄皮质类药物).
- 该PIP模型表现出强大的预测性能,开发C指数为0.87,验证C指数范围为0.829至0.837,用于90至360天的预测.
结论:
- 开发的PIP模型有效预测接受免疫抑制治疗的患者肺部感染的风险.
- 该模型显示出卓越的临床实用性和校准,支持个性化风险评估和临床决策.
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