在早产新生儿中早期发作的败血症的四因素名谱:开发和内部验证一个管理工具
Li Guo1, Zhiyang Zhang2, Chunhui Zhao1
1Department of Neonatal, The Fourth Hospital of Shijiazhuang, Shijiazhuang, China.
PloS one
|October 9, 2025
概括
一个新的名图准确地预测了使用四个关键变量的早产婴儿早发性败血症 (EOS) 风险. 这种工具有助于做出明智的抗生素决定,可能减少对脆弱新生儿的不必要治疗.
科学领域:
- 新生儿医学 新生儿医学
- 传染病流行病学 传染病流行病学
- 临床决策支持系统 临床决策支持系统
背景情况:
- 早期发作的败血症 (EOS) 是早产婴儿死亡和发育问题的主要原因.
- 现有的风险评估工具对于极度早产婴儿 (<35-37周妊娠期) 没有优化.
研究的目的:
- 开发和验证一个简单的,可解释的 EOS 风险分层在早产新生儿的nomogram.
- 评估诺米克图在指导抗生素管理中的实用性.
主要方法:
- 对1,059名早产婴儿进行了回顾性队列研究.
- 使用训练数据 (n=742) 开发一个多变量逻辑回归模型.
- 内部验证评估了歧视 (AUC),校准 (Brier分数,Hosmer-Lemeshow) 和临床实用性 (DCA).
主要成果:
- 开发了一个四个变量模型 (妊娠年龄,出生体重,带异常,机械通风).
- 纳米图表显示出强烈的歧视 (AUC 0.818) 和在验证队列中的良好校准.
- 该模型确定了88%的EOS病例,同时建议在≥0.70值时仅为~10%的婴儿服用抗生素.
结论:
- 一个使用电子医疗记录 (EMR) 数据的四因素名录精确地分层了早产婴儿的EOS风险.
- 这种工具显示了指导基于风险的抗生素使用的潜力,可能限制过度治疗.
- 建议在多中心前性研究中进行外部验证,以确认可概括性.
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