在儿童中早期识别严重的Mycoplasma pneumoniae肺炎:回顾性模型开发研究
Zijuan Dong1, Xiaojuan Zhang1, Lina Gu1
1Department of Infectious Disease, Affiliated Children's Hospital of Jiangnan University, Wuxi Children's Hospital, 299-1 Qingyang Road, Wuxi 214023, China.
Respiratory medicine
|March 8, 2026
概括
最近的一次疫情显示,近三分之一的儿科Mycoplasma pneumoniae肺炎 (MPP) 病例变得严重. 一种使用入院数据的新型名谱有助于预测儿童的严重MPP (SMPP),有助于早期治疗.
科学领域:
- 儿童传染病 儿童传染病
- 呼吸系统医学 呼吸系统医学
- 临床流行病学临床流行病学
背景情况:
- 自2023年中期以来,中国的儿科Mycoplasma pneumoniae肺炎 (MPP) 病例显著增加.
- 目前缺乏有效的工具来早期识别严重的儿科MPP (SMPP).
研究的目的:
- 确定严重儿科MPP (SMPP) 的独立预测因素.
- 开发和验证医院住院儿童中SMPP风险的预测名录.
主要方法:
- 对908名患有MPP住院的儿童 (≤14岁) 的回顾性分析.
- 严重MPP (SMPP) 和非SMPP组之间的人口统计,临床,实验室和药物数据的比较.
- 使用后勤回归和通过引导重新抽样进行内部验证,开发一个五参数的nomogram.
主要成果:
- 严重儿科MPP (SMPP) 占所有住院病例的30.5%.
- SMPP的独立预测因素包括更高的中性粒细胞百分比,年龄较大,入院前长时间暴露于阿齐思罗米辛,高峰温度和乳酸脱酶 (LDH) 的升高.
- 开发的诺米图表显示出良好的预测准确性,AUC为0.75.
结论:
- 在2023-2024年爆发期间,近三分之一的儿科MPP入院病例进展为严重疾病.
- 使用常规录取数据的五参数名录图为SMPP提供了可靠的风险分层.
- 诺米图可以支持及时的临床决策,尽管需要外部验证和宏类抗药性评估.
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