预测儿童中度至重度喘发作的相关风险因素:基于后勤回归和决策树的分析
Qianqian Li1, Yinghong Fan1, Ronghua Luo1
1Pediatric Respiratory Medicine Department, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610000, People's Republic of China.
International journal of general medicine
|July 21, 2025
概括
过敏史,病史,Mycoplasma pneumoniae (MP) 感染,以及中性粒细胞百分比升高 (NEU%) 是儿童中度至严重喘发作的主要危险因素. 这些因素通过后勤回归和决策树分析确定,有助于预测严重喘恶化.
科学领域:
- 儿科肺病学 儿科肺病学
- 流行病学 流行病学
- 医疗信息学 医疗信息学
背景情况:
- 喘是儿童常见的慢性呼吸道疾病.
- 识别严重喘发作的危险因素对于有效的管理和预防至关重要.
- 之前的研究已经探索了各种触发因素,但使用先进的统计模型进行全面分析正在进行中.
研究的目的:
- 分析与儿科患者中度至重度喘发作相关的风险因素.
- 为了比较物流回归和决策树模型在识别这些风险因素方面的预测能力.
主要方法:
- 对患有喘发作的儿童的临床数据的回顾性分析 (2020年1月 - 2023年8月).
- 患者被分为轻度和中度到重度的发作组.
- 用单变量和多变量逻辑回归以及决策树分析来确定风险因素.
主要成果:
- 通过多变量逻辑回归确定的显著风险因素包括年龄 (≥6年),病史,过敏史,家族史,中性粒细胞百分比升高 (NEU%),Mycoplasma pneumoniae (MP) 感染和Rhinovirus (RV) 感染.
- 决策树模型强调了MP感染,C反应蛋白 (CRP),过敏史,NEU%和病史作为关键预测因素.
- 多变量逻辑回归 (AUC=0.733) 和决策树 (AUC=0.694) 均表现出良好的预测准确性.
结论:
- 过敏史,病史,MP感染和增加的NEU%是预测儿童中度至重度喘发作的重要危险因素.
- 多变量逻辑回归和决策树模型都是分析和预测儿童群体严重喘发作风险的有效工具.
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