开发和验证热发作预测模型的发展和验证
Anna Cheng1, Qin Xiong1, Jing Wang1
1Department of Emergency, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Scientific reports
|November 1, 2023
概括
这项研究开发了一种新的预测模型,用于使用全血细胞计数 (CBCs) 的儿童发烧性 (FS). 该模型显示出强大的预测能力,为识别FS风险儿童提供了潜在的临床价值.
科学领域:
- 儿科 儿科 儿科
- 临床预测建模临床预测建模
- 血液学 血液学 血液学
背景情况:
- 发烧性发作 (FS) 在儿童中很常见,但目前的预测模型缺乏准确性.
- 准确预测FS对于及时干预和管理至关重要.
研究的目的:
- 开发和验证儿童发烧 (FS) 的高性能预测模型.
- 通过人口统计数据和完整血液计数 (CBCs) 来识别FS的关键预测因素.
主要方法:
- 从2020年7月到2021年3月,对发烧儿童进行了回顾性分析.
- 使用最少绝对收缩和选择运算符 (LASSO) 进行预测器选择.
- 开发了一个使用多变量逻辑回归的预测模型,并构建了一个名ogram.
主要成果:
- 预测模型表现出强的表现,训练集的曲线下的面积 (AUC) 为0.884.
- 内部和外部验证显示了强大的预测能力,AUC分别为0.883和0.858.
- 诺米图还表现出良好的预测准确度,C统计值为0.884.
结论:
- 基于CBCs的FS的新型预测模型表现出显著的临床效用.
- 与现有方法相比,开发的模型提供了更好的预测性能.
- 这种工具可以帮助临床医生评估儿科患者发烧的风险.
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