新的法国高度速度增长图:基于常规测量的创新大数据方法
Pauline Scherdel1, Marion Taine1, Manon Bergerat2
1Inserm, Center for Research in Epidemiology and StatisticS (CRESS), Obstetrical, Perinatal and Pediatric Epidemiology Research Team (Epopé), Université Paris Cité, Paris, France.
Acta paediatrica (Oslo, Norway : 1992)
|September 24, 2024
概括
更新的法国高度速度增长图表是使用大数据方法创建的. 这些基于常规测量的图表有助于优化儿童成长监测性能.
科学领域:
- 儿科内分泌学 儿科内分泌学
- 辅助学 辅助学是指辅助学
- 生物统计学 生物统计学
背景情况:
- 高度速度对于监测儿童成长至关重要.
- 法国现有的身高速度增长图已经过时了.
- 需要根据当前数据更新增长图表.
研究的目的:
- 通过大数据方法获得新的法国高度速度增长图表.
- 为增长监测提供最新的auxological工具.
- 将新图表与现有的法国和世卫组织标准进行比较.
主要方法:
- 利用了法国42名初级保健医生的电子病历.
- 包括1个月至18岁儿童的成长数据 (1990-2018).
- 应用了Lambda-Mu-Sigma方法来生成年和半年高度速度图表,直到15岁.
主要成果:
- 创建了新的高度速度图表,使用超过19万个年度和20万个半年值,来自8万-87000名儿童.
- 图表显示内部适应性很好.
- 中位数曲线与以前的法国和世卫组织图表保持一致,但标准偏差曲线显示出显著差异.
结论:
- 新的法国15岁的身高增长速度图表已经成功制作出来.
- 大数据方法利用了常规的临床测量.
- 这些更新的图表可以提高临床实践中生长监测的性能.
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