Department of Microbiome Science, Max Planck Institute for Biology, Tübingen, Germany.
Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA, 94305-5170, USA.
BMC Med Res Methodol. 2024 Feb 1;24(1):27. doi: 10.1186/s12874-024-02145-1.
Standard pediatric growth curves cannot be used to impute missing height or weight measurements in individual children. The Michaelis-Menten equation, used for characterizing substrate-enzyme saturation curves, has been shown to model growth in many organisms including nonhuman vertebrates. We investigated whether this equation could be used to interpolate missing growth data in children in the first three years of life and compared this interpolation to several common interpolation methods and pediatric growth models.
We developed a modified Michaelis-Menten equation and compared expected to actual growth, first in a local birth cohort (N = 97) then in a large, outpatient, pediatric sample (N = 14,695).
The modified Michaelis-Menten equation showed excellent fit for both infant weight (median RMSE: boys: 0.22 kg [IQR:0.19; 90% < 0.43]; girls: 0.20 kg [IQR:0.17; 90% < 0.39]) and height (median RMSE: boys: 0.93 cm [IQR:0.53; 90% < 1.0]; girls: 0.91 cm [IQR:0.50;90% < 1.0]). Growth data were modeled accurately with as few as four values from routine well-baby visits in year 1 and seven values in years 1-3; birth weight or length was essential for best fit. Interpolation with this equation had comparable (for weight) or lower (for height) mean RMSE compared to the best performing alternative models.
A modified Michaelis-Menten equation accurately describes growth in healthy babies aged 0-36 months, allowing interpolation of missing weight and height values in individual longitudinal measurement series. The growth pattern in healthy babies in resource-rich environments mirrors an enzymatic saturation curve.
标准儿科生长曲线不能用于推断个体儿童缺失的身高或体重测量值。米氏方程(Michaelis-Menten equation),用于描述基质-酶饱和曲线,已被证明可用于建模包括非人类脊椎动物在内的许多生物体的生长。我们研究了该方程是否可用于推断生命前三年儿童缺失的生长数据,并将这种推断与几种常见的插值方法和儿科生长模型进行了比较。
我们开发了一种改良的米氏方程,并在当地出生队列(N=97)和大型门诊儿科样本(N=14695)中比较了预期和实际的生长情况。
改良的米氏方程对婴儿体重(男孩中位数 RMSE:0.22kg [IQR:0.19; 90%<0.43];女孩中位数 RMSE:0.20kg [IQR:0.17; 90%<0.39])和身高(男孩中位数 RMSE:0.93cm [IQR:0.53; 90%<1.0];女孩中位数 RMSE:0.91cm [IQR:0.50; 90%<1.0])的拟合效果均非常好。在第一年中,只需从常规的婴儿健康检查中获得四个值,在 1-3 年中获得七个值,即可准确地建模生长数据;最佳拟合需要出生体重或身长。与表现最佳的替代模型相比,这种方程的插值具有可比(体重)或更低(身高)的平均 RMSE。
改良的米氏方程准确描述了 0-36 个月健康婴儿的生长情况,允许对个体纵向测量系列中缺失的体重和身高值进行插值。资源丰富环境中健康婴儿的生长模式与酶饱和曲线相似。