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一种通过生物电阻抗分析(BIA)估算正常体重和超重儿童全身水含量的新预测模型。

A new prediction model for total body water estimation by BIA in children with normal and excessive weight.

作者信息

Lu Hong, Shinki Kazuhiko, Mattoo Tej K

机构信息

Department of Pediatrics (Nephrology), Wayne State University, Detroit, MI, USA.

Department of Mathematics, Wayne State University, Detroit, MI, USA.

出版信息

Clin Nutr ESPEN. 2023 Feb;53:53-59. doi: 10.1016/j.clnesp.2022.11.014. Epub 2022 Nov 26.

Abstract

BACKGROUND

Various methods, including bioelectrical impedance analysis (BIA), are used for total body water (TBW) estimation. The objective of our study by BIA was to develop a new predication model based on corrected TBW for normal adult BMI, a concept similar to the standardization of glomerular filtration rate by relating it to the average adult body surface area.

METHOD

We measured TBW by BIA in 335 children 3-21 years old with normal or excessive body weight. Based on our data, we derived a new prediction model for TBW (L) for females {[(72.784 + 0.4093 × weight)∗Corrected TBW]/100} and males {[(57.944 + 0.6551 × weight)∗Corrected TBW]/100}. For validation, we compared our prediction model with three other models on TBW by BIA and dilution methods.

RESULTS

Our model's error size to predict TBW showed lower cross-validated root mean square error (CV-RMSE) as compared to three other models versus our dataset by BIA and two other datasets by dilution methods. Our model also showed a smaller error (2.059) in CV-RMSE as compared to other models by dilution methods (2.126, 2.873, and 4.384) for normal and excessive weight combined. This implies that our model is more robust when excessive weight individuals are included in the data..

CONCLUSION

Our prediction model for TBW estimation by BIA performs better as compared to some other models based on BIA and dilution method datasets. Furthermore, our prediction model is the only one that is devised to be applicable to children and young adults with both normal as well as excessive weight.

摘要

背景

包括生物电阻抗分析(BIA)在内的各种方法被用于估计总体水(TBW)。我们通过BIA进行研究的目的是基于校正后的TBW为正常成人BMI建立一个新的预测模型,这一概念类似于通过将肾小球滤过率与成人平均体表面积相关联来进行标准化。

方法

我们通过BIA测量了335名3至21岁体重正常或超重儿童的TBW。基于我们的数据,我们得出了女性TBW(升)的新预测模型{[(72.784 + 0.4093×体重)×校正后的TBW]/100}和男性的{[(57.944 + 0.6551×体重)×校正后的TBW]/100}。为了进行验证,我们将我们的预测模型与通过BIA和稀释法得出的其他三个TBW模型进行了比较。

结果

与其他三个模型相比,我们的模型预测TBW的误差大小在通过BIA得到的我们的数据集以及通过稀释法得到的其他两个数据集上显示出更低的交叉验证均方根误差(CV-RMSE)。与通过稀释法得到的其他模型(2.126、2.873和4.384)相比,我们的模型在正常体重和超重合并情况下的CV-RMSE中也显示出更小的误差(2.059)。这意味着当数据中包含超重个体时,我们的模型更稳健。

结论

与基于BIA和稀释法数据集的其他一些模型相比,我们通过BIA估计TBW的预测模型表现更好。此外,我们的预测模型是唯一设计用于适用于体重正常和超重的儿童及年轻人的模型。

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