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睡眠期间的连续血糖监测 (CGM) 数据建模。

Modeling continuous glucose monitoring (CGM) data during sleep.

机构信息

Department of Statistics, Texas A&M University, MS 3143, College Station, TX, 77843, USA.

School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

出版信息

Biostatistics. 2022 Jan 13;23(1):223-239. doi: 10.1093/biostatistics/kxaa023.

Abstract

We introduce a multilevel functional Beta model to quantify the blood glucose levels measured by continuous glucose monitors for multiple days in study participants with type 2 diabetes mellitus. The model estimates the subject-specific marginal quantiles, quantifies the within- and between-subject variability, and produces interpretable parameters of blood glucose dynamics as a function of time from the actigraphy-estimated sleep onset. Results are validated via simulations and by studying the association between the estimated model parameters and hemoglobin A1c, the gold standard for assessing glucose control in diabetes.

摘要

我们引入了一个多层次功能贝塔模型,以量化 2 型糖尿病患者连续血糖监测多日的血糖水平。该模型估计了个体特异性边缘分位数,量化了个体内和个体间的变异性,并根据活动计估计的睡眠起始时间,生成了可解释的血糖动力学参数。结果通过模拟和研究估计模型参数与糖化血红蛋白(评估糖尿病患者血糖控制的金标准)之间的关联进行了验证。

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本文引用的文献

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