A Case Study of Glucose Levels During Sleep Using Multilevel Fast Function on Scalar Regression Inference
A Case Study of Glucose Levels During Sleep Using Multilevel Fast Function on Scalar Regression Inference
复制标题
使用标量回归推理上的多级快速函数进行睡眠期间血糖水平的案例研究
DOI：
10.1111/biom.13878
复制
发表时间：
2023
期刊：
影响因子：
1.9
通讯作者：
Gaynanova, Irina
中科院分区：
文献类型：
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作者：
Sergazinov, Renat;Leroux, Andrew;Cui, Erjia;Crainiceanu, Ciprian;Aurora, R. Nisha;Punjabi, Naresh M.;Gaynanova, Irina
动态血糖监测仪（CGM）越来越多地用于测量血糖水平，并提供有关糖尿病治疗和管理的信息。我们的激励研究包含174名II型糖尿病研究参与者睡眠期间的CGM数据，平均10个晚上，以5分钟的频率测量。我们的目标是量化糖尿病药物和睡眠呼吸暂停严重程度对血糖水平的影响。从统计学上讲，这是一个关于标量协变量与多次访视（睡眠期）时观察到的功能反应之间相关性的推断问题。然而，数据的许多特征使得分析变得困难，包括（1）非平稳的周期内模式;（2）大量的周期间异质性，非高斯性和离群值;以及（3）由于研究参与者，睡眠期和时间点的数量而导致的大维度。对于我们的分析，我们评估和比较两种方法：快速单变量推理（FUI）和功能添加剂混合模型（FAMM）。我们扩展了FUI，并引入了一种新的方法来检验协变量的无效应和时间不变性的假设。我们还强调了进一步发展FAMM方法的领域。我们的研究表明，（1）双胍类药物和睡眠呼吸暂停严重程度显著影响睡眠期间的血糖轨迹，（2）估计的影响是时不变的。
Continuous glucose monitors (CGMs) are increasingly used to measure blood glucose levels and provide information about the treatment and management of diabetes. Our motivating study contains CGM data during sleep for 174 study participants with type II diabetes mellitus measured at a 5-min frequency for an average of 10 nights. We aim to quantify the effects of diabetes medications and sleep apnea severity on glucose levels. Statistically, this is an inference question about the association between scalar covariates and functional responses observed at multiple visits (sleep periods). However, many characteristics of the data make analyses difficult, including (1) nonstationary within-period patterns; (2) substantial between-period heterogeneity, non-Gaussianity, and outliers; and (3) large dimensionality due to the number of study participants, sleep periods, and time points. For our analyses, we evaluate and compare two methods: fast univariate inference (FUI) and functional additive mixed models (FAMMs). We extend FUI and introduce a new approach for testing the hypotheses of no effect and time invariance of the covariates. We also highlight areas for further methodological development for FAMM. Our study reveals that (1) biguanide medication and sleep apnea severity significantly affect glucose trajectories during sleep and (2) the estimated effects are time invariant.