Using Continuous Glucose Monitoring Data and Detrended Fluctuation Analysis to Determine Patient Condition: A Review.
Using Continuous Glucose Monitoring Data and Detrended Fluctuation Analysis to Determine Patient Condition: A Review.
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DOI：
10.1177/1932296815592410
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发表时间：
2015-06-30
影响因子：
5
通讯作者：
Chase, J Geoffrey
中科院分区：
文献类型：
--
作者：
Thomas, Felicity;Signal, Matthew;Chase, J Geoffrey
接受重症监护的患者经常会出现血糖异常和高水平的胰岛素抵抗，各种强化胰岛素治疗方案和方法都试图安全地使血糖 (BG) 水平正常化。与传统的血糖测量相比，连续血糖监测 (CGM) 设备可以更频繁地（每 2-5 分钟）捕获血糖动态，并已开始用于重症监护患者和新生儿，以帮助监测血糖异常。为了更好地了解生物医学信号和患者状态，一些研究人员转向了先进的时间序列分析方法。特别是，去趋势波动分析 (DFA) 已成为许多近期血糖动态研究的主题。 DFA 研究信号的“复杂性”，即一个时间点相对于其相邻点如何变化，并且 DFA 已应用于人类心跳间隔等信号，以区分健康和病理状况。随着高质量 CGM 设备的出现，使用 DFA 等信号处理工具分析葡萄糖代谢系统成为可能。然而，已发表的将 DFA 应用于 CGM 信号的工作中存在一些不一致之处。因此，本文对 DFA 进行了回顾和“操作方法”教程，特别是其在 CGM 信号中的应用，以确保正确使用用于确定复杂性的方法，从而确保复杂性与患者结果之间的任何关系都是稳健的。
Patients admitted to critical care often experience dysglycemia and high levels of insulin resistance, various intensive insulin therapy protocols and methods have attempted to safely normalize blood glucose (BG) levels. Continuous glucose monitoring (CGM) devices allow glycemic dynamics to be captured much more frequently (every 2-5 minutes) than traditional measures of blood glucose and have begun to be used in critical care patients and neonates to help monitor dysglycemia. In an attempt to obtain a better insight relating biomedical signals and patient status, some researchers have turned toward advanced time series analysis methods. In particular, Detrended Fluctuation Analysis (DFA) has been a topic of many recent studies in to glycemic dynamics. DFA investigates the "complexity" of a signal, how one point in time changes relative to its neighboring points, and DFA has been applied to signals like the inter-beat-interval of human heartbeat to differentiate healthy and pathological conditions. Analyzing the glucose metabolic system with such signal processing tools as DFA has been enabled by the emergence of high quality CGM devices. However, there are several inconsistencies within the published work applying DFA to CGM signals. Therefore, this article presents a review and a "how-to" tutorial of DFA, and in particular its application to CGM signals to ensure the methods used to determine complexity are used correctly and so that any relationship between complexity and patient outcome is robust.