The study on complexity of glucose fluctuation not only helps us understand the regulation of the glucose homeostasis system but also brings us a new insight of the research methodology on glucose regulation. In the experiments, we analyzed the complexity of the temporal structure of the 72 hours continuous glucose time series from a group of 93 subjects with type Ⅱ diabetes mellitus using the multi-scale entropy method. We adapted the most recently improved refined composite multi-scale entropy(RCMSE) algorithm which could overcome the shortcomings on the 72 hours short time series analysis. We then quantified and compared the complexity of continuous glucose time series between groups with type Ⅱ diabetes mellitus with different mean absolute glycemic excursion(MAGE) and glycated hemoglobin(Hb A1c). The results implied that the complexity of glucose time series decreased on lower MAGE group compared to high MAGE group, and the entropy on scale 1 to 6 which corresponded to 5 to 30 min had significant differences between these two groups; the complexity of glucose time series decreased with the increasing Hb A1 c level but the entropy had no statistical difference among groups at different scales. Therefore, RCMSE provided us with a new prospect to analyze the glucose time series and it was proved that less complexity of glucose dynamics could indicate the impaired gluco-regulation function from the MAGE point of view or Hb A1 c for patients, and the glucose complexity had the potential to become a new biomarker to reflect the fluctuation of the glucose time series.
血糖波动复杂性的研究有助于理解血糖调节系统的内在规律。本文以Ⅱ型糖尿病患者（93人）72 h 动态血糖序列为分析对象，使用多尺度熵分析技术研究动态血糖序列结构的复杂性。针对72 h 动态血糖序列较短的问题，采用了最新改进的精细复合多尺度熵（RCMSE）分析技术，分别观察了基于平均血糖波动幅度（MAGE）和糖化血红蛋白（HbA1c）进行分组的糖尿病患者的血糖波动复杂性。研究发现，MAGE 值大的组其复杂度低，熵值在尺度 1～6（5～30 min）之间的差异具有统计学意义，HbA1c 值高的组其复杂度也较低，但是分组之间的熵值差异没有统计学意义。本文研究结果表明，血糖调控不好（无论从 MAGE 值还是从 HbA1c 值来看），将会带来血糖序列动态结构复杂度的损失。本文所提的 RCMSE 分析技术可为血糖序列波动分析提供一个新的视角，血糖序列复杂度有可能成为血糖波动分析的一个新的生物学指标。