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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(Hb A1c)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,Hb A1c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Hb A1c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。
The study of the complexity of blood glucose fluctuations helps to understand the inherent laws of the blood glucose regulation system. In this paper, 72-h dynamic blood glucose levels in patients with type 2 diabetes mellitus (93 patients) were analyzed. The complexity of dynamic glycemic sequence structure was studied using multiscale entropy analysis. Aiming at the problem of short dynamic blood glucose sequence at 72 h, the latest improved fine composite multiscale entropy (RCMSE) analysis technique was used to observe the changes of blood glucose in patients with diabetes mellitus based on mean blood glucose fluctuation (MAGE) and glycosylated hemoglobin (Hb A1c) The complexity of blood sugar fluctuations. The study found that the group with high MAGE value had low complexity and the difference between the entropy values at scale 1 ~ 6 (5 ~ 30 min) was statistically significant, while the group with high Hb A1c value was also lower in complexity. However, The difference between the entropy values was not statistically significant. The results of this study show that the poor blood glucose regulation (from the MAGE value or from the Hb A1c value), will bring about the loss of the dynamic structural complexity of blood glucose. The RCMSE analysis technology proposed in this paper can provide a new perspective for the analysis of blood glucose sequence fluctuation, and the complexity of blood glucose sequence may become a new biological indicator of blood glucose fluctuation analysis.