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Glycemic Variability: The Third Component of the Dysglycemia in Diabetes. Is It Important? How to Measure It?

机译:血糖变异性:糖尿病患者血糖异常的第三部分。那很重要么?如何测量?

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摘要

The dysglycemia of diabetes includes two components: (1) sustained chronic hyperglycemia that exerts its effects through both excessive protein glycation and activation of oxidative stress and (2) acute glucose fluctuations. Glycemic variability seems to have more deleterious effects than sustained hyperglycemia in the development of diabetic complications as both upward (postprandial glucose increments) and downward (interprandial glucose decrements) changes activate the oxidative stress. For instance, the urinary excretion rate of 8-iso-PGF2α, a reliable marker of oxidative stress, was found to be strongly, positively correlated (r = 0.86, p < .001) with glycemic variability assessed from the mean amplitude of glycemic excursions (MAGE) as estimated by continuous glucose monitoring systems (CGMS). These observations therefore raise the question of whether we have the appropriate tools for assessing glycemic variability in clinical practice. From a statistical point of view, the standard deviation (SD) around the mean glucose value appears as the “gold standard.” By contrast, the MAGE index is probably more appropriate for selecting the major glucose swings that are calculated as the arithmetic mean of differences between consecutive peaks and nadirs, provided that the differences be greater than the SD around the mean values. Furthermore, calculating the MAGE index requires continuous glucose monitoring, which has the advantage to detect all isolated upward and downward acute glucose fluctuations. In conclusion, the increasing use of CGMSs will certainly promote better assessment and management of glycemic variability.
机译:糖尿病的血糖异常包括两个部分:(1)持续的慢性高血糖症,其通过过度的蛋白质糖基化和氧化应激的激活发挥作用,以及(2)急性葡萄糖波动。在持续发展的糖尿病并发症中,血糖变化似乎比持续性高血糖更具有害作用,因为向上(餐后葡萄糖增加)和向下(餐间葡萄糖减少)的变化都激活了氧化应激。例如,发现8-iso-PGF2α(一种可靠的氧化应激指标)的尿排泄率与根据血糖波动的平均幅度评估的血糖变异性呈强正相关(r = 0.86,p <.001)。 (MAGE),由连续葡萄糖监测系统(CGMS)估算。因此,这些观察提出了一个问题,即我们是否具有在临床实践中评估血糖变异性的适当工具。从统计角度来看,平均葡萄糖值附近的标准偏差(SD)似乎是“黄金标准”。相比之下,MAGE指数可能更适合选择主要的葡萄糖波动,这些波动被计算为连续峰和最低点之间差异的算术平均值,但前提是差异要大于平均值附近的SD。此外,计算MAGE指数需要连续进行葡萄糖监测,这具有检测所有孤立的向上和向下急性葡萄糖波动的优势。总之,越来越多的CGMS使用必将促进更好地评估和管理血糖变异性。

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