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首页> 外文期刊>Diabetes care >Mean blood glucose and biological variation have greater influence on HbA1c levels than glucose instability: an analysis of data from the Diabetes Control and Complications Trial.
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Mean blood glucose and biological variation have greater influence on HbA1c levels than glucose instability: an analysis of data from the Diabetes Control and Complications Trial.

机译:平均血糖和生物学变异对HbA1c水平的影响大于对葡萄糖的不稳定性:对糖尿病控制和并发症试验数据的分析。

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OBJECTIVE: Mean blood glucose (MBG) over 2-3 months is a strong predictor of HbA(1c) (A1C) levels. Glucose instability, the variability of blood glucose levels comprising the MBG, and biological variation in A1C (BV) have also been suggested as predictors of A1C independent of MBG. To assess the relative importance of MBG, BV, and glucose instability on A1C, we analyzed patient data from the Diabetes Control and Complications Trial (DCCT). RESEARCH DESIGN AND METHODS: A glucose profile set and sample for A1C were collected quarterly over the course of the DCCT from each participant (n = 1,441). The glucose profile set consisted of seven samples, one each drawn before and 90 min after breakfast, lunch, and dinner and one before bedtime. MBG and glucose instability (SD of blood glucose [SDBG]) were calculated as the arithmetic mean and SD of glucose profile set samples for each visit, respectively. A statistical model was developed to predict A1C from MBG, SDBG, and BV, adjusted for diabetes duration, sex, treatment group, stratum, and race. RESULTS: Data from 32,977 visits were available. The overall model was highly statistically significant (log likelihood = -41,818.75, likelihood ratio chi2[7] = 7,218.71, P > chi2 = 0.0000). MBG and BV had large influences on A1C based on their standardized coefficients. SDBG had only 1/14 of the impact of MBG and 1/10 of the impact of BV. CONCLUSIONS: MBG and BV have a large influence on A1C, whereas SDBG is relatively unimportant. Consideration of BV as well as MBG in the interpretation of A1C may enhance our ability to monitor diabetes management and predict complications.
机译:目的:2-3个月的平均血糖(MBG)是HbA(1c)(A1C)水平的强烈预测指标。葡萄糖不稳定性,包括MBG的血糖水平的可变性以及A1C(BV)的生物学变异也已被建议作为A1C独立于MBG的预测因子。为了评估MBG,BV和葡萄糖不稳定性对A1C的相对重要性,我们分析了来自糖尿病控制和并发症试验(DCCT)的患者数据。研究设计与方法:在DCCT过程中每季度从每个参与者(n = 1,441)每季度收集一次葡萄糖曲线集和A1C样品。血糖分布由七个样本组成,每个样本在早餐,午餐和晚餐之前和之后90分钟抽取,另一个在睡前抽取。计算MBG和葡萄糖不稳定性(血糖的SD [SDBG]),分别作为每次就诊时血糖分布图样本的算术平均值和SD。建立了统计模型以根据MBG,SDBG和BV预测A1C,并调整了糖尿病持续时间,性别,治疗组,阶层和种族。结果:可获得来自32,977次访问的数据。总体模型具有高度的统计学意义(对数似然= -41,818.75,似然比chi2 [7] = 7,218.71,P> chi2 = 0.0000)。基于它们的标准化系数,MBG和BV对A1C的影响很大。 SDBG仅受到MBG影响的1/14和BV影响的1/10。结论:MBG和BV对A1C的影响很大,而SDBG则相对不重要。在A1C的解释中考虑BV和MBG可能会增强我们监测糖尿病管理和预测并发症的能力。

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