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从 1 型糖尿病患者的连续血糖监测数据估算糖化血红蛋白:我们是否只需要达标时间?

Estimation of Hemoglobin A1c from Continuous Glucose Monitoring Data in Individuals with Type 1 Diabetes: Is Time In Range All We Need?

机构信息

Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia, USA.

Science Consulting in Diabetes GmbH, Neuss, Germany.

出版信息

Diabetes Technol Ther. 2020 Jul;22(7):501-508. doi: 10.1089/dia.2020.0236.

Abstract

To bridge the gap between laboratory-measured hemoglobin A1c (HbA1c) and continuous glucose monitoring (CGM)-derived time in target range (TIR), introducing TIR-driven estimated A1c (eA1c). Data from Protocol 1 (training data set) and Protocol 3 (testing data set) of the International Diabetes Closed-Loop Trial were used. Training data included 3 months of CGM recordings from 125 individuals with type 1 diabetes, and HbA1c at 3 months; testing data included 9 months of CGM recordings from 168 individuals, and HbA1c at 3, 6, and 9 months. Hemoglobin glycation was modeled by a first-order differential equation driven by TIR. Three model parameters were estimated in the training data set and fixed thereafter. A fourth parameter was estimated in the testing data set, to individualize the model by calibration with month 3 HbA1c. The accuracy of eA1c was assessed on months 6 and 9 HbA1c. eA1c was tracked for each individual in the testing data set for 6 months after calibration. Mean absolute differences between HbA1c and eA1c 3- and 6-month postcalibration were 0.25% and 0.24%; Pearson's correlation coefficients were 0.93 and 0.93; percentages of eA1c within 10% from reference HbA1c were 97.6% and 96.3%, respectively. HbA1c and TIR are reflections of the same underlying process of glycemic fluctuation. Using a model individualized with one HbA1c measurement, TIR provides an accurate approximation of HbA1c for at least 6 months, reflecting blood glucose fluctuations and nonglycemic biological factors. Thus, eA1c is an intermediate metric that mathematically adjusts a CGM-based assessment of glycemic control to individual glycation rates.

摘要

为了弥合实验室测量的血红蛋白 A1c(HbA1c)与连续血糖监测(CGM)衍生的目标范围内时间(TIR)之间的差距,引入 TIR 驱动的估计 A1c(eA1c)。数据来自国际糖尿病闭环试验的方案 1(训练数据集)和方案 3(测试数据集)。训练数据包括 125 名 1 型糖尿病患者的 3 个月 CGM 记录和 3 个月的 HbA1c;测试数据包括 168 名患者的 9 个月 CGM 记录和 3、6 和 9 个月的 HbA1c。血红蛋白糖化作用由 TIR 驱动的一阶微分方程建模。在训练数据集中估计了三个模型参数,此后固定不变。在测试数据集中估计了第四个参数,通过与 3 个月 HbA1c 的校准来对模型进行个体化。在 6 个月和 9 个月的 HbA1c 上评估了 eA1c 的准确性。在校准后,对测试数据集中的每个个体进行了 6 个月的 eA1c 跟踪。校准后 3 个月和 6 个月的 HbA1c 和 eA1c 的平均绝对差异分别为 0.25%和 0.24%;Pearson 相关系数分别为 0.93 和 0.93;eA1c 与参考 HbA1c 的差值在 10%以内的百分比分别为 97.6%和 96.3%。HbA1c 和 TIR 反映了血糖波动的同一基本过程。使用一个 HbA1c 测量值进行个体化的模型,TIR 至少可以在 6 个月内准确估算 HbA1c,反映血糖波动和非血糖生物因素。因此,eA1c 是一种中间指标,它从数学上调整了基于 CGM 的血糖控制评估,以适应个体糖化率。

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