Baghurst Peter A, Rodbard David, Cameron Fergus J
Public Health Research Unit, Women's and Children's Hospital, Children Youth and Women's Health Service, North Adelaide, South Australia.
J Diabetes Sci Technol. 2010 Nov 1;4(6):1382-5. doi: 10.1177/193229681000400612.
While there has been much debate about the clinical importance of glycemic variation (GV), little attention has been directed to the properties of data sets from which it is measured. The purpose of this study is to assess the minimum frequency of glucose measurements from which GV can be consistently and meaningfully measured.
Forty-eight 72 h continuous glucose monitoring traces from children with type 1 diabetes were assessed. Measures of GV included standard deviation (SD), mean amplitude of glycemic excursion (MAGE), and continuous overlapping net glycemic action (CONGA1-4). Measures of GV calculated using 5 min sampling were designated as the 100% or "best estimate" value. Calculations were then repeated for each patient using glucose values spaced at increasing intervals. For each of the specified sampling frequencies, the ratio (%) of the between-subject SD based on the reduced subset of data to the estimate of the SD based on the full 5 min sampling data set was calculated.
As the interval between observations increased, so did the variability of the estimators of GV. Standard deviation exhibited the least systematic change at all measurement intervals, and MAGE exhibited the greatest systematic change.
In patients with type 1 diabetes, GV as measured by SD or CONGA4, becomes unreliable if observations are more than 2-4 h apart, and estimates of MAGE become unreliable if glucose measurements are more than 1 h apart. MAGE is more unstable and prone to random measurement error than either SD or CONGA. The frequency of glycemic measurements is thus pivotal when selecting a parameter for measurement of GV.
虽然关于血糖波动（GV）的临床重要性存在诸多争论，但很少有人关注用于测量GV的数据集的特性。本研究的目的是评估能够持续且有意义地测量GV所需的最低血糖测量频率。
评估了48例1型糖尿病儿童的72小时连续血糖监测记录。GV的测量指标包括标准差（SD）、血糖波动幅度均值（MAGE）和连续重叠净血糖作用（CONGA1 - 4）。使用5分钟采样计算的GV测量值被指定为100%或“最佳估计”值。然后，对每位患者使用间隔逐渐增加的血糖值重复进行计算。对于每个指定的采样频率，计算基于数据简化子集的受试者间标准差与基于完整5分钟采样数据集的标准差估计值的比率（%）。
随着观察间隔的增加，GV估计值的变异性也增加。在所有测量间隔中，标准差的系统变化最小，而MAGE的系统变化最大。
在1型糖尿病患者中，如果观察间隔超过2 - 4小时，通过SD或CONGA4测量的GV变得不可靠；如果血糖测量间隔超过1小时，MAGE的估计值变得不可靠。与SD或CONGA相比，MAGE更不稳定，更容易出现随机测量误差。因此，在选择测量GV的参数时，血糖测量频率至关重要。
