Continuous glucose monitoring in subjects with type 1 diabetes: improvement in accuracy by correcting for background current.
Continuous glucose monitoring in subjects with type 1 diabetes: improvement in accuracy by correcting for background current.
复制标题
DOI：
10.1089/dia.2010.0020
复制
发表时间：
2010-11
影响因子：
5.4
通讯作者：
J. El Youssef;J. Castle;J. Engle;Ryan G. Massoud;W. Ward
中科院分区：
文献类型：
--
作者：
J. El Youssef;J. Castle;J. Engle;Ryan G. Massoud;W. Ward
电流型葡萄糖传感器中次优精度的原因是存在未考虑的背景电流（在不存在葡萄糖的情况下产生的电流）。我们假设，与我们假设背景电流为零的情况相比，对市售传感器的估计背景电流进行数学校正将导致更高的准确性。我们还测试了增加传感器校准频率是否会提高传感器的准确性。本报告包括对来自7名1型糖尿病受试者的20个传感器数据集的分析。数据被分成用于算法开发的训练集和用于测试算法的验证集。测试了一系列潜在背景电流。结果使用4 nA的背景电流校正导致准确度的实质性改善（绝对相对差或绝对差改善3.5-5.5个单位）。校准频率的增加导致了适度的精度提高，最佳值为每4小时。结论：与无校正相比，对市售葡萄糖探头的估计背景电流进行校正可提高准确度，并更好地检测低血糖和高血糖。本文提出的精度优化方案可以真实的实时实现。
BACKGROUND A cause of suboptimal accuracy in amperometric glucose sensors is the presence of a background current (current produced in the absence of glucose) that is not accounted for. We hypothesized that a mathematical correction for the estimated background current of a commercially available sensor would lead to greater accuracy compared to a situation in which we assumed the background current to be zero. We also tested whether increasing the frequency of sensor calibration would improve sensor accuracy. METHODS This report includes analysis of 20 sensor datasets from seven human subjects with type 1 diabetes. Data were divided into a training set for algorithm development and a validation set on which the algorithm was tested. A range of potential background currents was tested. RESULTS Use of the background current correction of 4 nA led to a substantial improvement in accuracy (improvement of absolute relative difference or absolute difference of 3.5-5.5 units). An increase in calibration frequency led to a modest accuracy improvement, with an optimum at every 4 h. CONCLUSIONS Compared to no correction, a correction for the estimated background current of a commercially available glucose sensor led to greater accuracy and better detection of hypoglycemia and hyperglycemia. The accuracy-optimizing scheme presented here can be implemented in real time.