Institute of Informatics and Applications, University of Girona, Girona, Spain.
Med Sci Monit. 2010 Jun;16(6):MT51-8.
The CGMS Gold continuous glucose monitor presents a problem of lack of accuracy, especially in the lower range, sometimes leading to missed or false alarms. The new algorithm aims to improve the measurement accuracy and hypoglycemia detection.
MATERIAL/METHODS: Twenty-one patients with type 1 diabetes were monitored for 3 days (1 day at the hospital and 2 at home) using the CGMS Gold. For these patients, blood glucose samples were taken every 15 minutes for 2 hours after meals and every half hour otherwise during the first day. A new calibration algorithm was developed and implemented using CGMS Gold intensity readings and capillary glucose.
After 1 day, a comparison of results from either the CGMS Gold algorithm and the proposed algorithm, compared with results from blood (2450 points), showed an increase of data in zone A with the proposed algorithm (4.4% in the Clarke error grid analysis (EGA) and 5.0% in the Consensus EGA). After comparing for 3 days, a reduction of 24.7%, p<0.05, in the overall median relative absolute difference (RAD) was also obtained. In the hypoglycemic range, a significant decrease in median RAD was observed (64.4%, p<0.05). Furthermore, the undetected hypoglycemia events in capillary samples by the proposed algorithm were reduced by 59.8% compared to the CGMS Gold algorithm.
The performance as measured with clinical and numerical accuracy criteria illustrates the improved accuracy of the proposed algorithm in comparison with the CGMS Gold algorithm. A significant improvement in hypoglycemia detection was observed.
CGMS Gold 连续血糖监测仪存在准确性不足的问题,尤其是在低值范围,有时会导致漏报或误报。新算法旨在提高测量准确性和低血糖检测能力。
材料/方法:21 名 1 型糖尿病患者使用 CGMS Gold 监测了 3 天(1 天在医院,2 天在家)。这些患者在第一天,用餐后每 15 分钟和其他时间每半小时取一次指尖血糖样本,共 2 小时。开发并实施了一种新的校准算法,使用 CGMS Gold 强度读数和毛细血管葡萄糖值。
使用 CGMS Gold 算法和提出的算法与血液(2450 个点)结果进行比较,在第一天后,与提出的算法相比,数据在 A 区增加(Clarke 误差网格分析(EGA)中增加 4.4%,共识 EGA 中增加 5.0%)。比较 3 天后,还获得了总体中位数相对绝对差(RAD)降低 24.7%(p<0.05)。在低血糖范围内,中位 RAD 显著降低(p<0.05)。此外,与 CGMS Gold 算法相比,提出的算法检测到毛细血管样本中未被检测到的低血糖事件减少了 59.8%。
临床和数值准确性标准的性能表明,与 CGMS Gold 算法相比,提出的算法在准确性方面有显著提高。观察到低血糖检测能力显著提高。