Favero Simone Del, Facchinetti Andrea, Sparacino Giovanni, Cobelli Claudio
Department of Information Engineering, University of Padova , Padova, Italy .
Diabetes Technol Ther. 2017 Apr;19(4):237-245. doi: 10.1089/dia.2016.0413. Epub 2017 Mar 13.
We proposed in 2014 a retrofitting algorithm to retrospectively increase the accuracy of continuous glucose monitoring (CGM) data by using some blood glucose (BG) measurements. The method proved effective on Dexcom SEVEN Plus when about 10 highly accurate YSI measurements/session were available. In this study, we test the method on Dexcom G5 sensor in a more realistic setup, where only five capillary BG measurements (self-monitoring blood glucose [SMBG]) per 12 h-session are available. Furthermore, we investigate how accuracy is affected by the number of BG measurements.
The algorithm was tested in 51 adults and 46 adolescents studied for 7 days with Dexcom G5. Each patient also underwent an ∼12-h hospital admission where frequent SMBG and YSI measurements were collected. First, five SMBGs per 12-h session were used to retrofit the CGM. Then, we varied the number of SMBGs provided to the method from 2 to 10 per 12-h session.
Retrofitted CGM traces with five SMBGs per 12-h session have lower mean absolute difference than original CGM, reduced from 16.2 to 10.7 mg/dL (P < 0.001) in adults and from 17.6 to 11.5 mg/dL (P < 0.001) in adolescents, and mean absolute relative difference is reduced from 9.0% to 6.4% (P < 0.001) in adults and from 10.3% to 6.8% (P < 0.001) in adolescents. Reducing the number of BG measurements reduces improvement in the accuracy from >30% with 10 SMBGs per 12-h session to <16% with 2 SMBGs/day.
The retrofitting method retrospectively improves the accuracy of CGM data, even if applied to one of the most accurate CGM sensors currently available on the market.
2014年我们提出了一种改进算法,通过使用一些血糖(BG)测量值来回顾性提高连续血糖监测(CGM)数据的准确性。当每个监测时段约有10次高度准确的YSI测量值时,该方法在德康SEVEN Plus血糖仪上被证明是有效的。在本研究中,我们在更实际的环境中对德康G5传感器测试该方法,即每个12小时监测时段仅有5次毛细血管血糖测量值(自我监测血糖[SMBG])。此外,我们研究了血糖测量次数对准确性的影响。
该算法在51名成年人和46名青少年中进行测试,他们使用德康G5进行了7天的研究。每位患者还经历了约12小时的住院治疗,期间收集了频繁的自我监测血糖和YSI测量值。首先,每个12小时监测时段使用5次自我监测血糖值来改进连续血糖监测。然后,我们将每个12小时监测时段提供给该方法的自我监测血糖值数量从2次变化到10次。
每个12小时监测时段使用5次自我监测血糖值改进后的连续血糖监测轨迹的平均绝对差值低于原始连续血糖监测,成年人中从16.2降至10.7mg/dL(P<0.001),青少年中从17.6降至11.5mg/dL(P<0.001),平均绝对相对差值在成年人中从9.0%降至6.4%(P<0.001),在青少年中从10.3%降至6.8%(P<0.001)。减少血糖测量次数会使准确性的提高从每个12小时监测时段10次自我监测血糖值时的>30%降至每天2次自我监测血糖值时的<16%。
即使应用于目前市场上最准确的连续血糖监测传感器之一,这种改进方法也能回顾性提高连续血糖监测数据的准确性。