Wu Zhenghao, Liu Zhaoxiang, Zhao Wenhui, Wang Shaocheng, Gu Liangbiao, Xiao Jianzhong
Department of Endocrinology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.
Department of Endocrinology, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou Peoples Hospital, Quzhou, Zhejiang, China.
Front Endocrinol (Lausanne). 2025 Apr 22;16:1466358. doi: 10.3389/fendo.2025.1466358. eCollection 2025.
Based on FreeStyle Libre, we designed QT AIR, an advanced real-time, calibrated Continuous Glucose Monitoring (CGM) device. This study aim to validate the consistency and clinical accuracy of the product by comparing the capillary blood glucose (CBG) with CGM data in both in-hospital and outpatient scenarios.
Results of CGM devices were compared with random capillary glucose values from users in both in-hospital and outpatient settings. The accuracy of CGMs was assessed through consistency analysis, Bland-Altman analysis, calculation of MARD and MAD, Consensus Error Grids, as well as analysis using the Continuous Glucose Deviation Interval and Variability Analysis (CG-DIVA).
In outpatient setting, 1907 values from 138 users were analyzed. FreeStyle Libre data, QT AIR calibrated and uncalibrated data showed strong positive correlations with capillary blood glucose values. The MARD values for the FreeStyle Libre, uncalibrated QT AIR, and calibrated QT AIR groups were 18.33%, 20.63%, and 12.39%, respectively. Consensus Error Grid, reference values in Zone A: FreeStyle Libre: 69.75%, QT AIR uncalibrated: 67.80%, QT AIR calibrated: 87.62%. The Bland-Altman analysis results suggest that FreeStyle Libre exhibitsed a systematic underestimation of blood glucose levels, while QT AIR almost rectified the differences. In the in-Hospital setting, the MARD of QT AIR after calibration was reduced to 7.24%. The Consensus error grid analyses of the in-Hospital data revealed that 95% of the calibrated QT AIR values fell within Zone A, a significantly higher proportion than that of other two group. The CG-DIVA analysis of the calibrated QT AIR device showed a median bias of -0.49% and a between-sensor variability of 26.65%, both of which are significantly lower than the corresponding values observed for the FreeStyle Libre device.
We successfully transformed a retrospective CGM system into a real-time monitoring device. The monitoring accuracy of the device could be improved by calibration.
基于FreeStyle Libre,我们设计了QT AIR,一种先进的实时、校准连续血糖监测(CGM)设备。本研究旨在通过比较住院和门诊场景下的毛细血管血糖(CBG)与CGM数据,验证该产品的一致性和临床准确性。
将CGM设备的结果与住院和门诊环境中用户的随机毛细血管血糖值进行比较。通过一致性分析、Bland-Altman分析、MARD和MAD计算、一致性误差网格以及使用连续血糖偏差区间和变异性分析(CG-DIVA)进行评估,以确定CGM的准确性。
在门诊环境中,分析了138名用户的1907个值。FreeStyle Libre数据、QT AIR校准和未校准数据与毛细血管血糖值显示出强正相关。FreeStyle Libre、未校准QT AIR和校准QT AIR组的MARD值分别为18.33%、20.63%和12.39%。一致性误差网格,A区参考值:FreeStyle Libre:69.75%,未校准QT AIR:67.80%,校准QT AIR:87.62%。Bland-Altman分析结果表明,FreeStyle Libre表现出血糖水平的系统性低估,而QT AIR几乎纠正了差异。在住院环境中,校准后QT AIR的MARD降至7.24%。住院数据的一致性误差网格分析显示,95%的校准QT AIR值落在A区,这一比例显著高于其他两组。校准后的QT AIR设备的CG-DIVA分析显示,中位数偏差为-0.49%,传感器间变异性为26.65%,均显著低于FreeStyle Libre设备观察到的相应值。
我们成功地将一个回顾性CGM系统转变为一个实时监测设备。通过校准可以提高该设备的监测准确性。