Division of Endocrinology and Metabolic Diseases, Department of Medical Sciences, University of Turin, Torino, Piemonte, Italy.
Institute of Electronics, Information and Telecommunication Engineering, CNR IEIIT, Torino, Piemonte, Italy.
BMJ Open Diabetes Res Care. 2021 Jan;9(1). doi: 10.1136/bmjdrc-2019-001045.
The availability of easily accessible continuous glucose monitoring (CGM) metrics can improve glycemic control in diabetes, and they may even become a viable alternative to hemoglobin A1c (HbA1c) laboratory tests in the next years. The REALISM-T1D study (REAl-Life glucoSe Monitoring in Type 1 Diabetes) was aimed at contributing, with real-world data, to a deeper understanding of these metrics, including the time in range (TIR)-HbA1c relationship, to facilitate their adoption by diabetologists in everyday practice.
70 adults affected by type 1 diabetes were monitored for 1 year by means of either flash (FGM) or real-time (rtCGM) glucose monitoring devices. Follow-up visits were performed after 90, 180 and 365 days from baseline and percentage TIR evaluated for the 90-day time period preceding each visit. HbA1c tests were also carried out in the same occasions and measured values paired with the corresponding TIR data.
A monovariate linear regression analysis confirms a strong correlation between TIR and HbA1c as found in previous studies, but leveraging more homogeneous data (n=146) collected in real-life conditions. Differences were determined between FGM and rtCGM devices in Pearson's correlation (r=0.703, r=0.739), slope (β=-11.77, β=-10.74) and intercept (β=141.19, β=140.77) coefficients. Normality of residuals and homoscedasticity were successfully verified in both cases.
Regression lines for two patient groups monitored through FGM and rtCGM devices, respectively, while confirming a linear relationship between TIR and A1c hemoglobin (A1C) in good accordance with previous studies, also show a statistically significant difference in the regression intercept, thus suggesting the need for different models tailored to device characteristics. The predictive power of A1C as a TIR estimator also deserves further investigations.
易于获取的连续血糖监测（CGM）指标的可用性可以改善糖尿病患者的血糖控制，并且它们甚至可能在未来几年成为替代血红蛋白 A1c（HbA1c）实验室检测的可行方法。REALISM-T1D 研究（1 型糖尿病的 REAL-Life 葡萄糖监测）旨在通过真实世界的数据，深入了解这些指标，包括时间在目标范围内（TIR）-HbA1c 关系，以促进糖尿病医生在日常实践中采用这些指标。
70 名 1 型糖尿病患者使用瞬态血糖仪（FGM）或实时 CGM 设备进行了为期 1 年的监测。从基线开始，在第 90、180 和 365 天进行随访，并在每次随访前的 90 天内评估 TIR 的百分比。在同一时间点还进行了 HbA1c 检测，并将测量值与相应的 TIR 数据配对。
单变量线性回归分析证实了 TIR 与 HbA1c 之间的强相关性，这与之前的研究一致，但利用了更同质的真实数据。在 Pearson 相关系数（r=0.703，r=0.739）、斜率（β=-11.77，β=-10.74）和截距（β=141.19，β=140.77）系数方面，FGM 和 rtCGM 设备之间存在差异。在两种情况下均成功验证了残差的正态性和同方差性。
通过 FGM 和 rtCGM 设备分别监测的两组患者的回归线，虽然与之前的研究一致，证实了 TIR 与 A1c 血红蛋白（A1C）之间的线性关系，但回归截距也存在统计学显著差异，因此需要针对设备特点定制不同的模型。A1C 作为 TIR 估计值的预测能力也值得进一步研究。
