scholarly journals Ultra-Rapid Lispro Improves Postprandial Glucose Control and Time in Range in Type 1 Diabetes Compared to Lispro: PRONTO-T1D Continuous Glucose Monitoring Substudy

2020 ◽  
Vol 22 (11) ◽  
pp. 853-860
Author(s):  
Maciej T. Malecki ◽  
Dachuang Cao ◽  
Rong Liu ◽  
Thomas Hardy ◽  
Bruce Bode ◽  
...  
Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1179-P ◽  
Author(s):  
THOMAS DANNE ◽  
BERTRAND CARIOU ◽  
JOHN B. BUSE ◽  
SATISH K. GARG ◽  
JULIO ROSENSTOCK ◽  
...  

2019 ◽  
Author(s):  
Arkadiusz Michalak ◽  
Konrad Pagacz ◽  
Wojciech Młynarski ◽  
Agnieszka Szadkowska ◽  
Wojciech Fendler

2021 ◽  
Vol 9 (1) ◽  
pp. e001045
Author(s):  
Marina Valenzano ◽  
Ivan Cibrario Bertolotti ◽  
Adriano Valenzano ◽  
Giorgio Grassi

IntroductionThe 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.Research design and methods70 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 TIR70–180 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.ResultsA 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 (rFGM=0.703, rrtCGM=0.739), slope (β1,FGM=−11.77, β1,rtCGM=−10.74) and intercept (β0,FGM=141.19, β0,rtCGM=140.77) coefficients. Normality of residuals and homoscedasticity were successfully verified in both cases.ConclusionsRegression 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.


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