Time in range–A1c hemoglobin relationship in continuous glucose monitoring of type 1 diabetes: a real-world study

Abstract

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.

Low and high carbohydrate isocaloric diets on performance, fat oxidation, glucose and cardiometabolic health in middle age males

“…Participants' interstitial glucose concentrations were measured throughout each 31-day dietary intervention via CGM (Freestyle Libre 2, Abbott Diabetes Care Inc; Almeda, CA) utilizing Levels, Inc., mobile application software to capture glucose response and trends in real-time (Levels Health, Levels, Inc., New York, New York). CGM tracks long-term to HbA 1c (54)(55)(56), short term CGM readings (10-14d) are good estimates of 3-month CGM averages (57), and (iii) CGM can also capture both fasting and post-prandial differences in glucose (validated diagnostic tools). Participants were instructed to apply a 14-day sensor to the back of the arm following the manufacturer's written instructions and demonstration video.…”

“…Continuous glucose monitors are unique tools which allow researchers to extract changes in glycemic control every ≤ 15 min over extended periods of time without relying on the limitations at a single timepoint which may only provide limited biological feedback (78,79). Importantly, (i) CGM tracks long-term with HbA 1c (54)(55)(56), (ii) shorter term CGM readings (10-14d) are good estimates of 3-month CGM averages (57), and (iii) can also capture both fasting and post-prandial differences in glucose (validated diagnostic tool) demonstrating a powerful monitoring tool for glycemic control, particularly in interventions not long enough to confirm alterations in HbA 1c (< 2-3 months in length). The value of these tools has been shown in previous observations utilizing lower carbohydrate (80) or ketogenic interventions (81) where continuous glucose patterns found key shifts in glycemic control before and/or in the absence of changes in traditional biochemical cardiometabolic biomarkers.…”

Improvement in Mean CGM Glucose in Young People with Type 1 Diabetes During 1 Year of the COVID-19 Pandemic

“…Another limitation relates to our inability to report glucose TIR, an important metric for diabetes care delivery. [24][25][26][27] In our clinic, we review and discuss this metric with patients/families; however, it is currently not entered into the EHR in a unique data field like CGM glucose mean and SD; future studies could use downloadable raw CGM data. Another limitation stems from the reduced ability of our EHR data capture to report when patients may have changed their insulin programs or adopted a hybrid closed loop system.…”

Todo lo que usted quiso saber sobre la monitorización de la glucosa y nunca se atrevió a preguntar

“…La HbA1c es la métrica utilizada hasta la fecha en ensayos clínicos que demuestra los beneficios de un mejor control glucémico 1 . Aún así, la monitorización continua de la glucosa durante 14 días de los valores TIR y GMI se está abriendo camino como posible sustituta de la HbA1c en el manejo clínico del paciente con DM 11,12 .…”