scholarly journals The Relationships Between Time in Range, Hyperglycemia Metrics, and HbA1c

2019 ◽  
Vol 13 (4) ◽  
pp. 614-626 ◽  
Author(s):  
Roy W. Beck ◽  
Richard M. Bergenstal ◽  
Peiyao Cheng ◽  
Craig Kollman ◽  
Anders L. Carlson ◽  
...  
Keyword(s):  
Hemoglobin A1c ◽  
Glucose Monitoring ◽  
Area Under The Curve ◽  
High Blood Glucose ◽  
Wide Range ◽  
Time In Range ◽  
Highly Correlated ◽  
Mean Glucose ◽  
Considerable Spread

Background: As the use of continuous glucose monitoring (CGM) increases, there is a need to better understand key metrics of time in range 70-180 mg/dL (TIR70-180) and hyperglycemia and how they relate to hemoglobin A1c (A1C). Methods: Analyses were conducted utilizing datasets from four randomized trials encompassing 545 adults with type 1 diabetes (T1D) who had central-laboratory measurements of A1C. CGM metrics were calculated and compared with each other and A1C cross-sectionally and longitudinally. Results: Correlations among CGM metrics (TIR70-180, time >180 mg/dL, time >250 mg/dL, mean glucose, area under the curve above 180 mg/dL, high blood glucose index, and time in range 70-140 mg/dL) were typically 0.90 or greater. Correlations of each metric with A1C were lower (absolute values 0.66-0.71 at baseline and 0.73-0.78 at month 6). For a given TIR70-180 percentage, there was a wide range of possible A1C levels that could be associated with that TIR70-180 level. On average, a TIR70-180 of 70% and 50% corresponded with an A1C of approximately 7% and 8%, respectively. There also was considerable spread of change in A1C for a given change in TIR70-180, and vice versa. An increase in TIR70-180 of 10% (2.4 hours per day) corresponded to a decrease in A1C of 0.6%, on average. Conclusions: In T1D, CGM measures reflecting hyperglycemia (including TIR and mean glucose) are highly correlated with each other but only moderately correlated with A1C. For a given TIR or change in TIR there is a wide range of possible corresponding A1C values.

scholarly journals Effects of Glucose Control and Variability on Endothelial Function and Repair in Adolescents with Type 1 Diabetes

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Robert P. Hoffman ◽  
Amanda S. Dye ◽  
Hong Huang ◽  
John A. Bauer
Keyword(s):  
Type 1 Diabetes ◽  
Endothelial Dysfunction ◽  
Endothelial Function ◽  
Hemoglobin A1c ◽  
Glucose Monitoring ◽  
Area Under The Curve ◽  
Vascular Occlusion ◽  
Venous Occlusion ◽  
Mean Glucose

Background. Endothelial dysfunction and increased inflammation are precursors of cardiovascular disease in type 1 diabetes (T1D) and occur even in adolescents with T1D. The goal of this study was to determine the relationship of endothelial dysfunction to various measures of glycemia. Research Design and Methods. Forearm blood flow (FBF, venous occlusion plethysmography) was measured before and after 5 min of upper arm vascular occlusion in 17 adolescents with uncomplicated type 1 diabetes. Endothelial function was assessed as postocclusion FBF and forearm vascular resistance (FVR, mean arterial pressure/FBF). Fasting glucose, 72 hour mean glucose and standard deviation from continuous glucose monitoring, hemoglobin A1c, and hemoglobin A1c by duration area under the curve were used to assess immediate, short-term, and intermediate- and long-term glycemia. Results. Postocclusion FBF (r=-0.53, P=0.030) negatively correlated and postocclusion FVR positively correlated (r=0.52, P=0.031) with hemoglobin A1c levels. FVR was positively associated with log 3 day mean glucose (r=0.55, P=0.027). Postocclusion FBF (2.8±1.1 versus 3.4±0.5 mL/dL/min, mean ± SE, P=0.084) tended to be lower and FVR (31.4±10.4 versus 23.9±4.4 mmHg dL min/mL, P=0.015) was significantly higher in subjects with hemoglobin A1c above the median (8.3%) compared to those with lower hemoglobin A1c levels. Conclusions. These results demonstrate that poor intermediate-term glycemic control is associated with impaired endothelial function.

Frequency of flash glucose monitoring readings, hemoglobin A1c and time in range: a real life study in adults with type 1 diabetes

2020 ◽  
Vol 57 (11) ◽  
pp. 1395-1397 ◽  
Author(s):  
Andrea Laurenzi ◽  
Amelia Caretto ◽  
Mariluce Barrasso ◽  
Andrea Mario Bolla ◽  
Nicoletta Dozio ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Hemoglobin A1c ◽  
Real Life ◽  
Glucose Monitoring ◽  
Flash Glucose Monitoring ◽  
Life Study ◽  
Time In Range ◽  
Real Life Study

scholarly journals Eight-Point Glucose Testing Versus the Continuous Glucose Monitoring System in Evaluation of Glycemic Control in Type 1 Diabetes

2005 ◽  
Vol 90 (6) ◽  
pp. 3387-3391 ◽  
Keyword(s):  
Type 1 Diabetes ◽  
Monitoring System ◽  
Continuous Glucose Monitoring ◽  
Hemoglobin A1c ◽  
Glucose Monitoring ◽  
Continuous Glucose Monitoring System ◽  
Diabetes Research ◽  
Glucose Profiles ◽  
Mean Glucose

Context: Advantages/disadvantages of continuous vs. discrete glucose monitoring are not well documented. Objective: Compare glucose profiles from home meters vs. continuous sensors. Design: Randomized clinical trial conducted by the Diabetes Research in Children Network (DirecNet) to assess the utility of the GlucoWatch G2 Biographer. Setting: Home glucose measurements. Patients: Two hundred children (age, 7 to < 18 yr) with type 1 diabetes. Intervention: At baseline, subjects were asked to wear the continuous glucose monitoring system (CGMS) sensor and perform meter tests at eight prespecified times of the day (eight-point testing) each for 3 d (2 d using both, 1 d eight-point testing only, 1 d CGMS only). Hemoglobin A1c was measured in a central laboratory. Main Outcome Measure: Six-month hemoglobin A1c. This analysis looked at baseline glucose profiles/hemoglobin A1c. Results: Only 10% of subjects completed full eight-point testing for 3 d, but median CGMS use was 70 h. Mean glucose was lower when measured by the CGMS compared with eight-point testing (183 ± 37 vs. 188 ± 41 mg/dl; 10.2 ± 2.1 vs.10.4 ± 2.3 mmol/liter; P = 0.009), especially overnight (2400–0400 h; 174 vs. 199 mg/dl; 9.7 vs. 11.1 mmol/liter; P < 0.001). Associations of hemoglobin A1c with mean glucose were similar for eight-point testing [slope 23 mg/dl per 1% (1.3 mmol/liter); correlation 0.40; P < 0.001] and CGMS [slope 19 mg/dl per 1% (1.1 mmol/liter); correlation 0.39; P < 0.001]. Postprandial excursions were lower for eight-point testing vs. CGMS, especially after dinner (mean excursion −17 vs. 63 mg/dl; −1.0 vs. 3.5 mmol/liter; P < 0.001). Conclusions: Both methods gave similar mean glucose profiles and associations with hemoglobin A1c. Advantages of the CGMS were higher density of data and better detection of postprandial peaks. However, the CGMS may overestimate the frequency of low glucose levels, especially overnight.

scholarly journals Achieving the HbA1c Target Requires Longer Time in Range in Pregnant Women with Type 1 Diabetes

2021 ◽  
Author(s):  
Ping Ling ◽  
Daizhi Yang ◽  
Nan Gu ◽  
Xinhua Xiao ◽  
Jing Lu ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Pregnant Women ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Pregnancy And Postpartum ◽  
Best Fitting ◽  
Time In Range ◽  
Hba1c Target ◽  
Mean Glucose

Abstract Aims Continuous glucose monitoring (CGM) overcomes the limitations of glycated hemoglobin (HbA1c). This study was to investigate the relationship between CGM metrics and laboratory HbA1c in pregnant women with type 1 diabetes. Methods An observational study enrolled pregnant women with type 1 diabetes who wore CGM devices during pregnancy and postpartum from 11 hospitals in China from January 2015 to June 2019. CGM data were collected to calculate time-in-range (TIR), time above range (TAR), time below range (TBR), and glycemic variability parameters. Relationships between the CGM metrics and HbA1c were explored. Linear and curvilinear regressions were conducted to investigate the best-fitting model to clarify the influence of HbA1c on the TIR-HbA1c relationship during pregnancy. Results A total of 272 CGM data and corresponding HbA1c from 98 pregnant women with type 1 diabetes and their clinical characteristics were analyzed in this study. Mean HbA1c and TIR were 6.49±1.29% and 76.16±17.97% during pregnancy, respectively. HbA1c was moderately correlated with TIR 3.5-7.8(R= -0.429, P=0.001), mean glucose (R= 0.405, P=0.001) and TAR 7.8 (R=0.435, P=0.001), but was weakly correlated with TBR 3.5 (R=0.034, P=0.001) during pregnancy. On average, a 1% (11 mmol/mol) decrease in HbA1c corresponded to an 8.5% increase in TIR 3.5-7.8. During pregnancy, HbA1c of 6.0%, 6.5% and 7.0% were equivalent to a TIR 3.5-7.8 of 78%, 74%, and 69%, respectively. Conclusions We found that there was a moderate correlation between HbA1c and TIR 3.5-7.8 during pregnancy. To achieve the HbA1c target <6.0%, pregnant women with type 1 diabetes should strive for TIR 3.5-7.8 >78% (18h 43min) during pregnancy.

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

2021 ◽  
Vol 9 (1) ◽  
pp. e001045
Author(s):  
Marina Valenzano ◽  
Ivan Cibrario Bertolotti ◽  
Adriano Valenzano ◽  
Giorgio Grassi
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Real World ◽  
Hemoglobin A1c ◽  
Linear Regression Analysis ◽  
Real Life ◽  
Glucose Monitoring ◽  
Significant Difference ◽  
Time In Range

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.

Increased Time-in-Range with Sotagliflozin as Adjunct Therapy to Insulin in Adults with Type 1 Diabetes as Demonstrated by 24-Week Continuous Glucose Monitoring (inTandem1, inTandem2)

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1179-P ◽  
Author(s):  
THOMAS DANNE ◽  
BERTRAND CARIOU ◽  
JOHN B. BUSE ◽  
SATISH K. GARG ◽  
JULIO ROSENSTOCK ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Adjunct Therapy ◽  
Time In Range
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