2021
DOI: 10.1210/clinem/dgab688
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Relationship Between Time in Range, Glycemic Variability, HbA1c, and Complications in Adults With Type 1 Diabetes Mellitus

Abstract: Purpose Real-time continuous glucose monitoring (RT-CGM) provides information on glycaemic variability (GV), time in range (TIR) and guidance to avoid hypoglycemia, thereby complimenting HbA1c for diabetes management. We investigated whether GV and TIR were independently associated with chronic and acute diabetes complications. Methods Between September 2014 and January 2017 515 subjects with type 1 diabetes using sensor-augm… Show more

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Cited by 57 publications
(43 citation statements)
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“…One of the possible explanations for such disparity may be due to the absence of standardized definitions for HbA1c variability. For instance, EI Malahi et al ( 29 ) demonstrated that GV [assessed by time in range (TIR)] was independently associated with the presence of composite microvascular complications, while it (assessed by TIR, SD, and CV) did not show a link with macrovascular complications. Thus, further research defining the standardized GV is required to elucidate these controversial results.…”
Section: Discussionmentioning
confidence: 99%
“…One of the possible explanations for such disparity may be due to the absence of standardized definitions for HbA1c variability. For instance, EI Malahi et al ( 29 ) demonstrated that GV [assessed by time in range (TIR)] was independently associated with the presence of composite microvascular complications, while it (assessed by TIR, SD, and CV) did not show a link with macrovascular complications. Thus, further research defining the standardized GV is required to elucidate these controversial results.…”
Section: Discussionmentioning
confidence: 99%
“…4 Our goal was to identify the metrics most closely correlated with HbA1c and Mean Glucose, based on the premise that metrics with the highest correlation with Mean Glucose would be associated with the long-term complications of diabetes. 8 Results for the T1D datasets are summarized in graphical representations showing the six correlations among the four metrics at baseline and after 6 months of use of real-time CGM (Figure 1A), [6][7][8][9][10][11] and correlations of the changes in each of the four metrics with changes in other metrics after 6 months of intervention with real-time CGM (Figure 1B). For CGM data obtained from people with T2D, where HbA1c values were not available, we examined correlations among Mean Glucose, %TAR and %TIR (Figure 1C).…”
Section: Methodsmentioning
confidence: 99%
“…Evidence indicating an association between glucose variability and an increased risk of microvascular and macrovascular complications of diabetes has been emerging. [33][34][35][36][37] Glucose variability is defined within the AGP report using the coefficient of variation of the standard deviation of mean glucose values (CV) and summarizes the glucose variability at a specific time between different days. 38 The target for CV is ≤36%, as the risk of hypoglycaemic events rises significantly above this value.…”
Section: : Investigating Time Below Rangementioning
confidence: 99%