Relationship between glycaemic variability and hyperglycaemic clamp-derived functional variables in (impending) type
Annelien Van Dalem1, Simke Demeester1, Eric V Balti1
1Diabetes Research Center, Vrije Universiteit Brussel, Laarbeeklaan 100, 1090, Brussels, Belgium.
Diabetologia
|September 28, 2015
Summary
Continuous glucose monitoring (CGM) and glucose disposal rate better detect type 1 diabetes progression than traditional measures. These findings support developing CGM-based criteria for monitoring and clinical trials.
Area of Science:
- Endocrinology
- Metabolic Disease Research
- Diabetes Pathophysiology
Background:
- Type 1 diabetes (T1D) progression from preclinical stages involves complex changes in beta cell function and insulin action.
- Continuous glucose monitoring (CGM) and self-monitoring of blood glucose (SMBG) provide data on glycemic variability (GV).
- Identifying reliable markers for early detection of T1D development is crucial for intervention.
Purpose of the Study:
- To evaluate if glycemic variability (GV) measures from CGM and SMBG can substitute or enhance traditional markers of beta cell function and insulin action.
- To assess the utility of GV in detecting the transition from preclinical stages to type 1 diabetes.
- To compare the diagnostic efficiency of different glycemic monitoring methods in high-risk individuals.
Main Methods:
- Twenty-two autoantibody-positive first-degree relatives (FDRs) at high risk for T1D underwent CGM, hyperglycaemic clamp tests, and oral glucose tolerance tests (OGTT).
- Beta cell function was assessed via C-peptide release (AUC5-10 min and AUC120-150 min) during clamp tests.
- Insulin resistance was measured by glucose disposal rate (M 120-150 min); GV was analyzed from CGM and SMBG data.
Main Results:
- The glucose disposal rate (M 120-150 min) below the 10th percentile of controls showed 86% efficiency in distinguishing normoglycemic FDRs from those with dysglycemia.
- CGM-derived GV measures demonstrated higher efficiency (77-82%) in detecting dysglycemia compared to SMBG (73%).
- Combined CGM measures and the glucose disposal rate exhibited equal diagnostic efficiency (86%), outperforming C-peptide measures (59-68%).
Conclusions:
- CGM-derived GV and glucose disposal rate are superior to SMBG and C-peptide AUC measures in identifying individuals with impending dysglycemia or type 1 diabetes.
- These findings suggest the potential for developing minimally invasive, CGM-based monitoring criteria.
- CGM-based metrics could serve as valuable outcome measures in clinical trials for type 1 diabetes progression.
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