Objective: The A1C assay, expressed as the percent of hemoglobin that is glycated, measures chronic glycemia and is widely used to judge the adequacy of diabetes treatment and adjust therapy. Day-to-day management is guided by self-monitoring of capillary glucose concentrations (milligrams per deciliter or millimoles per liter) as well as by using continuous glucose monitoring systems (CGMS). We found a mathematical relationship between A1C and average glucose (AG) levels measured by CGMS over 5 days and determined the correlation between the variable CGMS parameters and HbA1c in 50 children with type 1 diabetes mellitus (DM-1) on MDI therapy.
Research design and methods: A total of 50 diabetic children randomly selected from a cohort of children with DM-1 were included in the analyses. A1C levels obtained at the end of 3 months and measured in a central laboratory were compared with the AG levels during the previous 5 days recorded by CGMS. AG was calculated by combining weighted results from 5 days of continuous glucose monitoring performed before measuring HbA1C, with 35 point daily self-monitoring of capillary (fingerstick) glucose.
Results: Linear regression analysis between the A1C and AG values provided the tightest correlations HbA1c=0.0494 MG- 2E-14, R2=0.90, P<0.0001), allowing calculation of an estimated average glucose (eAG) for A1C values (Table 1).
|AG (mg/dl)||HbA1C %|
Conclusion: Our study showed a linear relationship between A1C and AG values measured by CGMS for 5 days before HbA1c measurement. The AG can be easily calculated using a formula derived from linear regression analysis of HbA1c data obtained in our diabetic children. The proper use of CGMS enables monitoring glucose variability and can help controlling glucose fluctuations.
27 - 29 Sep 2018
European Society for Paediatric Endocrinology