ESPE Abstracts (2018) 89 P-P2-087

Translating the A1C Assay into Estimated Average Glucose Values in Children with Type 1 Diabetes Mellitus

Ahmed Mohamed Sayeda, Fawzia Alyafeia, Ashraf Solimana,b & Mona Algamala


aHamad Medical Center, Doha, Qatar; bUniversity of Alexandria, Alexandria, Egypt


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 3–5 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).

Table 1
AG (mg/dl)HbA1C %
804
904.45
1004.94
1205.93
1406.92
1607.9
1808.8
2009.8
24011.8
28013.8
30014.8

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.

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