Background/Aims: HbA1c is the gold standard parameter for diabetes monitoring and therapy adjustment. With the advent of continuous glucose monitoring system(CGMS), a near complete glucose profile could be obtained. We aimed to examine the relationship between HbA1c and the CGMS-derived mean blood glucose(MBG) in our population and to analyse possible factors that may influence this relationship. We also wanted to derive an equation that could relate these parameters.

Methods: We studied 87 type 2 diabetes subjects (45 males), mean age 57.4 ± 9.9 years with HbA1c between 6-13.5% longitudinally over a period of 12 weeks. The subjects wore a professional CGM over a period of 6 days intermittently on weeks 4, 8 and 12 of the study. The MBG was derived from these CGMS values and correlated with HbA1c on week 12. Subjects with anaemia or abnormal haemoglobin and eGFR < 60ml/min were excluded.

Results: The HbA1c at week 12 was highly correlated with MBG values at weeks 4, 8 and 12 separately and in total, cumulative r =0.73, p<0.01. The regression equation derived was MBG = (1.04 * HbA1c) + 1.06 (95% CI for slope: 1.03, 1.06). The regression equations do not significantly vary at different levels of control (between HbA1c < 8.5% and ≥ 8.5%; difference in slope: -0.22 ± 0.3, p= 0.56, difference in intercept:1.38 ± 3.21, p=0.66). There was no significant difference in the regression equations between gender, age, BMI, ethnicity, smoking status, type of therapy or duration of diabetes. Our study population was also found to glycosylate at a higher rate compared to other studies as 1 mmol/L elevation of mean glucose translates to an elevation of HbA1c by 1%.

Conclusion: The correlation is between HbA1c and CGM derived MBG is high. However, the regression equation appears unique to each population and different populations may glycosylate haemoglobin at different rates.

The authors have no conflict of interest.