Application of a biokinetic model for prediction and assessment of glycated haemoglobins in diabetic patients

Abstract

An improved biokinetic model describing the haemoglobin A_1c ketoamine fraction (HbA_1c), and the haemoglobin A_1d aldimine fraction (HbA_1d), as a function of preceding blood glucose levels has been studied. The model requires knowledge of the chemical reaction rate constants and the life span of the erythrocytes. Calculated HbA_1c corresponding to constant blood glucose levels was about 6% lower than previously found using a simplified method of calculation. The predicted variations in the glycated haemoglobins in response to simulated variations in the glucose concentration were, however, similar to the improved and the simplified model calculations. Thus, HbA_1d reached a new steady state level within 24 h and HbA_1c within 4 weeks after sudden change in glucose concentration. When the blood glucose concentration was simulated by sine waves with periods from 2 to 60 days it was observed that the HbA_1d varied in parallel with the glucose concentration with a time delay of about 2 h, whereas the HbA_1c was almost constant with periods less than 7 days. Haemoglobin A_1c predicted from observed blood glucose levels in diabetic patients followed over several weeks varied in parallel with measured HbA_1c. However, the measured values were systematically higher than the calculated. This could be due to an underestimation of the daily mean blood glucose levels used for calculation of HbA_1c or to inaccurate estimates of the reaction rate constants. Based on the model it could be demonstrated that the HbA_1c fraction corresponds to an exponentially weighted average of daily mean blood glucose levels over the preceding 4 weeks. It was further shown that up to 30% reduction in the erythrocyte life span had no appreciable effect on the fraction of glycated haemoglobins. It is concluded that these results are of importance for interpretation of glycated haemoglobin levels in the assessment of diabetic control.

Key Words:

• biokinetic models
• blood glucose
• diabetes mellitus
• glycated haemoglobins