The ratio of glycated albumin to hemoglobin A1c measured in IFCC units accurately represents the glycation gap

Potential Clinical Error Arising From Use of HbA1c in Diabetes: Effects of the Glycation Gap

The glycation gap (GGap) and the similar hemoglobin glycation index (HGI) define consistent differences between glycated hemoglobin and actual glycemia derived from fructosamine or mean blood glucose, respectively. Such a disparity may be found in a substantial proportion of people with diabetes, being >1 U of glycated HbA1c% or 7.2 mmol/mol in almost 40% of estimations. In this review we define these indices and explain how they can be calculated and that they are not spurious, being consistent in individuals over time. We evaluate the evidence that GGap and HGI are associated with variation in risk of complications and mortality and demonstrate the potential for clinical error in the unquestioning use of HbA1c. We explore the underlying etiology of the variation of HbA1c from mean glucose in blood plasma, including the potential role of enzymatic deglycation of hemoglobin by fructosamine-3-kinase. We conclude that measurement of GGap and HGI are important to diabetes clinicians and their patients in individualization of therapy and the avoidance of harm arising from consequent inappropriate assessment of glycemia and use of therapies.

Estimation of glycaemic control in the past month using ratio of glycated albumin to HbA1c

AIMS

To evaluate comprehensively the use of the glycated albumin to HbA_1c ratio for estimation of glycaemic control in the previous month.

METHODS

A total of 306 children with Type 1 diabetes mellitus underwent ≥10 simultaneous measurements of glycated albumin and HbA_1c . Correlation and concordance rates were examined between HbA_1c measurements taken 1 month apart (ΔHbA_1c ) and glycated albumin/HbA_1c ratio fluctuations were calculated as Z-scores from the cohort value at enrolment of this study cohort (method A) or the percent difference from the individual mean over time (method B).

RESULTS

Fluctuations in glycated albumin/HbA_1c ratio (using both methods) were weakly but significantly correlated with ΔHbA_1c , whereas concordance rates were significant for glycaemic deterioration but not for glycaemic improvement. Concordance rates were higher using method B than method A.

CONCLUSIONS

The glycated albumin/HbA_1c ratio was able to estimate glycaemic deterioration in the previous month, while estimation of glycaemic improvement in the preceding month was limited. Because method B provided a better estimate of recent glycaemic control than method A, the individual mean of several measurements of the glycated albumin/HbA_1c ratio over time may also identify individuals with high or low haemoglobin glycation phenotypes in a given population, such as Japanese children with Type 1 diabetes, thereby allowing more effective diabetes management.

Discordance in the levels of hemoglobin A1C and glycated albumin: Calculation of the glycation gap based on glycated albumin level

OBJECTIVE

The glycation gap (G-gap) is an empirical measure of the extent of the difference between HbA1C and fructosamine levels. Several studies have shown that the presence of a G-gap is linked to diabetic nephropathy, but possible artifacts caused by dependence of the fructosamine level on the extent of serum protein metabolism require careful consideration. We investigated the consistency of G-gaps measured by assaying glycated albumin (GA) levels to identify factors associated with G-gap variations.

METHOD

A total of 457 pairs of observations, like an HbA1c and GA measurement at the same clinic visit, were obtained from 170 Korean patients with type 2 diabetes. HbA1c and GA levels were measured simultaneously in two or three separate occasions. Each G-gap was calculated as the difference between the measured HbA1c level and that predicted by the GA level. All patients underwent abdominal computed tomography, and the areas of subcutaneous and visceral fat were measured.

RESULTS

The G-gaps were all significantly inter-correlated over time (γ=0.755, P<0.001).The direction of each G-gap was consistent. The body mass index (BMI), visceral fat area, and the estimated glomerular filtration rate (eGFR) increased linearly from the lowest to the highest G-gap quartile (all P values <0.05). Upon multivariate analysis, both visceral fat area and the eGFR were significantly associated with a G-gap.

CONCLUSIONS

A G-gap determined using GA measurements is consistent within an individual over time. The G-gap is associated with visceral fat and kidney function in patients with type 2 diabetes.