In 2002, Hempe et al. introduced the concept of the haemoglobin glycation index (HGI) in response to the fact that HbA1c is not necessarily correlated with mean blood glucose (MBG),… Click to show full abstract
In 2002, Hempe et al. introduced the concept of the haemoglobin glycation index (HGI) in response to the fact that HbA1c is not necessarily correlated with mean blood glucose (MBG), especially in patients with type 1 diabetes. Even if there is a significant linear correlation between MBG and HbA1c, there is also a large variability of HbA1c. To overcome this problem, Hempe et al. proposed the calculation of the haemoglobin glycation index (HGI1⁄4 observed HbA1c – predicted HbA1c), which quantifies the magnitude and direction of the difference between each patient’s set of observed and predicted HbA1c results. In the 1441 Diabetes Control and Complications Trial (DCCT) participants, HGI was calculated for each visit to assess biological variation based on the directional deviation of observed HbA1c from that predicted by MBG in the model. The population was subdivided by tertiles (high, moderate and low HGI groups) based on participants’ mean HGI during the study. At seven years of follow-up, patients in the high HGI group (‘higher-than-predicted HbA1c’) had three times greater risk of retinopathy (30% vs. 9%, p< 0.001) and six times greater risk of nephropathy (6% vs. 1%, p< 0.001) compared with the low HGI group. The authors suggested that HbA1c levels could reflect both differences in blood glucose levels over time and the individual effects of additional biological factors that influence non-enzymatic protein glycation; if so, they hypothesized that HGI identifies a phenotype of glucose metabolism characterized by individual differences in susceptibility to haemoglobin glycation. Thus the existence of high and low haemoglobin glycation phenotypes could help explain why some individuals with apparently poor control escape complications while others with apparently good control develop severe complications. Finally they proposed that HGI should be considered as a marker of inherent risk for developing diabetes complications and advocated for using it as a clinical tool to identify highrisk diabetic patients. More recently, since the results of the ACCORD trial have been published and further reanalysed, Hempe et al. have shown that HGI was able to identify subpopulations of type 2 diabetic patients who benefited or not from intensive treatment. For the record, ACCORD was a randomized trial of more than 10,000 patients with type 2 diabetes assigned to standard or intensive treatment with HbA1c goals of 7% to 7.9% or less than 6%, respectively. ACCORD participants were middle-aged and older people with type 2 diabetes and established cardiovascular disease or known cardiovascular risk factors. Intensive treatment failed to improve primary cardiovascular outcomes and was associated with 22% greater total mortality compared with standard treatment. Severe hypoglycaemia was associated with an increased risk of death in both groups but differences in HbA1c or rates of hypoglycaemia between groups failed to explain the greater mortality in the intensive group. In order to compute HGI, a linear regression equation was derived from 1000 patients randomly extracted from ACCORD at inclusion. Baseline fasting plasma glucose (FPG) values were used to calculate predicted HbA1c and HGI for the whole study population. The results showed that subjects with high HGIs at baseline had more retinopathy and nephropathy as previously reported in the DCCT trial. Further analyses demonstrated that intensive treatment was associated with improved cardiovascular outcomes in the low (hazard ratio1⁄4 0.75; 95% confidence interval: 0.59–0.95) and moderate (hazard ratio1⁄4 0.77; 0.61–0.97) HGI subgroups but not in the high HGI subgroup (hazard ratio1⁄4 1.14; 0.93–1.40). Higher total mortality was confined to the high HGI subgroup in the intensively treated patients although a high HGI was confirmed to be associated with a greater risk for hypoglycaemia in both standard and intensive treatment groups. These results call for taking into account HGI besides
               
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