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Beyond HbA1c, second take

It is topical to revisit the subject of glycemic outcomes beyond HbA1c, an area we continue to find fascinating. There can be no doubt that glycemia is related to the microvascular complications of diabetes, whether based on HbA1c, glucose levels, or even urine glucose measurement. The same relationship can be seen between glycemia and macrovascular disease, beginning below the glucose levels at which diabetes begins, whether based on fasting glucose or HbA1c levels. The issue of quantitating glycemic exposure, and whether HbA1c or fasting glucose or the combination of fasting and post-load glucose is more important, and whether one can use HbA1c to precisely determine average glucose is of some interest, and this has led us to strongly question the use of HbA1c to diagnose diabetes. Because HbA1c itself not only depends on erythrocyte exposure to a given mean level of glucose, but is also a measure integrating characteristics of the hemoglobin molecule, intraerythrocyte glycation and deglycation, and levels of erythropoiesis and erythrocyte destruction, it should come as no surprise that HbA1c does not consistently reflect mean glucose levels. Recent studies have tried to directly measure the proportion of variance in HbA1c explained by nonglycemic factors such as age, sex, body mass index, and ethnicity, showing this to be particularly prominent in people not having diabetes, so that Blacks with similar levels of prediabetes typically have HbA1c 0.4% higher than nonHispanic Whites, although such differences are not observed in glycated albumin or fructosamine. Because of these concerns, other approaches to measurement of glycemia have been sought in endeavoring to understand glycemic exposure. One such approach is the quantitation of glycemic variability. Using data from the Diabetes Control and Complications Trial, the time in range from 70 to 180 mg/dL tracks closely with both retinopathy and microalbuminuria development. Although time in range correlates strongly with HbA1c and mean glucose, in a given individual the two measures may differ greatly. A readily available measure of glycemic variability, the standard deviation of capillary glucose measurements during hospitalization following myocardial infarction, was recently shown to be a strong predictor of subsequent major adverse cardiovascular events, and mean glucose, HbA1c, and the glucose standard deviation all independently contribute to hypoglycemia frequency on continuous glucose monitoring (CGM). The CGM measure of time in hypoglycemia tracks with atherosclerotic cardiovascular complications, whereas the mean amplitude of glycemic excursions on CGM tracks with the development of neuropathy independent of HbA1c. Interestingly, when HbA1c variability over time is taken into account, many of the short-term measures of glycemic variability fail to significantly correlate with neuropathy. The standard deviation of HbA1c over time correlates with nephropathy, retinopathy, and cardiovascular events in people with type 1 diabetes, and with nephropathy, foot ulceration, and mortality in people with type 2 diabetes. The relationship between HbA1c variability and mortality is independent of mean HbA1c. A similar relationship was observed between mortality and the coefficient of variability of the fasting glucose in a population of people with diabetes. One hypothesis is that variability in HbA1c is a measure of adherence and, in comparing individuals with lower vs higher HbA1c standard deviation, the latter group generally has lower social class, as well as being on more complex diabetes treatment regimens. However, glycemic variability among people not having diabetes tracks with both mortality and cardiovascular disease (CVD), both for variability of fasting glucose and, for CVD, for variability of HbA1c, suggesting that simply attributing this relationship to different degrees of adherence to diabetes treatment cannot be the entire explanation. Indeed, Mendelian randomization analysis of HbA1c as a cardiovascular risk factor suggests that not only do genetic variants associated with different levels of glycemia have a strong correlation with cardiovascular disease, but so do variants associated with differences in erythrocyte iron stores and lifespans. A fascinating recent study suggests that it is not only glycemia, but also variability in lipids, blood pressure, and weight that is associated with adverse outcome. In a study of 6 748 773 people without diabetes, hypertension, or DOI: 10.1111/1753-0407.12910