8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      HbA1c: a review of non-glycaemic variables

      , ,
      Journal of Clinical Pathology
      BMJ

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Identification of the correlation between HbA1c and diabetic complications has yielded one of the most clinically useful biomarkers. HbA1c has revolutionised the diagnosis and monitoring of diabetes mellitus. However, with widespread adoption of HbA1c has come increasing recognition that non-glycaemic variables can also affect HbA1c, with varying clinical significance. Furthermore, the identification of a discrepancy between predicted and measured HbA1c in some individuals, the so-called ‘glycation gap’, may be clinically significant. We aimed to review the current body of evidence relating to non-glycaemic variables to quantify any significance and provide subsequent suggestions. A PubMed-based literature search was performed, using a variety of search terms, to retrieve articles detailing the non-glycaemic variables suggested to affect HbA1c. Articles were reviewed to assess the relevance of any findings in clinical practice and where possible guidance is given. A range of non-glycaemic variables have statistically significant effects on HbA1c. While the clinical implications are generally irrelevant, a small number of non-glycaemic variables do have clinically significant effects and alternative biomarkers should be considered instead of, or in addition to, HbA1c. There are a small number of non-glycaemic variables which have a clinically significant effect on HbA1c, However, the vast majority of non-glycaemic variables have no clinical relevance. While clinicians should have an awareness of those non-glycaemic variables with clinical significance, in the vast majority of clinical scenarios HbA1c should continue to be used with confidence.

          Related collections

          Most cited references65

          • Record: found
          • Abstract: found
          • Article: not found

          Red cell life span heterogeneity in hematologically normal people is sufficient to alter HbA1c.

          Although red blood cell (RBC) life span is a known determinant of percentage hemoglobin A1c (HbA1c), its variation has been considered insufficient to affect clinical decisions in hematologically normal persons. However, an unexplained discordance between HbA1c and other measures of glycemic control can be observed that could be, in part, the result of differences in RBC life span. To explore the hypothesis that variation in RBC life span could alter measured HbA1c sufficiently to explain some of this discordance, we determined RBC life span using a biotin label in 6 people with diabetes and 6 nondiabetic controls. Mean RBC age was calculated from the RBC survival curve for all circulating RBCs and for labeled RBCs at multiple time points as they aged. In addition, HbA1c in magnetically isolated labeled RBCs and in isolated transferrin receptor-positivereticulocytes was used to determine the in vivo synthetic rate of HbA1c. The mean age of circulating RBCs ranged from 39 to 56 days in diabetic subjects and 38 to 60 days in nondiabetic controls. HbA1c synthesis was linear and correlated with mean whole blood HbA1c (R(2) = 0.91). The observed variation in RBC survival was large enough to cause clinically important differences in HbA1c for a given mean blood glucose.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Effect of Aging on A1C Levels in Individuals Without Diabetes

            OBJECTIVE—Although glycemic levels are known to rise with normal aging, the nondiabetic A1C range is not age specific. We examined whether A1C was associated with age in nondiabetic subjects and in subjects with normal glucose tolerance (NGT) in two population-based cohorts. RESEARCH DESIGN AND METHODS—We performed cross-sectional analyses of A1C across age categories in 2,473 nondiabetic participants of the Framingham Offspring Study (FOS) and in 3,270 nondiabetic participants from the National Health and Nutrition Examination Survey (NHANES) 2001–2004. In FOS, we examined A1C by age in a subset with NGT, i.e., after excluding those with impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT). Multivariate analyses were performed, adjusting for sex, BMI, fasting glucose, and 2-h postload glucose values. RESULTS—In the FOS and NHANES cohorts, A1C levels were positively associated with age in nondiabetic subjects. Linear regression revealed 0.014- and 0.010-unit increases in A1C per year in the nondiabetic FOS and NHANES populations, respectively. The 97.5th percentiles for A1C were 6.0% and 5.6% for nondiabetic individuals aged <40 years in FOS and NHANES, respectively, compared with 6.6% and 6.2% for individuals aged ≥70 years (P trend < 0.001). The association of A1C with age was similar when restricted to the subset of FOS subjects with NGT and after adjustments for sex, BMI, fasting glucose, and 2-h postload glucose values. CONCLUSIONS—A1C levels are positively associated with age in nondiabetic populations even after exclusion of subjects with IFG and/or IGT. Further studies are needed to determine whether age-specific diagnostic and treatment criteria would be appropriate.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Racial Differences in the Relationship of Glucose Concentrations and Hemoglobin A1c Levels.

              Debate exists as to whether the higher hemoglobin A1c (HbA1c) levels observed in black persons than in white persons are due to worse glycemic control or racial differences in the glycation of hemoglobin.
                Bookmark

                Author and article information

                Journal
                Journal of Clinical Pathology
                J Clin Pathol
                BMJ
                0021-9746
                1472-4146
                December 13 2018
                January 2019
                January 2019
                October 25 2018
                : 72
                : 1
                : 12-19
                Article
                10.1136/jclinpath-2017-204755
                30361394
                d7ffee7e-dc98-481f-bd26-85a87b61f6e4
                © 2018
                History

                Comments

                Comment on this article