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Importance of the Hemoglobin Glycation Index for Risk of Cardiovascular and Microvascular Complications and Mortality in Individuals with Type 2 Diabetes (Endocrinol Metab 2024;39:732-47, Claudia Regina Lopes Cardoso et al.)

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Endocrinol Metab. 2024;39(6):973-974
Publication date (electronic) : 2024 December 23
doi : https://doi.org/10.3803/EnM.2024.603
Department of Internal Medicine, University Hospital Clementino Fraga Filho, School of Medicine, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
Corresponding author: Claudia Regina Lopes Cardoso. Department of Internal Medicine, University Hospital Clementino Fraga Filho, School of Medicine, Federal University of Rio de Janeiro, Rua Croton, 72 Jacarepagua, Rio de Janeiro 22750-240, Brazil Tel: +55-21-98465-5853, Fax: +55-21-39838-2514, E-mail: claudiacardoso@hucff.ufrj.br
Received 2024 November 24; Accepted 2024 December 4.

We appreciate Dr. Chalew’s interest in our recently published study [1]. In this long-term prospective cohort study of 687 individuals with type 2 diabetes, we demonstrated that neither baseline nor mean first-year hemoglobin glycation index (HGI) and its variability were superior to their respective hemoglobin A1c (HbA1c) parameters as predictors of macro- and microvascular complications, all-cause mortality, and severe hypoglycemia occurrence [1]. Additionally, our findings showed no differences in the overall predictive performance of each model, as assessed by the C-statistic, and no differences in risk prediction across any of the evaluated subgroups in interaction/subgroup analyses [1]. These results suggest that no HGI parameter clearly outperforms its corresponding HbA1c parameter in predicting any adverse outcomes. This conclusion aligns with most previous studies and meta-analyses in type 2 diabetes [2-6]. Therefore, given the complexity of obtaining the HGI and its lack of additional predictive benefit over HbA1c, we do not currently recommend its clinical use in managing type 2 diabetes.

However, as originally proposed as a measure of the so-called glycation gap, the HGI involves calculating the predicted HbA1c based on the regression between HbA1c and its respective fasting plasma glucose (FPG), not mean blood glucose (MBG). Hence, although true inter-individual differences in glycation rates may exist (for example, between African descendants and Caucasians), most variations in the HGI among individuals likely stem from significant glycemic fluctuations, particularly postprandial, which FPG does not capture, rather than actual discrepancies between HbA1c and MBG [7]. Dr. Chalew suggests that using MBG, which is derived from continuous glucose monitoring, could improve the predictive accuracy of the HGI—especially in type 1 diabetes—and improve individual care. However, in the Diabetes Control and Complications Trial (DCCT) involving type 1 diabetes, the HGI calculated with MBG (obtained from a 7-point self-monitoring blood glucose profile at each 3-month interval) did not emerge as an independent risk marker for microvascular complications, and the influence of HGI on risk was entirely accounted for by associated HbA1c levels [8]. Whether continuous blood glucose monitoring will alter this outcome remains uncertain, pending future prospective studies. Until such data are available, we maintain that HGI should not currently be recommended as an alternative or additional glycemic metric to mean HbA1c levels and its variability in the clinical management of type 2 diabetes, particularly as a risk marker for diabetes-related complications. Nevertheless, we agree that it should not yet be dismissed as a potential research tool.

Notes

CONFLICTS OF INTEREST

No potential conflict of interest relevant to this article was reported.

References

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