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Glucose management indicator – potential factors affecting differences in comparison with HbA1c and clinical significance of this phenomenon

HbA1c and the glucose management indicator (GMI) are now widely recognized as the gold standard for assessing the effectiveness of diabetes therapy. The GMI is a result of a mathematical formula used to estimate HbA1c with continuous glucose monitoring (CGM) data in patients with diabetes. It is a u...

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Detalles Bibliográficos
Autores principales: Wybrańczyk, Łukasz, Brudzińska, Aleksandra, Jarosz-Chobot, Przemysława, Deja, Grażyna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Termedia Publishing House 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10679910/
http://dx.doi.org/10.5114/pedm.2023.130028
Descripción
Sumario:HbA1c and the glucose management indicator (GMI) are now widely recognized as the gold standard for assessing the effectiveness of diabetes therapy. The GMI is a result of a mathematical formula used to estimate HbA1c with continuous glucose monitoring (CGM) data in patients with diabetes. It is a useful parameter providing a good estimate of CGM metrics for a 3-month period with just 10–14 days of data. It can reflect the effectiveness of administered/modified therapy of insulin faster than traditional measurements of laboratory HbA1c and can be used as an educational tool and in telemedicine. Unfortunately, there are significant discordances between GMI and laboratory-measured HbA1c, reaching as much as 0.5–1% in many patients. It may be caused by well-known factors influencing HbA1c measurement and red blood cell turnover like anaemia, haemoglobinopathies, or certain medications, but these causes of potential errors are too rare in everyday practice to account for the amount of discrepancy reported in the literature. In this article we would like to review other new potential factors that may influence HbA1c estimation based on GMI and cause potential differences between results calculated from CGM and those measured in the laboratory. In addition, we will present clinical implications of the observed differences between GMI and HbA1c. Recognizing the factors that cause such differences is an important clinical skill. Moreover, understanding the principles of evaluating paired measures of these parameters will allow us to individualize the treatment of each person with diabetes.