Biomarkers in diabetes mellitus: contributions and discrepancies of new technologies. A case report

Florian Mialon, Bogdan Catargi, Lila Rami, Pascal Barat, Aurélie Bedel, Geneviève Lacape, Annie M. Bérard, Marie-Christine Beauvieux
Annales de Biologie Clinique. 2021-10-01; 79(5): 445-451
DOI: 10.1684/abc.2021.1680

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Article in French

Mialon F(1), Catargi B(2), Rami L(1), Barat P(3), Bedel A(4), Lacape G(5), Bérard AM(5), Beauvieux MC(6).

Author information:
(1)Service de biochimie, CHU de Bordeaux, France.
(2)Université de Bordeaux, France, Hôpital Saint-André, CHU de Bordeaux, France.
(3)Centre DiaBEA, Hôpital des Enfants, CHU de Bordeaux, France, UMR 1286 NutriNeuro, Université de Bordeaux, France.
(4)Service de biochimie, CHU de Bordeaux, France, Inserm U1035, Université de
Bordeaux, France.
(5)Service de biochimie, CHU de Bordeaux, France, Université de Bordeaux, France.
(6)Service de biochimie, CHU de Bordeaux, France, UMR5536, CNRS-Université de
Bordeaux, France.

Potential discrepancies between laboratory and estimated (from Continuous Glucose Monitoring (CGM)) glycated hemoglobin (HbA1c) have been reported by diabetologists. CGM devices produce an eA1c derived from average glucose and correlated with Time-in-Range (TIR, %) which is the relative time spent in a range of normal glycaemia. Through a case report, we studied the potential causes for these discrepancies. CGM devices estimate eA1c during the lifespan of the sensor, that is replaced every 14 days and HbA1c is a retrospective data of exposure to hyperglycemia over 8 to 12 weeks. In our case report, the patient had a poor glycemic control resulting in 9% eA1c compared to 7,4% HbA1c got by delocalized immune-assay (Siemens DCA-Vantage®), confirmed at 7,7% by HPLC (Variant II Turbo). On top of the CGM data, an increased labile A1c (LA1c) fraction was found on the patient’s HbA1c HPLC profile, both in favor of a recently altered glycemic control. Thus, recent and/or substantial variations in glycemic control will increase the gap between HbA1c and eA1c, being a potential source of therapeutic errors. The differences of those markers, particularly the time window during which it is estimated, make them hardly comparable. As the use of CGM is becoming widespread, it is important to understand and harness its data and biomarkers.


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