Evaluation of continuous glucose monitoring-derived person-specific HbA1c in the presence and absence of complications in type 1 diabetes.

Journal: Diabetes, Obesity & Metabolism
Published:
Abstract

Objective: A recent novel kinetic model proposes an individual-specific relationship between glucose levels and HbA1c. The objectives of this study were to i) evaluate accuracy of this model at predicting HbA1c under real-world setting and ii) Understand the role of diabetes complications in altering glucose-HbA1c relationship and explore the mechanisms involved.

Methods: De-identified HbA1c and continuous glucose monitoring values were collected from 93 individuals with T1D. Person-specific kinetic parameters were used, including red blood cell (RBC) glucose uptake and lifespan, to characterize the relationship between glucose levels and HbA1c. The resulting calculated HbA1c (cHbA1c) was compared with glucose management indicator (GMI) for prospective agreement with laboratory HbA1c.

Results: The cohort (42/51 men/women) had a median age (IQR) of 61 (43, 72) years and diabetes duration of 21 (10, 33) years. A total of 24,459 days of continuous glucose monitoring (CGM) data were available and n=357 laboratory HbA1c were used to assess average glucose-HbA1c relationship. cHbA1c had a superior correlation with laboratory HbA1c compared with GMI with mean absolute deviation of 1.7 and 6.7 mmol/mol, r2 =0.85 and 0.44, respectively. The fraction within 10% of absolute relative deviation from laboratory HbA1c was 93% for cHbA1c and 63% for GMI. Macrovascular disease had no effect on model accuracy, whereas microvascular complications resulted in a trend towards higher HbA1c, secondary to increased RBC glucose uptake.

Conclusions: cHbA1c, which takes into account RBC glucose uptake and lifespan, accurately reflect laboratory HbA1c in a real-world setting and can aid in the management of individuals with diabetes. This article is protected by copyright. All rights reserved.

Authors
Yongjin Xu, Philippe Oriot, Timothy Dunn, Michel Hermans, Yashesvini Ram, Alan Cheng, Ramzi Ajjan
Relevant Conditions

Type 1 Diabetes (T1D), Obesity