학술논문

Assessment of the relationship between glucose and A1c using kinetic modeling
Document Type
Clinical report
Source
Journal of Diabetes and Its Complications. Sept-Oct, 2006, Vol. 20 Issue 5, p285, 10 p.
Subject
Glycosylated hemoglobin -- Models
Glycosylated hemoglobin -- Analysis
Blood sugar -- Models
Blood sugar -- Analysis
Language
English
ISSN
1056-8727
Abstract
To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jdiacomp.2005.07.009 Byline: Siv M. Osterman-Golkar (a), Hubert W. Vesper (b) Keywords: Glycated hemoglobin; HbA1c; Glucose; Mathematical modeling Abstract: Treatment goals for diabetic patients are directed towards lowering A1c values by controlling blood glucose concentrations (BGC), making it important to understand the relationship between the two parameters. Because findings from clinical trials about the relationship between BGC and A1c values show a profound variability around the obtained regression lines, they are difficult to apply to individual patients. Therefore, a model was developed and applied based on the kinetics of HbA1c formation and removal. It takes the instability of A1c and loss of hemoglobin into consideration. Data from clinical studies and hypothetical scenarios were used to test the model and to describe the relationship between A1c and BGC. A close agreement between experimental and calculated data was obtained in steady-state and non-steady-state conditions. Aside the erythrocyte life span, the chemical instability of A1c appears to affect A1c levels markedly and their changes due to therapy. A threefold increase in BGC over 30 days prior to A1c measurement can cause an increase in A1c value of about 120% as compared with 4% when it occurs 4 months prior to A1c measurement. Profound daily fluctuations in BGC result in minor changes in A1c. In conclusion, A1c provides information about a patient's glycemia, mainly over the past 2 months, and may not reflect well daily blood glucose fluctuations. This model might be suitable to identify individual differences in glycation rates. Author Affiliation: (a) Department of Molecular Biology and Functional Genomics, Stockholm University, SE-106 91, Stockholm, Sweden (b) National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA Article History: Received 16 February 2005; Revised 6 July 2005; Accepted 13 July 2005