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Methods Inf Med 2008; 47(04): 346-355
DOI: 10.3414/ME0468
Original Article
Schattauer GmbH

HbA1c Values Calculated from Blood Glucose Levels Using Truncated Fourier Series and Implementation in Standard SQL Database Language

W. Temsch
1   Section of Medical Information and Retrieval Systems, Core Unit for Medical Statistics and Informatics, Medical University of Vienna, Vienna, Austria
,
A. Luger
2   Division of Endocrinology and Metabolism, General Hospital of Vienna, Vienna, Austria
,
M. Riedl
3   Department of Medicine III, General Hospital of Vienna, Vienna, Austria
› Author Affiliations
Further Information

Publication History

Received: 04 December 2006

Accepted: 17 December 2007

Publication Date:
18 January 2018 (online)

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Summary

Objectives: This article presents a mathematical model to calculate HbA1c values based on self-measured blood glucose and past HbA1c levels, there by enabling patients to monitor diabetes therapy between scheduled checkups. This method could help physicians to make treatment decisions if implemented in a system where glucose data are transferred to a remote server. The method, however, cannot replace HbA1c measurements; past HbA1c values are needed to gauge the method.

Methods: The mathematical model of HbA1c formation was developed based on biochemical principles. Unlike an existing HbA1c formula [1], the new model respects the decreasing contribution of older glucose levels to current HbA1c values. About 12 standard SQL statements embedded in a php program were used to per-form Fourier transform. Regression analysis was used to gauge results with previous HbA1c values. The method can be readily implemented in any SQL database. Results: The predicted HbA1c values thus obtained were in accordance with measured values. They also matched the results of the HbA1c formula in the elevated range. By contrast, the formula was too “optimistic” in the range of better glycemic control. Individual analysis of two subjects improvedthe accuracy of values and reflected the bias introduced by different glucometers and individual measurement habits.

Keywords

Diabetes mellitus - glycosylated hemoglobin A - Fourier analysis - SQL database - regression analysis
 

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