Exp Clin Endocrinol Diabetes 2000; Vol. 108(6): 406-413
DOI: 10.1055/s-2000-8137
Articles

© Johann Ambrosius Barth

Non-invasive blood glucose monitoring by means of near infrared spectroscopy: investigation of long-term accuracy and stability

A. Sämann 1 , Ch. Fischbacher 2 , K.-U. Jagemann 2 , K. Danzer 2 , J. Schüler 3 , L. Papenkordt 3 , U. A. Müller 1
  • 1 Department of Internal Medicine II, Medical School, Friedrich-Schiller-University, Jena, Germany 2 Institute of Inorganic and Analytical Chemistry, Friedrich-Schiller-University, Jena, Germany 3 independent research workers
Further Information

Publication History

Submitted December 8, 1999

Accepted in revised form June 20, 2000

Publication Date:
31 December 2000 (online)

Summary:

Modern strategies in the treatment of Diabetes mellitus require frequent blood glucose tests. Near-infrared spectroscopy [NIR] is considered to be a method for non-invasive blood glucose testing. The present study evaluated the long-term accuracy and stability of the method. Spectra of 10 patients were recorded. An individual calibration models were calculated for each patient from spectra which were recorded at the beginning of the investigation. These models were then applied to calculate blood glucose values from spectra which were recorded 84 to 169 days later. The long-term accuracy and stability of the calibration models expressed as root mean squared error of prediction [RMSP] varied from 3.1 to 35.9 mmol/l and the error grid analysis [EGA] from 13 to 92% clinically acceptable values in zones A and B. The results of the investigation indicate that long-term monitoring of blood glocose by means of NIR-spectroscopy and individual calibration models over a period of 3 to 4 months is basically possible once long-term stability of the method will be improved. Further technological progress and a better understanding of the underlying physiological processes is necessary to achieve a level of accuracy, reliability and stability of the method as required for clinical application.

Abbreviations: RMSP root mean squared error of prediction; EGA error grid analysis; LOO-CV leaving-one-out cross-validation

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Alexander Sämann

Klinik für Innere Medizin II

Friedrich-Schiller-Universität Jena

c/o U. A. Müller, MD, MSc

D-07740 Jena

Phone: +49-36 41-93 96 39

Fax: +49-36 41-93 96 49

Email: ua.mueller@med.uni-jena.de

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