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Automated computation of glycemic index for foodstuffs using continuous glucose monitoring.
MedLine Citation:
PMID:  19885179     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
BACKGROUND: The glycemic index (GI) is a measure of the ability of a food to raise glucose levels after it is eaten. Continuous glucose monitoring (CGM) has been shown to give identical values of GI when compared to traditional methods. However, there has been no standardized protocol for measuring GI that takes into account interindividual variability and chronophysiological glycemic response to food. Our aim was (1) to create and describe software based on a Microsoft Excel 2000 spreadsheet to facilitate rapid, automated, accurate, and standardized processing of data obtained using recent CGM methodology to measure GI and its variability and (2) to assess the benefits of this new approach.
METHOD: Twenty healthy subjects consumed 50 grams of glucose or four alternative foodstuffs (chocolate, apple baby food, rice squares, or yogurt) at breakfast and dinner during 1 week, resulting in 300 CGMS glucose profiles; 92% of meal tests were satisfactory for evaluation. Application and functions of the software DegifXL are described.
RESULTS: Using the new spreadsheet software DegifXL, time required for data processing for the 15 data sets for each subject was reduced from 2000 to 160 minutes relative to previously used manual methods. We characterized the GI for four foodstuffs with three replicate measurements in each of 20 subjects and evaluated between person, between time period, and between replicate GI variabilities.
CONCLUSION: DegifXL, combined with CGM, was an efficient and effective tool for routine measurement of group- and subject-related GI.
Authors:
Rudolf Chlup; Pavel Seckar; Jana Zapletalová; Katerina Langová; Pavla Kudlová; Karolina Chlupová; Josef Bartek; Daniela Jelenová
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of diabetes science and technology     Volume:  2     ISSN:  1932-2968     ISO Abbreviation:  J Diabetes Sci Technol     Publication Date:  2008 Jan 
Date Detail:
Created Date:  2009-11-03     Completed Date:  2009-12-15     Revised Date:  2013-05-23    
Medline Journal Info:
Nlm Unique ID:  101306166     Medline TA:  J Diabetes Sci Technol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  67-75     Citation Subset:  -    
Affiliation:
Department of Physiology, Faculty of Medicine, Palacký University, Olomouc, Czech Republic. rudolf.chlup@fnol.cz
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