Document Detail


Is glycemic variability important to assessing antidiabetes therapies?
MedLine Citation:
PMID:  17076995     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Traditionally, statistical estimation of glycemic variability includes computing standard deviation of glucose readings or related statistics (eg, M value, mean amplitude of glucose excursions, and so forth). We advocate an alternative approach using risk measures of variability, which have substantial clinical and numerical advantages. In addition, continuous glucose monitoring (CGM) data have clinically important inherent temporal structure that should be taken into consideration. Thus, temporal variability methods are discussed for the analysis and interpretation of CGM output.
Authors:
Boris P Kovatchev
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Review    
Journal Detail:
Title:  Current diabetes reports     Volume:  6     ISSN:  1534-4827     ISO Abbreviation:  Curr. Diab. Rep.     Publication Date:  2006 Nov 
Date Detail:
Created Date:  2006-11-01     Completed Date:  2007-02-26     Revised Date:  2007-12-03    
Medline Journal Info:
Nlm Unique ID:  101093791     Medline TA:  Curr Diab Rep     Country:  United States    
Other Details:
Languages:  eng     Pagination:  350-6     Citation Subset:  IM    
Affiliation:
University of Virginia Health System, Box 800137, Charlottesville, VA 22908, USA. boris@virginia.edu
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MeSH Terms
Descriptor/Qualifier:
Blood Glucose / analysis*
Diabetes Mellitus / blood,  drug therapy*
Humans
Hyperglycemia / blood
Hypoglycemia / blood
Hypoglycemic Agents / therapeutic use*
Grant Support
ID/Acronym/Agency:
R01 DK 51562/DK/NIDDK NIH HHS
Chemical
Reg. No./Substance:
0/Blood Glucose; 0/Hypoglycemic Agents

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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