Document Detail


Dynamical glucometry: Use of multiscale entropy analysis in diabetes.
MedLine Citation:
PMID:  25273219     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
Diabetes mellitus (DM) is one of the world's most prevalent medical conditions. Contemporary management focuses on lowering mean blood glucose values toward a normal range, but largely ignores the dynamics of glucose fluctuations. We probed analyte time series obtained from continuous glucose monitor (CGM) sensors. We show that the fluctuations in CGM values sampled every 5 min are not uncorrelated noise. Next, using multiscale entropy analysis, we quantified the complexity of the temporal structure of the CGM time series from a group of elderly subjects with type 2 DM and age-matched controls. We further probed the structure of these CGM time series using detrended fluctuation analysis. Our findings indicate that the dynamics of glucose fluctuations from control subjects are more complex than those of subjects with type 2 DM over time scales ranging from about 5 min to 5 h. These findings support consideration of a new framework, dynamical glucometry, to guide mechanistic research and to help assess and compare therapeutic interventions, which should enhance complexity of glucose fluctuations and not just lower mean and variance of blood glucose levels.
Authors:
Madalena D Costa; Teresa Henriques; Medha N Munshi; Alissa R Segal; Ary L Goldberger
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Chaos (Woodbury, N.Y.)     Volume:  24     ISSN:  1089-7682     ISO Abbreviation:  Chaos     Publication Date:  2014 Sep 
Date Detail:
Created Date:  2014-10-02     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100971574     Medline TA:  Chaos     Country:  United States    
Other Details:
Languages:  eng     Pagination:  033139     Citation Subset:  IM    
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