title: Dynamical glucometry: use of multiscale entropy analysis in diabetes.
abstract: 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.affiliation: The Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, Massachusetts 02115, USA.
authors.forename: Madalena D
authors.initials: MD
authors.lastname: Costa
authors.affiliation: The Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, Massachusetts 02115, USA.
authors.forename: Teresa
authors.initials: T
authors.lastname: Henriques
authors.affiliation: Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02215, USA.
authors.forename: Medha N
authors.initials: MN
authors.lastname: Munshi
authors.affiliation: Joslin Diabetes Center, Boston, Massachusetts 02215, USA.
authors.forename: Alissa R
authors.initials: AR
authors.lastname: Segal
authors.affiliation: The Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, Massachusetts 02115, USA.
authors.forename: Ary L
authors.initials: AL
authors.lastname: Goldberger
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001786:Blood Glucose / Q000378:metabolism*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood*; D019277:Entropy; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D012189:Retrospective Studies
chemical_list: D001786:Blood Glucose