Literature DB >> 22304838

The lack of long-range negative correlations in glucose dynamics is associated with worse glucose control in patients with diabetes mellitus.

Hitomi Ogata1, Kumpei Tokuyama, Shoichiro Nagasaka, Takeshi Tsuchita, Ikuyo Kusaka, Shun Ishibashi, Hiroaki Suzuki, Nobuhiro Yamada, Kumiko Hamano, Ken Kiyono, Zbigniew R Struzik, Yoshiharu Yamamoto.   

Abstract

Glucose dynamics measured in ambulatory settings are fluid in nature and exhibit substantial complexity. We recently showed that a long-range negative correlation of glucose dynamics, which is considered to reflect blood glucose controllability over a substantial period, is absent in patients with diabetes mellitus. This was demonstrated using detrended fluctuation analysis (DFA), a modified random-walk analysis method for the detection of long-range correlations. In the present study, we further assessed the relationships between the established clinical indices of glycemic or insulinogenic control of hemoglobin A(1c) (HbA(1c)), glycated albumin (GA), 1,5-anhydroglucitol, and urine C-peptide immunoreactivity and the recently proposed DFA-based indices obtained from continuous glucose monitoring in 104 Japanese diabetic patients. Significant correlations between the following parameters were observed: (1) HbA(1c) and the long-range scaling exponent α(2) (r = 0.236, P < .05), (2) GA and α(2) (r = 0.254, P < .05), (3) GA and the short-range scaling exponent α(1) (r = 0.233, P < .05), and (4) urine C-peptide immunoreactivity and the mean glucose fluctuations (r = -0.294, P < .01). Therefore, we concluded that increases in the long-range DFA scaling exponent, which are indicative of the lack of a long-range negative correlation in glucose dynamics, reflected abnormalities in average glycemic control as clinically determined using HbA(1c) and GA parameters.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22304838     DOI: 10.1016/j.metabol.2011.12.007

Source DB:  PubMed          Journal:  Metabolism        ISSN: 0026-0495            Impact factor:   8.694


  13 in total

1.  Response to "Comment on 'Dynamical glucometry: Use of multiscale entropy analysis in diabetes'" [Chaos 25, 058101 (2015)].

Authors:  Madalena D Costa; Ary L Goldberger
Journal:  Chaos       Date:  2015-05       Impact factor: 3.642

2.  Dynamical glucometry: use of multiscale entropy analysis in diabetes.

Authors:  Madalena D Costa; Teresa Henriques; Medha N Munshi; Alissa R Segal; Ary L Goldberger
Journal:  Chaos       Date:  2014-09       Impact factor: 3.642

3.  Associations of blood glucose dynamics with antihyperglycemic treatment and glycemic variability in type 1 and type 2 diabetes.

Authors:  K-D Kohnert; P Heinke; L Vogt; P Augstein; A Thomas; E Salzsieder
Journal:  J Endocrinol Invest       Date:  2017-05-08       Impact factor: 4.256

Review 4.  Glycemic variability in hospitalized patients: choosing metrics while awaiting the evidence.

Authors:  Susan S Braithwaite
Journal:  Curr Diab Rep       Date:  2013-02       Impact factor: 4.810

5.  Applications of Variability Analysis Techniques for Continuous Glucose Monitoring Derived Time Series in Diabetic Patients.

Authors:  Klaus-Dieter Kohnert; Peter Heinke; Lutz Vogt; Petra Augstein; Eckhard Salzsieder
Journal:  Front Physiol       Date:  2018-09-06       Impact factor: 4.566

6.  Detrended Fluctuation Analysis in the prediction of type 2 diabetes mellitus in patients at risk: Model optimization and comparison with other metrics.

Authors:  Ana Colás; Luis Vigil; Borja Vargas; David Cuesta-Frau; Manuel Varela
Journal:  PLoS One       Date:  2019-12-18       Impact factor: 3.240

7.  Glycemic variability is complex--is glucose complexity variable?

Authors:  Roosmarijn T M van Hooijdonk; Ameen Abu-Hanna; Marcus J Schultz
Journal:  Crit Care       Date:  2012-11-21       Impact factor: 9.097

8.  Delay in the Detrended Fluctuation Analysis Crossover Point as a Risk Factor for Type 2 Diabetes Mellitus.

Authors:  Manuel Varela; Luis Vigil; Carmen Rodriguez; Borja Vargas; Rafael García-Carretero
Journal:  J Diabetes Res       Date:  2016-05-16       Impact factor: 4.011

9.  Glucose time series complexity as a predictor of type 2 diabetes.

Authors:  Carmen Rodríguez de Castro; Luis Vigil; Borja Vargas; Emilio García Delgado; Rafael García Carretero; Julián Ruiz-Galiana; Manuel Varela
Journal:  Diabetes Metab Res Rev       Date:  2016-06-30       Impact factor: 4.876

10.  Declining ß-cell function is associated with the lack of long-range negative correlation in glucose dynamics and increased glycemic variability: A retrospective analysis in patients with type 2 diabetes.

Authors:  Klaus-Dieter Kohnert; Peter Heinke; Lutz Vogt; Petra Augstein; Eckhard Salzsieder
Journal:  J Clin Transl Endocrinol       Date:  2014-10-16
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