ISSN: 1449-2288International Journal of Biological Sciences
Global reach, higher impact
Int J Biol Sci 2019; 15(11):2373-2380. doi:10.7150/ijbs.33825 This issue Cite
Research Paper
Analyzing Complexity and Fractality of Glucose Dynamics in a Pregnant Woman with Type 2 Diabetes under Treatment
1. Department of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China
2. Faculty of Health Sciences, University of Macau, Taipa 999078, Macau
3. Department of Statistical Science, Duke University, Durham, NC 27708, USA
4. Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Diseases, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China
5. Department of Electrical Engineering - Systems, University of Southern California, CA 90089, USA
*These two authors contributed equally to this work and should be regarded as Joint First Authors.
Abstract
Currently, the rapid development of continuous glucose monitoring (CGM) device brings new insights into the treatment of diabetic patients including those during pregnancy. Complexity and fractality have recently under fast development for extracting information embodied in glucose dynamics measured using CGM. Although scientists have investigated the difference of complexity in glucose dynamics between diabetes and non-diabetes in order to discover better approaches for diabetes care, no one has analyzed the complexity and fractality of glucose dynamics during the process of adopting CGM to successfully treat pregnant women with type 2 diabetes. Thus, we analyzed the complexity and fractality using power spectral density (PSD), multi-scale sample entropy (MSE) and multifractal detrended fluctuation analysis (MF-DFA) in a clinical case. Our results show that (i) there exists multifractal behavior in blood glucose dynamics; (ii) the alpha stable distribution fits to the glucose increment data better than the Gaussian distribution; and (iii) the “global” complexity indicated by multiscale entropy, spectrum exponent and Hurst exponent increase and the “local” complexity indicated by multifractal spectrum decrease after the successful therapy. Our results offer findings that may bring value to health care providers for managing glucose levels of pregnant women with type 2 diabetes as well as provide scientists a reference on applying complexity and fractality in the clinical practice of treating diabetes.
Keywords: Continuous glucose monitoring, Complexity analysis, Multiscale sample entropy, Fractal analysis, Type 2 diabetes with pregnancy
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