Evidence map›Paper›PMID 31595155›Full record

ArticleInternational journal of biological sciences2019

Analyzing Complexity and Fractality of Glucose Dynamics in a Pregnant Woman with Type 2 Diabetes under Treatment.

Xiaoyan Chen, Dandan Wang, Jinxiang Lin, Teng Zhang, Shunyou Deng, Lianyi Huang, Yu Jin, Chang Chen, Zhaozhi Zhang, Jun Zheng and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 87% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 5 institutions in 3 countries.

Xiaoyan ChenDepartment of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China.
Dandan WangFaculty of Health Sciences, University of Macau, Taipa 999078, Macau.
Jinxiang LinDepartment of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China.
Teng ZhangFaculty of Health Sciences, University of Macau, Taipa 999078, Macau.
Shunyou DengDepartment of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China.
Lianyi HuangDepartment of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China.
Yu JinFaculty of Health Sciences, University of Macau, Taipa 999078, Macau.
Chang ChenFaculty of Health Sciences, University of Macau, Taipa 999078, Macau.
Zhaozhi ZhangDepartment of Statistical Science, Duke University, Durham, NC 27708, USA.
Jun ZhengFaculty of Health Sciences, University of Macau, Taipa 999078, Macau.
Baoqing SunDepartment 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.
Paul BogdanDepartment of Electrical Engineering - Systems, University of Southern California, CA 90089, USA.
Xiaohua Douglas ZhangFaculty of Health Sciences, University of Macau, Taipa 999078, Macau.
University of Macau · MOFirst Affiliated Hospital of Guangzhou Medical University · CNDuke University · USEngineering Systems (United States) · USGuangzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AdultBlood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 2FemaleHumansModels, TheoreticalPregnancyBlood GlucoseComplexity analysisContinuous glucose monitoringFractal analysisMultiscale sample entropyType 2 diabetes with pregnancy

Identifiers

PMID31595155
PMCPMC6775315
OpenAlexW2976743738

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.