Literature DB >> 29315360

CGManalyzer: an R package for analyzing continuous glucose monitoring studies.

Xiaohua Douglas Zhang1, Zhaozhi Zhang2, Dandan Wang1.   

Abstract

Summary: The R package CGManalyzer contains functions for analyzing data from a continuous glucose monitoring (CGM) study. It covers a wide and comprehensive range of data analysis methods including reading a series of datasets, obtaining summary statistics of glucose levels, plotting data, transforming the time stamp format, fixing missing values, evaluating the mean of daily difference and continuous overlapping net glycemic action, calculating multiscale sample entropy, conducting pairwise comparison, displaying results using various plots including a new type of plot called an antenna plot, etc. This package has been developed from our work in directly analyzing data from various CGM devices such as the FreeStyle Libre, Glutalor, Dexcom and Medtronic CGM. Thus, this package should greatly facilitate the analysis of various CGM studies. Availability and implementation: The package for Windows is available from CRAN: http://cran.r-project.org/mirrors.html. The source file CGManalyzer_1.0.tar.gz is available in the Supplementary Material and at the website of Zhang's lab https://quantitativelab.fhs.umac.mo/analytic-tool/. Contact: douglaszhang@umac.mo. Supplementary information: Supplementary data are available at Bioinformatics online.

Entities:  

Mesh:

Substances:

Year:  2018        PMID: 29315360     DOI: 10.1093/bioinformatics/btx826

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  12 in total

1.  Cgmquantify: Python and R Software Packages for Comprehensive Analysis of Interstitial Glucose and Glycemic Variability from Continuous Glucose Monitor Data.

Authors:  Brinnae Bent; Maria Henriquez; Jessilyn Dunn
Journal:  IEEE Open J Eng Med Biol       Date:  2021-08-18

2.  Evaluating perioperative glycemic status after different types of pancreatic surgeries via continuous glucose monitoring system: a pilot study.

Authors:  Yishen Mao; Xingfei Zhao; Lihui Zhou; Bin Lu; Chen Jin; Deliang Fu; Lie Yao; Ji Li
Journal:  Gland Surg       Date:  2021-10

3.  Non-invasive wearables for remote monitoring of HbA1c and glucose variability: proof of concept.

Authors:  Brinnae Bent; Peter J Cho; April Wittmann; Connie Thacker; Srikanth Muppidi; Michael Snyder; Matthew J Crowley; Mark Feinglos; Jessilyn P Dunn
Journal:  BMJ Open Diabetes Res Care       Date:  2021-06

4.  An Interactive Web Application for the Statistical Analysis of Continuous Glucose Monitoring Data in Epidemiological Studies.

Authors:  Alysha M De Livera; Jonathan E Shaw; Neale Cohen; Anne Reutens; Agus Salim
Journal:  J Diabetes Sci Technol       Date:  2021-01-12

5.  Introducing the Continuous Glucose Data Analysis (CGDA) R Package: An Intuitive Package to Analyze Continuous Glucose Monitoring Data.

Authors:  Ilias Attaye; Eduard W J van der Vossen; Diogo N Mendes Bastos; Max Nieuwdorp; Evgeni Levin
Journal:  J Diabetes Sci Technol       Date:  2022-01-19

6.  Classification of Sputum Sounds Using Artificial Neural Network and Wavelet Transform.

Authors:  Yan Shi; Guoliang Wang; Jinglong Niu; Qimin Zhang; Maolin Cai; Baoqing Sun; Dandan Wang; Mei Xue; Xiaohua Douglas Zhang
Journal:  Int J Biol Sci       Date:  2018-05-22       Impact factor: 6.580

7.  cgmanalysis: An R package for descriptive analysis of continuous glucose monitor data.

Authors:  Tim Vigers; Christine L Chan; Janet Snell-Bergeon; Petter Bjornstad; Philip S Zeitler; Gregory Forlenza; Laura Pyle
Journal:  PLoS One       Date:  2019-10-11       Impact factor: 3.240

8.  A comprehensive comparison and overview of R packages for calculating sample entropy.

Authors:  Chang Chen; Shixue Sun; Zhixin Cao; Yan Shi; Baoqing Sun; Xiaohua Douglas Zhang
Journal:  Biol Methods Protoc       Date:  2019-12-13

9.  An Improved Method of Handling Missing Values in the Analysis of Sample Entropy for Continuous Monitoring of Physiological Signals.

Authors:  Xinzheng Dong; Chang Chen; Qingshan Geng; Zhixin Cao; Xiaoyan Chen; Jinxiang Lin; Yu Jin; Zhaozhi Zhang; Yan Shi; Xiaohua Douglas Zhang
Journal:  Entropy (Basel)       Date:  2019-03-12       Impact factor: 2.524

10.  GLU: a software package for analysing continuously measured glucose levels in epidemiology.

Authors:  Louise A C Millard; Nashita Patel; Kate Tilling; Melanie Lewcock; Peter A Flach; Debbie A Lawlor
Journal:  Int J Epidemiol       Date:  2020-06-01       Impact factor: 7.196

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.