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

Continuous glucose monitors (CGM) record interstitial glucose levels ‘continuously’, producing a sequence of measurements for each participant (e.g. the average glucose level every 5 min over several days, both day and night). To analyse these data, researchers tend to derive summary variables such...

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Detalles Bibliográficos
Autores principales: Millard, Louise A C, Patel, Nashita, Tilling, Kate, Lewcock, Melanie, Flach, Peter A, Lawlor, Debbie A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394960/
https://www.ncbi.nlm.nih.gov/pubmed/32737505
http://dx.doi.org/10.1093/ije/dyaa004
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author Millard, Louise A C
Patel, Nashita
Tilling, Kate
Lewcock, Melanie
Flach, Peter A
Lawlor, Debbie A
author_facet Millard, Louise A C
Patel, Nashita
Tilling, Kate
Lewcock, Melanie
Flach, Peter A
Lawlor, Debbie A
author_sort Millard, Louise A C
collection PubMed
description Continuous glucose monitors (CGM) record interstitial glucose levels ‘continuously’, producing a sequence of measurements for each participant (e.g. the average glucose level every 5 min over several days, both day and night). To analyse these data, researchers tend to derive summary variables such as the area under the curve (AUC), to then use in subsequent analyses. To date, a lack of consistency and transparency of precise definitions used for these summary variables has hindered interpretation, replication and comparison of results across studies. We present GLU, an open-source software package for deriving a consistent set of summary variables from CGM data. GLU performs quality control of each CGM sample (e.g. addressing missing data), derives a diverse set of summary variables (e.g. AUC and proportion of time spent in hypo-, normo- and hyper- glycaemic levels) covering six broad domains, and outputs these (with quality control information) to the user. GLU is implemented in R and is available on GitHub at https://github.com/MRCIEU/GLU. Git tag v0.2 corresponds to the version presented here.
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spelling pubmed-73949602020-08-04 GLU: a software package for analysing continuously measured glucose levels in epidemiology Millard, Louise A C Patel, Nashita Tilling, Kate Lewcock, Melanie Flach, Peter A Lawlor, Debbie A Int J Epidemiol Software Application Profile Continuous glucose monitors (CGM) record interstitial glucose levels ‘continuously’, producing a sequence of measurements for each participant (e.g. the average glucose level every 5 min over several days, both day and night). To analyse these data, researchers tend to derive summary variables such as the area under the curve (AUC), to then use in subsequent analyses. To date, a lack of consistency and transparency of precise definitions used for these summary variables has hindered interpretation, replication and comparison of results across studies. We present GLU, an open-source software package for deriving a consistent set of summary variables from CGM data. GLU performs quality control of each CGM sample (e.g. addressing missing data), derives a diverse set of summary variables (e.g. AUC and proportion of time spent in hypo-, normo- and hyper- glycaemic levels) covering six broad domains, and outputs these (with quality control information) to the user. GLU is implemented in R and is available on GitHub at https://github.com/MRCIEU/GLU. Git tag v0.2 corresponds to the version presented here. Oxford University Press 2020-06 2020-02-13 /pmc/articles/PMC7394960/ /pubmed/32737505 http://dx.doi.org/10.1093/ije/dyaa004 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the International Epidemiological Association. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Application Profile
Millard, Louise A C
Patel, Nashita
Tilling, Kate
Lewcock, Melanie
Flach, Peter A
Lawlor, Debbie A
GLU: a software package for analysing continuously measured glucose levels in epidemiology
title GLU: a software package for analysing continuously measured glucose levels in epidemiology
title_full GLU: a software package for analysing continuously measured glucose levels in epidemiology
title_fullStr GLU: a software package for analysing continuously measured glucose levels in epidemiology
title_full_unstemmed GLU: a software package for analysing continuously measured glucose levels in epidemiology
title_short GLU: a software package for analysing continuously measured glucose levels in epidemiology
title_sort glu: a software package for analysing continuously measured glucose levels in epidemiology
topic Software Application Profile
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394960/
https://www.ncbi.nlm.nih.gov/pubmed/32737505
http://dx.doi.org/10.1093/ije/dyaa004
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