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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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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. |
format | Online Article Text |
id | pubmed-7394960 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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