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Defining a Continuous Glucose Baseline to assess the impact of nutritional interventions
Accurate and robust estimation of individuals’ basal glucose level is a crucial measure in nutrition research but is typically estimated from one or more morning fasting samples. The use of Continuous Glucose Monitoring (CGM) devices presents an opportunity to define more robust basal glucose levels...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10425768/ https://www.ncbi.nlm.nih.gov/pubmed/37588050 http://dx.doi.org/10.3389/fnut.2023.1203899 |
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author | Chkroun, Célina Trouwborst, Inez Cherta-Murillo, Anna Owen, Lauren Darimont, Christian Rytz, Andreas |
author_facet | Chkroun, Célina Trouwborst, Inez Cherta-Murillo, Anna Owen, Lauren Darimont, Christian Rytz, Andreas |
author_sort | Chkroun, Célina |
collection | PubMed |
description | Accurate and robust estimation of individuals’ basal glucose level is a crucial measure in nutrition research but is typically estimated from one or more morning fasting samples. The use of Continuous Glucose Monitoring (CGM) devices presents an opportunity to define more robust basal glucose levels, which estimates can be generalized to any time of the day. However, to date, no standardized method has been delineated. The current paper seeks to define a reliable algorithm to characterize the individual’s basal glucose level over 24 h from CGM measurements. Data drawn from four nutritional intervention studies performed on adults free from chronic diseases were used to define that basal glucose levels were optimally estimated using the 40th percentile of the previous 24 h CGM data. This simple algorithm provides a Continuous Glucose Baseline over 24 h (24 h-CGB) that is an unbiased and highly correlated estimator (r = 0.86, p-value < 0.01) of standard fasting glucose. We conclude that 24-CGB can provide reliable basal glucose estimates across the day while being more robust to interference than standard fasting glucose, adaptable to evolving daily routines and providing useful reference values for free-living nutritional intervention research in non-diabetic individuals. |
format | Online Article Text |
id | pubmed-10425768 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104257682023-08-16 Defining a Continuous Glucose Baseline to assess the impact of nutritional interventions Chkroun, Célina Trouwborst, Inez Cherta-Murillo, Anna Owen, Lauren Darimont, Christian Rytz, Andreas Front Nutr Nutrition Accurate and robust estimation of individuals’ basal glucose level is a crucial measure in nutrition research but is typically estimated from one or more morning fasting samples. The use of Continuous Glucose Monitoring (CGM) devices presents an opportunity to define more robust basal glucose levels, which estimates can be generalized to any time of the day. However, to date, no standardized method has been delineated. The current paper seeks to define a reliable algorithm to characterize the individual’s basal glucose level over 24 h from CGM measurements. Data drawn from four nutritional intervention studies performed on adults free from chronic diseases were used to define that basal glucose levels were optimally estimated using the 40th percentile of the previous 24 h CGM data. This simple algorithm provides a Continuous Glucose Baseline over 24 h (24 h-CGB) that is an unbiased and highly correlated estimator (r = 0.86, p-value < 0.01) of standard fasting glucose. We conclude that 24-CGB can provide reliable basal glucose estimates across the day while being more robust to interference than standard fasting glucose, adaptable to evolving daily routines and providing useful reference values for free-living nutritional intervention research in non-diabetic individuals. Frontiers Media S.A. 2023-07-31 /pmc/articles/PMC10425768/ /pubmed/37588050 http://dx.doi.org/10.3389/fnut.2023.1203899 Text en Copyright © 2023 Chkroun, Trouwborst, Cherta-Murillo, Owen, Darimont and Rytz. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Nutrition Chkroun, Célina Trouwborst, Inez Cherta-Murillo, Anna Owen, Lauren Darimont, Christian Rytz, Andreas Defining a Continuous Glucose Baseline to assess the impact of nutritional interventions |
title | Defining a Continuous Glucose Baseline to assess the impact of nutritional interventions |
title_full | Defining a Continuous Glucose Baseline to assess the impact of nutritional interventions |
title_fullStr | Defining a Continuous Glucose Baseline to assess the impact of nutritional interventions |
title_full_unstemmed | Defining a Continuous Glucose Baseline to assess the impact of nutritional interventions |
title_short | Defining a Continuous Glucose Baseline to assess the impact of nutritional interventions |
title_sort | defining a continuous glucose baseline to assess the impact of nutritional interventions |
topic | Nutrition |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10425768/ https://www.ncbi.nlm.nih.gov/pubmed/37588050 http://dx.doi.org/10.3389/fnut.2023.1203899 |
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