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Glycemic deviation index: a novel method of integrating glycemic numerical value and variability
BACKGROUND: There are many continuous blood glucose monitoring (CGM) data-based indicators, and most of these focus on a single characteristic of abnormal blood glucose. An ideal index that integrates and evaluates multiple characteristics of blood glucose has not yet been established. METHODS: In t...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7976707/ https://www.ncbi.nlm.nih.gov/pubmed/33736619 http://dx.doi.org/10.1186/s12902-021-00691-z |
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author | Zou, Yizhou Wang, Wanli Zheng, Dongmei Hou, Xu |
author_facet | Zou, Yizhou Wang, Wanli Zheng, Dongmei Hou, Xu |
author_sort | Zou, Yizhou |
collection | PubMed |
description | BACKGROUND: There are many continuous blood glucose monitoring (CGM) data-based indicators, and most of these focus on a single characteristic of abnormal blood glucose. An ideal index that integrates and evaluates multiple characteristics of blood glucose has not yet been established. METHODS: In this study, we proposed the glycemic deviation index (GDI) as a novel integrating characteristic, which mainly incorporates the assessment of the glycemic numerical value and variability. To verify its effectiveness, GDI was applied to the simulated 24 h glycemic profiles and the CGM data of type 2 diabetes (T2D) patients (n = 30). RESULTS: Evaluation of the GDI of the 24 h simulated glycemic profiles showed that the occurrence of hypoglycemia was numerically the same as hyperglycemia in increasing GDI. Meanwhile, glycemic variability was added as an independent factor. One-way ANOVA results showed that the application of GDI showed statistically significant differences in clinical glycemic parameters, average glycemic parameters, and glycemic variability parameters among the T2D groups with different glycemic levels. CONCLUSIONS: In conclusion, GDI integrates the characteristics of the numerical value and the variability in blood glucose levels and may be beneficial for the glycemic management of diabetic patients undergoing CGM treatment. |
format | Online Article Text |
id | pubmed-7976707 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79767072021-03-19 Glycemic deviation index: a novel method of integrating glycemic numerical value and variability Zou, Yizhou Wang, Wanli Zheng, Dongmei Hou, Xu BMC Endocr Disord Research Article BACKGROUND: There are many continuous blood glucose monitoring (CGM) data-based indicators, and most of these focus on a single characteristic of abnormal blood glucose. An ideal index that integrates and evaluates multiple characteristics of blood glucose has not yet been established. METHODS: In this study, we proposed the glycemic deviation index (GDI) as a novel integrating characteristic, which mainly incorporates the assessment of the glycemic numerical value and variability. To verify its effectiveness, GDI was applied to the simulated 24 h glycemic profiles and the CGM data of type 2 diabetes (T2D) patients (n = 30). RESULTS: Evaluation of the GDI of the 24 h simulated glycemic profiles showed that the occurrence of hypoglycemia was numerically the same as hyperglycemia in increasing GDI. Meanwhile, glycemic variability was added as an independent factor. One-way ANOVA results showed that the application of GDI showed statistically significant differences in clinical glycemic parameters, average glycemic parameters, and glycemic variability parameters among the T2D groups with different glycemic levels. CONCLUSIONS: In conclusion, GDI integrates the characteristics of the numerical value and the variability in blood glucose levels and may be beneficial for the glycemic management of diabetic patients undergoing CGM treatment. BioMed Central 2021-03-19 /pmc/articles/PMC7976707/ /pubmed/33736619 http://dx.doi.org/10.1186/s12902-021-00691-z Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Zou, Yizhou Wang, Wanli Zheng, Dongmei Hou, Xu Glycemic deviation index: a novel method of integrating glycemic numerical value and variability |
title | Glycemic deviation index: a novel method of integrating glycemic numerical value and variability |
title_full | Glycemic deviation index: a novel method of integrating glycemic numerical value and variability |
title_fullStr | Glycemic deviation index: a novel method of integrating glycemic numerical value and variability |
title_full_unstemmed | Glycemic deviation index: a novel method of integrating glycemic numerical value and variability |
title_short | Glycemic deviation index: a novel method of integrating glycemic numerical value and variability |
title_sort | glycemic deviation index: a novel method of integrating glycemic numerical value and variability |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7976707/ https://www.ncbi.nlm.nih.gov/pubmed/33736619 http://dx.doi.org/10.1186/s12902-021-00691-z |
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