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Simulation of a computed HbA(1c) using a weighted average glucose
BACKGROUND: The A(1c)-derived average glucose examined the link between the glycated haemoglobin and the estimated average glucose, and provided a linear relation between them. Other studies proved that, over a period of 4 months, plasma glucose in the preceding 30 days contribute to about 50 % to t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4771657/ https://www.ncbi.nlm.nih.gov/pubmed/27026920 http://dx.doi.org/10.1186/s40064-016-1877-2 |
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author | Boutayeb, W. Boutayeb, A. Lamlili, M. Ben El Mostafa, S. Zitouni, N. |
author_facet | Boutayeb, W. Boutayeb, A. Lamlili, M. Ben El Mostafa, S. Zitouni, N. |
author_sort | Boutayeb, W. |
collection | PubMed |
description | BACKGROUND: The A(1c)-derived average glucose examined the link between the glycated haemoglobin and the estimated average glucose, and provided a linear relation between them. Other studies proved that, over a period of 4 months, plasma glucose in the preceding 30 days contribute to about 50 % to the glycated haemoglobin value while the other 50 % is due to the remaining 3 months altogether. TECHNICAL DETAILS OF THE METHOD: In this technical note, we propose a weighted method assuming that the contribution of glucose to glycated haemoglobin over 3 months is chronologically 20 %, 30 % and 50 % respectively. A comparison is made with the linear regression method which uses the same estimated average glucose over the whole period. Results yielded by the weighted method are also compared to those given by the model proposed by Ladyzyński et al. FINDINGS: A simulation is carried out on data assumed to come from a first individual with nearly the same level of glucose over 3 months, a second individual who starts with high levels of glucose and then reaches a stabilised low level by the last month, and finally, a third case who had just been diagnosed with diabetes during the last month whereas he/she had a normal glycaemia during the preceding 2 months. The weighted method gives more realistic values of HbA(1c) (7.36 %, 6.80 %, 8.49 %) than the linear regression method without weights which gives the same value (7.45 %) for the three cases. Another comparison shows that the three values given by the weighted method are slightly smaller than the corresponding values given by the model of Ladyzynski et al. (7.62 %, 7.02 %, 8.8 %) but the relative variation is nearly the same for the three values (≈3 %). CONCLUSSION: Without regular self-testing and day-to-day insights, a sole HbA(1c) value can be confusing and misleading. For physicians and patients, a clear understanding of the relationship between the weighted average glucose and HbA(1c) is necessary in order to set an appropriate daily control depending on whether the glucose is stabilized over the whole period, at the beginning, at the end; or still under recurrent episodes of high and low levels. The measured HbA(1c) at a biological laboratory gives no indication on glucose variation. Moreover, low values of glucose may cancel high values and lead to a “good” average glucose and ideal glycated haemoglobin. |
format | Online Article Text |
id | pubmed-4771657 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-47716572016-03-29 Simulation of a computed HbA(1c) using a weighted average glucose Boutayeb, W. Boutayeb, A. Lamlili, M. Ben El Mostafa, S. Zitouni, N. Springerplus Technical Note BACKGROUND: The A(1c)-derived average glucose examined the link between the glycated haemoglobin and the estimated average glucose, and provided a linear relation between them. Other studies proved that, over a period of 4 months, plasma glucose in the preceding 30 days contribute to about 50 % to the glycated haemoglobin value while the other 50 % is due to the remaining 3 months altogether. TECHNICAL DETAILS OF THE METHOD: In this technical note, we propose a weighted method assuming that the contribution of glucose to glycated haemoglobin over 3 months is chronologically 20 %, 30 % and 50 % respectively. A comparison is made with the linear regression method which uses the same estimated average glucose over the whole period. Results yielded by the weighted method are also compared to those given by the model proposed by Ladyzyński et al. FINDINGS: A simulation is carried out on data assumed to come from a first individual with nearly the same level of glucose over 3 months, a second individual who starts with high levels of glucose and then reaches a stabilised low level by the last month, and finally, a third case who had just been diagnosed with diabetes during the last month whereas he/she had a normal glycaemia during the preceding 2 months. The weighted method gives more realistic values of HbA(1c) (7.36 %, 6.80 %, 8.49 %) than the linear regression method without weights which gives the same value (7.45 %) for the three cases. Another comparison shows that the three values given by the weighted method are slightly smaller than the corresponding values given by the model of Ladyzynski et al. (7.62 %, 7.02 %, 8.8 %) but the relative variation is nearly the same for the three values (≈3 %). CONCLUSSION: Without regular self-testing and day-to-day insights, a sole HbA(1c) value can be confusing and misleading. For physicians and patients, a clear understanding of the relationship between the weighted average glucose and HbA(1c) is necessary in order to set an appropriate daily control depending on whether the glucose is stabilized over the whole period, at the beginning, at the end; or still under recurrent episodes of high and low levels. The measured HbA(1c) at a biological laboratory gives no indication on glucose variation. Moreover, low values of glucose may cancel high values and lead to a “good” average glucose and ideal glycated haemoglobin. Springer International Publishing 2016-02-29 /pmc/articles/PMC4771657/ /pubmed/27026920 http://dx.doi.org/10.1186/s40064-016-1877-2 Text en © Boutayeb et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Technical Note Boutayeb, W. Boutayeb, A. Lamlili, M. Ben El Mostafa, S. Zitouni, N. Simulation of a computed HbA(1c) using a weighted average glucose |
title | Simulation of a computed HbA(1c) using a weighted average glucose |
title_full | Simulation of a computed HbA(1c) using a weighted average glucose |
title_fullStr | Simulation of a computed HbA(1c) using a weighted average glucose |
title_full_unstemmed | Simulation of a computed HbA(1c) using a weighted average glucose |
title_short | Simulation of a computed HbA(1c) using a weighted average glucose |
title_sort | simulation of a computed hba(1c) using a weighted average glucose |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4771657/ https://www.ncbi.nlm.nih.gov/pubmed/27026920 http://dx.doi.org/10.1186/s40064-016-1877-2 |
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