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A1c Variability Can Predict Coronary Artery Disease in Patients with Type 2 Diabetes with Mean A1c Levels Greater than 7

BACKGROUND: Recent studies suggested that the association of acute glucose variability and diabetic complications was not consistent, and that A1c variability representing long term glucose fluctuation may be related to coronary atherosclerosis in patients with type 1 diabetes. In this study, we att...

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Autores principales: Lee, Eun Ju, Kim, You Jeong, Kim, Tae Nyun, Kim, Tae Ik, Lee, Won Kee, Kim, Mi-Kyung, Park, Jeong Hyun, Rhee, Byoung Doo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Endocrine Society 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3811710/
https://www.ncbi.nlm.nih.gov/pubmed/24396666
http://dx.doi.org/10.3803/EnM.2013.28.2.125
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author Lee, Eun Ju
Kim, You Jeong
Kim, Tae Nyun
Kim, Tae Ik
Lee, Won Kee
Kim, Mi-Kyung
Park, Jeong Hyun
Rhee, Byoung Doo
author_facet Lee, Eun Ju
Kim, You Jeong
Kim, Tae Nyun
Kim, Tae Ik
Lee, Won Kee
Kim, Mi-Kyung
Park, Jeong Hyun
Rhee, Byoung Doo
author_sort Lee, Eun Ju
collection PubMed
description BACKGROUND: Recent studies suggested that the association of acute glucose variability and diabetic complications was not consistent, and that A1c variability representing long term glucose fluctuation may be related to coronary atherosclerosis in patients with type 1 diabetes. In this study, we attempt to determine whether or not A1c variability can predict coronary artery disease (CAD) in patients with type 2 diabetes. METHODS: We reviewed data of patients with type 2 diabetes who had undergone coronary angiography (CAG) and had been followed up with for 5 years. The intrapersonal standard deviation (SD) of serially-measured A1c levels adjusted by the different number of assessments among patients (adj-A1c-SD) was considered to be a measure of the variability of A1c. RESULTS: Among the 269 patients, 121 of them had type 2 diabetes with CAD. In patients with A1c ≥7%, the mean A1c levels and A1c levels at the time of CAG among the three groups were significantly different. The ratio of patients with CAD was the highest in the high adj-A1c-SD group and the lowest in the low adj-A1c-SD group (P=0.017). In multiple regression analysis, adj-A1c-SD was an independent predictor for CAD in subjects with A1c ≥7% (odds ratio, 2.140; P=0.036). CONCLUSION: Patients with higher A1c variability for several years showed higher mean A1c levels. A1c variability can be an independent predictor for CAD as seen in angiographs of patients with type 2 diabetes with mean A1c levels over 7%.
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spelling pubmed-38117102014-01-06 A1c Variability Can Predict Coronary Artery Disease in Patients with Type 2 Diabetes with Mean A1c Levels Greater than 7 Lee, Eun Ju Kim, You Jeong Kim, Tae Nyun Kim, Tae Ik Lee, Won Kee Kim, Mi-Kyung Park, Jeong Hyun Rhee, Byoung Doo Endocrinol Metab (Seoul) Original Article BACKGROUND: Recent studies suggested that the association of acute glucose variability and diabetic complications was not consistent, and that A1c variability representing long term glucose fluctuation may be related to coronary atherosclerosis in patients with type 1 diabetes. In this study, we attempt to determine whether or not A1c variability can predict coronary artery disease (CAD) in patients with type 2 diabetes. METHODS: We reviewed data of patients with type 2 diabetes who had undergone coronary angiography (CAG) and had been followed up with for 5 years. The intrapersonal standard deviation (SD) of serially-measured A1c levels adjusted by the different number of assessments among patients (adj-A1c-SD) was considered to be a measure of the variability of A1c. RESULTS: Among the 269 patients, 121 of them had type 2 diabetes with CAD. In patients with A1c ≥7%, the mean A1c levels and A1c levels at the time of CAG among the three groups were significantly different. The ratio of patients with CAD was the highest in the high adj-A1c-SD group and the lowest in the low adj-A1c-SD group (P=0.017). In multiple regression analysis, adj-A1c-SD was an independent predictor for CAD in subjects with A1c ≥7% (odds ratio, 2.140; P=0.036). CONCLUSION: Patients with higher A1c variability for several years showed higher mean A1c levels. A1c variability can be an independent predictor for CAD as seen in angiographs of patients with type 2 diabetes with mean A1c levels over 7%. Korean Endocrine Society 2013-06 2013-06-18 /pmc/articles/PMC3811710/ /pubmed/24396666 http://dx.doi.org/10.3803/EnM.2013.28.2.125 Text en Copyright © 2013 Korean Endocrine Society http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Lee, Eun Ju
Kim, You Jeong
Kim, Tae Nyun
Kim, Tae Ik
Lee, Won Kee
Kim, Mi-Kyung
Park, Jeong Hyun
Rhee, Byoung Doo
A1c Variability Can Predict Coronary Artery Disease in Patients with Type 2 Diabetes with Mean A1c Levels Greater than 7
title A1c Variability Can Predict Coronary Artery Disease in Patients with Type 2 Diabetes with Mean A1c Levels Greater than 7
title_full A1c Variability Can Predict Coronary Artery Disease in Patients with Type 2 Diabetes with Mean A1c Levels Greater than 7
title_fullStr A1c Variability Can Predict Coronary Artery Disease in Patients with Type 2 Diabetes with Mean A1c Levels Greater than 7
title_full_unstemmed A1c Variability Can Predict Coronary Artery Disease in Patients with Type 2 Diabetes with Mean A1c Levels Greater than 7
title_short A1c Variability Can Predict Coronary Artery Disease in Patients with Type 2 Diabetes with Mean A1c Levels Greater than 7
title_sort a1c variability can predict coronary artery disease in patients with type 2 diabetes with mean a1c levels greater than 7
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3811710/
https://www.ncbi.nlm.nih.gov/pubmed/24396666
http://dx.doi.org/10.3803/EnM.2013.28.2.125
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