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The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c

BACKGROUND: Diabetic peripheral neuropathy (DPN) is one of the most common microvascular complications of diabetes. Glycemic variability could be an independent risk factor for diabetes complications in addition to average glucose. Type 2 diabetes with well-controlled glycosylated hemoglobin A1c (Hb...

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Autores principales: Xu, Feng, Zhao, Li-hua, Su, Jian-bin, Chen, Tong, Wang, Xue-qin, Chen, Jin-feng, Wu, Gang, Jin, Yan, Wang, Xiao-hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4272789/
https://www.ncbi.nlm.nih.gov/pubmed/25530811
http://dx.doi.org/10.1186/1758-5996-6-139
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author Xu, Feng
Zhao, Li-hua
Su, Jian-bin
Chen, Tong
Wang, Xue-qin
Chen, Jin-feng
Wu, Gang
Jin, Yan
Wang, Xiao-hua
author_facet Xu, Feng
Zhao, Li-hua
Su, Jian-bin
Chen, Tong
Wang, Xue-qin
Chen, Jin-feng
Wu, Gang
Jin, Yan
Wang, Xiao-hua
author_sort Xu, Feng
collection PubMed
description BACKGROUND: Diabetic peripheral neuropathy (DPN) is one of the most common microvascular complications of diabetes. Glycemic variability could be an independent risk factor for diabetes complications in addition to average glucose. Type 2 diabetes with well-controlled glycosylated hemoglobin A1c (HbA1c) may have different terms of glycemic variability and vascular complication consequences. The aim of the study is to investigate the relationship between glycemic variability and DPN in type 2 diabetes with well-controlled HbA1c (HbA1c < 7.0%). METHODS: 45 type 2 diabetes with well-controlled HbA1c(HbA1c < 7.0%) and with DPN (DM/DPN group) were recruited in the study, and 45 type 2 diabetes with well-controlled HbA1c and without DPN (DM/–DPN group) were set as controls. The two groups were also matched for age and diabetic duration. Blood pressure, body mass index(BMI), insulin sensitivity index (Matsuda index, ISI), total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDLC), and low density lipoprotein cholesterol (LDLC) were tested in the two groups. And all patients were monitored using the continuous glucose monitoring (CGM) system for consecutive 72 hours. The multiple parameters of glycemic variability included the standard deviation of blood glucose (SDBG), mean of daily differences (MODD) and mean amplitude of glycemic excursions (MAGE). RESULTS: The DM/DPN group had a greater SDBG, MODD and MAGE, when compared to the DM/–DPN group (p < 0.05). BMI, TC, and LDLC of DM/DPN group were lower than those of DM/–DPN group (p < 0.05). The patients with hypoglycemia were comparable between the two groups (p > 0.05). Univariate analysis showed DPN was closely associated with BMI (OR 0.82, CI 0.72–0.94, p = 0.005), TC (OR 0.63, CI 0.42–0.93, p = 0.02), LDLC (OR 0.4, CI 0.20–0.80, p = 0.009), SDBG (OR 2.95, CI 1.55–5.61, p = 0.001), MODD (OR 4.38, CI 1.48–12.93, p = 0.008), MAGE (OR 2.18, CI 1.47–3.24, p < 0.001). Multivariate logistic regression analysis showed that MAGE (OR 2.05, CI 1.36–3.09, p = 0.001) and BMI (OR 0.85, CI 0.73–0.99, p = 0.033) were significantly correlating with DPN. Glycemic variability, evaluated by MAGE, was the most significantly independent risk factor for DPN. CONCLUSIONS: There was a close relationship between glycemic variability evaluated by MAGE and DPN in type 2 diabetes with well-controlled HbA1c.
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spelling pubmed-42727892014-12-22 The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c Xu, Feng Zhao, Li-hua Su, Jian-bin Chen, Tong Wang, Xue-qin Chen, Jin-feng Wu, Gang Jin, Yan Wang, Xiao-hua Diabetol Metab Syndr Research BACKGROUND: Diabetic peripheral neuropathy (DPN) is one of the most common microvascular complications of diabetes. Glycemic variability could be an independent risk factor for diabetes complications in addition to average glucose. Type 2 diabetes with well-controlled glycosylated hemoglobin A1c (HbA1c) may have different terms of glycemic variability and vascular complication consequences. The aim of the study is to investigate the relationship between glycemic variability and DPN in type 2 diabetes with well-controlled HbA1c (HbA1c < 7.0%). METHODS: 45 type 2 diabetes with well-controlled HbA1c(HbA1c < 7.0%) and with DPN (DM/DPN group) were recruited in the study, and 45 type 2 diabetes with well-controlled HbA1c and without DPN (DM/–DPN group) were set as controls. The two groups were also matched for age and diabetic duration. Blood pressure, body mass index(BMI), insulin sensitivity index (Matsuda index, ISI), total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDLC), and low density lipoprotein cholesterol (LDLC) were tested in the two groups. And all patients were monitored using the continuous glucose monitoring (CGM) system for consecutive 72 hours. The multiple parameters of glycemic variability included the standard deviation of blood glucose (SDBG), mean of daily differences (MODD) and mean amplitude of glycemic excursions (MAGE). RESULTS: The DM/DPN group had a greater SDBG, MODD and MAGE, when compared to the DM/–DPN group (p < 0.05). BMI, TC, and LDLC of DM/DPN group were lower than those of DM/–DPN group (p < 0.05). The patients with hypoglycemia were comparable between the two groups (p > 0.05). Univariate analysis showed DPN was closely associated with BMI (OR 0.82, CI 0.72–0.94, p = 0.005), TC (OR 0.63, CI 0.42–0.93, p = 0.02), LDLC (OR 0.4, CI 0.20–0.80, p = 0.009), SDBG (OR 2.95, CI 1.55–5.61, p = 0.001), MODD (OR 4.38, CI 1.48–12.93, p = 0.008), MAGE (OR 2.18, CI 1.47–3.24, p < 0.001). Multivariate logistic regression analysis showed that MAGE (OR 2.05, CI 1.36–3.09, p = 0.001) and BMI (OR 0.85, CI 0.73–0.99, p = 0.033) were significantly correlating with DPN. Glycemic variability, evaluated by MAGE, was the most significantly independent risk factor for DPN. CONCLUSIONS: There was a close relationship between glycemic variability evaluated by MAGE and DPN in type 2 diabetes with well-controlled HbA1c. BioMed Central 2014-12-15 /pmc/articles/PMC4272789/ /pubmed/25530811 http://dx.doi.org/10.1186/1758-5996-6-139 Text en © Xu et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. 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 use, distribution, and reproduction in any medium, provided the original work is properly credited. 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.
spellingShingle Research
Xu, Feng
Zhao, Li-hua
Su, Jian-bin
Chen, Tong
Wang, Xue-qin
Chen, Jin-feng
Wu, Gang
Jin, Yan
Wang, Xiao-hua
The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c
title The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c
title_full The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c
title_fullStr The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c
title_full_unstemmed The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c
title_short The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c
title_sort relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled hba1c
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4272789/
https://www.ncbi.nlm.nih.gov/pubmed/25530811
http://dx.doi.org/10.1186/1758-5996-6-139
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