Glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications

The routine approach to evaluating the effectiveness of diabetes treatment based on the level of glycated haemoglobin (HbA. 1c) accounts for the average glucose level but does not consider the scope and frequency of its fluctuations. The development of computational methods to analyse glycaemic osci...

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Autores principales:	Vadim Valer'evich Klimontov, Natalya Evgen'evna Myakina
Formato:	article
Lenguaje:	EN RU
Publicado:	Endocrinology Research Centre 2014
Materias:	diabetes glycaemic variability continuous glucose monitoring hypoglycaemia cardiovascular complications risk factors Nutritional diseases. Deficiency diseases RC620-627
Acceso en línea:	https://doaj.org/article/7e91a4c6da2443a9a3e2a74168d1b8fe
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spelling	oai:doaj.org-article:7e91a4c6da2443a9a3e2a74168d1b8fe2021-11-14T09:00:19ZGlycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications2072-03512072-037810.14341/DM2014276-82https://doaj.org/article/7e91a4c6da2443a9a3e2a74168d1b8fe2014-07-01T00:00:00Zhttps://www.dia-endojournals.ru/jour/article/view/6405https://doaj.org/toc/2072-0351https://doaj.org/toc/2072-0378The routine approach to evaluating the effectiveness of diabetes treatment based on the level of glycated haemoglobin (HbA. 1c) accounts for the average glucose level but does not consider the scope and frequency of its fluctuations. The development of computational methods to analyse glycaemic oscillations has made it possible to propose the concept of glycaemic variability (GV). The interest in research focused on GV increased dramatically after continuous glucose monitoring (CGM) technology was introduced, which provided the opportunity to study in detail the temporal structure of blood glucose curves. Numerous methods for assessing GV proposed over the past five decades characterize glycaemic fluctuations as functions of concentration and time and estimate the risks of hypoglycaemia and hyperglycaemia. Accumulating evidence indicates that GV may serve as a significant predictor of diabetic complications. Prospective studies demonstrate that certain GV parameters have independent significance for predicting diabetic retinopathy, nephropathy and cardiovascular diseases. There is evidence that GV correlates with the severity of atherosclerotic vascular lesions and cardiovascular outcomes in diabetic patients. The mechanisms underlying the relationship between GV and vascular complications are being intensively studied, and recent data show that the effect of GV on vascular walls may be mediated by oxidative stress, chronic inflammation and endothelial dysfunction. Average blood glucose levels and GV are considered independent predictors of hypoglycaemia. Increased GV is associated with impaired hormonal response to hypoglycaemia and is a long-term predictor of hypoglycaemia unawareness. These data allow us to conclude that computational methods for analysing GV in patients with diabetes may serve as a promising tool for personalized assessment of glycaemic control and the risk of vascular complications and hypoglycaemia. Thus, the reduction of GV can be regarded as one of the therapeutic targets to treat diabetes.Vadim Valer'evich KlimontovNatalya Evgen'evna MyakinaEndocrinology Research Centrearticlediabetesglycaemic variabilitycontinuous glucose monitoringhypoglycaemiacardiovascular complicationsrisk factorsNutritional diseases. Deficiency diseasesRC620-627ENRUСахарный диабет, Vol 17, Iss 2, Pp 76-82 (2014)
institution	DOAJ
collection	DOAJ
language	EN RU
topic	diabetes glycaemic variability continuous glucose monitoring hypoglycaemia cardiovascular complications risk factors Nutritional diseases. Deficiency diseases RC620-627
spellingShingle	diabetes glycaemic variability continuous glucose monitoring hypoglycaemia cardiovascular complications risk factors Nutritional diseases. Deficiency diseases RC620-627 Vadim Valer'evich Klimontov Natalya Evgen'evna Myakina Glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications
description	The routine approach to evaluating the effectiveness of diabetes treatment based on the level of glycated haemoglobin (HbA. 1c) accounts for the average glucose level but does not consider the scope and frequency of its fluctuations. The development of computational methods to analyse glycaemic oscillations has made it possible to propose the concept of glycaemic variability (GV). The interest in research focused on GV increased dramatically after continuous glucose monitoring (CGM) technology was introduced, which provided the opportunity to study in detail the temporal structure of blood glucose curves. Numerous methods for assessing GV proposed over the past five decades characterize glycaemic fluctuations as functions of concentration and time and estimate the risks of hypoglycaemia and hyperglycaemia. Accumulating evidence indicates that GV may serve as a significant predictor of diabetic complications. Prospective studies demonstrate that certain GV parameters have independent significance for predicting diabetic retinopathy, nephropathy and cardiovascular diseases. There is evidence that GV correlates with the severity of atherosclerotic vascular lesions and cardiovascular outcomes in diabetic patients. The mechanisms underlying the relationship between GV and vascular complications are being intensively studied, and recent data show that the effect of GV on vascular walls may be mediated by oxidative stress, chronic inflammation and endothelial dysfunction. Average blood glucose levels and GV are considered independent predictors of hypoglycaemia. Increased GV is associated with impaired hormonal response to hypoglycaemia and is a long-term predictor of hypoglycaemia unawareness. These data allow us to conclude that computational methods for analysing GV in patients with diabetes may serve as a promising tool for personalized assessment of glycaemic control and the risk of vascular complications and hypoglycaemia. Thus, the reduction of GV can be regarded as one of the therapeutic targets to treat diabetes.
format	article
author	Vadim Valer'evich Klimontov Natalya Evgen'evna Myakina
author_facet	Vadim Valer'evich Klimontov Natalya Evgen'evna Myakina
author_sort	Vadim Valer'evich Klimontov
title	Glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications
title_short	Glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications
title_full	Glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications
title_fullStr	Glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications
title_full_unstemmed	Glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications
title_sort	glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications
publisher	Endocrinology Research Centre
publishDate	2014
url	https://doaj.org/article/7e91a4c6da2443a9a3e2a74168d1b8fe
work_keys_str_mv	AT vadimvalerevichklimontov glycaemicvariabilityindiabetesatoolforassessingthequalityofglycaemiccontrolandtheriskofcomplications AT natalyaevgenevnamyakina glycaemicvariabilityindiabetesatoolforassessingthequalityofglycaemiccontrolandtheriskofcomplications
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Glycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications

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