Open AccessGlycaemic variability in diabetes: a tool for assessing the quality of glycaemic control and the risk of complications
Author(s) -
Vadim V. Klimontov,
Natalia E. Myakina
Publication year - 2014
Publication title -
saharnyj diabet
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.155
H-Index - 12
eISSN - 2072-0378
pISSN - 2072-0351
DOI - 10.14341/dm2014276-82
Subject(s) - medicine , diabetes mellitus , glycated haemoglobin , endothelial dysfunction , endocrinology , cardiology , nephropathy , diabetic retinopathy , continuous glucose monitoring , type 2 diabetes , glycemic
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.