Applied Medical Informatics (Feb 2013)
Glycemic Variability and Type 2 Diabetes Mellitus
Abstract
Aim: The purpose of the present study was to quantify glucose variability in type 2 diabetic patients and establishing relationship with cardiometabolic parameters and type of glucose-lowering treatment. Material and Methods: Continuous glucose monitoring (CGM) was used in 373 type 2 diabetic patients. Glycemic variability (GV) was evaluated by many indices based on CGM data such as mean amplitude of glycemic excursions (MAGE), standard deviation (SD), nMAGE (calculating MAGE from glucose monitoring data using the algorithm proposed by Baghurst) and mean interstitial glucose values (MG). Results: GV increases significantly from diet to insulin group (p=0.001) and from oral therapy to insulin therapy (p=0.001) by MAGE, SD and nMAGE indices and less powerful for MG (p=0.042 and 0.003 respectively). All GV indices are correlated with each other, the strong relationship being shown between MAGE, SD and nMAGE (p=0.0001). Conclusions: There exists a progressive alteration of GV from diet to insulin therapy in individuals with type 2 diabetes mellitus. The simple standard deviation of CGM (continuous glucose monitoring) readings appears to be the best practical pathway to quantify glucose variability.
