Introduction: Currently measures of glycaemic variability (Standard Deviation, Mean and MAGE) all fail to fully highlight the extent of blood glucose variability so there is a need for improved measures of glycaemic variability. Aim: To utilise clinical data produced using CGMS to develop and validate a clinically-relevant novel measure of glycaemic variability and to use it to compare CSII with MDI. Methods: 20 participants (6 months pre and post CSII) with 24 hr CGM data sets were analysed. Glucose variability Rating (GVR) was calculated in three steps including change in sensor reading at 5 minute intervals which were then squared and av- eraged to obtain GVR (mmol/L) 2/hr. GVR was plotted, area under curve (AUC) calculated and pre vs. post-CSII GVR compared. Time series analysis was also investigated to try and identify specific periods with increased variability. A compari- son of the percentage change in GVR vs the change in HbA1c value in pre vs post-CSII was also analysed to identify correla- tion between these two measures. Results: GVR was applied to pre and post-CSII CGM data; 75% of participants showed < 20% reduction of GVR post-CSII vs. MDI. The group also showed a significant reduction in GVR (p < 0.003) post-CSII (vs MDI). Conclusions: Results indicate a reduction in glucose vari- ability with CSII and highlight the limitations of HbA1c, as well as the useful potential of GVR to highlight specific time periods where intervention is required to control blood glucose variability.
|Number of pages
|Diabetes Technology & Therapeutics
|Published - 1 Feb 2014