*Geek Box: Measuring Glycaemic Variability
Typically, there are several standardised measures that are used to investigate glycaemic control, e.g., fasting plasma glucose, or 2 h post-prandial glucose response to an oral glucose tolerance test [OGTT]. However, while these measures may capture glycaemic control, they may not necessarily capture glycaemic variability. The term “glycaemic variability [GV]” broadly refers to swings in blood glucose levels, which may include blood glucose oscillations that occur throughout the day [i.e., post-prandial excursions], or blood glucose fluctuations that occur at the same time on different days.
The broad definition of GV considers between-day and withing-day glycaemic excursions, including episodes of hyperglycaemia and hypoglycaemia. Glycaemic variability may be influenced by several factors, including circadian timing of glucose rhythms and glucose tolerance, meal timing and meal composition, and other environmental factors, e.g., sleep. Some have argued that GV may not be adequately captured by measures like HbA1c, particularly in individuals who have good glycaemic control. Using CGM data has allowed for other measures of GV to be developed, including:
- MAGE [Mean Amplitude of Glycaemic Excursions]: designed to capture mealtime-related glucose excursions, assessed as glucose levels 1-SD above or below the 24 h average minimum or maximum, respectively.
- CONGA [Continuous Overlapping Net Glycaemic Action]: describes intra-day glycaemic variation as difference between current time-period of observation [e.g., 60min or 120min] and previous same time-period.
- MODD [Mean of Daily Differences]: Compares glucose at same time point to determine similarity in patterns of glucose fluctuations inter-day.
However, it is important to note that these measures have not been fully validated for their ability to predict outcomes more accurately over standardised glycaemic measures such as fasting plasma glucose or HbA1c. These measures are primarily used in clinical dietetic management of diabetes, which is where the utility of CGMs is confined beyond research, for now.