Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

The prevalence of diabetes is increasing globally, particularly in Asia. According to the 2013 Diabetes Atlas, an estimated 366 million people are affected by diabetes worldwide; 36% of those affected live in the Western Pacific region, with a significant proportion in East Asia. The reasons for this marked increase in the prevalence of diabetes can be extrapolated from several distinct features of the Asian region. First, the two most populated countries, China and India, are located in Asia. Second, Asians have experienced extremely rapid economic growth, including rapid changes in dietary patterns, during the past decades. As a result, Asians tend to have more visceral fat within the same body mass index range compared with Westerners. In addition, increased insulin resistance relative to reduced insulin secretory function is another important feature of Asian individuals with diabetes. Young age of disease onset is also a distinctive characteristic of these patients. Moreover, changing dietary patterns, such as increased consumption of white rice and processed red meat, contributes to the deteriorated lifestyle of this region. Recent studies suggest a distinctive responsiveness to novel anti-diabetic agents in Asia; however, further research and efforts to reverse the increasing prevalence of diabetes are needed worldwide.

Lee YH, et al. Diabetes Metab J. 2019 Feb;43(1):31-45. https://doi.org/10.4093/dmj.2019.0011