Guillermo E. Umpierrez, Viral N. Shah, Veronica Brady, Mark A. Clements, Juan Espinoza, Elizabeth Healey, M. Kohn, David M. Maahs, Ralph Oiknine, Jane Jeffrie Seley, Steven Weitzman, David Kerr, Halis K. Akturk, Grazia Aleppo, Mohammed E. Al-Sofiani, Eda Cengiz, Francis J. Doyle, Osagie Ebekozien, Steven V. Edelman, Laya Ekhlaspour, GUIDO FRECKMANN, Lutz Heinemann, I. B. Hirsch, Victoria C. Hsiao, Sun H. Kim, Boris Kovatchev, Rayhan A. Lal, Marcus Lind, Julia K. Mader, Nestoras Mathioudakis, Tracey McLaughlin, Sultan A. Meo, Deborah Osafehinti, Moshe Phillip, Priya Prahalad, David Scheinker, M Snyder, Jing Wang, Jenise C. Wong, Eugene E. Wright, Mandy M. Shao, Agatha F. Scheideman, A Dunová, D C Klonoff
A panel of experts in the use of continuous glucose monitoring (CGM) data in the treatment of diabetes met in Burlingame, California on October 27, 2025 to discuss the utility of the glycemia risk index (GRI) for clinical care research and population health management. The GRI composite metric is a single number (on a 0-100 percentile scale-lower is better) based on an expert-determined weighting of the seven individual components in the existing ambulatory glucose profile (AGP). The GRI describes the quality of glycemia based on glucose values collected in a 14-day CGM tracing, thus providing additional insights into CGM profiles beyond the AGP. During the meeting, the mathematical derivation of the GRI metric was presented along with its use for adult and pediatric individuals with diabetes and cancer who require medications that can adversely affect the glucose concentration. Examples where the GRI provided useful insights into the quality of CGM tracings were also discussed by the expert panel. In addition, a new smartphone application, the GRI Calculator, was presented. This app calculates the GRI of a CGM tracing and provides visualization of sequential CGM tracings for a specific individual. The GRI provides a reference measurement for the accuracy of artificial intelligence (AI) models assigning levels of glycemic quality to CGM tracings intended to match the assessments of clinicians. The GRI is now part of the data visualization panel for the Integration of Connected Diabetes Device Data into the Electronic Health Record (iCoDE-2) project, which standardizes both CGM and insulin dosing data. Further exploration of the potential value of the GRI for non-insulin users needs to be undertaken. The panel unanimously recommended that CGM manufacturers and developers of data visualization software for CGMs add the GRI to their data platforms for insulin users.