A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings

David C. Klonoff(Mills Peninsula Health Services), Jing Wang(Florida State University), David Rodbard, Michael A. Kohn(University of California, San Francisco), Chengdong Li(Florida State University), Dorian Liepmann(University of California, Berkeley), David Kerr(Sansum Diabetes Research Institute), David Ahn(Hoag Memorial Hospital Presbyterian), Anne L. Peters(University of Southern California), Guillermo E. Umpierrez(Emory University), Jane Jeffrie Seley(Cornell University), Nicole Y. Xu(Diabetes Technology Society), Kevin T. Nguyen(Diabetes Technology Society), Gregg D. Simonson, Michael S. D. Agus(Boston Children's Hospital), Mohammed E. Al‐Sofiani(Johns Hopkins University), Gustavo Armaiz-Peña(The University of Texas at San Antonio Health Science Center), Timothy S. Bailey(AMCR Institute), Ananda Basu(University of Virginia), Tadej Battelino(University of Ljubljana), Sewagegn Yeshiwas(Addis Ababa University), Pierre‐Yves Benhamou(Centre Hospitalier Universitaire de Grenoble), B. Wayne Bequette(Rensselaer Polytechnic Institute), Thomas Blevins(Texas Diabetes & Endocrinology), Marc D. Breton(University of Virginia), Jessica R. Castle(Oregon Health & Science University), J. Geoffrey Chase(University of Canterbury), Kong Y. Chen(National Institute of Diabetes and Digestive and Kidney Diseases), Pratik Choudhary(University of Leicester), Mark A. Clements(Children's Mercy Hospital), Kelly L. Close(Close Concerns (United States)), Curtiss B. Cook(Mayo Clinic in Arizona), Thomas Danne(Medizinische Hochschule Hannover), Francis J. Doyle(Harvard University Press), Angela Drincic(University of Nebraska at Omaha), Kathleen Dungan(The Ohio State University), Steven V. Edelman(University of California San Diego), Niels Ejskjær(Steno Diabetes Centers), Juan Espinoza(University of Southern California), G. Alexander Fleming(Harper College), Gregory P. Forlenza(University of Colorado Anschutz Medical Campus), Guido Freckmann(German Center for Diabetes Research), Rodolfo J. Galindo(Emory University), Ana María Gómez(Pontificia Universidad Javeriana), Hanna A. Gutow(Close Concerns (United States)), Lutz Heinemann, Irl B. Hirsch(University of Washington), Thanh D. Hoang(Walter Reed National Military Medical Center), Roman Hovorka(University of Cambridge), Johan Jendle(Örebro University), Linong Ji(Peking University), Shashank Joshi(Joshi Hospital), Michaël Joubert(Université de Caen Normandie), Suneil K. Koliwad(University of California, San Francisco), Rayhan Lal(Stanford University), M. Cecilia Lansang(Cleveland Clinic), Wei-An Lee(LAC+USC Medical Center), Lalantha Leelarathna(Manchester University NHS Foundation Trust), Lawrence A. Leiter(St. Michael's Hospital), Marcus Lind(University of Gothenburg), Michelle L. Litchman(University of Utah), Julia K. Mader(Medical University of Graz), Katherine Mahoney(Close Concerns (United States)), Boris Mankovsky, Umesh Masharani(University of California, San Francisco), Nestoras Mathioudakis(Johns Hopkins University), Alexander Yur'evich Mayorov(Endocrinology Research Center), Jordan Messler(Morton Plant Hospital), Joshua D. Miller(Stony Brook University), Viswanathan Mohan(Madras Diabetes Research Foundation), James H. Nichols(Vanderbilt University Medical Center), Kirsten Nørgaard(Steno Diabetes Centers), David N. O’Neal(The University of Melbourne), Francisco J. Pasquel(Emory University), Athena Philis‐Tsimikas(Scripps Whittier Diabetes Institute), Thomas R. Pieber(Medical University of Graz), Moshe Phillip(Tel Aviv University), William H. Polonsky, Rodica Pop‐Busui(University of Michigan), Gerry Rayman(University of East Anglia), Eun‐Jung Rhee(Kangbuk Samsung Hospital), Steven J. Russell(Massachusetts General Hospital), Viral N. Shah(University of Colorado Anschutz Medical Campus), Jennifer L. Sherr(Yale University), Koji Sode(University of North Carolina at Chapel Hill), Elias K. Spanakis(University of Maryland, Baltimore), Deborah J. Wake(University of Edinburgh), Kayo Waki(The University of Tokyo), Amisha Wallia(Northwestern University), Melissa E. Weinberg(California Pacific Medical Center), Howard Wolpert(Boston Medical Center), Eugene E. Wright, Mihail Zilbermint(Johns Hopkins University), Boris Kovatchev(University of Virginia)
Journal of Diabetes Science and Technology
March 29, 2022
10.1177/19322968221085273
Cited by 271Open Access
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Abstract

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.

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