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A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings
Open accessAbstract
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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“In fact, CGM supports people with DM to optimize their therapy, diet, and activity, facilitating improved HbA1c, increased time in target range of 70 to 180 mg/dL, reduced time below range (<70 mg/dL), and improved Glycemia Risk Index scores.5-11”
From Importance of FDA-integrated continuous glucose monitors to ensure accuracy of continuous glucose monitoring (2025) · cites this paper as [9]
Experimental — accuracy not yet measuredIn the citing paper
“Continuous glucose monitoring (CGM) has been shown to improve glycemic control and self-monitoring, as well as to reduce the risk of hypoglycemia.”
From Importance of FDA-integrated continuous glucose monitors to ensure accuracy of continuous glucose monitoring (2025) · cites this paper as [9]
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Cites
Regularization Paths for Generalized Linear Models via Coordinate Descent
Friedman, J., Hastie, T., & Tibshirani, R. (2010) · Journal of Statistical Software · doi:10.18637/jss.v033.i01 · Cited by 19,927
Gene selection for cancer classification using support vector machines
Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002) · Machine Learning · doi:10.1023/a:1012487302797 · Cited by 9,954
Feature Selection with the Boruta Package
Kursa, M. B., & Rudnicki, W. R. (2010) · Journal of Statistical Software · doi:10.18637/jss.v036.i11 · Cited by 5,659
Draper, N. R., & Smith, H. (1998) · Wiley series in probability and statistics · doi:10.1002/9781118625590 · Cited by 5,086
Battelino, T., Danne, T., Bergenstal, R. M., Amiel, S. A., Beck, R., Biester, T., Bosi, E., Buckingham, B. A., Cefalu, W. T., Close, K. L., et al. (2019) · Diabetes Care · doi:10.2337/dci19-0028 · Cited by 4,237
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Beck, R. W., Riddlesworth, T., Ruedy, K., Ahmann, A., Bergenstal, R., Haller, S., Kollman, C., Kruger, D., McGill, J. B., Polonsky, W., et al. (2017) · JAMA · doi:10.1001/jama.2016.19975 · Cited by 1,185
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Oriot, P., Prévost, G., Philips, J., kurz, N. K. D., & Hermans, M. P. (2025) · Journal of Endocrinological Investigation · doi:10.1007/s40618-025-02609-1 · Cited by 11
Dong, S., Wang, L., Zhao, C., Zhang, R., Gao, Z., Jiang, L., Guo, Y., Zhou, H., & Xu, S. (2023) · BMC Neurology · doi:10.1186/s12883-023-03242-2 · Cited by 11
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Castorani, V., Favalli, V., Rigamonti, A., Frontino, G., Tonno, R. D., Morotti, E., Sandullo, F., Scialabba, F., Arrigoni, F., Dionisi, B., et al. (2023) · Acta Diabetologica · doi:10.1007/s00592-023-02155-3 · Cited by 9
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Torimoto, K., Okada, Y., Mita, T., Tanaka, K., Sato, F., Katakami, N., Yoshii, H., Nishida, K., Tanaka, Y., Ishii, R., et al. (2025) · Journal of Diabetes · doi:10.1111/1753-0407.70065 · Cited by 9
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Metadata
- Authors
- Klonoff, D. C., Wang, J., Rodbard, D., Kohn, M. A., Li, C., Liepmann, D., Kerr, D., Ahn, D., Peters, A. L., Umpierrez, G. E., Seley, J. J., Xu, N. Y., Nguyen, K. T., Simonson, G., Agus, M. S. D., Al-Sofiani, M. E., Armaiz-Pena, G., Bailey, T. S., Basu, A., Battelino, T., Bekele, S. Y., Benhamou, P.-Y., Bequette, B. W., Blevins, T., Breton, M. D., Castle, J. R., Chase, J. G., Chen, K. Y., Choudhary, P., Clements, M. A., Close, K. L., Cook, C. B., Danne, T., Doyle, F. J., Drincic, A., Dungan, K. M., Edelman, S. V., Ejskjaer, N., Espinoza, J. C., Fleming, G. A., Forlenza, G. P., Freckmann, G., Galindo, R. J., Gomez, A. M., Gutow, H. A., Heinemann, L., Hirsch, I. B., Hoang, T. D., Hovorka, R., Jendle, J. H., Ji, L., Joshi, S. R., Joubert, M., Koliwad, S. K., Lal, R. A., Lansang, M. C., Lee, W.-A. (., Leelarathna, L., Leiter, L. A., Lind, M., Litchman, M. L., Mader, J. K., Mahoney, K. M., Mankovsky, B., Masharani, U., Mathioudakis, N. N., Mayorov, A., Messler, J., Miller, J. D., Mohan, V., Nichols, J. H., Nørgaard, K., O’Neal, D. N., Pasquel, F. J., Philis-Tsimikas, A., Pieber, T., Phillip, M., Polonsky, W. H., Pop-Busui, R., Rayman, G., Rhee, E.-J., Russell, S. J., Shah, V. N., Sherr, J. L., Sode, K., Spanakis, E. K., Wake, D. J., Waki, K., Wallia, A., Weinberg, M. E., Wolpert, H., Wright, E. E., Zilbermint, M., & Kovatchev, B.
- Affiliations
- San Mateo Medical Center (US)
- Florida State University (US)
- Biomedical Informatics Consultants LLC, Potomac, MD, USA
- University of California, San Francisco (US)
- University of California, Berkeley (US)
- Sansum Diabetes Research Institute (US)
- Hoag Memorial Hospital Presbyterian (US)
- University of Southern California (US)
- Emory University (US)
- Weill Cornell Medicine (US)
- Diabetes Technology Society (US)
- International Diabetes Center, Minneapolis, MN, USA
- Boston Children's Hospital (US)
- King Saud University, Riyadh, Saudi Arabia
- UT Health San Antonio, San Antonio, TX, USA
- AMCR Institute (US)
- University of Virginia (US)
- University of Ljubljana (SI)
- Addis Ababa University, Addis Ababa, Ethiopia
- Centre Hospitalier Universitaire de Grenoble (FR)
- Rensselaer Polytechnic Institute (US)
- Texas Diabetes & Endocrinology (US)
- Oregon Health & Science University (US)
- University of Canterbury (NZ)
- National Institute of Diabetes and Digestive and Kidney Diseases (US)
- University of Leicester (GB)
- Children's Mercy Hospital (US)
- Close Concerns (United States) (US)
- Mayo Clinic in Arizona (US)
- Medizinische Hochschule Hannover (DE)
- Harvard University (US)
- University of Nebraska at Omaha (US)
- The Ohio State University (US)
- University of California San Diego (US)
- Steno Diabetes Center North Denmark, Aalborg University Hospital, Aalborg, Denmark
- Kinexum, Harpers Ferry, WV, USA
- University of Colorado Health (US)
- Institut für Diabetes-Technologie (Germany) (DE)
- Pontificia Universidad Javeriana, Bogotá, Colombia
- Science Consulting in Diabetes GmbH, Kaarst, Germany
- University of Washington (US)
- Walter Reed National Military Medical Center (US)
- University of Cambridge (GB)
- Örebro University (SE)
- Peking University People's Hospital (CN)
- Joshi Clinic, Mumbai, India
- Caen University Hospital, Caen, France
- Stanford University (US)
- Cleveland Clinic (US)
- Los Angeles County Department of Health Services (US)
- University of Manchester (GB)
- St. Michael's Hospital (CA)
- University of Gothenburg (SE)
- University of Utah (US)
- Medical University of Graz (AT)
- National Healthcare University of Ukraine, Kiev, Ukraine
- Johns Hopkins University (US)
- Endocrinology Research Center (RU)
- Morton Plant Hospital (US)
- Stony Brook University (US)
- Madras Diabetes Research Foundation (IN)
- Vanderbilt University Medical Center (US)
- Steno Diabetes Center Copenhagen (DK)
- University of Melbourne, Melbourne, VIC, Australia
- Scripps Whittier Diabetes Institute, San Diego, CA, USA
- Tel Aviv University (IL)
- Behavioral Diabetes Institute, San Diego, CA, USA
- University of Michigan, Ann Arbor, MI, USA
- University of East Anglia (GB)
- Kangbuk Samsung Hospital (KR)
- Massachusetts General Hospital (US)
- Yale University (US)
- University of North Carolina at Chapel Hill (US)
- University of Maryland, Baltimore (US)
- University of Edinburgh (GB)
- The University of Tokyo (JP)
- Northwestern University (US)
- California Pacific Medical Center (US)
- Boston Medical Center (US)
- Charlotte AHEC, Charlotte, NC, USA
- Corresponding author
- Klonoff, David C.
- ORCID
- Klonoff, David C.
- Wang, Jing
- Rodbard, David
- Kohn, Michael A.
- Li, Chengdong
- Liepmann, Dorian
- Kerr, David
- Ahn, David
- Peters, Anne L.
- Umpierrez, Guillermo E.
- Seley, Jane Jeffrie
- Xu, Nicole Y.
- Nguyen, Kevin T.
- Simonson, Gregg
- Agus, Michael S. D.
- Al-Sofiani, Mohammed E.
- Armaiz-Pena, Gustavo
- Bailey, Timothy S.
- Basu, Ananda
- Battelino, Tadej
- Bekele, Sewagegn Yeshiwas
- Benhamou, Pierre-Yves
- Bequette, B. Wayne
- Blevins, Thomas
- Breton, Marc D.
- Castle, Jessica R.
- Chase, James Geoffrey
- Chen, Kong Y.
- Choudhary, Pratik
- Clements, Mark A.
- Close, Kelly L.
- Cook, Curtiss B.
- Danne, Thomas
- Doyle, Francis J.
- Drincic, Angela
- Dungan, Kathleen M.
- Edelman, Steven V.
- Ejskjaer, Niels
- Espinoza, Juan C.
- Fleming, G. Alexander
- Forlenza, Gregory P.
- Freckmann, Guido
- Galindo, Rodolfo J.
- Gomez, Ana Maria
- Gutow, Hanna A.
- Heinemann, Lutz
- Hirsch, Irl B.
- Hoang, Thanh D.
- Hovorka, Roman
- Jendle, Johan H.
- Ji, Linong
- Joshi, Shashank R.
- Joubert, Michael
- Koliwad, Suneil K.
- Lal, Rayhan A.
- Lansang, M. Cecilia
- Lee, Wei-An (Andy)
- Leelarathna, Lalantha
- Leiter, Lawrence A.
- Lind, Marcus
- Litchman, Michelle L.
- Mader, Julia K.
- Mahoney, Katherine M.
- Mankovsky, Boris
- Masharani, Umesh
- Mathioudakis, Nestoras N.
- Mayorov, Alexander
- Messler, Jordan
- Miller, Joshua D.
- Mohan, Viswanathan
- Nichols, James H.
- Nørgaard, Kirsten
- O’Neal, David N.
- Pasquel, Francisco J.
- Philis-Tsimikas, Athena
- Pieber, Thomas
- Phillip, Moshe
- Polonsky, William H.
- Pop-Busui, Rodica
- Rayman, Gerry
- Rhee, Eun-Jung
- Russell, Steven J.
- Shah, Viral N.
- Sherr, Jennifer L.
- Sode, Koji
- Spanakis, Elias K.
- Wake, Deborah J.
- Waki, Kayo
- Wallia, Amisha
- Weinberg, Melissa E.
- Wolpert, Howard
- Wright, Eugene E.
- Zilbermint, Mihail
- Kovatchev, Boris
- Venue
- Journal of Diabetes Science and Technology
- Publisher
- SAGE Publications
- Published
- 2022-03-29
- Volume
- 17
- Issue
- 5
- Pages
- 1226-1242
- ISSN
- 1932-2968 (ISSN-L)
- PMC
- PMC10563532
- OpenAlex
- W4221045506
- Cited by
- 295
- References
- 30
- Citations by year
- 2026: 58 · 2025: 81 · 2024: 90 · 2023: 50 · 2022: 14
- FWCI
- 43.55
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Diabetes Science and Technology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- eScholarship (California Digital Library) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- VBN Forskningsportal (Aalborg Universitet) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Funders
- U.S. Department of Veterans Affairs (I01 CX001825)
- Amgen
- Eli Lilly and Company
- Pfizer
- AstraZeneca
- Sanofi
- Insulet Corporation
- MannKind Corporation
- Dexcom
- Horizon Therapeutics
- Glenmark Pharmaceuticals
- Novo Nordisk
- Novo Nordisk Fonden (NNF17SA0031404-1)
- Servier
- Roche Diabetes Care
- National Institutes of Health (UL1TR000130, 5r01dk051562-23, DK098722, NIH P30 DK098722, UL1TR001855, UL1TR001863)
- U.S. Food and Drug Administration (P50FD006425)
- University of California, San Francisco
- Abbott Diabetes Care
- National Institute of Diabetes and Digestive and Kidney Diseases (R01-DK-051562, P30DK098722, K23DK123384, P30DK020572, P30DK111024, P30DK045735, P30DK111022)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- glycemia risk index, continuous glucose monitoring, hypoglycemia, hyperglycemia, time in range, ambulatory glucose profile, clinician ratings, insulin-treated diabetes
- MeSH terms
- Adult, Blood Glucose, Glucose, Humans, Hyperglycemia, Hypoglycemia, Blood Glucose Self-Monitoring
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