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

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    Author
    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
    Show allShow less

    Date
    2022-03-29
    Journal
    Journal of Diabetes Science and Technology
    Publisher
    SAGE Publications Inc.
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.1177/19322968221085273
    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.
    Keyword
    ambulatory glucose profile
    composite metric
    continuous glucose monitor
    diabetes
    glycemia risk index
    hyperglycemia
    hypoglycemia
    time in range
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/18597
    ae974a485f413a2113503eed53cd6c53
    10.1177/19322968221085273
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