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

Creator(s)

David C. Klonoff
Jing Wang
David Rodbard
Michael A. Kohn
Chengdong Li
Dorian Liepmann
David Kerr
David Ahn
Anne L. Peters
Guillermo E. Umpierrez
Jane Jeffrie Seley
Nicole Y. Xu
Kevin T. Nguyen
Gregg Simonson
Michael S D Agus
Mohammed E. Al-Sofiani
Gustavo Armaiz-Pena
Timothy S. Bailey
Ananda Basu
Tadej Battelino
Sewagegn Yeshiwas Bekele
Pierre-Yves Benhamou
B Wayne Bequette
Thomas Blevins
Marc D. Breton
Jessica R. Castle
James Geoffrey Chase
Kong Y. Chen
Pratik Choudhary
Mark A. Clements, Children's Mercy HospitalFollow
Kelly L. Close
Curtiss B. Cook
Thomas Danne
Francis J. Doyle
Angela Drincic
Kathleen M. Dungan
Steven V. Edelman
Niels Ejskjaer
Juan C. Espinoza
G Alexander Fleming
Gregory P. Forlenza
Guido Freckmann
Rodolfo J. Galindo
Ana Maria Gomez
Hanna A. Gutow
Lutz Heinemann
Irl B. Hirsch
Thanh D. Hoang
Roman Hovorka
Johan H. Jendle
Linong Ji
Shashank R. Joshi
Michael Joubert
Suneil K. Koliwad
Rayhan A. Lal
M Cecilia Lansang
Wei-An Andy Lee
Lalantha Leelarathna
Lawrence A. Leiter
Marcus Lind
Michelle L. Litchman
Julia K. Mader
Katherine M. Mahoney
Boris Mankovsky
Umesh Masharani
Nestoras N. Mathioudakis
Alexander Mayorov
Jordan Messler
Joshua D. Miller
Viswanathan Mohan
James H. Nichols
Kirsten Nørgaard
David N. O'Neal
Francisco J. Pasquel
Athena Philis-Tsimikas
Thomas Pieber
Moshe Phillip
William H. Polonsky
Rodica Pop-Busui
Gerry Rayman
Eun-Jung Rhee
Steven J. Russell
Viral N. Shah
Jennifer L. Sherr
Koji Sode
Elias K. Spanakis
Deborah J. Wake
Kayo Waki
Amisha Wallia
Melissa E. Weinberg
Howard Wolpert
Eugene E. Wright
Mihail Zilbermint
Boris Kovatchev

Document Type

Article

Publication Date

9-2023

Identifier

DOI: 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.

Journal Title

J Diabetes Sci Technol

Volume

17

Issue

5

First Page

1226

Last Page

1242

MeSH Keywords

Adult; Humans; Blood Glucose; Blood Glucose Self-Monitoring; Hypoglycemia; Hyperglycemia; Glucose

Keywords

ambulatory glucose profile; composite metric; continuous glucose monitor; diabetes; glycemia risk index; hyperglycemia; hypoglycemia; time in range

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