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

Authors :
Klonoff DC
Wang J
Rodbard D
Kohn MA
Li C
Liepmann D
Kerr D
Ahn D
Peters AL
Umpierrez GE
Seley JJ
Xu NY
Nguyen KT
Simonson G
Agus MSD
Al-Sofiani ME
Armaiz-Pena G
Bailey TS
Basu A
Battelino T
Bekele SY
Benhamou PY
Bequette BW
Blevins T
Breton MD
Castle JR
Chase JG
Chen KY
Choudhary P
Clements MA
Close KL
Cook CB
Danne T
Doyle FJ 3rd
Drincic A
Dungan KM
Edelman SV
Ejskjaer N
Espinoza JC
Fleming GA
Forlenza GP
Freckmann G
Galindo RJ
Gomez AM
Gutow HA
Heinemann L
Hirsch IB
Hoang TD
Hovorka R
Jendle JH
Ji L
Joshi SR
Joubert M
Koliwad SK
Lal RA
Lansang MC
Lee WA
Leelarathna L
Leiter LA
Lind M
Litchman ML
Mader JK
Mahoney KM
Mankovsky B
Masharani U
Mathioudakis NN
Mayorov A
Messler J
Miller JD
Mohan V
Nichols JH
Nørgaard K
O'Neal DN
Pasquel FJ
Philis-Tsimikas A
Pieber T
Phillip M
Polonsky WH
Pop-Busui R
Rayman G
Rhee EJ
Russell SJ
Shah VN
Sherr JL
Sode K
Spanakis EK
Wake DJ
Waki K
Wallia A
Weinberg ME
Wolpert H
Wright EE
Zilbermint M
Kovatchev B
Source :
Journal of diabetes science and technology [J Diabetes Sci Technol] 2023 Sep; Vol. 17 (5), pp. 1226-1242. Date of Electronic Publication: 2022 Mar 29.
Publication Year :
2023

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.<br />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.<br />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.<br />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.

Details

Language :
English
ISSN :
1932-2968
Volume :
17
Issue :
5
Database :
MEDLINE
Journal :
Journal of diabetes science and technology
Publication Type :
Academic Journal
Accession number :
35348391
Full Text :
https://doi.org/10.1177/19322968221085273