The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors.

Creator(s)

David C. Klonoff
Guido Freckmann
Stefan Pleus
Boris P. Kovatchev
David Kerr
Chui Cindy Tse
Chengdong Li
Michael S D Agus
Kathleen Dungan
Barbora Voglová Hagerf
Jan S. Krouwer
Wei-An Andy Lee
Shivani Misra
Sang Youl Rhee
Ashutosh Sabharwal
Jane Jeffrie Seley
Viral N. Shah
Nam K. Tran
Kayo Waki
Chris Worth
Tiffany Tian
Rachel E. Aaron
Keetan Rutledge
Cindy N. Ho
Alessandra T. Ayers
Amanda Adler
David T. Ahn
Halis Kaan Aktürk
Mohammed E. Al-Sofiani
Timothy S. Bailey
Matt Baker
Lia Bally
Raveendhara R. Bannuru
Elizabeth M. Bauer
Yong Mong Bee
Julia E. Blanchette
Eda Cengiz
James Geoffrey Chase
Kong Y. Chen
Daniel Cherñavvsky
Mark A. Clements, Children's Mercy HospitalFollow
Gerard L. Cote
Ketan K. Dhatariya
Andjela Drincic
Niels Ejskjaer
Juan Espinoza
Chiara Fabris
G Alexander Fleming
Monica A L Gabbay
Rodolfo J. Galindo
Ana María Gómez-Medina
Lutz Heinemann
Norbert Hermanns
Thanh Hoang
Sufyan Hussain
Peter G. Jacobs
Johan Jendle
Shashank R. Joshi
Suneil K. Koliwad
Rayhan A. Lal
Lawrence A. Leiter
Marcus Lind
Julia K. Mader
Alberto Maran
Umesh Masharani
Nestoras Mathioudakis
Michael McShane
Chhavi Mehta
Sun-Joon Moon
James H. Nichols
David N. O'Neal
Francisco J. Pasquel
Anne L. Peters
Andreas Pfützner
Rodica Pop-Busui
Pratistha Ranjitkar
Connie M. Rhee
David B. Sacks
Signe Schmidt
Simon M. Schwaighofer
Bin Sheng
Gregg D. Simonson
Koji Sode
Elias K. Spanakis
Nicole L. Spartano
Guillermo E. Umpierrez
Maryam Vareth
Hubert W. Vesper
Jing Wang
Eugene Wright
Alan H B Wu
Sewagegn Yeshiwas
Mihail Zilbermint
Michael A. Kohn

Document Type

Article

Publication Date

11-2024

Identifier

DOI: 10.1177/19322968241275701; PMCID: PMC11531029

Abstract

INTRODUCTION: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs).

METHODS: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy.

RESULTS: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose.

CONCLUSION: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.

Journal Title

J Diabetes Sci Technol

Volume

18

Issue

6

First Page

1346

Last Page

1361

MeSH Keywords

Humans; Blood Glucose Self-Monitoring; Blood Glucose; Diabetes Mellitus; Reproducibility of Results

Keywords

accuracy; blood glucose; continuous glucose monitoring; error grid; glucose trend; surveillance

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