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

  • Klonoff, David C. MD, FACP, FRCP (Edin), Fellow AIMBE
  • Freckmann, Guido MD
  • Pleus, Stefan PhD
  • Kovatchev, Boris P. PhD
  • Kerr, David MBChB, DM, FRCP, FRCPE
  • Tse, Chui (Cindy) MS
  • Li, Chengdong PhD
  • Agus, Michael S. D. MD
  • Dungan, Kathleen MD, MPH
  • Voglová Hagerf, Barbora MD
  • Krouwer, Jan S. PhD
  • Lee, Wei-An (Andy) DO
  • Misra, Shivani MBBS, BMedSci, MSc, PhD, FRCP
  • Rhee, Sang Youl MD, PhD
  • Sabharwal, Ashutosh PhD
  • Seley, Jane Jeffrie DNP, MPH, MSN, BSN
  • Shah, Viral N. MD
  • Tran, Nam K. PhD, MS, MAS
  • Waki, Kayo MD, MPH, PhD
  • Worth, Chris PhD, MBChB, BMedSci
  • Tian, Tiffany BA
  • Aaron, Rachel E. BA
  • Rutledge, Keetan BA
  • Ho, Cindy N. BA
  • Ayers, Alessandra T. BA
  • Adler, Amanda MD, PhD
  • Ahn, David T. MD
  • Aktürk, Halis Kaan MD
  • Al-Sofiani, Mohammed E. MD, MSc
  • Bailey, Timothy S. MD, FACE, CPI
  • Baker, Matt PharmD, MS
  • Bally, Lia MD, PhD
  • Bannuru, Raveendhara R. MD, PhD, FAGE
  • Bauer, Elizabeth M. MD, FACP
  • Bee, Yong Mong MBBS, MRCP(UK), FRCP Edin
  • Blanchette, Julia E. PhD, RN, BC-ADM, CDCES
  • Cengiz, Eda MD, MHS
  • Chase, James Geoffrey BS, MS, PhD
  • Y. Chen, Kong PhD, MSCI
  • Cherñavvsky, Daniel MD
  • Clements, Mark MD, PhD
  • Cote, Gerard L. PhD
  • Dhatariya, Ketan K. MBBS, MSc, MD, MS, FRCP, PhD
  • Drincic, Andjela MD
  • Ejskjaer, Niels MD, PhD
  • Espinoza, Juan MD
  • Fabris, Chiara PhD
  • Fleming, G. Alexander MD
  • Gabbay, Monica A. L. MD, PhD
  • Galindo, Rodolfo J. MD, FACE
  • Gómez-Medina, Ana María MD
  • Heinemann, Lutz PhD
  • Hermanns, Norbert PhD
  • Hoang, Thanh DO, FACP, FACE
  • Hussain, Sufyan MA, MB BChir, MRCP, PhD
  • Jacobs, Peter G. PhD
  • Jendle, Johan MD, PhD
  • Joshi, Shashank R. MD, DM, FRCP, MACE
  • Koliwad, Suneil K. MD, PhD
  • Lal, Rayhan A. MD
  • Leiter, Lawrence A. MD, FRCPC, FACP, FACE, FAHA, FACC
  • Lind, Marcus MD, PhD
  • Mader, Julia K. MD
  • Maran, Alberto MD, PhD
  • Masharani, Umesh MBBS
  • Mathioudakis, Nestoras MD, MHS
  • McShane, Michael BS, PhD
  • Mehta, Chhavi MD
  • Moon, Sun-Joon MD
  • Nichols, James H. PhD, DABCC, FADLM
  • O’Neal, David N. MD
  • Pasquel, Francisco J. MD, MPH
  • Peters, Anne L. MD
  • Pfützner, Andreas MD, PhD
  • Pop-Busui, Rodica MD, PhD
  • Ranjitkar, Pratistha PhD
  • Rhee, Connie M. MD, MSc
  • Sacks, David B. MB, ChB, FRCPath
  • Schmidt, Signe MD, PhD
  • Schwaighofer, Simon M. MD
  • Sheng, Bin PhD
  • Simonson, Gregg D. PhD
  • Sode, Koji PhD
  • Spanakis, Elias K. MD
  • Spartano, Nicole L. PhD
  • Umpierrez, Guillermo E. MD, CDCES, FACE, MACP
  • Vareth, Maryam PhD
  • Vesper, Hubert W. PhD
  • Wang, Jing PhD, MPH
  • Wright, Eugene MD
  • Wu, Alan H.B. PhD
  • Yeshiwas, Sewagegn MD
  • Zilbermint, Mihail MD, MBA, FACE
  • Kohn, Michael A. MD, MPP
Journal of Diabetes Science and Technology 18(6):p 1346-1361, November 2024. | DOI: 10.1177/19322968241275701

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.

Copyright ©2024Sage Publications
View full text|Download PDF