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 Clements, 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
{"title":"The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors.","authors":"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 Clements, 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","doi":"10.1177/19322968241275701","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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).</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11531029/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Diabetes Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/19322968241275701","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/6 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍：
The Journal of Diabetes Science and Technology (JDST) is a bi-monthly, peer-reviewed scientific journal published by the Diabetes Technology Society. JDST covers scientific and clinical aspects of diabetes technology including glucose monitoring, insulin and metabolic peptide delivery, the artificial pancreas, digital health, precision medicine, social media, cybersecurity, software for modeling, physiologic monitoring, technology for managing obesity, and diagnostic tests of glycation. The journal also covers the development and use of mobile applications and wireless communication, as well as bioengineered tools such as MEMS, new biomaterials, and nanotechnology to develop new sensors. Articles in JDST cover both basic research and clinical applications of technologies being developed to help people with diabetes.
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