糖尿病技术协会血糖监测仪误差网格和趋势准确性矩阵。

IF 4.1 Q2 ENDOCRINOLOGY & METABOLISM Journal of Diabetes Science and Technology Pub Date : 2024-11-01 Epub Date: 2024-10-06 DOI:10.1177/19322968241275701
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":"糖尿病技术协会血糖监测仪误差网格和趋势准确性矩阵。","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":" ","pages":"1346-1361"},"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":"{\"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\":\" \",\"pages\":\"1346-1361\"},\"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}","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

摘要

介绍:误差格栅将测量的葡萄糖浓度与参考值进行比较,从而为观察到的误差赋予临床风险值。广泛使用的血糖监测仪(BGMs)误差网格的价值有限,因为它们不能同时反映连续血糖监测仪(CGMs)的临床准确性:糖尿病技术协会(DTS)召集了 89 位血糖监测领域的国际专家,目的是:(1) 简化监测误差网格(SEG)区域的边界,并创建一个用户友好型工具--DTS 误差网格;(2) 界定五个临床点准确性风险区域(A-E),使 BGM 和 CGM 的临床点准确性相同;(3) 通过分析 22 项 BGM 和 9 项 CGM 准确性研究,确定 A 区 DTS 误差网格百分比与平均绝对相对差值 (MARD) 之间的关系;以及 (4) 为 CGM 趋势准确性创建趋势风险类别(1-5)。结果:针对点准确度的 DTS 误差网格包含五个风险区域(A-E),其直线边界可适用于 BGM 和 CGM 准确度数据。在结合了 18 个 BGM 的点准确度数据的数据集中,2.6% 的数据对同样从 A 区移动到了 B 区,反之亦然(SEG 与 DTS 误差网格比较)。A 区数据百分比每增加 1%,误差平均值就会减少约 0.33%。我们还创建了一个 DTS 趋势准确性矩阵,将 CGM 报告的趋势指标与参考血糖计算出的参考趋势进行比较,得出五个趋势风险类别(1-5):DTS 误差网格结合了当代临床医生对血糖仪和 CGM 临床点准确性的意见。DTS 趋势准确性矩阵可评估 CGM 趋势指标的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors.

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Diabetes Science and Technology
Journal of Diabetes Science and Technology Medicine-Internal Medicine
CiteScore
7.50
自引率
12.00%
发文量
148
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.
期刊最新文献
Artificial Intelligence to Diagnose Complications of Diabetes. Is Continuous Glucose Monitoring Feasible in Tribal India? Navigating the Benefits and Overcoming the Challenges. Continuous Glucose Monitoring-Derived Glycemic Phenotyping of Childhood Hypoglycemia due to Hyperinsulinism: A Year-long Prospective Nationwide Observational Study. Diabetes Technology Use in Special Populations: A Narrative Review of Psychosocial Factors. Addressing Inequity in Continuous Glucose Monitoring Access: Leveraging the Hospital in the Continuum of Care.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1