Nina Jendrike, Manuel Eichenlaub, Manuela Link, Sükrü Öter, Anne Beltzer, Marta Gil Miró, Cornelia Haug, Jung Hee Seo, Moon Hwan Kim, Stefan Pleus, Guido Freckmann
{"title":"CareSens Air CGM系统手动和更新可选校准算法的性能比较分析。","authors":"Nina Jendrike, Manuel Eichenlaub, Manuela Link, Sükrü Öter, Anne Beltzer, Marta Gil Miró, Cornelia Haug, Jung Hee Seo, Moon Hwan Kim, Stefan Pleus, Guido Freckmann","doi":"10.1177/19322968251351318","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The CE-marked CareSens Air continuous glucose monitoring (CGM) system (CSAir) features a 15-day sensor lifetime, a 2-hour warm-up period and mandatory manual calibrations. During subsequent product development, the algorithm was updated to reduce the warm-up period to 30 minutes and make user-entered calibrations optional. This study compared the CSAir's performance between the manual and updated algorithms.</p><p><strong>Methods: </strong>Thirty adults with diabetes wore three CSAir sensors on their upper arms for 15 days. The study included three in-clinic sessions with capillary comparator measurements at 15-minute intervals over seven hours and glucose manipulation in the hypo- or hyperglycemic range. Point accuracy was assessed via mean absolute relative difference (MARD), 20/20 agreement rates (AR) stratified by BG range, and sensor wear time. Further evaluations included clinical point accuracy, alert reliability, technical reliability, safety and user satisfaction.</p><p><strong>Results: </strong>The CSAir's updated algorithm exhibited improved accuracy compared with the manual calibration algorithm, with a total 20/20 AR of 93.9% (vs 90.1%) and an MARD of 8.7% (vs 9.9%). Accuracy remained stable across measurement ranges and sensor lifetime. Diabetes Technology Society Error Grid analysis revealed high clinical accuracy, with 88.0% and 92.4% of data pairs in zone A for the manual and updated algorithms, respectively. The estimated survival probability was 88.8%. Participants reported positive user satisfaction. No safety concerns were identified.</p><p><strong>Conclusions: </strong>Both algorithms of CSAir demonstrated robust performance and reliability with improved accuracy with the updated version. The study results of the CSAir suggest its suitability for nonadjunctive use.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251351318"},"PeriodicalIF":3.7000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12226519/pdf/","citationCount":"0","resultStr":"{\"title\":\"Comparative Performance Analysis of Manual and Updated Optional Calibration Algorithms for the CareSens Air CGM System.\",\"authors\":\"Nina Jendrike, Manuel Eichenlaub, Manuela Link, Sükrü Öter, Anne Beltzer, Marta Gil Miró, Cornelia Haug, Jung Hee Seo, Moon Hwan Kim, Stefan Pleus, Guido Freckmann\",\"doi\":\"10.1177/19322968251351318\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The CE-marked CareSens Air continuous glucose monitoring (CGM) system (CSAir) features a 15-day sensor lifetime, a 2-hour warm-up period and mandatory manual calibrations. During subsequent product development, the algorithm was updated to reduce the warm-up period to 30 minutes and make user-entered calibrations optional. This study compared the CSAir's performance between the manual and updated algorithms.</p><p><strong>Methods: </strong>Thirty adults with diabetes wore three CSAir sensors on their upper arms for 15 days. The study included three in-clinic sessions with capillary comparator measurements at 15-minute intervals over seven hours and glucose manipulation in the hypo- or hyperglycemic range. Point accuracy was assessed via mean absolute relative difference (MARD), 20/20 agreement rates (AR) stratified by BG range, and sensor wear time. Further evaluations included clinical point accuracy, alert reliability, technical reliability, safety and user satisfaction.</p><p><strong>Results: </strong>The CSAir's updated algorithm exhibited improved accuracy compared with the manual calibration algorithm, with a total 20/20 AR of 93.9% (vs 90.1%) and an MARD of 8.7% (vs 9.9%). Accuracy remained stable across measurement ranges and sensor lifetime. Diabetes Technology Society Error Grid analysis revealed high clinical accuracy, with 88.0% and 92.4% of data pairs in zone A for the manual and updated algorithms, respectively. The estimated survival probability was 88.8%. Participants reported positive user satisfaction. No safety concerns were identified.</p><p><strong>Conclusions: </strong>Both algorithms of CSAir demonstrated robust performance and reliability with improved accuracy with the updated version. The study results of the CSAir suggest its suitability for nonadjunctive use.</p>\",\"PeriodicalId\":15475,\"journal\":{\"name\":\"Journal of Diabetes Science and Technology\",\"volume\":\" \",\"pages\":\"19322968251351318\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12226519/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Diabetes Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/19322968251351318\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"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/10.1177/19322968251351318","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Comparative Performance Analysis of Manual and Updated Optional Calibration Algorithms for the CareSens Air CGM System.
Background: The CE-marked CareSens Air continuous glucose monitoring (CGM) system (CSAir) features a 15-day sensor lifetime, a 2-hour warm-up period and mandatory manual calibrations. During subsequent product development, the algorithm was updated to reduce the warm-up period to 30 minutes and make user-entered calibrations optional. This study compared the CSAir's performance between the manual and updated algorithms.
Methods: Thirty adults with diabetes wore three CSAir sensors on their upper arms for 15 days. The study included three in-clinic sessions with capillary comparator measurements at 15-minute intervals over seven hours and glucose manipulation in the hypo- or hyperglycemic range. Point accuracy was assessed via mean absolute relative difference (MARD), 20/20 agreement rates (AR) stratified by BG range, and sensor wear time. Further evaluations included clinical point accuracy, alert reliability, technical reliability, safety and user satisfaction.
Results: The CSAir's updated algorithm exhibited improved accuracy compared with the manual calibration algorithm, with a total 20/20 AR of 93.9% (vs 90.1%) and an MARD of 8.7% (vs 9.9%). Accuracy remained stable across measurement ranges and sensor lifetime. Diabetes Technology Society Error Grid analysis revealed high clinical accuracy, with 88.0% and 92.4% of data pairs in zone A for the manual and updated algorithms, respectively. The estimated survival probability was 88.8%. Participants reported positive user satisfaction. No safety concerns were identified.
Conclusions: Both algorithms of CSAir demonstrated robust performance and reliability with improved accuracy with the updated version. The study results of the CSAir suggest its suitability for nonadjunctive use.
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.