用于分析 1 型糖尿病患者连续血糖监测数据的计算统计软件包与参考软件 "非卧床血糖曲线 "的比较。

IF 5.7 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Kagan E Karakus, Janet K Snell-Bergeon, Halis K Akturk
{"title":"用于分析 1 型糖尿病患者连续血糖监测数据的计算统计软件包与参考软件 \"非卧床血糖曲线 \"的比较。","authors":"Kagan E Karakus, Janet K Snell-Bergeon, Halis K Akturk","doi":"10.1089/dia.2024.0410","DOIUrl":null,"url":null,"abstract":"<p><p><b><i>Objective:</i></b> To compare the accuracy of commonly used continuous glucose monitoring (CGM) analysis programs with ambulatory glucose profile (AGP) and Dexcom Clarity (DC) in analyzing CGM metrics in patients with type 1 diabetes (T1D). <b><i>Research Methods:</i></b> CGM data up to 90 days from 152 adults using the same CGM and automated insulin delivery system with T1D were collected. Six of the 19 CGM analysis programs (CDGA, cgmanalysis, Glyculator, iglu, EasyGV, and GLU) were selected to compare with AGP and DC. Metrics were compared etween all tools with two one-sided <i>t</i>-tests equivalence testing. For the equivalence test, the acceptable range of deviation was set as ±2 mg/dL for mean glucose, ±2% for time in range (TIR), ±1% for time above range (TAR), time above range level 1 (TAR1), time above range level 2 (TAR2), and coefficient of variation (CV). <b><i>Results:</i></b> All packages were compared with each other for all CGM metrics, and most of them had statistically significant differences for at least some metrics. All tools were equivalent to AGP for mean glucose, TIR, TAR, TAR1, and TAR2 within ±2 mg/dL, ±2%, ±1%, ±1% and 1%, respectively. CDGA, Glyculator, cgmanalysis, and iglu were not equivalent to AGP for CV within ±1%. All tools were equivalent to DC for mean glucose, TIR, and TAR2 within ±2 mg/dL, ±2%, and ±1%, respectively. Glyculator was not equivalent for TAR1, TAR, and CV. CGDA, cgmanalysis, and iglu were not equivalent to DC for TAR1 and TAR. EasyGV and GLU were not equivalent for TAR within ±1%. <b><i>Conclusions:</i></b> CGM analysis programs reported CGM metrics statistically differently, but these differences may not be applicable in clinical practice. The equivalence test also confirmed that the differences are negligible for TIR and mean glucose, while they can be important for hyperglycemic ranges and CV. A standardization for CGM data handling and analysis is necessary for clinical studies reporting CGM-generated outcomes.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.7000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of Computational Statistical Packages for the Analysis of Continuous Glucose Monitoring Data with a Reference Software, \\\"Ambulatory Glucose Profile,\\\" in Type 1 Diabetes.\",\"authors\":\"Kagan E Karakus, Janet K Snell-Bergeon, Halis K Akturk\",\"doi\":\"10.1089/dia.2024.0410\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b><i>Objective:</i></b> To compare the accuracy of commonly used continuous glucose monitoring (CGM) analysis programs with ambulatory glucose profile (AGP) and Dexcom Clarity (DC) in analyzing CGM metrics in patients with type 1 diabetes (T1D). <b><i>Research Methods:</i></b> CGM data up to 90 days from 152 adults using the same CGM and automated insulin delivery system with T1D were collected. Six of the 19 CGM analysis programs (CDGA, cgmanalysis, Glyculator, iglu, EasyGV, and GLU) were selected to compare with AGP and DC. Metrics were compared etween all tools with two one-sided <i>t</i>-tests equivalence testing. For the equivalence test, the acceptable range of deviation was set as ±2 mg/dL for mean glucose, ±2% for time in range (TIR), ±1% for time above range (TAR), time above range level 1 (TAR1), time above range level 2 (TAR2), and coefficient of variation (CV). <b><i>Results:</i></b> All packages were compared with each other for all CGM metrics, and most of them had statistically significant differences for at least some metrics. All tools were equivalent to AGP for mean glucose, TIR, TAR, TAR1, and TAR2 within ±2 mg/dL, ±2%, ±1%, ±1% and 1%, respectively. CDGA, Glyculator, cgmanalysis, and iglu were not equivalent to AGP for CV within ±1%. All tools were equivalent to DC for mean glucose, TIR, and TAR2 within ±2 mg/dL, ±2%, and ±1%, respectively. Glyculator was not equivalent for TAR1, TAR, and CV. CGDA, cgmanalysis, and iglu were not equivalent to DC for TAR1 and TAR. EasyGV and GLU were not equivalent for TAR within ±1%. <b><i>Conclusions:</i></b> CGM analysis programs reported CGM metrics statistically differently, but these differences may not be applicable in clinical practice. The equivalence test also confirmed that the differences are negligible for TIR and mean glucose, while they can be important for hyperglycemic ranges and CV. A standardization for CGM data handling and analysis is necessary for clinical studies reporting CGM-generated outcomes.</p>\",\"PeriodicalId\":11159,\"journal\":{\"name\":\"Diabetes technology & therapeutics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2024-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Diabetes technology & therapeutics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1089/dia.2024.0410\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes technology & therapeutics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1089/dia.2024.0410","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0

摘要

目的比较常用的连续血糖监测(CGM)分析程序与非卧床血糖档案(AGP)和 Dexcom Clarity(DC)在分析 1 型糖尿病(T1D)患者 CGM 指标方面的准确性。研究方法:收集了 152 名使用相同 CGM 和胰岛素自动给药系统的 1 型糖尿病成人长达 90 天的 CGM 数据。从 19 种 CGM 分析程序(CDGA、cgmanalysis、Glyculator、iglu、EasyGV 和 GLU)中选出六种与 AGP 和 DC 进行比较。所有工具之间的指标比较均采用两个单侧 t 检验等效测试。在等效测试中,平均血糖的可接受偏差范围为±2 mg/dL,在量程内的时间(TIR)为±2%,超过量程的时间(TAR)为±1%,超过量程 1 级的时间(TAR1)、超过量程 2 级的时间(TAR2)和变异系数(CV)为±1%。结果:对所有 CGM 指标对所有软件包进行了比较,其中大多数软件包至少在某些指标上有显著的统计学差异。所有工具的平均血糖、TIR、TAR、TAR1 和 TAR2 分别在 ±2 mg/dL、±2%、±1%、±1% 和 1% 的范围内与 AGP 相当。CDGA、Glyculator、cgmanalysis 和 iglu 的 CV 值在±1%以内,不等同于 AGP。在平均血糖、TIR 和 TAR2 方面,所有工具与 DC 的等效结果分别为 ±2 mg/dL、±2% 和 ±1%。Glyculator 对 TAR1、TAR 和 CV 的测量结果不等同。就 TAR1 和 TAR 而言,CGDA、cgmanalysis 和 iglu 与 DC 不等效。EasyGV 和 GLU 在 ±1% 的范围内与 TAR 的等效。结论:CGM 分析程序报告的 CGM 指标在统计学上存在差异,但这些差异可能不适用于临床实践。等效性测试还证实,TIR 和平均血糖的差异可以忽略不计,而高血糖范围和 CV 的差异可能很重要。对于报告 CGM 生成结果的临床研究来说,有必要对 CGM 数据处理和分析进行标准化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Computational Statistical Packages for the Analysis of Continuous Glucose Monitoring Data with a Reference Software, "Ambulatory Glucose Profile," in Type 1 Diabetes.

Objective: To compare the accuracy of commonly used continuous glucose monitoring (CGM) analysis programs with ambulatory glucose profile (AGP) and Dexcom Clarity (DC) in analyzing CGM metrics in patients with type 1 diabetes (T1D). Research Methods: CGM data up to 90 days from 152 adults using the same CGM and automated insulin delivery system with T1D were collected. Six of the 19 CGM analysis programs (CDGA, cgmanalysis, Glyculator, iglu, EasyGV, and GLU) were selected to compare with AGP and DC. Metrics were compared etween all tools with two one-sided t-tests equivalence testing. For the equivalence test, the acceptable range of deviation was set as ±2 mg/dL for mean glucose, ±2% for time in range (TIR), ±1% for time above range (TAR), time above range level 1 (TAR1), time above range level 2 (TAR2), and coefficient of variation (CV). Results: All packages were compared with each other for all CGM metrics, and most of them had statistically significant differences for at least some metrics. All tools were equivalent to AGP for mean glucose, TIR, TAR, TAR1, and TAR2 within ±2 mg/dL, ±2%, ±1%, ±1% and 1%, respectively. CDGA, Glyculator, cgmanalysis, and iglu were not equivalent to AGP for CV within ±1%. All tools were equivalent to DC for mean glucose, TIR, and TAR2 within ±2 mg/dL, ±2%, and ±1%, respectively. Glyculator was not equivalent for TAR1, TAR, and CV. CGDA, cgmanalysis, and iglu were not equivalent to DC for TAR1 and TAR. EasyGV and GLU were not equivalent for TAR within ±1%. Conclusions: CGM analysis programs reported CGM metrics statistically differently, but these differences may not be applicable in clinical practice. The equivalence test also confirmed that the differences are negligible for TIR and mean glucose, while they can be important for hyperglycemic ranges and CV. A standardization for CGM data handling and analysis is necessary for clinical studies reporting CGM-generated outcomes.

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
Diabetes technology & therapeutics
Diabetes technology & therapeutics 医学-内分泌学与代谢
CiteScore
10.60
自引率
14.80%
发文量
145
审稿时长
3-8 weeks
期刊介绍: Diabetes Technology & Therapeutics is the only peer-reviewed journal providing healthcare professionals with information on new devices, drugs, drug delivery systems, and software for managing patients with diabetes. This leading international journal delivers practical information and comprehensive coverage of cutting-edge technologies and therapeutics in the field, and each issue highlights new pharmacological and device developments to optimize patient 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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信