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更新的软件,用于自动评估糖尿病患者的血糖变异性和血糖控制质量。

Updated Software for Automated Assessment of Glucose Variability and Quality of Glycemic Control in Diabetes.

机构信息

Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, València, Spain.

Diabetes Unit, Endocrinology and Nutrition Department, Hospital Clínic Universitari, IDIBAPS, Barcelona, Spain.

出版信息

Diabetes Technol Ther. 2020 Oct;22(10):701-708. doi: 10.1089/dia.2019.0416. Epub 2020 Apr 22.

Abstract

Glycemic variability is an important factor to consider in diabetes management. It can be assessed with multiple glycemic variability metrics and quality of control indices based on continuous glucose monitoring (CGM) recordings. For this, a robust repeatable calculation is important. A widely used tool for automated assessment is the EasyGV software. The aim of this work is to implement new methods of glycemic variability assessment in EasyGV and to validate implementation of each glucose metric in EasyGV against a reference implementation of the calculations. Validation data used came from the JDRF CGM study. Validation of the implementation of metrics that are available in EasyGV software v9 was carried out and the following new methods were added and validated: personal glycemic state, index of glycemic control, times in ranges, and glycemic variability percentage. Reference values considered gold standard calculations were derived from MATLAB implementation of each metric. The Pearson correlation coefficient was above 0.98 for all metrics, except for mean amplitude of glycemic excursion ( = 0.87) as EasyGV implements a fuzzy logic approach to assessment of variability. Bland-Altman plots demonstrated validation of the new software. The new freely available EasyGV software v10 (www.phc.ox.ac.uk/research/technology-outputs/easygv) is a validated robust tool for analyzing different glycemic variabilities and control metrics.

摘要

血糖变异性是糖尿病管理中需要考虑的一个重要因素。它可以通过多种血糖变异性指标和基于连续血糖监测 (CGM) 记录的质量控制指数来评估。为此,稳健可重复的计算非常重要。一种广泛使用的自动评估工具是 EasyGV 软件。本工作的目的是在 EasyGV 中实现新的血糖变异性评估方法,并针对 EasyGV 中每种血糖指标的实现,针对计算的参考实现来验证其实施。验证使用的数据来自 JDRF CGM 研究。对 EasyGV 软件 v9 中可用指标的实施进行了验证,并添加和验证了以下新方法:个人血糖状态、血糖控制指数、范围时间和血糖变异性百分比。被认为是金标准计算的参考值是从每个指标的 MATLAB 实现中得出的。除了平均血糖波动幅度( = 0.87)外,所有指标的 Pearson 相关系数均高于 0.98,因为 EasyGV 采用模糊逻辑方法来评估变异性。Bland-Altman 图证明了新软件的验证。新的免费可用的 EasyGV 软件 v10(www.phc.ox.ac.uk/research/technology-outputs/easygv)是一种经过验证的强大工具,可用于分析不同的血糖变异性和控制指标。

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本文引用的文献

1
cgmanalysis: An R package for descriptive analysis of continuous glucose monitor data.
PLoS One. 2019 Oct 11;14(10):e0216851. doi: 10.1371/journal.pone.0216851. eCollection 2019.
5
Metrics for glycaemic control - from HbA to continuous glucose monitoring.
Nat Rev Endocrinol. 2017 Jul;13(7):425-436. doi: 10.1038/nrendo.2017.3. Epub 2017 Mar 17.
7
Utility of different glycemic control metrics for optimizing management of diabetes.
World J Diabetes. 2015 Feb 15;6(1):17-29. doi: 10.4239/wjd.v6.i1.17.
8
Glycemic variability is higher in type 1 diabetes patients with microvascular complications irrespective of glycemic control.
Diabetes Technol Ther. 2014 Apr;16(4):198-203. doi: 10.1089/dia.2013.0205. Epub 2014 Jan 8.
9
Poor agreement of computerized calculators for mean amplitude of glycemic excursions.
Diabetes Technol Ther. 2014 Feb;16(2):72-5. doi: 10.1089/dia.2013.0138. Epub 2013 Nov 5.
10
Glucose variability.
Diabetes. 2013 May;62(5):1398-404. doi: 10.2337/db12-1396.

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