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不同类型数据丢失对最佳连续血糖监测采样时间的影响。

Impact of Different Types of Data Loss on Optimal Continuous Glucose Monitoring Sampling Duration.

机构信息

Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.

Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom.

出版信息

Diabetes Technol Ther. 2022 Oct;24(10):749-753. doi: 10.1089/dia.2022.0093. Epub 2022 Jun 27.

Abstract

To determine if a longer duration of continuous glucose monitoring (CGM) sampling is needed to correctly assess the quality of glycemic control given different types of data loss. Data loss was generated in two different methods until the desired percentage of data loss (10-50%) was achieved with (1) eliminating random individual CGM values and (2) eliminating gaps of a predefined time length (1-5 h). For CGM metrics, days required to cross predetermined targets for median absolute percentage error (MdAPE) for the different data loss strategies were calculated and compared with current international consensus recommendation of >70% of optimal data sampling. Up to 90 days of CGM data from 291 adults with type 1 diabetes were analyzed. MdAPE threshold crossing remained virtually constant for random CGM data loss up to 50% for all CGM metrics. However, the MdAPE crossing threshold increased when losing data with longer gaps. For all CGM metrics assessed in our study (%T70-180, %T < 70, %T < 54, %T > 180, and %T > 250), up to 50% data loss in a random manner did not cause any significant change on optimal sampling duration; however, >30% of data loss in gaps up to 5 h required longer optimal sampling duration. Optimal sampling duration for CGM metrics depends on percentage of data loss as well as duration of data loss. International consensus recommendation for 70% CGM data adequacy is sufficient to report %T70-180 with 2 weeks of data without large data gaps.

摘要

为了确定在不同类型的数据丢失情况下,是否需要更长时间的连续血糖监测 (CGM) 采样才能正确评估血糖控制质量。通过两种不同的方法生成数据丢失,直到达到所需的数据丢失百分比(10-50%):(1)消除随机个体 CGM 值,(2)消除预定时间长度(1-5 小时)的间隙。对于 CGM 指标,计算了不同数据丢失策略达到中位数绝对百分比误差 (MdAPE) 预定目标所需的天数,并与当前国际共识推荐的 >70%最佳数据采样进行了比较。分析了来自 291 名 1 型糖尿病成年人的长达 90 天的 CGM 数据。对于所有 CGM 指标,随机 CGM 数据丢失达到 50%时,MdAPE 阈值交叉基本保持不变。然而,当丢失具有较长间隙的数据时,MdAPE 交叉阈值增加。在我们的研究中评估的所有 CGM 指标(%T70-180、%T < 70、%T < 54、%T > 180 和 %T > 250),以随机方式丢失高达 50%的数据不会对最佳采样持续时间造成任何显著变化;然而,长达 5 小时的间隙中丢失超过 30%的数据需要更长的最佳采样持续时间。CGM 指标的最佳采样持续时间取决于数据丢失的百分比和数据丢失的持续时间。70%CGM 数据充足的国际共识推荐足以在没有大的数据间隙的情况下使用 2 周的数据报告 %T70-180。

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