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多传感器无创血糖监测系统的特点:外部验证和前瞻性评估。

Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation.

机构信息

Solianis Monitoring AG, Leutschenbachstrasse 46, 8050 Zurich, Switzerland.

Clinic for Endocrinology and Diabetes, University Hospital Zurich, 8091 Zurich, Switzerland.

出版信息

Biosens Bioelectron. 2011 May 15;26(9):3794-800. doi: 10.1016/j.bios.2011.02.034. Epub 2011 Apr 13.

Abstract

The Multisensor Glucose Monitoring System (MGMS) features non invasive sensors for dielectric characterisation of the skin and underlying tissue in a wide frequency range (1 kHz-100 MHz, 1 and 2 GHz) as well as optical characterisation. In this paper we describe the results of using an MGMS in a miniaturised housing with fully integrated sensors and battery. Six patients with Type I Diabetes Mellitus (age 44±16 y; BMI 24.1±1.3 kg/m(2), duration of diabetes 27±12 y; HbA1c 7.3±1.0%) wore a single Multisensor at the upper arm position and performed a total of 45 in-clinic study days with 7 study days per patient on average (min. 5 and max. 10). Glucose changes were induced either orally or by i.v. glucose administration and the blood glucose was measured routinely. Several prospective data evaluation routines were applied to evaluate the data. The results are shown using one of the restrictive data evaluation routines, where measurements from the first 22 study days were used to train a linear regression model. The global model was then prospectively applied to the data of the remaining 23 study days to allow for an external validation of glucose prediction. The model application yielded a Mean Absolute Relative Difference of 40.8%, a Mean Absolute Difference of 51.9 mg dL(-1), and a correlation of 0.84 on average per study day. The Clarke error grid analyses showed 89.0% in A+B, 4.5% in C, 4.6% in D and 1.9% in the E region. Prospective application of a global, purely statistical model, demonstrates that glucose variations can be tracked non invasively by the MGMS in most cases under these conditions.

摘要

多传感器血糖监测系统 (MGMS) 采用非侵入式传感器,可在宽频率范围内 (1 kHz-100 MHz、1 和 2 GHz) 对皮肤和皮下组织进行介电特性以及光学特性分析。本文介绍了在具有完全集成传感器和电池的小型化外壳中使用 MGMS 的结果。六名 1 型糖尿病患者 (年龄 44±16 岁;BMI 24.1±1.3 kg/m(2),糖尿病病程 27±12 年;HbA1c 7.3±1.0%) 在手臂位置佩戴单个多传感器,总共进行了 45 次门诊研究,每位患者平均进行 7 天研究 (最少 5 天,最多 10 天)。血糖变化通过口服或静脉注射葡萄糖来诱导,常规测量血糖。应用了几种前瞻性数据评估例程来评估数据。结果使用其中一种限制性数据评估例程显示,前 22 天的测量值用于训练线性回归模型。然后,将全局模型前瞻性地应用于其余 23 天的数据,以允许对血糖预测进行外部验证。模型应用产生的平均绝对相对差异为 40.8%,平均绝对差异为 51.9 mg/dL(-1),平均相关系数为 0.84/天。Clarke 误差网格分析显示 A+B 区为 89.0%,C 区为 4.5%,D 区为 4.6%,E 区为 1.9%。在这些条件下,全局、纯统计模型的前瞻性应用表明,MGMS 可以在大多数情况下非侵入性地跟踪血糖变化。

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