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

被引:39
作者
Caduff, Andreas [1 ]
Mueller, Martin [1 ]
Megej, Alexander [1 ]
Dewarrat, Francois [1 ]
Suri, Roland E. [1 ]
Klisic, Jelena [1 ]
Donath, Marc [2 ]
Zakharov, Pavel [1 ]
Schaub, Dominik [1 ]
Stahel, Werner A. [3 ]
Talary, Mark S. [1 ]
机构
[1] Solianis Monitoring AG, CH-8050 Zurich, Switzerland
[2] Univ Zurich Hosp, Clin Endocrinol & Diabet, CH-8091 Zurich, Switzerland
[3] ETH, Seminar Stat, CH-8092 Zurich, Switzerland
关键词
Non invasive; Glucose; Multisensor; Perturbations; CGM; OPTICAL COHERENCE TOMOGRAPHY; DIELECTRIC-SPECTROSCOPY; BLOOD CONTENT; SENSOR; ERYTHROCYTE; SIMULATION; TYPE-1; SKIN;
D O I
10.1016/j.bios.2011.02.034
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
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 +/- 16y; BMI 24.1 +/- 1.3 kg/m(2), duration of diabetes 27 +/- 12y; 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. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:3794 / 3800
页数:7
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