Recording of subcutaneous glucose dynamics by a viscometric affinity sensor
Diabetologia(2001)
Disetronic Medical Systems GmbH
Abstract
Aims/hypothesis. To provide a nonenzymatic sensor for glucose monitoring in subcutaneous tissue. Methods. A continuously working affinity sensor based on the glucose-dependent viscosity of a sensitive liquid containing dextran and concanavalin A has been designed by arranging a microdialysis probe, two flow-resisting capillaries and two pressure transducers in a linear flow system. It allows synchronous processing of the viscosity of the sensitive liquid at the standard glucose concentration and the glucose concentration to be measured. In preliminary human trials the sensor was implanted into the subcutaneous tissue of the forearm and its read-out was compared with capillary blood concentrations. Results. In vitro, the viscometric sensor shows a linear and long-term stable dependence on the glucose concentration without detectable drift. At the applied flow rate of the sensitive liquid (about 5 μl/h) the technical delay is 5 to 10 min. The read-out of the implanted sensor followed the dynamics of the capillary blood glucose concentrations with a time-shift of 10 to 15 min but showed a systematic error when based on precalibration with polymer-free glucose solutions. After appropriate in vivo calibration, the read-out was in good or acceptable coincidence with capillary blood concentrations according to the error grid method and did not show any detectable reduction of sensitivity during the periods of measurement (up to 44 h). Conclusion/interpretion. The viscometric-affinity sensor is an efficient tool for current research on glucose monitoring in the subcutaneous tissue and can potentially be further developed for routine clinical use. [Diabetologia (2001) 44: 416–423]
MoreTranslated text
Key words
Keywords Concanavalin A,dextran,glucose monitoring,microdialysis probe,subcutaneous tissue,viscometric affinity sensor.
PDF
View via Publisher
AI Read Science
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined