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Continuous Glucose Monitoring: 40 Years, What We've Learned What's Next
RISE., Swedish ICT, Acreo.
2013 (Engelska)Ingår i: ChemPhysChem, ISSN 1439-4235, E-ISSN 1439-7641, Vol. 14, nr 10, s. 2032-2044Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

After 40 years of research development, today continuous glucose monitoring (CGM) is demonstrating the benefit it provides for millions with diabetes. To provide in vivo accuracy, new permselective membranes mediated systems have been developed to prevent enzyme saturation to minimize interference signals. Early in vivo implanted sensor research clearly showed that the foreign body response was a more difficult issue to overcome. Understanding the biological interface circumventing the inflammatory response continue to drive development of a CGM sensor with accuracy reliability performance suitable in a closed-loop artificial pancreas. Along with biocompatible polymer development, other complimentary algorithm data analysis techniques have improved the performance of commercial systems significantly. For example, the mean average relative difference of Dexcom€™s CGM system improved from 26 to 14€‰% its use-life was extended from 3 to 7 d. Significant gains in usability, including size, flexibility, insertion, calibration, data interface, have been incorporated into new generations of commercial CGM systems. Besides Medtronic, Dexcom, Abbott, other major players are also investing in CGM. Becton Dickinson is conducting clinical trials with an optical galactose glucose binding system. Development of fully implanted sensor systems fulfills the desire for a discreet, reliable CGM system. Research continues to find innovative ways to help make living with diabetes easier more normal, new segments are being pursued (intensive care unit, surgery, behavior modification) in which CGM is being utilized.

Ort, förlag, år, upplaga, sidor
2013. Vol. 14, nr 10, s. 2032-2044
Nyckelord [en]
biocompatibility, carbohydrates, electrochemistry, glucose, optical detection
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:ri:diva-31969DOI: 10.1002/cphc.201300172Scopus ID: 2-s2.0-84880941916OAI: oai:DiVA.org:ri-31969DiVA, id: diva2:1151827
Tillgänglig från: 2017-10-24 Skapad: 2017-10-24 Senast uppdaterad: 2020-12-01Bibliografiskt granskad

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