Literature DB >> 23439158

Acute in vivo performance evaluation of the fluorescence affinity sensor in the intravascular and interstitial space in Swine.

Ralph Dutt-Ballerstadt1, Colton Evans, Arun P Pillai, Ashok Gowda, Roger McNichols, Jesse Rios, William Cohn.   

Abstract

OBJECTIVE: We assessed and compared the performance levels of a fiber-coupled fluorescence affinity sensor (FAS) for glucose detection in the intradermal tissue and intravascular bed during glucose clamping and insulin administration in a large animal model. RESEARCH DESIGN AND METHODS: The FAS (BioTex Inc., Houston, TX) was implanted in interstitial tissue and in the intravenous space in nondiabetic, anesthetized pigs over 6-7 h. For intradermal assessment, a needle-type FAS was implanted in the upper back using a hypodermic needle. For intravenous assessment, the FAS was inserted through a catheter into the femoral artery and vein. Blood glucose changes were induced by infusion of dextrose and insulin through a catheterized ear or jugular vein.
RESULTS: Based on retrospective analysis, the mean absolute relative error (MARE) of the sensor in blood and interstitial tissue was 11.9% [standard deviation (SD) = ± 9.6%] and 23.8% (SD = ± 19.4%), respectively. When excluding data sets from sensors that were affected by exogenous insulin, the MARE for those sensors tested in interstitial tissue was reduced to 16.3% (SD = ± 12.5%).
CONCLUSIONS: The study demonstrated that the performance level of the FAS device implanted in interstitial tissue and blood can be very high. However, under certain circumstances, exogenous insulin caused the glucose concentration in interstitial tissue to be lower than in blood, which resulted in an overall lower level of accuracy of the FAS device. How significant this physiological effect is in insulin-treated persons with diabetes remains to be seen. In contrast, the level of accuracy of the FAS device in blood was very high because of high mass transfer conditions in blood. While the use of the FAS in both body sites will need further validation, its application in critically ill patients looks particularly promising.
© 2013 Diabetes Technology Society.

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Year:  2013        PMID: 23439158      PMCID: PMC3692214          DOI: 10.1177/193229681300700105

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  37 in total

1.  Fluorescence resonance energy transfer-based near-infrared fluorescence sensor for glucose monitoring.

Authors:  Ralph Ballerstadt; Ashok Gowda; Roger McNichols
Journal:  Diabetes Technol Ther       Date:  2004-04       Impact factor: 6.118

Review 2.  Continuous glucose monitoring: roadmap for 21st century diabetes therapy.

Authors:  David C Klonoff
Journal:  Diabetes Care       Date:  2005-05       Impact factor: 19.112

3.  Fluorescent nano-optodes for glucose detection.

Authors:  Kelvin Billingsley; Mary K Balaconis; J Matthew Dubach; Ning Zhang; Ed Lim; Kevin P Francis; Heather A Clark
Journal:  Anal Chem       Date:  2010-05-01       Impact factor: 6.986

4.  A fluorescence-based glucose biosensor using concanavalin A and dextran encapsulated in a poly(ethylene glycol) hydrogel.

Authors:  R J Russell; M V Pishko; C C Gefrides; M J McShane; G L Coté
Journal:  Anal Chem       Date:  1999-08-01       Impact factor: 6.986

5.  In vivo performance evaluation of a transdermal near- infrared fluorescence resonance energy transfer affinity sensor for continuous glucose monitoring.

Authors:  Ralph Ballerstadt; Colton Evans; Ashok Gowda; Roger McNichols
Journal:  Diabetes Technol Ther       Date:  2006-06       Impact factor: 6.118

6.  A bihormonal closed-loop artificial pancreas for type 1 diabetes.

Authors:  Firas H El-Khatib; Steven J Russell; David M Nathan; Robert G Sutherlin; Edward R Damiano
Journal:  Sci Transl Med       Date:  2010-04-14       Impact factor: 17.956

7.  Protracted glucose fall in subcutaneous adipose tissue and skeletal muscle compared with blood during insulin-induced hypoglycaemia.

Authors:  E Moberg; E Hagström-Toft; P Arner; J Bolinder
Journal:  Diabetologia       Date:  1997-11       Impact factor: 10.122

8.  Feasibility of automating insulin delivery for the treatment of type 1 diabetes.

Authors:  Garry M Steil; Kerstin Rebrin; Christine Darwin; Farzam Hariri; Mohammed F Saad
Journal:  Diabetes       Date:  2006-12       Impact factor: 9.461

9.  Early postoperative glucose control predicts nosocomial infection rate in diabetic patients.

Authors:  J J Pomposelli; J K Baxter; T J Babineau; E A Pomfret; D F Driscoll; R A Forse; B R Bistrian
Journal:  JPEN J Parenter Enteral Nutr       Date:  1998 Mar-Apr       Impact factor: 4.016

10.  Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients.

Authors:  James Stephen Krinsley
Journal:  Mayo Clin Proc       Date:  2003-12       Impact factor: 7.616

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  2 in total

1.  Thirty-fifth anniversary of the optical affinity sensor for glucose: a personal retrospective.

Authors:  Jerome S Schultz
Journal:  J Diabetes Sci Technol       Date:  2014-09-30

2.  Generation of an immortalized mesenchymal stem cell line producing a secreted biosensor protein for glucose monitoring.

Authors:  Evangelia K Siska; Itamar Weisman; Jacob Romano; Zoltán Ivics; Zsuzsanna Izsvák; Uriel Barkai; Spyros Petrakis; George Koliakos
Journal:  PLoS One       Date:  2017-09-26       Impact factor: 3.240

  2 in total

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