Literature DB >> 11831594

Determination of time delay between blood and interstitial adipose tissue glucose concentration change by microdialysis in healthy volunteers.

K J Wientjes1, A J Schoonen.   

Abstract

For the development and use of subcutaneous glucose sensors it is important to know the time lag between changes in blood glucose and subcutaneous interstitial glucose concentration. To determine the time lag we inserted a microdialysis probe into the abdominal subcutaneous adipose tissue of healthy volunteers (n = 19) and performed oral glucose tolerance tests (n = 39) over a 7-day period. After correction for the microdialysis system time lag, we compared the change in dialysate glucose concentration with the capillary blood glucose concentration. We found no significant delay time between a change in capillary blood glucose concentration and subcutaneous interstitial fluid glucose concentration using the Mann-Whitney test. The substantial interindividual variation of glucose recovery and the changing recovery in time makes it difficult to draw unambiguous conclusions about the exact physiological time lag. Based on the present experimental findings and theoretical calculations of glucose transport in adipose tissue, the physiological lag time is short and negligible compared to the system delay time of a glucose sensor.

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Year:  2001        PMID: 11831594

Source DB:  PubMed          Journal:  Int J Artif Organs        ISSN: 0391-3988            Impact factor:   1.595


  15 in total

1.  Continuous glucose monitoring in subjects with type 1 diabetes: improvement in accuracy by correcting for background current.

Authors:  Joseph El Youssef; Jessica R Castle; Julia M Engle; Ryan G Massoud; W Kenneth Ward
Journal:  Diabetes Technol Ther       Date:  2010-09-30       Impact factor: 6.118

2.  Modeling Plasma-to-Interstitium Glucose Kinetics from Multitracer Plasma and Microdialysis Data.

Authors:  Michele Schiavon; Chiara Dalla Man; Simmi Dube; Michael Slama; Yogish C Kudva; Thomas Peyser; Ananda Basu; Rita Basu; Claudio Cobelli
Journal:  Diabetes Technol Ther       Date:  2015-08-27       Impact factor: 6.118

3.  Graphical and numerical evaluation of continuous glucose sensing time lag.

Authors:  Boris P Kovatchev; Devin Shields; Marc Breton
Journal:  Diabetes Technol Ther       Date:  2009-03       Impact factor: 6.118

4.  Analysis of the Accuracy and Performance of a Continuous Glucose Monitoring Sensor Prototype: An In-Silico Study Using the UVA/PADOVA Type 1 Diabetes Simulator.

Authors:  Marc D Breton; Rolf Hinzmann; Enrique Campos-Nañez; Susan Riddle; Michael Schoemaker; Guenther Schmelzeisen-Redeker
Journal:  J Diabetes Sci Technol       Date:  2016-12-13

5.  Development of a highly responsive needle-type glucose sensor using polyimide for a wearable artificial endocrine pancreas.

Authors:  Shinji Ichimori; Kenro Nishida; Seiya Shimoda; Taiji Sekigami; Yasuto Matsuo; Kenshi Ichinose; Motoaki Shichiri; Michiharu Sakakida; Eiichi Araki
Journal:  J Artif Organs       Date:  2006       Impact factor: 1.731

6.  Interstitial fluid glucose dynamics during insulin-induced hypoglycaemia.

Authors:  G M Steil; K Rebrin; F Hariri; S Jinagonda; S Tadros; C Darwin; M F Saad
Journal:  Diabetologia       Date:  2005-07-07       Impact factor: 10.122

7.  Assessing sensor accuracy for non-adjunct use of continuous glucose monitoring.

Authors:  Boris P Kovatchev; Stephen D Patek; Edward Andrew Ortiz; Marc D Breton
Journal:  Diabetes Technol Ther       Date:  2014-12-01       Impact factor: 6.118

8.  Diabetes: Models, Signals, and Control.

Authors:  Claudio Cobelli; Chiara Dalla Man; Giovanni Sparacino; Lalo Magni; Giuseppe De Nicolao; Boris P Kovatchev
Journal:  IEEE Rev Biomed Eng       Date:  2009-01-01

9.  Noninvasive glucose detection in human skin using wavelength modulated differential laser photothermal radiometry.

Authors:  Xinxin Guo; Andreas Mandelis; Bernard Zinman
Journal:  Biomed Opt Express       Date:  2012-10-29       Impact factor: 3.732

10.  Closed-loop artificial pancreas systems: physiological input to enhance next-generation devices.

Authors:  Yogish C Kudva; Rickey E Carter; Claudio Cobelli; Rita Basu; Ananda Basu
Journal:  Diabetes Care       Date:  2014       Impact factor: 19.112

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