Literature DB >> 19885132

Putative delays in interstitial fluid (ISF) glucose kinetics can be attributed to the glucose sensing systems used to measure them rather than the delay in ISF glucose itself.

Gayane Voskanyan1, D Barry Keenan, John J Mastrototaro, Garry M Steil.   

Abstract

BACKGROUND: Since the advent of subcutaneous glucose sensors, there has been intense focus on characterizing the delay in the interstitial fluid (ISF) glucose response and the effect of insulin to alter the plasma-to-ISF glucose gradient. The Medtronic MiniMed continuous glucose monitoring system (CGMS) has often been used for this purpose; however, many of the studies have used experimental conditions that fall outside its intended use, for example, studies that have assessed the delay during rapid glucose excursions brought about by intravenous infusion of glucose or insulin. Under these conditions, it is possible that the rate of glucose change may exceed that allowed by CGMS filtering routines. If so, the estimated delay may be because of the filter rather than the ISF. Also, sensor characteristics, such as nonspecific offset current or stability, may have been inadvertently attributed to changes in the plasma-to-ISF gradient. The potential for these issues to have confounded the understanding of ISF glucose delay and gradient is investigated.
METHODS: An in vitro preparation in which no delay or gradient exists between sensor and measurement solution was used to recreate a rapidly changing glucose profile from a previously published in vivo study. The CGMS system (N = 6 sensors) was then used to estimate any artifactual delay and gradient introduced by the system per se.
RESULTS: One-point calibration resulted in an apparent change in gradient as glucose was lowered from approximately 100 to 50 mg/dl. After a two-point calibration, sensor glucose followed the glucose profile as it was decreased slowly from approximately 100 to approximately 60 mg/dl; however, when the glucose level was subsequently increased rapidly to approximately 150 mg/dl, CGMS filtering routines limited the rate of change of sensor glucose and introduced a delay similar to that previously attributed to ISF glucose equilibration delay.
CONCLUSIONS: Studies that have previously used the Medtronic MiniMed CGMS system to assess changes in the plasma-to-ISF glucose gradient may need to be reassessed to ensure that the offset current was estimated accurately. Studies that have used the system to assess ISF glucose delay during rapid, unphysiologic changes in glucose and did not remove the CGMS smoothing filters may have attributed CGMS filter delay to ISF glucose equilibration.

Entities:  

Keywords:  CGMS; delay; glucose gradient; glucose sensor; interstitial fluid glucose; one-point calibration; two-point calibration

Year:  2007        PMID: 19885132      PMCID: PMC2769670          DOI: 10.1177/193229680700100507

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


  11 in total

1.  Do sensor glucose levels accurately predict plasma glucose concentrations during hypoglycemia and hyperinsulinemia?

Authors:  Teresa P Monsod; Daniel E Flanagan; Fran Rife; Rebecca Saenz; Sonia Caprio; Robert S Sherwin; William V Tamborlane
Journal:  Diabetes Care       Date:  2002-05       Impact factor: 19.112

2.  Determination of plasma glucose during rapid glucose excursions with a subcutaneous glucose sensor.

Authors:  Garry M Steil; Kerstin Rebrin; John Mastrototaro; Basem Bernaba; Mohammed F Saad
Journal:  Diabetes Technol Ther       Date:  2003       Impact factor: 6.118

3.  Development of a wearable glucose sensor; studies in healthy volunteers and in diabetic patients.

Authors:  A L Aalders; F J Schmidt; A J Schoonen; I R Broek; A G Maessen; H Doorenbos
Journal:  Int J Artif Organs       Date:  1991-02       Impact factor: 1.595

4.  Continuous glucose monitoring in interstitial subcutaneous adipose tissue and skeletal muscle reflects excursions in cerebral cortex.

Authors:  Jannik Kruse Nielsen; Christian Born Djurhuus; Claus Højbjerg Gravholt; Andreas Christiansen Carus; Jacob Granild-Jensen; Hans Orskov; Jens Sandahl Christiansen
Journal:  Diabetes       Date:  2005-06       Impact factor: 9.461

Review 5.  Does fall in tissue glucose precede fall in blood glucose?

Authors:  F Sternberg; C Meyerhoff; F J Mennel; H Mayer; F Bischof; E F Pfeiffer
Journal:  Diabetologia       Date:  1996-05       Impact factor: 10.122

6.  Strategies for calibrating a subcutaneous glucose sensor.

Authors:  G Velho; P Froguel; D R Thevenot; G Reach
Journal:  Biomed Biochim Acta       Date:  1989

7.  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

Review 8.  Can interstitial glucose assessment replace blood glucose measurements?

Authors:  K Rebrin; G M Steil
Journal:  Diabetes Technol Ther       Date:  2000       Impact factor: 6.118

9.  Continuous in vivo monitoring in diabetes: the subcutaneous glucose concentration.

Authors:  U Fischer
Journal:  Acta Anaesthesiol Scand Suppl       Date:  1995

10.  Timing of changes in interstitial and venous blood glucose measured with a continuous subcutaneous glucose sensor.

Authors:  Michael S Boyne; David M Silver; Joy Kaplan; Christopher D Saudek
Journal:  Diabetes       Date:  2003-11       Impact factor: 9.461

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  14 in total

1.  Continuous glucose monitoring: real-time algorithms for calibration, filtering, and alarms.

Authors:  B Wayne Bequette
Journal:  J Diabetes Sci Technol       Date:  2010-03-01

2.  Use of subcutaneous interstitial fluid glucose to estimate blood glucose: revisiting delay and sensor offset.

Authors:  Kerstin Rebrin; Norman F Sheppard; Garry M Steil
Journal:  J Diabetes Sci Technol       Date:  2010-09-01

3.  Clinical overview of continuous glucose monitoring.

Authors:  Bruce Buckingham
Journal:  J Diabetes Sci Technol       Date:  2008-03

4.  Accuracy performance of the Medtronic NexSensor™ for 6 days in an inpatient setting using abdomen and buttocks insertion sites.

Authors:  Tim Peoples; Timothy Bailey; Brazg Ronald; Howard C Zisser; Bob Janowski; Suiying Huang; Cary Talbot; Qingqing Yang
Journal:  J Diabetes Sci Technol       Date:  2011-03-01

5.  The correlation of hemoglobin A1c to blood glucose.

Authors:  Ken Sikaris
Journal:  J Diabetes Sci Technol       Date:  2009-05-01

6.  Mathematical modeling research to support the development of automated insulin-delivery systems.

Authors:  Garry M Steil; Jaques Reifman
Journal:  J Diabetes Sci Technol       Date:  2009-03-01

Review 7.  Delays in minimally invasive continuous glucose monitoring devices: a review of current technology.

Authors:  D Barry Keenan; John J Mastrototaro; Gayane Voskanyan; Garry M Steil
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

8.  Time lag of glucose from intravascular to interstitial compartment in type 1 diabetes.

Authors:  Ananda Basu; Simmi Dube; Sona Veettil; Michael Slama; Yogish C Kudva; Thomas Peyser; Rickey E Carter; Claudio Cobelli; Rita Basu
Journal:  J Diabetes Sci Technol       Date:  2014-10-10

9.  Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems.

Authors:  Cosimo Scuffi
Journal:  Eur Endocrinol       Date:  2014-02-28

10.  Continuous glucose monitoring: changing diabetes behavior in real time and retrospectively.

Authors:  Jennifer M Block
Journal:  J Diabetes Sci Technol       Date:  2008-05
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