Literature DB >> 19756217

Modeling of Calibration Effectiveness and Blood-to-Interstitial Glucose Dynamics as Potential Confounders of the Accuracy of Continuous Glucose Sensors during Hyperinsulinemic Clamp.

Christopher King1, Stacey M Anderson, Marc Breton, William L Clarke, Boris P Kovatchev.   

Abstract

BACKGROUND: Models of the dynamics of interstitial fluid-based continuous glucose sensors imply a variable sensor deviation from reference blood glucose (BG), depending on both sensor calibration procedure and BG dynamics. These effects could have a significant effect on the cross-interpretation of nonidentical accuracy studies.
METHODS: Hyperinsulinemic euglycemic and hypoglycemic clamps were performed on 39 subjects with type 1 diabetes wearing the Medtronic Continuous Glucose Monitoring System®. Sensor calibration and interstitial glucose (IG) dynamics were modeled and analyzed as potential confounders of sensor deviation from reference BG.
RESULTS: The mean absolute deviation (MAD) of sensor data was 20.9 mg/dl during euglycemia and 24.5 mg/dl during descent into and recovery from hypoglycemia. Computer-generated recalibration reduced MAD to 10.6 and 14.6 mg/dl, respectively. Modeling of IG dynamics reduced the MAD further to 10.0 and 10.4 mg/dl (using idiosyncratic parameters) or to 10.6 and 11.5 mg/dl (using model parameters common for all subjects), respectively.
CONCLUSIONS: The sensor MAD from reference is strongly influenced by the choice of calibration points. Thus, cross-experiment comparisons of sensor accuracy are likely to be heavily dependent on the employed calibration procedures. Demanding calibration points substantially differing in value was found to improve calibration effectiveness. Simulation using existing IG models and population parameters reduced the bias resulting from BG-IG dynamics.

Entities:  

Keywords:  calibration; continuous glucose sensor; delay; hyperinsulinemic clamp; interstitial fluid; surrogate interstitial glucose

Year:  2007        PMID: 19756217      PMCID: PMC2743402          DOI: 10.1177/193229680700100302

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


  17 in total

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Authors:  M Gerritsen; J A Jansen; J A Lutterman
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3.  Performance of a continuous glucose monitoring system during controlled hypoglycaemia in healthy volunteers.

Authors:  E H Cheyne; D A Cavan; D Kerr
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5.  Physiological differences between interstitial glucose and blood glucose measured in human subjects.

Authors:  Eray Kulcu; Janet A Tamada; Gerard Reach; Russell O Potts; Matthew J Lesho
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Authors:  Philip J Stout; Joel R Racchini; Michael E Hilgers
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Review 7.  Continuous glucose monitoring: roadmap for 21st century diabetes therapy.

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Journal:  Diabetes Care       Date:  2005-05       Impact factor: 19.112

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

Authors:  K Rebrin; G M Steil
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9.  Performance evaluation of the MiniMed continuous glucose monitoring system during patient home use.

Authors:  T M Gross; B W Bode; D Einhorn; D M Kayne; J H Reed; N H White; J J Mastrototaro
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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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  35 in total

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Journal:  J Diabetes Sci Technol       Date:  2010-03-01

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

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6.  Modeling the error of continuous glucose monitoring sensor data: critical aspects discussed through simulation studies.

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Journal:  J Diabetes Sci Technol       Date:  2010-01-01

7.  Peculiarities of the continuous glucose monitoring data stream and their impact on developing closed-loop control technology.

Authors:  Boris Kovatchev; William Clarke
Journal:  J Diabetes Sci Technol       Date:  2008-01

8.  Signal processing algorithms implementing the "smart sensor" concept to improve continuous glucose monitoring in diabetes.

Authors:  Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

9.  Optimum subcutaneous glucose sampling and fourier analysis of continuous glucose monitors.

Authors:  Marc D Breton; Devin P Shields; Boris P Kovatchev
Journal:  J Diabetes Sci Technol       Date:  2008-05

10.  In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes.

Authors:  Boris P Kovatchev; Marc Breton; Chiara Dalla Man; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2009-01
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