Literature DB >> 23650900

Accuracy and reliability of continuous glucose monitoring systems: a head-to-head comparison.

Yoeri M Luijf1, Julia K Mader, Werner Doll, Thomas Pieber, Anne Farret, Jerome Place, Eric Renard, Daniela Bruttomesso, Alessio Filippi, Angelo Avogaro, Sabine Arnolds, Carsten Benesch, Lutz Heinemann, J Hans DeVries.   

Abstract

OBJECTIVE: This study assessed the accuracy and reliability of three continuous glucose monitoring (CGM) systems. RESEARCH DESIGN AND METHODS: We studied the Animas® (West Chester, PA) Vibe™ with Dexcom® (San Diego, CA) G4™ version A sensor (G4A), the Abbott Diabetes Care (Alameda, CA) Freestyle® Navigator I (NAV), and the Medtronic (Northridge, CA) Paradigm® with Enlite™ sensor (ENL) in 20 patients with type 1 diabetes mellitus. All systems were investigated both in a clinical research center (CRC) and at home. In the CRC, patients received a meal with a delayed and increased insulin dose to induce a postprandial glucose peak and nadir. Hereafter, randomization determined which two of the three systems would be worn at home until the end of functioning, attempting use beyond manufacturer-specified lifetime. Patients performed at least five reference finger sticks per day. An analysis of variance was performed on all data points ≥15 min apart.
RESULTS: Overall average mean absolute relative difference (MARD) (SD) measured at the CRC was 16.5% (14.3%) for NAV and 16.4% (15.6%) for ENL, outperforming G4A at 20.5% (18.2%) (P<0.001). Overall MARD when assessed at home was 14.5% (16.7%) for NAV and 16.5 (18.8%) for G4A, outperforming ENL at 18.9% (23.6%) (P=0.006). Median time until end of functioning was similar: 10.0 (1.0) days for G4A, 8.0 (3.5) days for NAV, and 8.0 (1.5) days for ENL (P=0.119).
CONCLUSIONS: In the CRC, G4A was less accurate than NAV and ENL sensors, which seemed comparable. However, at home, ENL was less accurate than NAV and G4A. Moreover, CGM systems often show sufficient accuracy to be used beyond manufacturer-specified lifetime.

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Year:  2013        PMID: 23650900      PMCID: PMC3746288          DOI: 10.1089/dia.2013.0049

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  10 in total

1.  Comparison of a needle-type and a microdialysis continuous glucose monitor in type 1 diabetic patients.

Authors:  Iris M Wentholt; Marit A Vollebregt; Augustus A Hart; Joost B Hoekstra; J Hans DeVries
Journal:  Diabetes Care       Date:  2005-12       Impact factor: 19.112

2.  Relationship between interstitial and blood glucose in type 1 diabetes patients: delay and the push-pull phenomenon revisited.

Authors:  Iris M E Wentholt; Augustus A M Hart; Joost B L Hoekstra; J Hans Devries
Journal:  Diabetes Technol Ther       Date:  2007-04       Impact factor: 6.118

3.  Accuracy of the SEVEN continuous glucose monitoring system: comparison with frequently sampled venous glucose measurements.

Authors:  Howard C Zisser; Timothy S Bailey; Sherwyn Schwartz; Robert E Ratner; Jonathan Wise
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

4.  Reimbursement for continuous glucose monitoring: a European view.

Authors:  Lutz Heinemann; Sylvia Franc; Moshe Phillip; Tadej Battelino; Francisco Javier Ampudia-Blasco; Jan Bolinder; Peter Diem; John Pickup; J Hans Devries
Journal:  J Diabetes Sci Technol       Date:  2012-11-01

5.  Comparison of the clinical information provided by the FreeStyle Navigator continuous interstitial glucose monitor versus traditional blood glucose readings.

Authors:  Geoffrey V McGarraugh; William L Clarke; Boris P Kovatchev
Journal:  Diabetes Technol Ther       Date:  2010-05       Impact factor: 6.118

Review 6.  Frequency characterization of blood glucose dynamics.

Authors:  David A Gough; Kenneth Kreutz-Delgado; Troy M Bremer
Journal:  Ann Biomed Eng       Date:  2003-01       Impact factor: 3.934

7.  Continuous glucose monitoring accuracy results vary between assessment at home and assessment at the clinical research center.

Authors:  Yoeri M Luijf; Angelo Avogaro; Carsten Benesch; Daniela Bruttomesso; Claudio Cobelli; Martin Ellmerer; Lutz Heinemann; Julia K Mader; J Hans DeVries
Journal:  J Diabetes Sci Technol       Date:  2012-09-01

8.  Sense and nonsense in sensors.

Authors:  J Hermanides; J H DeVries
Journal:  Diabetologia       Date:  2010-01-10       Impact factor: 10.122

9.  The accuracy and efficacy of real-time continuous glucose monitoring sensor in patients with type 1 diabetes.

Authors:  John Mastrototaro; John Shin; Alan Marcus; Giri Sulur
Journal:  Diabetes Technol Ther       Date:  2008-10       Impact factor: 6.118

Review 10.  Continuous glucose monitoring systems for type 1 diabetes mellitus.

Authors:  Miranda Langendam; Yoeri M Luijf; Lotty Hooft; J Hans Devries; Aart H Mudde; Rob J P M Scholten
Journal:  Cochrane Database Syst Rev       Date:  2012-01-18
  10 in total
  32 in total

1.  Performance Comparison of CGM Systems: MARD Values Are Not Always a Reliable Indicator of CGM System Accuracy.

Authors:  Harald Kirchsteiger; Lutz Heinemann; Guido Freckmann; Volker Lodwig; Günther Schmelzeisen-Redeker; Michael Schoemaker; Luigi Del Re
Journal:  J Diabetes Sci Technol       Date:  2015-09-01

2.  Assessing the Accuracy of Continuous Glucose Monitoring (CGM) Calibrated With Capillary Values Using Capillary or Venous Glucose Levels as a Reference.

Authors:  Mervi Andelin; Jort Kropff; Viktorija Matuleviciene; Jeffrey I Joseph; Stig Attvall; Elvar Theodorsson; Irl B Hirsch; Henrik Imberg; Sofia Dahlqvist; David Klonoff; Börje Haraldsson; J Hans DeVries; Marcus Lind
Journal:  J Diabetes Sci Technol       Date:  2016-06-28

Review 3.  AP@home: The Artificial Pancreas Is Now at Home.

Authors:  Lutz Heinemann; Carsten Benesch; J Hans DeVries
Journal:  J Diabetes Sci Technol       Date:  2016-06-28

4.  Accuracy evaluation of five blood glucose monitoring systems: the North American comparator trial.

Authors:  Solveig Halldorsdottir; Mary Ellen Warchal-Windham; Jane F Wallace; Scott Pardo; Joan Lee Parkes; David A Simmons
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

5.  Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

Authors:  Tony Zhou; Jennifer L Dickson; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2017-07-14

6.  Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space.

Authors:  Lutz Heinemann; Michael Schoemaker; Günther Schmelzeisen-Redecker; Rolf Hinzmann; Adham Kassab; Guido Freckmann; Florian Reiterer; Luigi Del Re
Journal:  J Diabetes Sci Technol       Date:  2019-06-19

7.  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

Review 8.  Current Trends in Continuous Glucose Monitoring.

Authors:  Volker Lodwig; Bernhard Kulzer; Oliver Schnell; Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2014-03-13

9.  Hypoglycemia Detection and Carbohydrate Suggestion in an Artificial Pancreas.

Authors:  Kamuran Turksoy; Jennifer Kilkus; Iman Hajizadeh; Sediqeh Samadi; Jianyuan Feng; Mert Sevil; Caterina Lazaro; Nicole Frantz; Elizabeth Littlejohn; Ali Cinar
Journal:  J Diabetes Sci Technol       Date:  2016-11-01

10.  A Multicenter Performance Evaluation of a Blood Glucose Monitoring System in 21 Leading Hospitals in Spain.

Authors:  José Luis Bedini; Jane F Wallace; Thorsten Petruschke; Scott Pardo
Journal:  J Diabetes Sci Technol       Date:  2015-08-07
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