Literature DB >> 30453761

Measures of Accuracy for Continuous Glucose Monitoring and Blood Glucose Monitoring Devices.

Guido Freckmann1, Stefan Pleus1, Mike Grady2, Steven Setford2, Brian Levy3.   

Abstract

Currently, patients with diabetes may choose between two major types of system for glucose measurement: blood glucose monitoring (BGM) systems measuring glucose within capillary blood and continuous glucose monitoring (CGM) systems measuring glucose within interstitial fluid. Although BGM and CGM systems offer different functionality, both types of system are intended to help users achieve improved glucose control. Another area in which BGM and CGM systems differ is measurement accuracy. In the literature, BGM system accuracy is assessed mainly according to ISO 15197:2013 accuracy requirements, whereas CGM accuracy has hitherto mainly been assessed by MARD, although often results from additional analyses such as bias analysis or error grid analysis are provided. The intention of this review is to provide a comparison of different approaches used to determine the accuracy of BGM and CGM systems and factors that should be considered when using these different measures of accuracy to make comparisons between the analytical performance (ie, accuracy) of BGM and CGM systems. In addition, real-world implications of accuracy and its relevance are discussed.

Entities:  

Keywords:  ISO 15197; MARD; accuracy; blood glucose monitoring; continuous glucose monitoring; performance

Mesh:

Substances:

Year:  2018        PMID: 30453761      PMCID: PMC6501529          DOI: 10.1177/1932296818812062

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


  42 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.  Fundamental Importance of Reference Glucose Analyzer Accuracy for Evaluating the Performance of Blood Glucose Monitoring Systems (BGMSs).

Authors:  Timothy S Bailey; Leslie J Klaff; Jane F Wallace; Carmine Greene; Scott Pardo; Bern Harrison; David A Simmons
Journal:  J Diabetes Sci Technol       Date:  2016-06-28

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.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

5.  Venous, Arterialized-Venous, or Capillary Glucose Reference Measurements for the Accuracy Assessment of a Continuous Glucose Monitoring System.

Authors:  Jort Kropff; Sigrid C van Steen; Peter deGraaff; Man W Chan; Rombout B E van Amstel; J Hans DeVries
Journal:  Diabetes Technol Ther       Date:  2017-08-22       Impact factor: 6.118

6.  Accuracy of a Factory-Calibrated, Real-Time Continuous Glucose Monitoring System During 10 Days of Use in Youth and Adults with Diabetes.

Authors:  R Paul Wadwa; Lori M Laffel; Viral N Shah; Satish K Garg
Journal:  Diabetes Technol Ther       Date:  2018-06-14       Impact factor: 6.118

7.  Performance Evaluation of Three Blood Glucose Monitoring Systems Using ISO 15197: 2013 Accuracy Criteria, Consensus and Surveillance Error Grid Analyses, and Insulin Dosing Error Modeling in a Hospital Setting.

Authors:  José Luis Bedini; Jane F Wallace; Scott Pardo; Thorsten Petruschke
Journal:  J Diabetes Sci Technol       Date:  2015-10-07

8.  Prediction Quality of Glucose Trend Indicators in Two Continuous Tissue Glucose Monitoring Systems.

Authors:  Guido Freckmann; Manuela Link; Antje Westhoff; Ulrike Kamecke; Stefan Pleus; Cornelia Haug
Journal:  Diabetes Technol Ther       Date:  2018-08       Impact factor: 6.118

9.  Measurement Performance of Two Continuous Tissue Glucose Monitoring Systems Intended for Replacement of Blood Glucose Monitoring.

Authors:  Guido Freckmann; Manuela Link; Stefan Pleus; Antje Westhoff; Ulrike Kamecke; Cornelia Haug
Journal:  Diabetes Technol Ther       Date:  2018-08       Impact factor: 6.118

10.  Evidence of a strong association between frequency of self-monitoring of blood glucose and hemoglobin A1c levels in T1D exchange clinic registry participants.

Authors:  Kellee M Miller; Roy W Beck; Richard M Bergenstal; Robin S Goland; Michael J Haller; Janet B McGill; Henry Rodriguez; Jill H Simmons; Irl B Hirsch
Journal:  Diabetes Care       Date:  2013-02-01       Impact factor: 19.112

View more
  19 in total

1.  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

Review 2.  Blood Sugar Targets in Surgical Intensive Care—Management and Special Considerations in Patients With Diabetes

Authors:  Johannes Roth; Oliver Sommerfeld; Andreas L Birkenfeld; Christoph Sponholz; Ulrich A Müller; Christian von Loeffelholz
Journal:  Dtsch Arztebl Int       Date:  2021-09-17       Impact factor: 5.594

3.  Maximal Glycemic Difference, the Possible Strongest Glycemic Variability Parameter to Predict Mortality in ICU Patients.

Authors:  Thanaphruet Issarawattana; Rungsun Bhurayanontachai
Journal:  Crit Care Res Pract       Date:  2020-08-24

4.  Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline.

Authors:  Rodolfo J Galindo; Guillermo E Umpierrez; Robert J Rushakoff; Ananda Basu; Suzanne Lohnes; James H Nichols; Elias K Spanakis; Juan Espinoza; Nadine E Palermo; Dessa Garnett Awadjie; Leigh Bak; Bruce Buckingham; Curtiss B Cook; Guido Freckmann; Lutz Heinemann; Roman Hovorka; Nestoras Mathioudakis; Tonya Newman; David N O'Neal; Michaela Rickert; David B Sacks; Jane Jeffrie Seley; Amisha Wallia; Trisha Shang; Jennifer Y Zhang; Julia Han; David C Klonoff
Journal:  J Diabetes Sci Technol       Date:  2020-09-28

5.  Use and Accuracy of Inpatient CGM During the COVID-19 Pandemic: An Observational Study of General Medicine and ICU Patients.

Authors:  Rebecca Rick Longo; Heather Elias; Mehvish Khan; Jane Jefferie Seley
Journal:  J Diabetes Sci Technol       Date:  2021-05-10

6.  Mean Absolute Relative Difference of Blood Glucose Monitoring Systems and Relationship to ISO 15197.

Authors:  Guido Freckmann; Jochen Mende; Stefan Pleus; Delia Waldenmaier; Annette Baumstark; Nina Jendrike; Cornelia Haug
Journal:  J Diabetes Sci Technol       Date:  2021-03-24

Review 7.  Monitoring of Pediatric Type 1 Diabetes.

Authors:  Brynn E Marks; Joseph I Wolfsdorf
Journal:  Front Endocrinol (Lausanne)       Date:  2020-03-17       Impact factor: 5.555

8.  Time in Range in Pregnancy: Is There a Role?

Authors:  Jennifer A Wyckoff; Florence M Brown
Journal:  Diabetes Spectr       Date:  2021-05-25

9.  Diabetes Technology Meeting 2020.

Authors:  Trisha Shang; Jennifer Y Zhang; B Wayne Bequette; Jennifer K Raymond; Gerard Coté; Jennifer L Sherr; Jessica Castle; John Pickup; Yarmela Pavlovic; Juan Espinoza; Laurel H Messer; Tim Heise; Carlos E Mendez; Sarah Kim; Barry H Ginsberg; Umesh Masharani; Rodolfo J Galindo; David C Klonoff
Journal:  J Diabetes Sci Technol       Date:  2021-07

10.  Glucose Patterns in Very Old Adults: A Pilot Study in a Community-Based Population.

Authors:  Elizabeth Selvin; Dan Wang; Olive Tang; Melissa Minotti; Justin B Echouffo-Tcheugui; Josef Coresh
Journal:  Diabetes Technol Ther       Date:  2021-08-19       Impact factor: 7.337

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.