Literature DB >> 29901421

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

R Paul Wadwa1, Lori M Laffel2, Viral N Shah1, Satish K Garg1.   

Abstract

BACKGROUND: Frequent use of continuous glucose monitoring (CGM) systems is associated with improved glycemic outcomes in persons with diabetes, but the need for calibrations and sensor insertions are often barriers to adoption. In this study, we evaluated the performance of G6, a sixth-generation, factory-calibrated CGM system specified for 10-day wear.
METHODS: The study enrolled participants of ages 6 years and up with type 1 diabetes or insulin-treated type 2 diabetes at 11 sites in the United States. Participation involved one sensor wear period of up to 10 days. Adults wore the system on the abdomen; youth of ages 6-17 years could choose to wear it on the abdomen or upper buttocks. Clinic sessions for frequent comparison with reference blood glucose measurements took place on days 1, 4-5, 7, and/or 10. Participants of ages 13 years and up underwent purposeful supervised glucose manipulation during in-clinic sessions. During the study, participants calibrated the systems once daily. However, analysis was performed on glucose values that were derived from reprocessed raw sensor data, independently of self-monitored blood glucose values used for calibration. Reprocessing used assigned sensor codes and a factory-calibration algorithm. Performance evaluation included the proportion of CGM values that were within ±20% of reference glucose values >100 mg/dL or within ±20 mg/dL of reference glucose values ≤100 mg/dL (%20/20), the analogous %15/15, and the mean absolute relative difference (MARD, expressed as a percentage) between temporally matched CGM and reference values.
RESULTS: Data from 262 study participants (21,569 matched CGM reference pairs) were analyzed. The overall %15/15, %20/20, and MARD were 82.4%, 92.3%, and 10.0%, respectively. Matched pairs from 134 adults and 128 youth of ages 6-17 years were similar with respect to %20/20 (92.4% and 91.9%) and MARD (9.9% and 10.1%). Overall %20/20 values on days 1 and 10 of sensor wear were 88.6% and 90.6%, respectively. The system's "Urgent Low Soon" (predictive of hypoglycemia within 20 min) hypoglycemia alert was correctly provided 84% of the time within 30 min before impending biochemical hypoglycemia (<70 mg/dL). The 10-day sensor survival rate was 87%.
CONCLUSION: The new factory-calibrated G6 real-time CGM system provides accurate readings for 10 days and removes several clinical barriers to broader CGM adoption.

Entities:  

Keywords:  Advanced algorithm; Clinical accuracy; Continuous glucose monitoring; Factory-calibrated; Glucose sensor performance; MARD

Mesh:

Substances:

Year:  2018        PMID: 29901421      PMCID: PMC6110124          DOI: 10.1089/dia.2018.0150

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


  20 in total

1.  System accuracy evaluation of systems for point-of-care testing of blood glucose: a comparison of a patient-use system with six professional-use systems.

Authors:  Guido Freckmann; Christina Schmid; Stefan Pleus; Annette Baumstark; Manuela Link; Erhard Stolberg; Cornelia Haug; Jochen Sieber
Journal:  Clin Chem Lab Med       Date:  2014-07       Impact factor: 3.694

2.  Factory-Calibrated Continuous Glucose Sensors: The Science Behind the Technology.

Authors:  Udo Hoss; Erwin Satrya Budiman
Journal:  Diabetes Technol Ther       Date:  2017-05       Impact factor: 6.118

3.  System accuracy evaluation of 43 blood glucose monitoring systems for self-monitoring of blood glucose according to DIN EN ISO 15197.

Authors:  Guido Freckmann; Christina Schmid; Annette Baumstark; Stefan Pleus; Manuela Link; Cornelia Haug
Journal:  J Diabetes Sci Technol       Date:  2012-09-01

4.  Continuous Glucose Monitoring Versus Usual Care in Patients With Type 2 Diabetes Receiving Multiple Daily Insulin Injections: A Randomized Trial.

Authors:  Roy W Beck; Tonya D Riddlesworth; Katrina Ruedy; Andrew Ahmann; Stacie Haller; Davida Kruger; Janet B McGill; William Polonsky; David Price; Stephen Aronoff; Ronnie Aronson; Elena Toschi; Craig Kollman; Richard Bergenstal
Journal:  Ann Intern Med       Date:  2017-08-22       Impact factor: 25.391

5.  Clinical accuracy of a continuous glucose monitoring system with an advanced algorithm.

Authors:  Timothy S Bailey; Anna Chang; Mark Christiansen
Journal:  J Diabetes Sci Technol       Date:  2014-11-03

6.  The Impact of Continuous Glucose Monitoring on Markers of Quality of Life in Adults With Type 1 Diabetes: Further Findings From the DIAMOND Randomized Clinical Trial.

Authors:  William H Polonsky; Danielle Hessler; Katrina J Ruedy; Roy W Beck
Journal:  Diabetes Care       Date:  2017-04-07       Impact factor: 19.112

7.  Continuous Glucose Monitoring vs Conventional Therapy for Glycemic Control in Adults With Type 1 Diabetes Treated With Multiple Daily Insulin Injections: The GOLD Randomized Clinical Trial.

Authors:  Marcus Lind; William Polonsky; Irl B Hirsch; Tim Heise; Jan Bolinder; Sofia Dahlqvist; Erik Schwarz; Arndís Finna Ólafsdóttir; Anders Frid; Hans Wedel; Elsa Ahlén; Thomas Nyström; Jarl Hellman
Journal:  JAMA       Date:  2017-01-24       Impact factor: 56.272

8.  Effect of Continuous Glucose Monitoring on Glycemic Control in Adults With Type 1 Diabetes Using Insulin Injections: The DIAMOND Randomized Clinical Trial.

Authors:  Roy W Beck; Tonya Riddlesworth; Katrina Ruedy; Andrew Ahmann; Richard Bergenstal; Stacie Haller; Craig Kollman; Davida Kruger; Janet B McGill; William Polonsky; Elena Toschi; Howard Wolpert; David Price
Journal:  JAMA       Date:  2017-01-24       Impact factor: 56.272

9.  Glucose monitoring after fruit peeling: pseudohyperglycemia when neglecting hand washing before fingertip blood sampling: wash your hands with tap water before you check blood glucose level.

Authors:  Takahisa Hirose; Tomoya Mita; Yoshio Fujitani; Ryuzo Kawamori; Hirotaka Watada
Journal:  Diabetes Care       Date:  2011-01-31       Impact factor: 19.112

10.  Resistance to Acetaminophen Interference in a Novel Continuous Glucose Monitoring System.

Authors:  Peter Calhoun; Terri Kang Johnson; Jonathan Hughes; David Price; Andrew K Balo
Journal:  J Diabetes Sci Technol       Date:  2018-01-16
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  51 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

2.  Use of Artificial Intelligence to Improve Diabetes Outcomes in Patients Using Multiple Daily Injections Therapy.

Authors:  Gregory P Forlenza
Journal:  Diabetes Technol Ther       Date:  2019-06       Impact factor: 6.118

3.  A Clinical Guide to Advanced Diabetes Devices and Closed-Loop Systems Using the CARES Paradigm.

Authors:  Laurel H Messer; Cari Berget; Gregory P Forlenza
Journal:  Diabetes Technol Ther       Date:  2019-05-29       Impact factor: 6.118

4.  Safety and Accuracy of Factory-Calibrated Continuous Glucose Monitoring in Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation.

Authors:  Jenna Sopfe; Tim Vigers; Laura Pyle; Roger H Giller; Gregory P Forlenza
Journal:  Diabetes Technol Ther       Date:  2020-03-17       Impact factor: 6.118

5.  Continuous Glucose Monitoring Predicts Progression to Diabetes in Autoantibody Positive Children.

Authors:  Andrea K Steck; Fran Dong; Iman Taki; Michelle Hoffman; Kimber Simmons; Brigitte I Frohnert; Marian J Rewers
Journal:  J Clin Endocrinol Metab       Date:  2019-08-01       Impact factor: 5.958

6.  A Head-to-Head Comparison Study of the First-Day Performance of Two Factory-Calibrated CGM Systems.

Authors:  Douglas Denham
Journal:  J Diabetes Sci Technol       Date:  2020-01-08

7.  Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction.

Authors:  Darpit Dave; Daniel J DeSalvo; Balakrishna Haridas; Siripoom McKay; Akhil Shenoy; Chester J Koh; Mark Lawley; Madhav Erraguntla
Journal:  J Diabetes Sci Technol       Date:  2020-06-01

Review 8.  Continuous noninvasive glucose monitoring; water as a relevant marker of glucose uptake in vivo.

Authors:  Andreas Caduff; Paul Ben Ishai; Yuri Feldman
Journal:  Biophys Rev       Date:  2019-11-18

9.  Benefits and Barriers of Continuous Glucose Monitoring in Young Children with Type 1 Diabetes.

Authors:  Marisa E Hilliard; Wendy Levy; Barbara J Anderson; Amanda L Whitehouse; Persis V Commissariat; Kara R Harrington; Lori M Laffel; Kellee M Miller; Michelle Van Name; William V Tamborlane; Daniel J DeSalvo; Linda A DiMeglio
Journal:  Diabetes Technol Ther       Date:  2019-07-09       Impact factor: 6.118

Review 10.  Measures of Accuracy for Continuous Glucose Monitoring and Blood Glucose Monitoring Devices.

Authors:  Guido Freckmann; Stefan Pleus; Mike Grady; Steven Setford; Brian Levy
Journal:  J Diabetes Sci Technol       Date:  2018-11-19
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