Literature DB >> 31613142

Differences for Percentage Times in Glycemic Range Between Continuous Glucose Monitoring and Capillary Blood Glucose Monitoring in Adults with Type 1 Diabetes: Analysis of the REPLACE-BG Dataset.

Parizad Avari1, Chukwuma Uduku1, Daniel George1, Pau Herrero1, Monika Reddy1, Nick Oliver1.   

Abstract

Background: Self-monitored blood glucose (SMBG) and real-time continuous glucose monitoring (rtCGM) are used by people living with type 1 diabetes (T1D) to assess glucose and inform decision-making. Percentage time in range (%TIR) between 3.9 and 10 mmol/L has been associated with incident microvascular complications using historical SMBG data. However, the association between %TIR calculated from rtCGM data has not been identified. This study investigates whether %TIR values generated from rtCGM and SMBG data significantly differ from each other in adults with T1D. Materials and
Methods: rtCGM and SMBG data from the REPLACE-BG study were obtained and analyzed. The dataset contained rtCGM (Dexcom G4 Platinum) and SMBG (Contour Next) values for 226 participants during a run-in phase lasting up to 10 weeks, followed by the 26-week trial. Percentages times in hypoglycemic, euglycemia and hyperglycemic ranges were generated from rtCGM and SMBG data using last observation carry forward method (zero-order hold) and linear interpolation (first-order hold).
Results: Participants had a median (interquartile range [IQR]) age of 43.0 (31.0-55.0) years, and hemoglobin A1C of 53 (49-57) mmol/mol [7.0 (6.6-7.4)%]. The median (IQR) %TIR was significantly higher with rtCGM than with SMBG; 63.0 (55.9-71.0)% versus 54.6 (45.6-63.0)%, respectively, P < 0.001. Median %times in hypoglycemia and hyperglycemia were significantly different with SMBG than rtCGM (P < 0.001). SMBG-derived data using linear interpolation significantly differed from the carry forward method (P < 0.001 for all glycemic ranges). Differences reported were greater at night than during the day (P < 0.001 for all glycemic ranges).
Conclusion: The %time in all glycemic ranges reported by SMBG and rtCGM differ significantly, suggesting relationships between times in ranges, and complication status may be different between monitoring modalities. In addition, varying methods of calculating %TIR from SMBG-derived data provide significantly differing results. %TIR targets may therefore vary by monitoring choice and methods of calculation and harmonization of TIR standards may be challenging.

Entities:  

Keywords:  Hypoglycemia; Real-time continuous glucose monitoring (rtCGM); Self-monitoring of blood glucose; Time in range; Type 1 diabetes

Mesh:

Substances:

Year:  2019        PMID: 31613142      PMCID: PMC7047084          DOI: 10.1089/dia.2019.0276

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


  16 in total

1.  Are Risk Indices Derived From CGM Interchangeable With SMBG-Based Indices?

Authors:  Chiara Fabris; Stephen D Patek; Marc D Breton
Journal:  J Diabetes Sci Technol       Date:  2015-08-14

Review 2.  Is it possible to constantly and accurately monitor blood sugar levels, in people with Type 1 diabetes, with a discrete device (non-invasive or invasive)?

Authors:  P Avari; M Reddy; N Oliver
Journal:  Diabet Med       Date:  2019-03-13       Impact factor: 4.359

3.  Discrepancies between methods of continuous glucose monitoring in key metrics of glucose control in children with type 1 diabetes.

Authors:  Arkadiusz Michalak; Konrad Pagacz; Wojciech Młynarski; Agnieszka Szadkowska; Wojciech Fendler
Journal:  Pediatr Diabetes       Date:  2019-04-17       Impact factor: 4.866

4.  A clinical trial of the accuracy and treatment experience of the Dexcom G4 sensor (Dexcom G4 system) and Enlite sensor (guardian REAL-time system) tested simultaneously in ambulatory patients with type 1 diabetes.

Authors:  Viktorija Matuleviciene; Jeffrey I Joseph; Mervi Andelin; Irl B Hirsch; Stig Attvall; Aldina Pivodic; Sofia Dahlqvist; David Klonoff; Börje Haraldsson; Marcus Lind
Journal:  Diabetes Technol Ther       Date:  2014-09-18       Impact factor: 6.118

5.  Assessing sensor accuracy for non-adjunct use of continuous glucose monitoring.

Authors:  Boris P Kovatchev; Stephen D Patek; Edward Andrew Ortiz; Marc D Breton
Journal:  Diabetes Technol Ther       Date:  2014-12-01       Impact factor: 6.118

6.  Use of continuous glucose monitoring as an outcome measure in clinical trials.

Authors:  Roy W Beck; Peter Calhoun; Craig Kollman
Journal:  Diabetes Technol Ther       Date:  2012-10       Impact factor: 6.118

7.  The Accuracy and Efficacy of the Dexcom G4 Platinum Continuous Glucose Monitoring System.

Authors:  Katherine Nakamura; Andrew Balo
Journal:  J Diabetes Sci Technol       Date:  2015-03-23

8.  Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials.

Authors:  Roy W Beck; Richard M Bergenstal; Tonya D Riddlesworth; Craig Kollman; Zhaomian Li; Adam S Brown; Kelly L Close
Journal:  Diabetes Care       Date:  2018-10-23       Impact factor: 19.112

9.  Diabetes Device Use in Adults With Type 1 Diabetes: Barriers to Uptake and Potential Intervention Targets.

Authors:  Molly L Tanenbaum; Sarah J Hanes; Kellee M Miller; Diana Naranjo; Rachel Bensen; Korey K Hood
Journal:  Diabetes Care       Date:  2016-11-29       Impact factor: 19.112

10.  REPLACE-BG: A Randomized Trial Comparing Continuous Glucose Monitoring With and Without Routine Blood Glucose Monitoring in Adults With Well-Controlled Type 1 Diabetes.

Authors:  Grazia Aleppo; Katrina J Ruedy; Tonya D Riddlesworth; Davida F Kruger; Anne L Peters; Irl Hirsch; Richard M Bergenstal; Elena Toschi; Andrew J Ahmann; Viral N Shah; Michael R Rickels; Bruce W Bode; Athena Philis-Tsimikas; Rodica Pop-Busui; Henry Rodriguez; Emily Eyth; Anuj Bhargava; Craig Kollman; Roy W Beck
Journal:  Diabetes Care       Date:  2017-02-16       Impact factor: 19.112

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  3 in total

1.  Association of Time in Range with Endothelial Injury in Patients with Type 2 Diabetes Treated with Exenatide.

Authors:  Yunyi Le; Kun Yang; Jin Yang; Wei Fu; Wenhua Xiao; Rui Wei; Tianpei Hong
Journal:  Diabetes Ther       Date:  2022-08-13       Impact factor: 3.595

Review 2.  Time in range: a new parameter to evaluate blood glucose control in patients with diabetes.

Authors:  Monica Andrade Lima Gabbay; Melanie Rodacki; Luis Eduardo Calliari; Andre Gustavo Daher Vianna; Marcio Krakauer; Mauro Scharf Pinto; Janice Sepúlveda Reis; Marcia Puñales; Leonardo Garcia Miranda; Ana Claudia Ramalho; Denise Reis Franco; Hermelinda Pedrosa Cordeiro Pedrosa
Journal:  Diabetol Metab Syndr       Date:  2020-03-16       Impact factor: 3.320

Review 3.  Time in range: A best practice guide for UK diabetes healthcare professionals in the context of the COVID-19 global pandemic.

Authors:  E G Wilmot; A Lumb; P Hammond; H R Murphy; E Scott; F W Gibb; J Platts; P Choudhary
Journal:  Diabet Med       Date:  2020-11-16       Impact factor: 4.213

  3 in total

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