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Comparative Study
. 2015 Jul;9(4):801-7.
doi: 10.1177/1932296815578716. Epub 2015 Apr 7.

Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings

Stefan Pleus  1 , Michael Schoemaker  2 , Karin Morgenstern  2 , Günther Schmelzeisen-Redeker  2 , Cornelia Haug  3 , Manuela Link  3 , Eva Zschornack  3 , Guido Freckmann  3
Affiliations
Comparative Study

Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings

Stefan Pleus et al. J Diabetes Sci Technol. 2015 Jul.

Abstract

Introduction: The accuracy of continuous glucose monitoring (CGM) systems is often assessed with respect to blood glucose (BG) readings. CGM readings are affected by a physiological and a technical time delay when compared to BG readings. In this analysis, the dependence of CGM performance parameters on the BG rate of change was investigated for 2 CGM systems.

Methods: Data from a previously published study were retrospectively analyzed. An established CGM system (Dexcom G4, Dexcom, San Diego, CA; system A) and a prototype system (Roche Diagnostics GmbH, Mannheim, Germany; system B) with 2 sensors each were worn by 10 subjects in parallel. Glucose swings were induced to achieve rapidly changing BG concentrations. Mean absolute relative differences (MARD) were calculated in different BG rate-of-change categories. In addition, sensor-to-sensor precision was assessed.

Results: At BG rates of change of -1 mg/dl/min to 0 mg/dl/min and 0 mg/dl/min to +1 mg/dl/min, MARD results were 12.6% and 11.3% for system A and 8.2% and 10.0% for system B. At rapidly changing BG concentrations (<-3 mg/dl/min and ≥+3 mg/dl/min), higher MARD results were found for both systems, but system B was less affected (system A: 24.9% and 29.6%, system B: 10.6% and 16.3%). The impact of rate of change on sensor-to-sensor precision was less pronounced.

Conclusions: Both systems were affected by rapidly changing BG concentrations to some degree, although system B was mostly unaffected by decreasing BG concentrations. It would seem that technological advancements in CGM systems might allow for a more precise tracking of BG concentrations even at rapidly changing BG concentrations.

Keywords: MARD; PARD; accuracy; continuous glucose monitoring; rate of change.

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Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: SP, CH, ML, and EZ have no conflict of interest to disclose. MS, KM, and GSR are employees of Roche Diagnostics GmbH, Germany. GF is general manager of the IDT (Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany), which carries out studies on the evaluation of BG meters and medical devices for diabetes therapy on behalf of various companies. GF/IDT have received speakers’ honoraria or consulting fees from Abbott, Bayer, Berlin-Chemie, Becton-Dickinson, Dexcom, Menarini Diagnostics, Novo Nordisk, Roche Diagnostics, Sanofi, and Ypsomed.

Figures

Figure 1.
Figure 1.
Example of a glucose trace obtained from 1 subject in 1 of 2 induced glucose swings. BG measurements are displayed by red diamonds. Light and dark traces (blue for system A and green for system B) show the CGM measurements obtained during the swing. Meals were served at 8:00 and at 13:00.
Figure 2.
Figure 2.
MARD over rate-of-change category; white numbers in bars are percentages of results within that category.
Figure 3.
Figure 3.
Distribution of individual sensor experiment MARD results. Overall MARD was 10.9% for system A and 8.6% for system B.
See this image and copyright information in PMC

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