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Comparative Study
. 2025 Jul 1;48(7):1213-1217.
doi: 10.2337/dc25-0129.

A Comparative Analysis of Glycemic Metrics Derived From Three Continuous Glucose Monitoring Systems

Guido Freckmann  1 , Stephanie Wehrstedt  1 , Manuel Eichenlaub  1 , Stefan Pleus  1 , Manuela Link  1 , Nina Jendrike  1 , Sükrü Öter  1 , Derek Brandt  2 , Cornelia Haug  1 , Delia Waldenmaier  1
Affiliations
Comparative Study

A Comparative Analysis of Glycemic Metrics Derived From Three Continuous Glucose Monitoring Systems

Guido Freckmann et al. Diabetes Care. .

Abstract

Objective: This study analyzed the differences in continuous glucose monitoring (CGM)-derived metrics among three current-generation systems and evaluated their impact on therapeutic decision-making.

Research design and methods: Twenty-three participants wore the FreeStyle Libre 3, Dexcom G7, and Medtronic Simplera CGM systems for 14 days in parallel. CGM metrics were calculated for each participant and CGM system separately.

Results: The apparent glucose profile was influenced by the used CGM system, resulting in substantially different glycemic metrics among the three systems. Agreement between FreeStyle Libre 3 and Dexcom G7 was higher than with Medtronic Simplera, which showed lower glucose levels, on average. There were marked intraparticipant discrepancies that would have resulted in different therapeutic recommendations.

Conclusions: The CGM systems indicated discordant glycemic metrics, which should be considered in diabetes therapy. Different CGM systems should provide the same glucose readings and CGM-derived metrics when used by the same person.

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Conflict of interest statement

Duality of Interest. G.F. is the general manager and medical director of the IfDT, which carries out clinical studies on its own initiative and on behalf of various companies. G.F. and IfDT have received research support, speakers’ honoraria, or consulting fees in the last 3 years from Abbott, Ascensia, Berlin Chemie, Boydsense, Dexcom, Lilly Deutschland, Novo Nordisk, Perfood, Pharmasens, Roche, Sinocare, Terumo, and Ypsomed. D.W., S.W., M.E., S.P., M.L., N.J., S.Ö., and C.H. are employees of IfDT. No other potential conflicts of interest relevant to this article were reported.

Figures

None
Graphical abstract
Figure 1
Figure 1
Median percentage of time in different glucose ranges across all study participants (n = 23) according to the different CGM systems.
Figure 2
Figure 2
A–D: CGM-derived metrics of each participant (dots; n = 23) according to different CGM systems. Identical participants are connected by lines. Red dashes show the medians. Dashed lines indicate therapy targets. E–H: Differences in CGM-derived metrics between pairs of CGM systems (indicated by the x-axis labels) within the same participant (dots). Dashed lines for TIR and GMI indicate clinically significant differences (1,10–12).
Figure 3
Figure 3
Mean time course of capillary comparator measurements and CGM glucose data from the three systems during experimentally induced hyperglycemia (A) and hypoglycemia (B). The individual profiles were synchronized according to the time of the first capillary measurement >250 mg/dL or <70 mg/dL, respectively, and averaged.
See this image and copyright information in PMC

Comment in

References

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