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. 2020 Sep 29;10(10):138.
doi: 10.3390/bios10100138.

Accuracy of the Dexcom G6 Glucose Sensor during Aerobic, Resistance, and Interval Exercise in Adults with Type 1 Diabetes

Florian H Guillot  1 , Peter G Jacobs  2 , Leah M Wilson  1 , Joseph El Youssef  1   2 , Virginia B Gabo  1 , Deborah L Branigan  1 , Nichole S Tyler  2 , Katrina Ramsey  3 , Michael C Riddell  4 , Jessica R Castle  1
Affiliations

Accuracy of the Dexcom G6 Glucose Sensor during Aerobic, Resistance, and Interval Exercise in Adults with Type 1 Diabetes

Florian H Guillot et al. Biosensors (Basel). .

Abstract

The accuracy of continuous glucose monitoring (CGM) sensors may be significantly impacted by exercise. We evaluated the impact of three different types of exercise on the accuracy of the Dexcom G6 sensor. Twenty-four adults with type 1 diabetes on multiple daily injections wore a G6 sensor. Participants were randomized to aerobic, resistance, or high intensity interval training (HIIT) exercise. Each participant completed two in-clinic 30-min exercise sessions. The sensors were applied on average 5.3 days prior to the in-clinic visits (range 0.6-9.9). Capillary blood glucose (CBG) measurements with a Contour Next meter were performed before and after exercise as well as every 10 min during exercise. No CGM calibrations were performed. The median absolute relative difference (MARD) and median relative difference (MRD) of the CGM as compared with the reference CBG did not differ significantly from the start of exercise to the end exercise across all exercise types (ranges for aerobic MARD: 8.9 to 13.9% and MRD: -6.4 to 0.5%, resistance MARD: 7.7 to 14.5% and MRD: -8.3 to -2.9%, HIIT MARD: 12.1 to 16.8% and MRD: -14.3 to -9.1%). The accuracy of the no-calibration Dexcom G6 CGM was not significantly impacted by aerobic, resistance, or HIIT exercise.

Keywords: aerobic exercise; continuous glucose monitoring; exercise; glucose sensor accuracy; high intensity interval training; resistance exercise; type 1 diabetes.

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Conflict of interest statement

J.R.C. and P.G.J. have a financial interest in Pacific Diabetes Technologies, Inc., a company that may have a commercial interest in the results of this type of research and technology. J.R.C. has also consulted for Dexcom, Inc. and has been on advisory panels for Adocia, AstraZeneca, Novo Nordisk, and Zealand Pharma. P.G.J. has received honorarium and research support from Dexcom, Inc. OHSU manages the conflict of interest for P.G.J. and J.R.C. M.C.R. has received speakers’ honoraria from Eli Lilly, Novo Nordisk, Medtronic, Insulet and Dexcom. The authors F.H.G., L.M.W., J.E.Y., V.B.G., D.L.B., N.S.T., and K.R. declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
(a) Absolute relative differences (ARD, %) and (b) relative differences (RD, %) for aerobic, resistance and high intensity interval training (HIIT) exercise. Median values that are statistically significant from baseline are indicated by an asterisk (*), with the corresponding p-value listed above.
Figure 2
Figure 2
Clarke error grid analysis showing paired continuous glucose monitoring (CGM) and capillary (reference) glucose during (a) aerobic, (b) resistance and (c) high intensity interval training (HIIT) exercise. In these scatterplots, the diagonal represents perfect agreement between capillary and sensed glucose. The regions (or zones) labelled A through E represent varying degrees of accuracy of glucose estimations. Zone A contains values within 20% of the reference sensor. Zone B values deviate more than 20% but would not lead to inappropriate treatment. Values within zone C would lead to overcorrecting while those in zone D represent a potentially “dangerous failure to detect and treat”. Lastly, zone E would result in opposite treatment decisions (e.g., treatment of hypoglycemia for hyperglycemia and vice versa) [38].
Figure 3
Figure 3
Clarke error grid analysis showing paired CGM and capillary (reference) glucose for all exercise types combined.
See this image and copyright information in PMC

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