Affiliation:
1. Pfützner Science & Health Institute, Mainz, Germany
2. University for Digital Technologies in Medicine and Dentistry, Wiltz, Luxembourg
3. Technical University, Bingen, Germany
Abstract
Background: Testing the potential influence of interfering substances on the measurement performance of needle sensors for continuous glucose monitoring (CGM) is a challenging task. For proper function, the sensors need an almost stable fluidic environment. Previously published in vitro interference experiments were measuring under static concentration conditons. Our experimental setup allows for interference testing with dynamic changes of the interferent concentrations. Methods: We designed a macrofluidic test stand that is fueled by several high-pressure liquid chromatography (HPLC) pumps generating programmable glucose and/or interferent gradients in phosphate-buffered saline (PBS). After optimizing experimental parameters (channel dimensions, temperature, flow rates, gradient slopes, buffer, pH etc.), we validated the setup using Dexcom G6 (G6) and Freestyle Libre 2 (L2) sensors with/without interferents, and using YSI 2300 Stat plus as the reference glucose device at room temperature. Results: Both sensors tracked the programmed glucose changes. After calibration, G6 results closely matched glucose reference readings, while L2 routinely showed ~50% to 60% lower readings, most likely because of the factory-based calibration and temperature compensation. Gradients of maltose, acetaminophen, and xylose were employed to further validate the setup. As expected, both sensors were not affected by maltose. We confirmed previous findings regarding susceptibility of G6 readings to acetaminophen and L2 readings to xylose. Signals from both sensors are influenced by temperature in a linear fashion. Conclusions: Our experimental in vitro setup and protocol may provide a useful method to dynamically test CGM sensors for interfering substances. This may help to improve the accuracy of future CGM sensor generations.
Funder
H2020 Innovation Grant
Lifescan Global Corporation
Subject
Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine
Cited by
3 articles.
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