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Evaluating the Accuracy of Continuous Glucose-Monitoring Sensors

Continuous glucose–error grid analysis illustrated by TheraSense Freestyle Navigator data

¹ Department of Psychiatric Medicine, University of Virginia Health System, Charlottesville, Virginia
² Department of Pediatrics, University of Virginia Health System, Charlottesville, Virginia

Address correspondence and reprint requests to Dr. Boris Kovatchev, PhD, University of Virginia Health System, Box 800137, Charlottesville, VA 22908. E-mail: boris{at}virginia.edu

OBJECTIVE—The objective of this study was to introduce continuous glucose–error grid analysis (CG-EGA) as a method of evaluating the accuracy of continuous glucose-monitoring sensors in terms of both accurate blood glucose (BG) values and accurate direction and rate of BG fluctuations and to illustrate the application of CG-EGA with data from the TheraSense Freestyle Navigator.

RESEARCH DESIGN AND METHODS—We approach the design of CG-EGA from the understanding that continuous glucose sensors (CGSs) allow the observation of BG fluctuations as a process in time. We account for specifics of process characterization (location, speed, and direction) and for biological limitations of the observed processes (time lags associated with interstitial sensors). CG-EGA includes two interacting components: 1) point–error grid analysis (P-EGA) evaluates the sensor’s accuracy in terms of correct presentation of BG values and 2) rate–error grid analysis (R-EGA) assesses the sensor’s ability to capture the direction and rate of BG fluctuations.

RESULTS—CG-EGA revealed that the accuracy of the Navigator, measured as a percentage of accurate readings plus benign errors, was significantly different at hypoglycemia (73.5%), euglycemia (99%), and hyperglycemia (95.4%). Failure to detect hypoglycemia was the most common error. The point accuracy of the Navigator was relatively stable over a wide range of BG rates of change, and its rate accuracy decreased significantly at high BG levels.

CONCLUSIONS—Traditional self-monitoring of BG device evaluation methods fail to capture the important temporal characteristics of the continuous glucose-monitoring process. CG-EGA addresses this problem, thus providing a comprehensive assessment of sensor accuracy that appears to be a useful adjunct to other CGS performance measures.

Abbreviations: BG, blood glucose • CG-EGA, continuous glucose–error grid analysis • CGS, continuous glucose sensor • EGA, error grid analysis • P-EGA, point–error grid analysis • RBG, reference blood glucose • R-EGA, rate–error grid analysis • SBG, sensor blood glucose • SMBG, self-monitoring of blood glucose

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