Evaluating the Accuracy of Continuous Glucose-Monitoring Sensors
Continuous glucose–error grid analysis illustrated by TheraSense Freestyle Navigator data
- Boris P. Kovatchev, PHD1,
- Linda A. Gonder-Frederick, PHD1,
- Daniel J. Cox, PHD1 and
- William L. Clarke, MD2
- 1Department of Psychiatric Medicine, University of Virginia Health System, Charlottesville, Virginia
- 2Department 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
Abstract
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.
- 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
Footnotes
-
Additional information for this article can be found in an online appendix at http://care.diabetesjournals.org.
B.P.K., L.A.G.-F., D.J.C., and W.L.C. have received consulting fees from TheraSense.
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.
-
- Accepted May 16, 2004.
- Received March 24, 2004.
- DIABETES CARE














