There is no consensus on how to optimally assess the accuracy of continuous glucose sensors. We examined the continuous glucose–error grid analysis (CG-EGA) and compared it with classical accuracy assessment methods, using data from a previously reported study comparing two different continuous glucose sensors in type 1 diabetic patients.RESEARCH DESIGN AND METHODS
Drift, delay, mean absolute difference (MAD), sensitivity, and specificity for detecting hypo- and hyperglycemia were calculated, and a Clarke error grid and a CG-EGA were constructed for both sensors, also including an examination of the influence of choosing different time intervals for paired sensor and reference glucose values.RESULTS
For sensor II, there was a delay between blood glucose and sensed glucose (7.1 min, P < 0.001). Sensor II was more accurate than sensor I during hypo- and hyperglycemia (e.g., smaller MAD, P = 0.011 and P = 0.024, respectively; better sensitivity for detecting hypoglycemia, P = 0.018). Correction for the 7-min delay improved sensor II MAD with 2.2% in every range. In contrast, CG-EGA did not reveal a difference in accuracy between the sensors. Paradoxically, CG-EGA results for sensor II deteriorated when corrected for the delay. CG-EGA calculated with shorter time intervals resulted in worsening accuracy for both sensors.CONCLUSIONS
CG-EGA did not detect differences in accuracy whereas conventional methods did. CG-EGA is time demanding; results are hard to interpret and seem to vary with chosen time intervals. At present, CG-EGA does not contribute to a combination of various established assessment methods.