A critical appraisal of the continuous glucose-error grid analysis.

OBJECTIVE 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.