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

Iris M Wentholt, Joost B Hoekstra, J Hans Devries
Author Information
  1. Iris M Wentholt: Department of Internal Medicine, Academic Medical Center, Amsterdam, Netherlands. i.m.wentholt@amc.uva.nl

Abstract

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.

MeSH Term

Adult
Blood Glucose
Blood Glucose Self-Monitoring
Female
Humans
Male

Chemicals

Blood Glucose

Word Cloud

Created with Highcharts 10.0.0CG-EGAaccuracyglucosesensorssensorcontinuousdelaytimeIIP0gridmethodsMADintervals=glucose-erroranalysisassessmentdifferent1differencesensitivitydetectinghypo-hyperglycemiacalculatedresultsOBJECTIVE:consensusoptimallyassessexaminedcomparedclassicalusingdatapreviouslyreportedstudycomparingtwotypediabeticpatientsRESEARCHDESIGNANDMETHODS:DriftmeanabsolutespecificityClarkeerrorconstructedalsoincludingexaminationinfluencechoosingpairedreferencevaluesRESULTS:bloodsensed7min<001Sensoraccurateegsmaller011024respectivelybetterhypoglycemia018Correction7-minimproved22%everyrangecontrastrevealParadoxicallydeterioratedcorrectedshorterresultedworseningCONCLUSIONS:detectdifferenceswhereasconventionaldemandinghardinterpretseemvarychosenpresentcontributecombinationvariousestablishedcriticalappraisal

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