image thumbnail

Clarke Error Grid Analysis

version 1.9.0.0 (27.1 KB) by Edgar Guevara
Clarke EGA quantifies the accuracy of glucose estimates generated by meters as compared to reference

4.1K Downloads

Updated 01 Apr 2013

View License

The Clarke error grid approach is used to assess the clinical significance of differences between the glucose measurement technique under test and the venous blood glucose reference measurements. The method uses a Cartesian diagram, in which the values predicted by the technique under test are displayed on the y-axis, whereas the values received from the reference method are displayed on the x-axis. The diagonal represents the perfect agreement between the two, whereas the points below and above the line indicate, respectively, overestimation and underestimation of the actual values. Zone A (acceptable) represents the glucose values that deviate from the reference values by ±20% or are in the hypoglycemic range (<70 mg/dl), when the reference is also within the hypoglycemic range. The values within this range are clinically exact and are thus characterized by correct clinical treatment. Zone B (benign errors) is located above and below zone A; this zone represents those values that deviate from the reference values, which are incremented by 20. The values that fall within zones A and B are clinically acceptable, whereas the values included in areas C-E are potentially dangerous, and there is a possibility of making clinically significant mistakes. [1-4]

Syntax:

[total, percentage] = clarke(y,yp)

Inputs:
y = reference values (mg/dl)
yp = predicted/estimtated values (mg/dl)

Outputs:
total = total points per zone:
total(1) = zone A,
total(2) = zone B, and so on

percentage = percentage of data which fell in certain region:
percentage(1) = zone A,
percentage(2) = zone B, and so on.

Example:
load example_data.mat
[tot, per] = clarke(y,yp)

References:
[1] A. Maran et al., “Continuous subcutaneous glucose monitoring in diabetic patients: a multicenter analysis,” Diabetes Care, vol. 25, no. 2, pp. 347–352, Feb. 2002.
[2] B. P. Kovatchev et al. “Evaluating the accuracy of continuous glucose-monitoring sensors: continuous glucose-error grid analysis illustrated by TheraSense Freestyle Navigator data,” Diabetes Care, vol. 27, no. 8, pp. 1922–1928, Aug. 2004.
[3] E. Guevara and F. J. Gonzalez, “Prediction of Glucose Concentration by Impedance Phase Measurements,” in MEDICAL PHYSICS: Tenth Mexican Symposium on Medical Physics, Mexico City (Mexico), 2008, vol. 1032, pp. 259–261.
[4] E. Guevara and F. J. Gonzalez, “Joint optical-electrical technique for noninvasive glucose monitoring,” REVISTA MEXICANA DE FISICA, vol. 56, no. 5, pp. 430–434, Sep. 2010.

© Edgar Guevara Codina
codina@REMOVETHIScactus.iico.uaslp.mx
File Version 1.2
March 29 2013

Ver. 1.2 Statistics verified, fixed some errors in the display; thanks to Tim Ruchti from Hospira Inc. for the corrections
Ver. 1.1 corrected upper B-C boundary, lower B-C boundary slope ok; thanks to Steven Keith from BD Technologies for the corrections!
MATLAB ver. 7.10.0.499 (R2010a)

Cite As

Edgar Guevara (2022). Clarke Error Grid Analysis (https://www.mathworks.com/matlabcentral/fileexchange/20545-clarke-error-grid-analysis), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2010a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!