Clarke error grid

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The Clarke Error Grid Analysis (EGA) was developed in 1987 to quantify clinical accuracy of patient estimates of their current blood glucose as compared to the blood glucose value obtained in their meter.^[1] It was then used to quantify the clinical accuracy of blood glucose estimates generated by meters as compared to a reference value. A description of the EGA appeared in Diabetes Care in 1987.^[2] Eventually, the EGA became accepted as one of the “gold standards” for determining the accuracy of blood glucose meters.

The grid breaks down a scatterplot of a reference glucose meter and an evaluated glucose meter into five regions:

Region A are those values within 20% of the reference sensor,
Region B contains points that are outside of 20% but would not lead to inappropriate treatment,
Region C are those points leading to unnecessary treatment,
Region D are those points indicating a potentially dangerous failure to detect hypoglycemia or hyperglycemia, and
Region E are those points that would confuse treatment of hypoglycemia for hyperglycemia and vice versa.

References[edit]

^ Clarke WL, Cox D, Gonder-Frederick LA, Carter W, Pohl SL: Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care 10:622–628,1987
^ Clarke, William L.; Cox, Daniel; Gonder-Frederick, Linda A.; Carter, William; Pohl, Stephen L. (1987). «Evaluating Clinical Accuracy of Systems for Self-Monitoring of Blood Glucose». Diabetes Care. 10 (5): 622–628. doi:10.2337/diacare.10.5.622. PMID 3677983. S2CID 26388964.

Источник

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.

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 (2023). Clarke Error Grid Analysis (https://www.mathworks.com/matlabcentral/fileexchange/20545-clarke-error-grid-analysis), MATLAB Central File Exchange.
Retrieved February 9, 2023.

Источник

Сетка ошибок Кларка

Сетка ошибок Кларка Анализ (EGA) был разработан в 1987 году для количественно оценить клиническую точность оценок пациентами их текущего уровня глюкозы в крови по сравнению со значением глюкозы крови, полученным на их глюкометре. Затем его использовали для количественной оценки клинической точности оценок уровня глюкозы в крови, полученных с помощью глюкометров, по сравнению с эталонным значением. Описание EGA появилось в Diabetes Care в 1987 году. В конце концов, EGA стал одним из «золотых стандартов» для определения точности глюкометров.

Сетка разбивает диаграмму рассеяния эталонного глюкометра и оцененного глюкометра на пять областей:

Область A — это значения в пределах 20% от эталонного датчика,
Область B содержит точки, выходящие за пределы 20%, но не приведшие к неправильному лечению,
Область C — это точки, ведущие к ненужному лечению,
Область D — те точки, указывающие потенциально опасная неспособность обнаружить гипогликемию или гипергликемию и
Область E — это те моменты, которые могут спутать лечение гипогликемии с гипергликемией и наоборот.

См. также

Ошибка консенсуса grid

Ссылки

Источник

Clarke Error Grid: The Clarke Error Grid

The Clarke Error Grid Analysis (EGA) was developed in 1987 to quantify clinical accuracy of patient estimates of their current blood glucose as compared to the blood glucose value obtained in their meter.^[1] It was then used to quantify the clinical accuracy of blood glucose estimates generated by meters as compared to a reference value. A description of the EGA appeared in Diabetes Care in 1987.^[2] Eventually, the EGA became accepted as one of the “gold standards” for determining the accuracy of blood glucose meters.

The grid breaks down a scatterplot of a reference glucose meter and an evaluated glucose meter into five regions:^[3]

Region A are those values within 20% of the reference sensor,

Region B contains points that are outside of 20% but would not lead to inappropriate treatment,

Region C are those points leading to unnecessary treatment,

Region D are those points indicating a potentially dangerous failure to detect hypoglycemia or hyperglycemia, and

Region E are those points that would confuse treatment of hypoglycemia] for hyperglycemia and vice-versa.

References

^ Clarke WL, Cox D, Gonder-Frederick LA ,Carter W, Pohl SL: Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care 10:622–628,1987

^ http://care.diabetesjournals.org/cgi/content/abstract/10/5/622?ijkey=959ce0073ff9f91dfd78630b4259267d96a9db0f&keytype2=tf_ipsecsha

^ http://www.fda.gov/cdrh/oivd/guidance/1171.gif

Look at other dictionaries:

Clarke error grid — The Clarke Error Grid Analysis (EGA) was developed in the 1970s to quantify clinical accuracy of patient estimates of their current blood glucose as compared to the blood glucose value obtained in their meter. It was then used to quantify the… … Wikipedia
Consensus error grid — The consensus error grid (also known as the Parkes error grid) was developed as a new tool for evaluating the accuracy of a blood glucose meter. In recent times, the consensus error grid has been used increasingly by blood glucose meter… … Wikipedia
Error-Grid-Analyse — Die Error Grid Analyse (kurz: EGA; auch Fehlerrasteranalyse) dient der Bewertung der klinischen Genauigkeit der Blutzuckermesswerte im Vergleich zu einem Referenzwert. Sie wurde u. a. von W. Clarke (Department of Pediatrics, University of… … Deutsch Wikipedia
Error Grid Analyse — Die Error Grid Analyse (kurz: EGA) dient der Bewertung der klinischen Genauigkeit der Blutzuckermesswerte im Vergleich zu einem Referenzwert. Sie wurde u. a. von W. Clarke (Department of Pediatrics, University of Virginia Medical School,… … Deutsch Wikipedia
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Источник

GlucoWatch Biographer data for comparison MARD 17-21% Clarke error grid A + B 94% Clarke error grid A 60% … [Pg.6]

In Ref. 36, the likelihood test described above is applied to five pairs of implanted sensors and examined on the Clarke error grid for clinical relevance. The percentage… [Pg.231]

Clarke error grid analysis of a study of 15 diabetic rats showed the percentage of readings that fell into the clinically correct regions (Zones A and B) increased from 92% to 96% when applying the Z-score rejection criteria.38 During the long-term implantation (25 4 days), Z-score calculations removed 32% of the individual sensor data from six fully implanted four-sensor arrays.39… [Pg.232]

Finally, the DT/MH AgFON was evaluated in vivo. A representative Clarke error grid analysis of a single rodent is shown in Figure 15.11. All measurements were taken from a single spot on the implanted DT/MH-functionalized AgFON surface. [Pg.436]

Figure 10 NIR-predicted serum glucose levels vs reference assays (see also NIR B in Table 4). Open circles correspond to the calibration (training) set, solid circles to the validation (test) set, and the solid line is the line of identity. A Clarke error grid(3°) is superimposed, distinguishing regions corresponding to clinically safe analytical errors (regions A, B) from analytical errors that would result in dangerously inappropriate clinical decisions (C, D, E). (Adapted from K.H. Hazen, M.A. Arnold, G.W. Small, Measurement of Glucose and Other Analytes in Undiluted Human Serum with Near-infrared Transmission Spectroscopy , Analytica Chimica Acta, 255-267, Vol. 371, 1998, with permission from Elsevier Science.)…

Источник

ClarkeErrorGrid

This has the function for the Clarke Error Grid

Made by Trevor Tsue
7/18/17

CLARKE ERROR GRID ANALYSIS ClarkeErrorGrid.py

Need Matplotlib Pyplot

The Clarke Error Grid shows the differences between a blood glucose predictive measurement and a reference measurement,
and it shows the clinical significance of the differences between these values.
The x-axis corresponds to the reference value and the y-axis corresponds to the prediction.
The diagonal line shows the prediction value is the exact same as the reference value.
This grid is split into five zones. Zone A is defined as clinical accuracy while
zones C, D, and E are considered clinical error.

Zone A: Clinically Accurate
This zone holds the values that differ from the reference values no more than 20 percent
or the values in the hypoglycemic range (<70 mg/dl).
According to the literature, values in zone A are considered clinically accurate.
These values would lead to clinically correct treatment decisions.

Zone B: Clinically Acceptable
This zone holds values that differe more than 20 percent but would lead to
benign or no treatment based on assumptions.

Zone C: Overcorrecting
This zone leads to overcorrecting acceptable BG levels.

Zone D: Failure to Detect
This zone leads to failure to detect and treat errors in BG levels.
The actual BG levels are outside of the acceptable levels while the predictions
lie within the acceptable range

Zone E: Erroneous treatment
This zone leads to erroneous treatment because prediction values are opposite to
actual BG levels, and treatment would be opposite to what is recommended.

SYNTAX:
plot, zone = ClarkeErrorGrid.clarke_error_grid(ref_values, pred_values)

INPUT:
ref_values List of n reference values
pred_values List of n prediciton values

OUTPUT:
plot The Clarke Error Grid Plot returned by the function.
Use this with plot.show()
zone List of values in each zone.
0=A, 1=B, 2=C, 3=D, 4=E

EXAMPLE:
from ClarkeErrorGrid import clarke_error_grid
…
plot, zone = clarke_error_grid(ref_values, pred_values)
plot.show()

References:
[1] Clarke, WL. (2005). «The Original Clarke Error Grid Analysis (EGA).»
Diabetes Technology and Therapeutics 7(5), pp. 776-779.
[2] Maran, A. et al. (2002). «Continuous Subcutaneous Glucose Monitoring in Diabetic
Patients» Diabetes Care, 25(2).
[3] Kovatchev, B.P. et al. (2004). «Evaluating the Accuracy of Continuous Glucose-
Monitoring Sensors» Diabetes Care, 27(8).
[4] Guevara, E. and Gonzalez, F. J. (2008). Prediction of Glucose Concentration by
Impedance Phase Measurements, in MEDICAL PHYSICS: Tenth Mexican
Symposium on Medical Physics, Mexico City, Mexico, vol. 1032, pp.
259261.
[5] Guevara, E. and Gonzalez, F. J. (2010). Joint optical-electrical technique for
noninvasive glucose monitoring, REVISTA MEXICANA DE FISICA, vol. 56,
no. 5, pp. 430434.

Made by:
Trevor Tsue
7/18/17

Based on the Matlab Clarke Error Grid Analysis File Version 1.2 by:
Edgar Guevara Codina
codina@REMOVETHIScactus.iico.uaslp.mx
March 29 2013

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:

Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in
the documentation and/or other materials provided with the distribution

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS «AS IS»
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.

Источник

The Clarke Error Grid Analysis (EGA) is one of the standards for quantifying the accuracy of CGM systems.

Clarke EGA measures accuracy by comparing subject glucose values taken from their CGM system to reference

values taken in a lab.

Clarke EGA calculates accuracy by looking at the number and percentage of data points that fell into 5 «clinical risk»

zones. Data is presented in both graph and chart formats.

•

Zone A (no risk) contains CGM values that fell within ±20% of the reference values.

– Zone A values are considered to be within the acceptable accuracy range of CGM systems.

•

Zone B (no risk) contains CGM values that fell outside ±20% of the reference values.

– Zone B values are not considered to be within the acceptable accuracy range, but their difference from

the reference values would not lead a subject to making an inappropriate treatment decision.

•

Zone C (low risk) contains CGM values that differed enough from the reference values that a subject might make

an unnecessary treatment decision based on the CGM information.

•

Zone D (medium risk) contains CGM values that were correctly identified as hypoglycaemic or hyperglycaemic

by the reference system but not the CGM system.

– Not correctly identifying a CGM value as hypoglycaemic or hyperglycaemic is a potentially dangerous

situation.

•

Zone E (high risk) contains CGM values that were incorrectly identified as hypoglycaemic when the reference

system correctly identified them as hyperglycaemic (and vice versa).

– Mistakenly identifying a CGM value as hypoglycaemic when it is actually hyperglycaemic (or vice versa)

is a potentially dangerous situation.

135

Eversense XL CGM User Guide

Источник

The Clarke Error Grid

The Clarke Error Grid Analysis (EGA) was developed in 1987 to quantify clinical accuracy of patient estimates of their current blood glucose as compared to the blood glucose value obtained in their meter. It was then used to quantify the clinical accuracy of blood glucose estimates generated by meters as compared to a reference value. A description of the EGA appeared in Diabetes Care in 1987. Eventually, the EGA became accepted as one of the “gold standards” for determining the accuracy of blood glucose meters.

The grid breaks down a scatterplot of a reference glucose meter and an evaluated glucose meter into five regions:

Region A are those values within 20% of the reference sensor,
Region B contains points that are outside of 20% but would not lead to inappropriate treatment,
Region C are those points leading to unnecessary treatment,
Region D are those points indicating a potentially dangerous failure to detect hypoglycemia or hyperglycemia, and
Region E are those points that would confuse treatment of hypoglycemia for hyperglycemia and vice versa.

The Clarke Error Grid Analysis (EGA) was developed in the 1970s to quantify clinical accuracy of patient estimates of their current blood glucose as compared to the blood glucose value obtained in their meter. It was then used to quantify the clinical accuracy of blood glucose estimates generated by meters as compared to a reference value. A description of the EGA appeared in Diabetes Care in 1987[1]. Eventually, the EGA became accepted as one of the “gold standards” for determining the accuracy of blood glucose meters.

Additional recommended knowledge

The grid breaks down a scatterplot of a reference glucose meter and an evaluated glucose meter into five regions. Region A are those values within 20% of the reference sensor, Region B contains points that are outside of 20% but would not lead to inappropriate treatment, Region C are those points leading to unnecessary treatment, Region D are those points indicating a potentially dangerous failure to detect hypo or hyper glycemia, and Region E are those points that would confuse treatment of hypoglycemia for hyperglycemia and vice-versa.

Needed: precise definitions of each region.

This article is licensed under the GNU Free Documentation License. It uses material from the Wikipedia article «Clarke_error_grid». A list of authors is available in Wikipedia.

Источник

Clarke error grid

See also[edit]

References[edit]

Cite As

См. также

Ссылки

References

Look at other dictionaries:

ClarkeErrorGrid

See also

Clarke error grid

Additional recommended knowledge