Technical Aspects of the Parkes Error Grid

Pfützner, Andreas; Klonoff, David C.; Pardo, Scott; Parkes, Joan Lee

doi:10.1177/193229681300700517

Cited by 99 publications

(81 citation statements)

References 8 publications

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“…These include construction of the scattergram (Figure 1), use of linear regression and correlation (Figure 1), use of the Bland-Altman plot 16 and related approaches (cf Figure 2), the use of the Clarke error grid 25 and the Clarke CGM error grid, 29 the use of the Parkes or consensus error grid, 26 and the use of mean or median ARD for specified ranges of glucose. [1][2][3][4][5][6][7][8][9][10]27 The present method helps to reduce problems related to large random sampling errors when dealing with an AD, ARD, SD, or %CV, and potentially enables the user to characterize ARD and %CV more precisely, accurately, and reliably than the use of a MARD or a mean %CV for a few specified ranges of glucose.…”

Section: Discussionmentioning

confidence: 99%

Characterizing Accuracy and Precision of Glucose Sensors and Meters

Rodbard¹

2014

J Diabetes Sci Technol

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Background: There is need for a method to describe precision and accuracy of glucose measurement as a smooth continuous function of glucose level rather than as a step function for a few discrete ranges of glucose. We propose and illustrate a method to generate a "Glucose Precision Profile" showing absolute relative deviation (ARD) and /or %CV versus glucose level to better characterize measurement errors at any glucose level. Method:We examine the relationship between glucose measured by test and comparator methods using linear regression. We examine bias by plotting deviation = (test -comparator method) versus glucose level. We compute the deviation, absolute deviation (AD), ARD, and standard deviation (SD) for each data pair. We utilize curve smoothing procedures to minimize the effects of random sampling variability to facilitate identification and display of the underlying relationships between ARD or %CV and glucose level.Results: AD, ARD, SD, and %CV display smooth continuous relationships versus glucose level. Estimates of MARD and %CV are subject to relatively large errors in the hypoglycemic range due in part to a markedly nonlinear relationship with glucose level and in part to the limited number of observations in the hypoglycemic range. Conclusions:The curvilinear relationships of ARD and %CV versus glucose level are helpful when characterizing and comparing the precision and accuracy of glucose sensors and meters.

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Section: Discussionmentioning

confidence: 99%

Characterizing Accuracy and Precision of Glucose Sensors and Meters

Rodbard¹

2014

J Diabetes Sci Technol

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“…Os gráficos foram confeccionados utilizando-se o aplicativo Analyse-it. As GAE foram elaboradas conforme os limites definidos por Parkes et al (12) e PFÜTZNER et al (16) e sua confecção também foi efetuada com o programa Excel versão 2017. Os valores de glicemia mensurados pelos glicosímetros foram comparados a partir da glicemia total capilar e da glicemia estimada para plasma equivalente, conforme proposto por Gerber e Freeman.…”

Section: Análise Dos Dadosunclassified

Avaliação da acurácia de dois glicosímetros veterinários para uso em cães

Correa

Leme

Val

2018

Semin. Cienc. Biol. Saude

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Os glicosímetros (GT) são estratégia importante para mensuração da glicemia. Devem estar dentro das especificações da ISO 15197:2013 e avaliados pela análise da grade de erros. Objetivou-se avaliar a acurácia de dois glicosímetros veterinários (GT1 e GT2), pela comparação dos valores de glicemia mensurados em sangue capilar, com aqueles fornecidos por métodos laboratoriais de referência em amostras plasmáticas, transformadas ou não em valores de plasma equivalente. Na avaliação de GT1 em amostras de sangue capilar e o método laboratorial hexoquinase obtiveram-se média das diferenças de 25,90 mg/dL e 26 % das amostras recaíram sobre os limites propostos pela ISO15197: 2013. A comparação de GT1 aos valores de glicemia estimados para plasma equivalente, mostrou média de diferenças de 10,89 mg/dL e 99 % das amostras atenderam aos limites pretendidos. Comparações avaliação de GT2 e o método laboratorial glicose oxidase em amostras de sangue total capilar, a média das diferenças foi 10,58 mg/dL e 22 % das amostras atenderam aos intervalos propostos pela ISO15197: 2013; quando avaliado pela glicemia estimada para plasma equivalente, a média das diferenças foi de 9,7029 mg/dL e 99% das amostras atenderam aos limites. Quando avaliados pela grade de erros de erros, 87% das amostras avaliadas por GT1 recaíram sobre as zonas de erros A e B e aquelas avaliadas por GT2 apresentaram 86% das amostras sobre tais zonas. Os glicosímetros avaliados não apresentaram a acurácia para mensuração da glicemia capilar conforme os padrões expostos pela normativa ISO 15197:2013. ARTIGOS / ARTICLES CIÊNCIAS BIOLÓGICAS E DA SAÚDEPalavras chave: Glicemia. Monitoramento. Ensaios clínicos.The glucometers (GT) are important strategy for measuring blood glucose. They must be within the specifications of ISO 15197: 2013 and evaluated by analysis of the error grid. The objective of this study was to evaluate the accuracy of two veterinary glucometers (GT1 and GT2) by comparing the blood glucose values measured in capillary blood with those provided by reference laboratory method in plasma samples, transformed or not at equivalent plasma values. In the evaluation of GT1 in capillary blood samples and the hexokinase laboratory method, the mean differences were 25.90 mg / dL and 26% of the samples fell within the limits proposed by ISO 15197: 2013. The comparison of GT1 to the estimated plasma glucose values showed a mean difference of 10.89 mg / dL and 99% of the samples were in the desired limits. Comparisons of GT2 and laboratory glucose oxidase in capillary blood samples, mean differences were 10.58 mg / dL and 22% of the samples met the ranges proposed by ISO; 15197: 2013. When evaluated by the estimated plasma glucose, the mean differences were 9.7029 mg / dL and 99% of the samples met the limits. When evaluated by the error grid, 87% of the samples evaluated by GT1 fell on the zones of errors A and B and those evaluated by GT2 presented 86% of the samples on such zones. The glucometers evaluated did not present the accuracy to measure capillary ...

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“…10 Although a consensus guideline was proposed in 2008, 12 the scientific community has yet to agree upon how to best assess CGM accuracy. Metrics for accuracy include MARD, mean absolute difference, which is commonly used for assessment of the hypoglycemic range, percentage of egregious errors (>20% error), Clarke error grid, 13 continuous glucose-error grid, 14 Parkes error grid, 15 and the Surveillance error grid. 16 The correct reference further complicates the issue.…”

Section: -6mentioning

confidence: 99%

Future of Automated Insulin Delivery Systems

Castle

DeVries

Kovatchev

2017

Diabetes Technology & Therapeutics

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Advances in continuous glucose monitoring (CGM) have brought on a paradigm shift in the management of type 1 diabetes. These advances have enabled the automation of insulin delivery, where an algorithm determines the insulin delivery rate in response to the CGM values. There are multiple automated insulin delivery (AID) systems in development. A system that automates basal insulin delivery has already received Food and Drug Administration approval, and more systems are likely to follow. As the field of AID matures, future systems may incorporate additional hormones and/or multiple inputs, such as activity level. All AID systems are impacted by CGM accuracy and future CGM devices must be shown to be sufficiently accurate to be safely incorporated into AID. In this article, we summarize recent achievements in AID development, with a special emphasis on CGM sensor performance, and discuss the future of AID systems from the point of view of their input-output characteristics, form factor, and adaptability.

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Technical Aspects of the Parkes Error Grid

Cited by 99 publications

References 8 publications

Characterizing Accuracy and Precision of Glucose Sensors and Meters

Characterizing Accuracy and Precision of Glucose Sensors and Meters

Avaliação da acurácia de dois glicosímetros veterinários para uso em cães

Future of Automated Insulin Delivery Systems

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