+ Site Statistics
References:
54,258,434
Abstracts:
29,560,870
PMIDs:
28,072,757
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

A new consensus error grid to evaluate the clinical significance of inaccuracies in the measurement of blood glucose



A new consensus error grid to evaluate the clinical significance of inaccuracies in the measurement of blood glucose



Diabetes Care 23(8): 1143-1148



The objectives of this study were 1) to construct new error grids (EGs) for blood glucose (BG) self-monitoring by using the expertise of a large panel of clinicians and 2) to use the new EGs to evaluate the accuracy of BG measurements made by patients. To construct new EGs for type 1 and type 2 diabetic patients, a total of 100 experts of diabetes were asked to assign any error in BG measurement to 1 of 5 risk categories. We used these EGs to evaluate the accuracy of self-monitoring of blood glucose (SMBG) levels in 152 diabetic patients. The SMBG data were used to compare the new type 1 diabetes EG with a traditional EG. Both the type 1 and type 2 diabetes EGs divide the risk plane into 8 concentric zones with no discontinuities. The new EGs are similar to each other, but they differ from the traditional EG in several significant ways. When used to evaluate a data set of measurements made by a sample of patients experienced in SMBG, the new type 1 diabetes EG rated 98.6% of their measurements as clinically acceptable, compared with 95% for the traditional EG. The consensus EGs furnish a new tool for evaluating errors in the measurement of BG for patients with type 1 and type 2 diabetes.

Please choose payment method:






(PDF emailed within 0-6 h: $19.90)

Accession: 045079702

Download citation: RISBibTeXText

PMID: 10937512

DOI: 10.2337/diacare.23.8.1143


Related references

Performance Evaluation of Three Blood Glucose Monitoring Systems Using ISO 15197: 2013 Accuracy Criteria, Consensus and Surveillance Error Grid Analyses, and Insulin Dosing Error Modeling in a Hospital Setting. Journal of Diabetes Science and Technology 10(1): 85-92, 2016

Technical and clinical accuracy of three blood glucose meters: clinical impact assessment using error grid analysis and insulin sliding scales. Journal of Clinical Pathology 69(10): 899-905, 2016

Technical and clinical accuracy of five blood glucose meters: clinical impact assessment using error grid analysis and insulin sliding scales. Journal of Clinical Pathology 68(9): E3-E3, 2015

Comparison of Clarke and consensus error grid analysis of frequent and automatic glucose measurements from the GlucoWatch biographer. Diabetologia 45(Supplement 2): A 280, August, 2002

Altered synaptic transmission and maturation of hippocampal CA1 neurons in a mouse model of human chr16p11.2 microdeletion. Journal of Neurophysiology: Jn.00306.2017-Jn.00306.2017, 2017

Clinical accuracy of the second generation GlucoWatch biographer Assessment by consensus error grid analysis. Diabetologia 45(Supplement 2): A 280, August, 2002

Assessment of blood glucose predictors: the prediction-error grid analysis. Diabetes Technology & Therapeutics 13(8): 787-796, 2011

Reservations on the use of error grid analysis for the validation of blood glucose assays. Diabetes Care 20(6): 1034-1036, 1997

Clinical review: Consensus recommendations on measurement of blood glucose and reporting glycemic control in critically ill adults. Critical Care 17(3): 229-229, 2015

Evaluating clinical accuracy of continuous glucose monitoring systems: Continuous Glucose-Error Grid Analysis (CG-EGA). Current Diabetes Reviews 4(3): 193-199, 2008

Evaluating the clinical accuracy of two continuous glucose sensors using continuous glucose-error grid analysis. Diabetes Care 28(10): 2412-2417, 2005

Evaluating 2 error grid methods using patient blood glucose data collected over an extended period. Diabetes 52(Supplement 1): A92, 2003

Using structural equation models to evaluate the magnitude of measurement error in blood pressure. Statistics in Medicine 20(15): 2351-2368, 2001

Self-measurement of blood glucose concentration: clinical significance of patient-generated measurements. Diabetes Care 8(6): 617-619, 1985

Use of error grid analysis to evaluate acceptability of a point of care prothrombin time meter. Clinica Chimica Acta; International Journal of Clinical Chemistry 411(3-4): 131-134, 2010