A new consensus error grid to evaluate the clinical significance of inaccuracies in the measurement of blood glucose
Open accessAbstract
OBJECTIVE: 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. RESEARCH DESIGN AND METHODS: 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. RESULTS: 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. CONCLUSIONS: The consensus EGs furnish a new tool for evaluating errors in the measurement of BG for patients with type 1 and type 2 diabetes.
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Analytical accuracy is evaluated by comparing the bias between the result provided by the device under test and a gold standard method.
“Analytical accuracy, instead, is evaluated by comparing the bias between the result provided by the device under test and a gold standard method (specified by the manufacturer) (Figure 2D) 57,58.”
From Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices (2022) · cites this paper as [57]
The SMBG clinical trial (pp. 2, 5) compares patients’ meter readings with hexokinase assay values and reports their percentage deviations, supporting the comparison with a reference method. The paper does not define analytical accuracy as a measure of bias or say that the reference method is specified by the manufacturer; its measurements also include user error. (LLM, conf=0.86)
Experimental — accuracy not yet measuredIn the clinical trial, 99.1% (209/211) of subject palm results were within Zone A of the Parkes-Consensus Error Grid.
“Furthermore, 99.5% (217/218) of trial staff capillary fingertip results and 99.1% (209/211) of subject palm results were within Zone A, with the remainder (0.5% [1/218] and 0.9% [2/211], respectively) within Zone B (Fig. 3B and C).”
From Accuracy and user performance evaluation of the Contour Next Link 2.4 blood glucose monitoring system (2015) · cites this paper as [15]
The Consensus EG section (p. 2) establishes the Parkes grid and defines Zone A, so the source supports the identification of the grid used to classify results. Its own SMBG clinical trial (p. 2) involved 152 subjects and 304 data points; it does not report subject palm results or the 209/211 (99.1%) figure attributed to it. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe Parkes error grid modified the Clarke grid for type 1 and type 2 diabetes to avoid discontinuity between risk areas.
“In 2000, this grid was further modified by Parkes et al., for type 1 and type 2 diabetes (Figure 2 B, C, respectively), to avoid discontinuity between risk areas, in which small changes in glucose levels could lead to significant changes of clinical impact (Parkes error grid or consensus error grid) 57.”
From Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices (2022) · cites this paper as [57]
In the laboratory study, all 600/600 results were within Zone A of the Parkes-Consensus Error Grid.
“Also, all results (600/600) were within Zone A of the Parkes-Consensus Error Grid (data not shown).”
From Accuracy and user performance evaluation of the Contour Next Link 2.4 blood glucose monitoring system (2015) · cites this paper as [15]
In the clinical trial, 99.5% (217/218) of trial staff capillary fingertip results were within Zone A of the Parkes-Consensus Error Grid.
“Furthermore, 99.5% (217/218) of trial staff capillary fingertip results and 99.1% (209/211) of subject palm results were within Zone A, with the remainder (0.5% [1/218] and 0.9% [2/211], respectively) within Zone B (Fig. 3B and C).”
From Accuracy and user performance evaluation of the Contour Next Link 2.4 blood glucose monitoring system (2015) · cites this paper as [15]
By Parkes-Consensus Error Grid analysis, 100% (218/218) of subject-obtained capillary fingertip results in the clinical trial were within Zone A.
“By Parkes-Consensus Error Grid analysis, 100% of subject capillary fingertip results were within Zone A.”
From Accuracy and user performance evaluation of the Contour Next Link 2.4 blood glucose monitoring system (2015) · cites this paper as [15]
The Parkes-Consensus Error Grid has 5 levels of increasing risk, with Zones A and B denoting little or no clinical risk to the patient.
“There are 5 levels of increasing risk, with Zones A and B denoting little or no clinical risk to the patient [15].”
From Accuracy and user performance evaluation of the Contour Next Link 2.4 blood glucose monitoring system (2015) · cites this paper as [15]
ISO 15197:2013 section 6.3 criteria also require that ≥99% of individual measured glucose values fall within Zones A and B of the Parkes-Consensus Error Grid for type 1 diabetes.
“ISO 15197:2013 section 6.3 criteria also require that ≥99% of individual measured glucose values shall fall within Zones A and B of the Parkes-Consensus Error Grid [15] for type 1 diabetes; thus, a Parkes-Consensus Error Grid analysis was performed.”
From Accuracy and user performance evaluation of the Contour Next Link 2.4 blood glucose monitoring system (2015) · cites this paper as [15]
The accuracy of continuous glucose monitors in the hypoglycemic range is poor.
“However, the accuracy of CGMs in the hypoglycemic range is poor as demonstrated by error grid analysis (19,20).”
From Hypoglycemia and Diabetes: A Report of a Workgroup of the American Diabetes Association and The Endocrine Society (2013) · cites this paper as [20]
The SMBG clinical trial (p. 5) uses error-grid analysis to assess measurements from patients using their own blood-glucose meters, not continuous glucose monitors. The paper discusses low-glucose error-grid boundaries, but our copy does not report CGM accuracy in the hypoglycemic range (searched: continuous glucose monitoring, hypoglycemia, low glucose accuracy). (LLM, conf=0.78)
Experimental — accuracy not yet measuredRetrospective and real-time CGMs have poor accuracy in the hypoglycemic range as demonstrated by error grid analysis.
“However, the accuracy of CGMs in the hypoglycemic range is poor as demonstrated by error grid analysis (19,20).”
From Hypoglycemia and Diabetes: A Report of a Workgroup of the American Diabetes Association and The Endocrine Society (2013) · cites this paper as [20]
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- Authors
- Parkes, J. L., Slatin, S. L., Pardo, S., & Ginsberg, B. H.
- Affiliations
- Becton Dickinson (United States) (US)
- ORCID
- Ginsberg, B H
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2000-08-01
- Volume
- 23
- Issue
- 8
- Pages
- 1143-1148
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- OpenAlex
- W2111352982
- Cited by
- 620
- References
- 13
- Citations by year
- 2026: 36 · 2025: 50 · 2024: 57 · 2023: 32 · 2022: 27 · 2021: 38 · 2020: 36 · 2019: 33 · 2018: 37 · 2017: 34 · 2016: 29 · 2015: 22 · 2014: 20 · 2013: 21 · 2012: 25
- FWCI
- 2.18
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes Care (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
- Keywords
- error grid analysis, self-monitoring of blood glucose, measurement error, type 1 diabetes, type 2 diabetes, diabetes self-management
- MeSH terms
- Adult, Blood Glucose, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Female, Humans, Male, Physicians, Regression Analysis, Software, United States, Blood Glucose Self-Monitoring, Reproducibility of Results
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