Continuous Glucose Sensors: Continuing Questions about Clinical Accuracy
Open accessAbstract
Continuous glucose sensors (CGS) offer the potential to greatly change the lives of people with diabetes. Even though two of these systems (Guardian RT, Medtronic, Northridge, CA, and DexCom STS, DexCom, San Diego, CA) have been approved by the Food and Drug Administration for use as adjuncts to self-blood glucose monitoring (SBGM), questions remain concerning the accuracy of these devices. When considering accuracy, two distinct approaches should be emphasized: (1) numerical and (2) clinical. Because CGS data are a process in time, each of these two approaches includes two subtypes of accuracy: point and rate. Conventional statistics such as correlation coefficients, mean and median relative absolute differences, and International Standards Organization criteria are measures of numerical point accuracy. A new measure, the R deviation, is introduced to quantify numerical rate accuracy. Error-grid analysis (Clarke EGA) measures clinical point accuracy. The only measure of both clinical point accuracy and rate accuracy is continuous glucose error-grid analysis. This analysis is a combination of two components, P-EGA measuring point accuracy and R-EGA measuring rate accuracy, which are designed to assess the information that distinguishes continuous glucose measurements from intermittent SBGM determinations. Further, a better understanding of the source of the error associated with time lag and its effect on CGS readings may improve sensor output. Finally, the reliability of the CGS sensors, in terms of initial calibration and long-term application, needs to be assessed carefully if current CGS systems are to be used as hypoglycemia monitors or incorporated in the future design of closed loop (artificial pancreas) systems.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Current numerical and clinical accuracy criteria for CGM include linear regressions and correlation coefficients, MAD and MARD, Clarke Error Grid Analysis, and ISO criteria.
“Current numerical and clinical accuracy criteria for CGM includes linear regressions and correlation coefficients; mean (or median) absolute and relative absolute difference (MAD and MARD); Clarke Error Grid Analysis (Clarke EGA); and, International Standard Organization (ISO) criteria.76”
From Biocompatible Materials for Continuous Glucose Monitoring Devices (2013) · cites this paper as [76]
Cites
Evaluating clinical accuracy of systems for self-monitoring of blood glucose
Clarke, W. L., Cox, D., Gonder-Frederick, L. A., Carter, W., & Pohl, S. L. (1987) · Diabetes Care · doi:10.2337/diacare.10.5.622 · Cited by 1,435 · see citing works
Self-citationKlonoff, D. C. (2005) · Diabetes Care · doi:10.2337/diacare.28.5.1231 · Cited by 725 · see citing works
Deiss, D., Bolinder, J., Riveline, J.-P., Battelino, T., Bosi, E., Tubiana-Rufi, N., Kerr, D., & Phillip, M. (2006) · Diabetes Care · doi:10.2337/dc06-1134 · Cited by 539 · see citing works
Feasibility of Automating Insulin Delivery for the Treatment of Type 1 Diabetes
Steil, G. M., Rebrin, K., Darwin, C. H., Hariri, F., & Saad, M. F. (2006) · Diabetes · doi:10.2337/db06-0419 · Cited by 473 · see citing works
Continuous glucose monitoring and closed‐loop systems
Hovorka, R. (2005) · Diabetic Medicine · doi:10.1111/j.1464-5491.2005.01672.x · Cited by 440 · see citing works
Improvement in Glycemic Excursions With a Transcutaneous, Real-Time Continuous Glucose Sensor
Garg, S. K., Zisser, H., Schwartz, S. L., Bailey, T. S., Kaplan, R. A., Ellis, S. L., & Jovanovič, L. (2006) · Diabetes Care · doi:10.2337/diacare.29.01.06.dc05-1686 · Cited by 429 · see citing works
Boyne, M. S., Silver, D. M., Kaplan, J., & Saudek, C. D. (2003) · Diabetes · doi:10.2337/diabetes.52.11.2790 · Cited by 404 · see citing works
Evaluating the Accuracy of Continuous Glucose-Monitoring Sensors
Kovatchev, B. P., Gonder-Frederick, L. A., Cox, D. J., & Clarke, W. L. (2004) · Diabetes Care · doi:10.2337/diacare.27.8.1922 · Cited by 312 · see citing works
Self-citationAccuracy of the 5-Day FreeStyle Navigator Continuous Glucose Monitoring System
Weinstein, R. L., Schwartz, S. L., Brazg, R., Bugler, J., Peyser, T. A., & McGarraugh, G. V. (2007) · Diabetes Care · doi:10.2337/dc06-1602 · Cited by 228 · see citing works
Clarke, W. L., Anderson, S. M., Farhy, L. S., Breton, M. D., Gonder-Frederick, L. A., Cox, D. J., & Kovatchev, B. P. (2005) · Diabetes Care · doi:10.2337/diacare.28.10.2412 · Cited by 154 · see citing works
Self-citationImplantable closed-loop glucose-sensing and insulin delivery: the future for insulin pump therapy
Renard, É. (2002) · Current Opinion in Pharmacology · doi:10.1016/s1471-4892(02)00216-3 · Cited by 151 · see citing works
KAUFMAN, F. R., Austin, J., Neinstein, A. B., Jeng, L., Halvorson, M., Devoe, D. J., & Pitukcheewanont, P. (2002) · The Journal of Pediatrics · doi:10.1067/mpd.2002.129175 · Cited by 136 · see citing works
Wilson, D. M., Beck, R. W., Tamborlane, W. V., Dontchev, M., Kollman, C., Chase, P., Fox, L. A., Ruedy, K. J., Tsalikian, E., WEINZIMER, S. A., et al. (2006) · Diabetes Care · doi:10.2337/dc06-1407 · Cited by 135 · see citing works
Closed-loop and Open-loop Devices for Blood Glucose Control in Normal and Diabetic Subjects
Santiago, J. V., Clemens, A. H., Clarke, W. L., & KIPNIS, D. M. (1978) · Diabetes · doi:10.2337/diab.28.1.71 · Cited by 134 · see citing works
Self-citationWentholt, I. M. E., Vollebregt, M. A., Hart, A. A. M., Hoekstra, J. B. L., & DeVries, J. H. (2005) · Diabetes Care · doi:10.2337/diacare.28.12.2871 · Cited by 118 · see citing works
(2003) · Diabetes Technology & Therapeutics · doi:10.1089/152091503322526987 · Cited by 113 · see citing works
The Diabetes Research in Children Network (DirecNet) Study Group (2005) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2005.7.109 · Cited by 82 · see citing works
King, C., Anderson, S. M., Breton, M. D., Clarke, W. L., & Kovatchev, B. P. (2007) · Journal of Diabetes Science and Technology · doi:10.1177/193229680700100302 · Cited by 65 · see citing works
Self-citation(2003) · Diabetes Technology & Therapeutics · doi:10.1089/152091503322526996 · Cited by 60 · see citing works
Klonoff, D. C. (2004) · Diabetes Care · doi:10.2337/diacare.27.3.834 · Cited by 56 · see citing works
Deiss, D., Kordonouri, O., Meyer, K., & Danne, T. (2001) · Diabetic Medicine · doi:10.1046/j.1464-5491.2001.00429-3.x · Cited by 25 · see citing works
A Critical Appraisal of the Continuous Glucose–Error Grid Analysis
Clarke, W. L., Gonder-Frederick, L. A., Cox, D. J., et al. (2007) · Diabetes Care · doi:10.2337/dc06-1901 · Cited by 7 · see citing works
Self-citationChang, Y., Chiu, K. C., & Chuang, L. (2007) · Diabetes · doi:10.2337/db07-1302 · Cited by 7 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
<i>In Silico</i> Preclinical Trials: A Proof of Concept in Closed-Loop Control of Type 1 Diabetes
Kovatchev, B. P., Breton, M., Dalla Man, C., & Cobelli, C. (2009) · Journal of Diabetes Science and Technology · doi:10.1177/193229680900300106 · Cited by 760 · see citing works
Self-citationArtificial Pancreas: Past, Present, Future
Cobelli, C., Renard, E., & Kovatchev, B. (2011) · Diabetes · doi:10.2337/db11-0654 · Cited by 600 · see citing works
Self-citationDiabetes: Models, Signals, and Control
Cobelli, C., Dalla Man, C., Sparacino, G., Magni, L., De Nicolao, G., & Kovatchev, B. P. (2009) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2009.2036073 · Cited by 511 · see citing works
“measurement [216]–[219] and may be reaching a physiological”
Self-citationBiocompatible Materials for Continuous Glucose Monitoring Devices
Nichols, S. P., Koh, A., Storm, W. L., Shin, J. H., & Schoenfisch, M. H. (2013) · Chemical Reviews · doi:10.1021/cr300387j · Cited by 347 · see citing works
Technologies for Continuous Glucose Monitoring: Current Problems and Future Promises
Vaddiraju, S., Burgess, D. J., Tomazos, I., Jain, F. C., & Papadimitrakopoulos, F. (2010) · Journal of Diabetes Science and Technology · doi:10.1177/193229681000400632 · Cited by 285 · see citing works
- Authors
- Clarke, W. L., & Kovatchev, B.
- Affiliations
- University of Virginia (US)
- Corresponding author
- Clarke, William L.
- ORCID
- Kovatchev, Boris
- Venue
- Journal of Diabetes Science and Technology
- Publisher
- SAGE Publications
- Published
- 2007-09
- Volume
- 1
- Issue
- 5
- Pages
- 669-675
- ISSN
- 1932-2968 (ISSN-L)
- PMC
- PMC2769659
- OpenAlex
- W2098977530
- Cited by
- 71
- References
- 23
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 1 · 2023: 2 · 2022: 1 · 2021: 2 · 2020: 3 · 2019: 1 · 2018: 6 · 2017: 4 · 2016: 2 · 2015: 8 · 2014: 10 · 2013: 3 · 2012: 3
- Type
- conference abstract
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Diabetes Science and Technology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01dk051562-23)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01-DK-051562)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrochemical sensors and biosensors
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- sensor accuracy, diabetes mellitus, error grid analysis, time delay, sensor calibration, artificial pancreas, self-monitoring of blood glucose
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
