Glucose meter performance criteria for tight glycemic control estimated by simulation modeling
Abstract
BACKGROUND: Glucose meter analytical performance criteria required for safe and effective management of patients on tight glycemic control (TGC) are not currently defined. We used simulation modeling to relate glucose meter performance characteristics to insulin dosing errors during TGC. METHODS: We used 29,920 glucose values from patients on TGC at 1 institution to represent the expected distribution of glucose values during TGC, and we used 2 different simulation models to relate glucose meter analytical performance to insulin dosing error using these 29,920 initial glucose values and assuming 10%, 15%, or 20% total allowable error (TEa) criteria. RESULTS: One-category insulin dosing errors were common under all error conditions. Two-category insulin dosing errors occurred more frequently when either 20% or 15% TEa was assumed compared with 10% total error. Dosing errors of 3 or more categories, those most likely to result in hypoglycemia and thus patient harm, occurred infrequently under all error conditions with the exception of 20% TEa. CONCLUSIONS: Glucose meter technologies that operate within a 15% total allowable error tolerance are unlikely to produce large (>or=3-category) insulin dosing errors during TGC. Increasing performance to 10% TEa should reduce the frequency of 2-category insulin dosing errors, although additional studies are necessary to determine the clinical impact of such errors during TGC. Current criteria that allow 20% total allowable error in glucose meters may not be optimal for patient management during TGC.
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Karon et al. found that if there were a total measurement error of 20%, 1- and 2-step errors in insulin dose would occur 45% and 6% of the time, respectively, in a tight glycemic control protocol.
“Karon et al. (18) translated these measurement errors into potential insulin-dosing errors using simulation modeling and found that if there were a total measurement error of 20%, 1- and 2-step errors in insulin dose would occur 45% and 6% of the time, respectively, in a tight glycemic control protocol.”
From Hypoglycemia and Diabetes: A Report of a Workgroup of the American Diabetes Association and The Endocrine Society (2013) · cites this paper as [18]
Cites
Intensive insulin therapy in critically ill patients.
Van den Berghe, G., Wouters, P., Weekers, F., Verwaest, C., Bruyninckx, F., Schetz, M., Vlasselaers, D., Ferdinande, P., Lauwers, P., & Bouillon, R. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa011300 · Cited by 9,977 · see citing works
Intensive versus Conventional Glucose Control in Critically Ill Patients
(2009) · New England Journal of Medicine · doi:10.1056/nejmoa0810625 · Cited by 5,119 · see citing works
Severe hypoglycemia in critically ill patients: risk factors and outcomes
Krinsley, J. S., & Grover, A. (2007) · Critical Care Medicine · doi:10.1097/01.ccm.0000282073.98414.4b · Cited by 671 · see citing works
Implementation of a Safe and Effective Insulin Infusion Protocol in a Medical Intensive Care Unit
Goldberg, P. A., Siegel, M. D., Sherwin, R. S., Halickman, J. I., Lee, M., Bailey, V., Lee, S. L., Dziura, J. D., & Inzucchi, S. E. (2004) · Diabetes Care · doi:10.2337/diacare.27.2.461 · Cited by 481 · see citing works
Reliability of point-of-care testing for glucose measurement in critically ill adults*
Kanji, S., Buffie, J., Hutton, B., Bunting, P. S., Singh, A., McDonald, K. B., Fergusson, D. A., McIntyre, L., & Hébert, P. C. (2005) · Critical Care Medicine · doi:10.1097/01.ccm.0000189939.10881.60 · Cited by 391 · see citing works
Glucose Measurement: Confounding Issues in Setting Targets for Inpatient Management
Dungan, K. M., Chapman, J., Braithwaite, S. S., & Buse, J. B. (2007) · Diabetes Care · doi:10.2337/dc06-1679 · Cited by 292 · see citing works
Consensus Statement on Self-Monitor ing of Blood Glucose
(1987) · Diabetes Care · doi:10.2337/diacare.10.1.95 · Cited by 247 · see citing works
Boyd, J. C., & Bruns, D. E. (2001) · Clinical Chemistry · doi:10.1093/clinchem/47.2.209 · Cited by 227 · see citing works
Self-citationKanji, S., Singh, A., Tierney, M., Meggison, H., McIntyre, L., & Hébert, P. C. (2004) · Intensive Care Medicine · doi:10.1007/s00134-004-2252-2 · Cited by 206 · see citing works
Tang, Z., Louie, R. F., Lee, J. H., Lee, D. M., Miller, E. E., & Kost, G. J. (2001) · Critical Care Medicine · doi:10.1097/00003246-200105000-00038 · Cited by 187 · see citing works
Accuracy of bedside glucose measurement from three glucometers in critically ill patients*
Hoedemaekers, C., Gunnewiek, J. M. T. K., Prinsen, M. A., Willems, J. L., & van der Hoeven, J. G. (2008) · Critical Care Medicine · doi:10.1097/ccm.0b013e318186ffe6 · Cited by 165 · see citing works
Tight glucose control in the intensive care unit: Are glucose meters up to the task?
Scott, M. G., Bruns, D. E., Boyd, J. C., & Sacks, D. B. (2009) · Clinical Chemistry · doi:10.1373/clinchem.2008.117291 · Cited by 162 · see citing works
Self-citationKhan, A. I., Vasquez, Y., Gray, J., Wians, F. H., & Kroll, M. H. (2006) · Archives of Pathology & Laboratory Medicine · doi:10.5858/2006-130-1527-tvorbp · Cited by 133 · see citing works
Karon, B. S., Griesmann, L. D., Scott, R. J., Bryant, S. C., DuBois, J. A., Shirey, T., Presti, S., & Santrach, P. J. (2008) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2007.0257 · Cited by 132 · see citing works
Self-citationAn Insulin Infusion Protocol in Critically Ill Cardiothoracic Surgery Patients
Zimmerman, C. R., Mlynarek, M. E., Jordan, J., Rajda, C. A., & Horst, H. M. (2004) · Annals of Pharmacotherapy · doi:10.1345/aph.1e018 · Cited by 121 · see citing works
Karon, B. S., Gandhi, G. Y., Nuttall, G. A., Bryant, S. C., Schaff, H. V., McMahon, M. M., & Santrach, P. J. (2007) · American Journal of Clinical Pathology · doi:10.1309/6rfqckaajgkwb8m4 · Cited by 98 · see citing works
Self-citationPetersen, J. R., Graves, D. F., Tacker, D. H., et al. (2008) · Clinica Chimica Acta · doi:10.1016/j.cca.2008.06.010 · Cited by 88 · see citing works
Intensive Insulin Therapy for Critically III Patients
Lewis, K. S., Kane‐Gill, S. L., Bobek, M. B., & Dasta, J. F. (2004) · Annals of Pharmacotherapy · doi:10.1345/aph.1d211 · Cited by 87 · see citing works
Boyd, J. C., & Bruns, D. E. (2009) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(09)67016-6 · Cited by 50 · see citing works
Self-citationAccuracy of Glycemic Measurements in the Critically Ill
Slater-MacLean, L., Cembrowski, G. S., Chin, D., et al. (2008) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2008.0263 · Cited by 47 · see citing works
Kost, G. J., Tran, N. K., Abad, V. J., & Louie, R. F. (2007) · Clinica Chimica Acta · doi:10.1016/j.cca.2007.11.019 · Cited by 45 · see citing works
Pelletier, O., & Arratoon, C. (1987) · Clinical Chemistry · doi:10.1093/clinchem/33.8.1397 · Cited by 41 · see citing works
Can Changes in Troponin Results Be Useful in Diagnosing Myocardial Infarction?
Aakre, K. M., & Sandberg, S. (2010) · Clinical Chemistry · doi:10.1373/clinchem.2010.146639 · Cited by 18 · see citing works
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Seaquist, E. R., Anderson, J., Childs, B., Cryer, P., Dagogo-Jack, S., Fish, L., Heller, S. R., Rodriguez, H., Rosenzweig, J., & Vigersky, R. (2013) · Diabetes Care · doi:10.2337/dc12-2480 · Cited by 1,389 · see citing works
“(18) translated these measurement errors into potential insulin-dosing errors using simulation modeling and found that if there were a total measurement error of 20%, 1- and 2-step errors in insulin dose would occur 45% and 6% of the time, respectively, in a tight glycemic control protocol.”
BackgroundSeaquist, E. R., Anderson, J., Childs, B., Cryer, P., Dagogo-Jack, S., Fish, L., Heller, S. R., Rodriguez, H., Rosenzweig, J., & Vigersky, R. (2013) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2012-4127 · Cited by 412 · see citing works
Performance of Cleared Blood Glucose Monitors
Klonoff, D. C., & Prahalad, P. (2015) · Journal of Diabetes Science and Technology · doi:10.1177/1932296815584797 · Cited by 59 · see citing works
Clinical impact of blood glucose monitoring accuracy: an in-silico study
Campos-Náñez, E., Fortwaengler, K., & Breton, M. D. (2017) · Journal of Diabetes Science and Technology · doi:10.1177/1932296817710474 · Cited by 22 · see citing works
Karon, B. S., Meeusen, J. W., & Bryant, S. C. (2016) · Journal of Diabetes Science and Technology · doi:10.1177/1932296815602099 · Cited by 16 · see citing works
Self-citation
- Authors
- Karon, B. S., Boyd, J. C., & Klee, G. G.
- Affiliations
- Mayo Clinic (US)
- University of Virginia Health System (US)
- Corresponding author
- Klee, George G
- ORCID
- Karon, Brad S
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-07-01
- Volume
- 56
- Issue
- 7
- Pages
- 1091-1097
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- OpenAlex
- W2116027030
- Cited by
- 94
- References
- 23
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 3 · 2021: 4 · 2020: 3 · 2019: 5 · 2018: 2 · 2017: 6 · 2016: 7 · 2015: 8 · 2014: 17 · 2013: 9 · 2012: 13
- FWCI
- 7.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Clinical Chemistry (publishedVersion)
- PubMed (publishedVersion)
- Funders
- World Anti-Doping Agency
- Topics
- Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Hyperglycemia and glycemic control in critically ill and hospitalized patients
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- blood glucose meters, tight glycemic control, insulin dosing errors, total allowable error, hypoglycemia, diabetes management, computer simulation, blood glucose measurement
- MeSH terms
- Blood Chemical Analysis, Blood Glucose, Computer Simulation, Humans, Hypoglycemic Agents, Insulin, Intensive Care Units, Monitoring, Physiologic, Critical Illness
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