Measurement of circulating glucose concentrations: the time is now for consistency among methods and types of samples
Abstract
Diabetes mellitus was first described in the Egyptian papyrus of Ebers in 1552 BC by people who noted the attraction of insects to the “sweet urine” of those who produced abnormal amounts and later by tasters of urine who could fashion a diagnosis by recognizing the “sweet taste”. The name “diabetes”, initially used in the 1st century AD, comes from the Greek word meaning “to pass through”. “Mellitus”, a Latin word meaning “sweet as honey”, was added in the 18th century. The first chemical tests to measure sugar in urine were developed in the early 19th century. Early in the last century, whole-blood colorimetric analyses became available to clinicians, despite complexities in the preparation and analysis of samples. The term “blood glucose” remains a prominent feature to describe the state of glycemia in patients with diabetes, whether as a fasting value, during a glucose tolerance test, or in monitoring glucose values to determine the insulin dose. Measurements of glucose in venous whole blood, capillary whole blood, or plasma still define diabetes mellitus by WHO criteria (1), with the American Diabetes Association (ADA) referring only to concentrations in plasma (2). Modern applications of glucose assays practically diverge in the diagnosis vs monitoring of treatment(s) of diabetes. Thus, diagnosis is best made in a certified laboratory with the measurement of glucose in plasma after a fast of at least 8 h (3). The benefits of relating closely monitored glucose concentrations to treatment decisions have become feasible and practical with the availability of small devices capable of measuring with precision and accuracy glucose from low to high concentrations in very small quantities of blood or extracellular fluid. The fact that most devices sample whole blood presents a dilemma when expressing values in plasma vs whole blood. In this issue, D’Orazio et al. (4) have admirably and directly addressed these conundrums with a strong recommendation to report all measured glucose concentrations (whether assayed in plasma, whole venous blood, whole capillary blood, or serum) as if they were assayed in plasma. Their commentary (and importantly, Fig. 1 in their report) suggests a constant to convert values in whole blood to comparable units in plasma. They aver that uniform application of their recommendations will rationalize the use of glucose measurements for diagnosis and monitoring of treatment. Certainly the consistent reporting of all values in plasma equivalents will reduce the 11% bias when values are reported in whole-blood equivalents but interpreted as equating to values in plasma. In addition, they recommend expressing glucose values in SI units. During the usual course of managing their disease, patients with diabetes mellitus will experience glucose measured on different samples by different techniques. For example, they may encounter the healthcare system in the emergency department or otherwise in a hospital or clinic and have venous blood collected and processed for measurement of glucose in plasma. Alternatively, if treated with insulin, they will quite frequently determine glucose concentrations with some kind of hand-held device, which most likely measures glucose in whole blood obtained from capillaries (5). Harmonization of the values reported by these two sets of instruments remains an imperative for clinical medicine in general and the management of diabetes in particular. Thus, the clinician may (and usually does) review the results with the expectation that the glucose values derived from measurement of whole blood or plasma are equivalent. However, that may not always be the case. D’Orazio et al. (4) have proposed a sensible solution with values reported exclusively as equivalents in plasma. This is not the first time these recommendations have been placed before the community of laboratory professionals. In 2001, an IFCC working group in a report (6) very similar to that of D’Orazio et al. (4) (and with several authors in common) recommended that glucose meters be harmonized to the concentration of glucose in plasma, regardless of the technology or type of sample. Two of the authors presented the same recommendation in a still earlier article (7). Similarly, the Clinical and Laboratory Standards Institute (formerly NCCLS) guidelines for point-of-care blood glucose testing published in 2002 recommend that institutions reporting plasma glucose results from instruments in the clinical laboratory should use point-of-care devices that report plasma-equivalent results (8). The practical applications of these recommendations remain somewhat uncertain. D’Orazio et al. (4) emphasize that the WHO guidelines for the diagnosis of diabetes mellitus quote glucose concentrations in plasma, venous whole blood, and capillary whole blood. If one were to use the contrasting concentrations to discriminate “normal” vs impaired glycemia vs diabetes mellitus according to the WHO guidelines, manufacturers o
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
Reporting plasma glucose by meters can improve harmonization and allow comparison with laboratory-generated results.
“This approach can improve harmonization and allow comparison with laboratorygenerated results (121).”
From Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus (2011) · cites this paper as [121]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Sacks, D. B., Arnold, M., Bakris, G. L., Bruns, D. E., Horvath, A. R., Kirkman, M. S., Lernmark, A., Metzger, B. E., & Nathan, D. M. (2011) · Clinical Chemistry · doi:10.1373/clinchem.2010.161596 · Cited by 1,360 · see citing works
Self-citationSacks, D. B., Bruns, D. E., Goldstein, D. E., Maclaren, N. K., McDonald, J. M., & Parrott, M. A. (2002) · Clinical Chemistry · doi:10.1093/clinchem/48.3.436 · Cited by 1,128 · see citing works
Self-citationDiagnosis and Classification of Diabetes Mellitus
American Diabetes Association (2005) · Diabetes Care · doi:10.2337/diacare.28.suppl_1.s37 · Cited by 830 · see citing works
Approved IFCC recommendation on reporting results for blood glucose (abbreviated)
D'Orazio, P. (2005) · Clinical Chemistry · doi:10.1373/clinchem.2005.051979 · Cited by 208 · see citing works
*The Diabetes Research in Children Network (DirecNet) Study Group (2004) · Diabetes Care · doi:10.2337/diacare.27.3.722 · Cited by 114 · see citing works
IFCC recommendation on reporting results for blood glucose
(2001) · Clinica Chimica Acta · doi:10.1016/s0009-8981(01)00431-4 · Cited by 110 · see citing works
Proposal for standardizing direct-reading biosensors for blood glucose
Fogh‐Andersen, N., & D’Orazio, P. (1998) · Clinical Chemistry · doi:10.1093/clinchem/44.3.655 · Cited by 84 · see citing works
Klonoff, D. C. (2004) · Diabetes Care · doi:10.2337/diacare.27.3.834 · Cited by 56 · see citing works
The Diabetes Research In Children, N. (2003) · Diabetes Technology & Therapeutics · doi:10.1089/152091503322640971 · Cited by 44 · see citing works
Alberti (1998) · doi:10.1002/(sici)1096-9136(199807)15:7
Flagged first, then by citations
Cited by
Sorted by citations
Sacks, D. B., Arnold, M., Bakris, G. L., Bruns, D. E., Horvath, A. R., Kirkman, M. S., Lernmark, A., Metzger, B. E., & Nathan, D. M. (2011) · Clinical Chemistry · doi:10.1373/clinchem.2010.161596 · Cited by 1,360 · see citing works
Self-citationSacks, D. B., Arnold, M., Bakris, G. L., Bruns, D. E., Horvath, A. R., Kirkman, M. S., Lernmark, A., Metzger, B. E., & Nathan, D. M. (2011) · Diabetes Care · doi:10.2337/dc11-9998 · Cited by 718 · see citing works
Self-citationA1c versus glucose testing: a comparison
Sacks, D. B. (2011) · Diabetes Care · doi:10.2337/dc10-1546 · Cited by 461 · see citing works
Self-citationSacks, D. B., Arnold, M., Bakris, G. L., Bruns, D. E., Horvath, A. R., Lernmark, Å., Metzger, B. E., Nathan, D. M., & Kirkman, M. S. (2023) · Diabetes Care · doi:10.2337/dci23-0036 · Cited by 351 · see citing works
“This approach can improve harmonization and allow comparison with laboratorygenerated results (121).”
Self-citationSacks, D. B., Arnold, M. A., Bakris, G. L., Bruns, D. E., Horvath, A. R., Lernmark, Å., Metzger, B. E., Nathan, D. M., & Kirkman, M. S. (2023) · Clinical Chemistry · doi:10.1093/clinchem/hvad080 · Cited by 157 · see citing works
Self-citationContinuous Noninvasive Glucose Monitoring Technology Based on “Occlusion Spectroscopy”
Amir, O., Weinstein, D., Zilberman, S., Less, M., Perl‐Treves, D., Primack, H., Weinstein, A., Gabis, E., Fikhte, B. A., & Karasik, A. (2007) · Journal of Diabetes Science and Technology · doi:10.1177/193229680700100403 · Cited by 123 · see citing works
Roomp, K., & Rand, J. S. (2009) · Journal of Feline Medicine and Surgery · doi:10.1016/j.jfms.2009.04.010 · Cited by 102 · see citing works
Blood Glucose Determination: Plasma or Serum?
Frank, E. A., Shubha, M. C., & D’Souza, C. J. M. (2012) · Journal of Clinical Laboratory Analysis · doi:10.1002/jcla.21524 · Cited by 53 · see citing works
Flegar-Meštrić, Z., & Perkov, S. (2006) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm.2006.148 · Cited by 32 · see citing works
How accurately do we measure blood glucose levels in intensive care unit (ICU) patients?
Wahl, H. G. (2009) · Best practice & research. Clinical anaesthesiology · doi:10.1016/j.bpa.2009.09.003 · Cited by 27 · see citing works
Evolution of Screening and Diagnostic Criteria for GDM Worldwide
Agarwal, M. (2010) · Springer eBooks · doi:10.1007/978-1-84882-120-0_3 · Cited by 15 · see citing works
NIR-Spectroscopic Classification of Blood Glucose Level using Machine Learning Approach
Habibullah, M., Oninda, M. A. M., Bahar, A. N., Dinh, A., & Wahid, K. A. (2019) · Conference proceedings - Canadian Conference on Electrical and Computer Engineering · doi:10.1109/ccece.2019.8861843 · Cited by 12 · see citing works
Kunstman, J. W., Healy, J. M., Araya, D. A., & Salem, R. R. (2014) · The American Journal of Surgery · doi:10.1016/j.amjsurg.2014.06.029 · Cited by 8 · see citing works
Effect of delay on measurement of blood glucose levels in young subjects with type 1 diabetes
Elleri, D., Acerini, C. L., Allen, J. M., Larsen, A. M. F., Wilinska, M. E., Dunger, D. B., & Hovorka, R. (2009) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2009.06.025 · Cited by 4 · see citing works
Methods for the determination of glucose in blood. Part 2
Buzanovskii, V. A. (2015) · Review Journal of Chemistry · doi:10.1134/s2079978015020028 · Cited by 4 · see citing works
Shatilo, V. B., Bondarenko, E. V., & Antoniuk-Shcheglova, I. A. (2013) · Advances in Gerontology · doi:10.1134/s207905701301013x · Cited by 3 · see citing works
Tumani, H., & Hegen, H. (2015) · Springer eBooks · doi:10.1007/978-3-319-01225-4_7 · Cited by 2 · see citing works
Validation of two human point-of-care glucometers for glucose concentration determination in rats
(2021) · Journal of Sustainable Veterinary and Allied Sciences · doi:10.54328/covm/josvas.2021.030 · Cited by 1 · see citing works
Harris, R. L. (2008) · doi:10.12794/metadc9774 · Cited by 1 · see citing works
Sacks, D. B., Arnold, M. A., Metzger, B. E., & Nathan, D. M. (2012) · Cited by 1 · see citing works
Self-citationAnalysis of ECG signal and Non-Invasive Blood Glucose Monitoring using Neural Networks
Gangadhar, C., Madhav, P. V., Durga, K. D. N., Kamaraju, G., Krishna, J. T. R., & Kowshik, K. G. S. (2024) · International Conference on Pervasive Computing and Social Networking (ICPCSN) · doi:10.1109/icpcsn62568.2024.00025
Daimane, D., & Basu, S. (2024) · Cureus · doi:10.7759/cureus.72641
Which sample matrix is suitable for glucometer external quality control?
Springer, D., Omastová, K., Budina, M., & Zima, T. (2012) · Klinická biochemie a metabolismus · doi:10.61568/kbm.2012.027
Monaghan, J. F., Cullen, D., Medipally, D., Suresh, R., Redmond, K. M., Fairmichael, C., Jain, S., Meade, A. D., & Lyng, F. M. (2026) · Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy · doi:10.1016/j.saa.2026.127529
- Authors
- Steffes, M. W., & Sacks, D. B.
- Affiliations
- University of Minnesota (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Steffes, Michael W
- ORCID
- Sacks, David B
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-09-01
- Volume
- 51
- Issue
- 9
- Pages
- 1569-1570
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- OpenAlex
- W2165284736
- Cited by
- 24
- References
- 10
- Citations by year
- 2026: 1 · 2024: 2 · 2023: 2 · 2021: 1 · 2019: 1 · 2015: 2 · 2014: 1 · 2013: 1 · 2012: 3
- 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)
- Topics
- Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Scientific Measurement and Uncertainty Evaluation
- Keywords
- blood glucose measurement, diabetes mellitus, plasma glucose, whole blood glucose, capillary blood glucose, venous whole blood, SI units, blood glucose monitoring, diabetes diagnosis, measurement bias, point-of-care glucose testing, WHO criteria, American Diabetes Association criteria, glucose tolerance test, insulin dose adjustment
- MeSH terms
- Blood Chemical Analysis, Blood Glucose, Blood Specimen Collection, Diabetes Mellitus, Humans, Hyperglycemia, Plasma, Reference Standards, Reference Values, World Health Organization, Practice Guidelines as Topic, Serum, History, 18th Century, History, 19th Century, History, 20th Century, History, Ancient
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