Tight glucose control in the intensive care unit: Are glucose meters up to the task?
Abstract
Many institutions use tight glycemic control (TGC)1 protocols in their intensive care units (ICUs). TGC protocols became standard of care after the initial, very promising, studies demonstrating that it improved patient outcomes (1). For instance, Van den Berghe et al. (1) demonstrated that TGC reduced mortality by one-third in surgical intensive care patients. Other early studies of TGC also demonstrated marked and significant benefits in infection rates and mortality. Typical TGC protocols consist of placing postoperative and critically ill patients on a continuous intravenous insulin infusion, checking their blood glucose concentrations on an hourly basis (or other schedule), and giving a bolus of insulin and/or changing the infusion rate of insulin based on the glucose concentration, with a goal of maintaining glucose between 4.4 and 6.7 mmol/L (80 and 120 mg/dL). Of the numerous variations in protocols regarding timing and frequency of glucose measurements, insulin infusion rates, and target glucose values, all have a goal of maintaining tight glycemic control in critically ill patients. A new metaanalysis has suggested that TGC protocols offer limited if any benefits in critically ill adults and revealed that these protocols resulted in a 3- to 5-fold increased risk of hypoglycemia (2). The metaanalysis examined 29 randomized controlled trials that met predefined inclusion criteria. Of the 27 trials that examined mortality as an endpoint, 16 favored TGC and 11 favored usual care, but the reductions in relative risk were statistically significant (95% confidence) in only 2 of the 16 favoring TGC and in none of the 11 favoring usual care. The only outcome for which TGC demonstrated a significantly reduced risk was the development of septicemia; this was seen in surgical intensive care patients but not in medical ICU patients. The metaanalysis concluded that TGC may not be as beneficial as predicted from some of the original studies and may cause harm. We would like to raise the question of whether error introduced by measuring glucose with point-of-care (POC) glucose meters in some, but not all, of the studies may have contributed to the findings of this metaanalysis. The use of glucose meters in hospitals became common in the late 1980s, and their use became standard of care in virtually all inpatient settings by the mid-1990s without evidence that it improved patient outcomes or decreased costs. It just happened. Nevertheless, the encouraging results of TGC studies in the early part of this decade appeared to provide the first evidence-based support for POC glucose testing in hospitalized patients. Whereas POC testing is clearly needed if TGC protocols are to be implemented (central laboratory testing would be too slow), the choice of device to use for POC glucose testing in TGC protocols may not be as clear, nor is the sample type for testing. The original TGC study by Van den Berghe et al. (1) used a precise arterial blood gas instrument for glucose measurement and obtained arterial blood samples for testing. In other studies, some showing benefit for TGC and others not, blood glucose meters and capillary blood samples have been used to measure glucose. Similarly, glucose meters and capillary blood samples are widely used in hospitals for TGC. We believe that one possibility for the mixed results of the TGC studies examined by Wiener et al. (2) may be the methods and samples used to measure glucose. Glucose meters are less precise than central laboratory or blood gas analyzer methods and can display large mean differences from laboratory methods. The most recent College of American Pathologists proficiency testing data (Surveys C-B 2008 and WBG-B 2008) shows CVs for all 29 central laboratory methods (5664 laboratories) to be 2.5% to 4.3%, and the bias between any 2 methods to be no more than 11%. In contrast, CVs between 17 glucose meter methods (19 597 sites) were 12% to 14%, and bias between any 2 methods was as much as 41%. It should be noted that some of the bias between methods could be due to matrix effects. Nevertheless, one study from the CDC of 5 common glucose meters showed mean differences from a central laboratory method to be as high as 32% and CVs in the hands of a single trained medical technologist to range from 6% to 11% (3). At our institutions, total imprecision for glucose meters shows a CV of approximately 5% to 6%, whereas it is approximately 1% for our central laboratory methods. One of us (M.G. Scott) also identifies in the laboratory information systems glucose meter values that are repeated within 15 min of each other for billing and compliance purposes. Interestingly, about 1.3% of meter values are repeated within 15 min. One week of data from August 2007 showed 84 repeat measurements with a mean difference between repeat values of 106 mg/dL (range of differences 5–361 mg/dL). Clearly, repeat testing often is performed because users believe the results to be incorrect. How
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The van den Berghe study used a precise and accurate glucose analyzer and arterial blood samples, whereas subsequent studies often used glucose meters and capillary finger-stick samples.
“A Clinical Chemistry Perspective article (137) pointed out that the study of van den Berghe et al. used a precise and accurate glucose analyzer and collected arterial blood samples, whereas subsequent studies often used glucose meters and capillary blood samples obtained by finger stick.”
From Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus (2011) · cites this paper as [137]
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References 6 · Cited by 162
Research works printed but not linked: 1
- Wiener RS, Wiener DC, Larson RJ. Benefits and risks of tight glucose control in critically ill adults. JAMA 2008;300:933-44.
- Authors
- Scott, M. G., Bruns, D. E., Boyd, J. C., & Sacks, D. B.
- Affiliations
- Washington University in St. Louis (US)
- University of Virginia Health System (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Scott, Mitchell G
- ORCID
- Sacks, David B
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-01-01
- Volume
- 55
- Issue
- 1
- Pages
- 18-20
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- OpenAlex
- W2136494315
- Cited by
- 162
- References
- 6
- Citations by year
- 2026: 4 · 2025: 2 · 2023: 3 · 2022: 5 · 2021: 2 · 2020: 3 · 2019: 4 · 2018: 5 · 2017: 6 · 2016: 5 · 2015: 9 · 2014: 23 · 2013: 14 · 2012: 28
- FWCI
- 11.57
- 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
- Abbott Diagnostics
- Topics
- 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
- Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
- Keywords
- tight glycemic control, point-of-care glucose meters, critically ill patients, hypoglycemia, continuous insulin infusion, intensive care unit, mortality, septicemia, insulin dose, critically ill children, critically ill adults, surgical intensive care patients
- MeSH terms
- Blood Chemical Analysis, Blood Glucose, Clinical Protocols, Humans, Intensive Care Units, Glycemic Index
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