Sage Journals: Discover world-class research

Abstract

Background:

To summarize new evidence regarding the methodological aspects of blood glucose control in the intensive care unit (ICU).

Methods:

We reviewed the literature on blood glucose control in the ICU up to August 2019 through Ovid Medline and Pubmed.

Results:

Since the publication of the Leuven studies, the benefits of glycemic control have been recognized. However, the methodology of blood glucose control, notably the blood glucose measurement accuracy and the insulin titration protocol, plays an important but underestimated role. This may partially explain the negative results of the large, pragmatic multicenter trials and made everyone realize that tight glycemic control with less-frequent glucose measurements on less accurate blood glucose meters is neither feasible nor advisable in daily practice. Blood gas analyzers remain the gold standard. New generation point-of-care blood glucose meters may be an alternative when using whole blood of critically ill patients in combination with a clinically validated insulin dosing algorithm.

Conclusion:

When implementing blood glucose management in an ICU one needs to take into account the interaction between aimed glycemic target and blood glucose measurement methodology.

Keywords

blood glucose control blood glucose level intensive care unit monitoring tight glycemic control

Blood Glucose Control: The Clinical Trials

It has been known for a long time that blood glucose levels correlate well with the outcome of critically ill patients, following a J-shaped relationship (Figure 1).¹ Both hyperglycemia and hypoglycemia are associated with increased mortality and morbidity.^2-5 Similar relationships between blood glucose levels and the outcome are found in patients suffering from acute myocardial infarction and stroke. However, it is important to realize that this relationship is affected by long-term exposure to blood glucose levels before the acute phase of critical illness. Therefore, the latter relationship is blunted and shifted toward higher glycemic levels in patients with established diabetes, certainly in the ones with poorly controlled diabetes. This also explains the stronger correlation between new-onset hyperglycemia in acute critical illness and poor outcomes in patients, who were not known to have diabetes mellitus.⁶ However, a significant number of these patients may have undiagnosed diabetes mellitus.⁷

Figure 1.

J-shaped curve showing negative effects for both hypoglycemia and hyperglycemia.

Before the landmark studies by Greet Van den Berghe in the early 2000s, blood glucose control (BGC) in the intensive care unit (ICU) was mainly reserved for patients with diabetes. Higher blood glucose levels up to 215 mg/dL were generally not acted upon by physicians.¹ In patients without diabetes, higher blood glucose levels were generally tolerated without intervention, under the premise that hyperglycemia would eventually resolve since the patient did not have diabetes mellitus.

In 2001, their first randomized controlled trial (RCT), tight glycemic control (TGC), in comparison with conventional BGC, reduced mortality and morbidity in critically ill patients, mainly admitted after surgery. This study applied a TGC, targeting blood glucose levels between 80 and 110 mg/dL. In the conventional group, blood glucose levels up to 215 mg/dL were accepted, and insulin administration was ceased when glycemia fell below 180 mg/dL. TGC was achieved by a nurse-driven protocol. A blood gas analyzer was used to make frequent measurements of glucose concentrations in arterial blood. Insulin was only administered intravenously via a central line. Basically, all patients admitted to the ICU were included in the trial, leading to a high level of expertise among the nursing staff.

In 2003, Krinsley et al showed similar benefits in a well-controlled study in medical critically ill patients.⁸ However, the single-center RCT by the Leuven group on TGC in the medical ICU only showed effect in prolonged critically ill patients (ICU stay over 3 days), using the same TGC protocol as in the surgical ICU RCT.³ It appeared that single-center studies using a very standardized protocol in all admitted patients, in combination with a high level of expertise of ICU staff, showed benefit of TGC in comparison with very loose glycemic control.

Several large multicenter trials, such as the normoglycemia in intensive care evaluation and survival using glucose algorithm regulation (NICE-SUGAR) study (n = 6104), Glucontrol study (n = 1101), VISEP (n = 537) and the studies by Arabi (n = 523) and De La Rosa (n = 504), did not succeed in reproducing the same benefits with TGC.^9-13 These studies were not only pragmatic, reflecting the daily setting of critical care, but also allowing more variability in the execution of the study protocol. Another crucial difference with the original Leuven studies on TGC is that the large multicenter trials compared TGC with intermediate BGC (<145 mg/dL), instead of no control (<215 mg/dL) (Table 1).

Table 1.

Key Differences between Leuven Studies and NICE-SUGAR Study.

	Leuven adult studies	NICE-SUGAR (adults)
Setting	Single center	Multicenter (41 centers)
No. of patients	2748	6100
Inclusion (% of admissions)	60% medical, 95% surgical	15%
Outcome
Hypoglycemia episodes	6	13
Morbidity	Reduced organ failure and infections	Neutral
Mortality	Lowered by absolute 3%	Increased by absolute 3%
Methodology
Control group target range	180-215 mg/dL	140-180 mg/dL
Glucose measurement tool	ABL blood gas analyzer (surgical), HemoCue (medical)	Arterial, venous, capillary. Not standardized, all types glucometers allowed
Insulin infusion	Continuously only via central line, infused via syringe pump	Continuous and bolus via all routes, all types of pumps allowed
Nurse instructions	Guideline and intuitive decision making	A strict if-then algorithm
Feeding route first week	Enteral and parenteral	Enteral only
Compliance
Blood glucose target reached	70%	<50%
Overlap in blood glucose between two groups	<10%	>50%

Adapted from Van den Berghe et al.¹

NICE-SUGAR, normoglycemia in intensive care evaluation and survival using glucose algorithm regulation.

This discrepancy between the Leuven single-center studies with high internal validity (strict study protocol) and the large multicenter studies with low internal validity, but higher external validity or generalizability, led to important controversy on the benefit of TGC.^14-16 All meta-analyses and systematic reviews conclude that TGC does not reduce mortality, but increases the incidence of hypoglycemia strongly.^17,18 Insulin-induced hypoglycemia may thus be the culprit in mitigating the benefits of TGC.

The Balancing Act: Controlling Hyperglycemia While Avoiding Hypoglycemia

After the publication of these contradicting clinical trials and the ensuing controversy, a unifying approach emerged, going from intensive insulin therapy over TGC to the current practice of blood glucose management (BGM). There is now a wide consensus on the negative effects of both long episodes of hyperglycemia and even short episodes of severe hypoglycemia.^19,20 In the framework of current BGM, the goal is therefore to avoid exposure to hyperglycemia (>180 mg/dL) and severe hypoglycemia (<40 mg/dL), thus accepting a wider range of blood glucose levels that do not require insulin administration. The importance of adequate glucose control is stressed by several international guidelines, such as the American Diabetes Association (preprandial 90-130 mg/dL, postprandial <180 mg/dL) and the Society for Critical Care Medicine (70-150 mg/dL at any given point).^21,22 More importantly, we believe that the emphasis should shift from a preoccupation with target ranges to the selection of the patient populations which may benefit the most of BGM and even more important to the methodological aspects of BGM.

The basics of any BGC or BGM remain rock steady. To know the blood glucose level and to act upon, it needs to be measured, frequently. The blood glucose measurement has to be accurate as its value is used in a BGC algorithm to initiate or adjust insulin administration. This algorithm may be a skilled bedside nurse or a sophisticated computer program. The resulting insulin administration needs to be reliable by avoiding unnoticed interruptions or boluses. Everyone involved in BGC needs to be aware of the interfering factors in BGC such as steroids and parenteral as well as enteral nutrition.

Measurement of Blood Glucose Levels

Different methods of blood glucose measurement in critically ill patients are used in daily practice, ranging from point-of-care (POC) glucose measurements with capillary or arterial blood, arterial whole blood in blood gas analyzers, to plasma or serum from venous or arterial blood measured in the central lab.^23-25 Blood glucose measurements in plasma in remote central laboratory facilities of the hospital may be impractical, inefficient, and unsafe to implement TGC due to the inevitable time delay between sampling and availability of the blood glucose result to the clinical staff.²⁶ Methodologies for blood glucose measurements at the patient’s bedside or in the ICU itself are therefore preferred from a logistical point-of-view.²⁷ Additionally, the tendency to decrease the number of arterial and central lines, in order to decrease the incidence of bloodstream infections, makes frequent blood sampling in the ICU more difficult. To tackle this issue of blood sampling, the pragmatic studies mainly used capillary glucose measurements in their BGM protocols.^9-11

However, POC blood glucose meters were developed for the management of out-of-hospital patients with diabetes to help them control their own glycemia. Because of the advent of TGC protocols after the publication of the Leuven studies, the POC blood glucose meters became more often used in the setting of critically ill patients.²⁸ Nevertheless, critically ill patients differ tremendously from out-of-hospital patients with diabetes.²⁹ Critically ill patients are exposed to factors that may affect blood glucose measurements: anemia, peripheral edema, vasoconstrictive drugs, and interfering drugs such as icodextrin.^30-35 This had been underestimated and may have had a major influence on the results of the pragmatic trials. Not surprisingly, many studies revealed that the accuracy of these POC devices was not sufficient for the tight ranges aimed for in the TGC protocol.^36-38 A simple study by Duncan Young, presented at the 29th International Symposium on Intensive Care and Emergency Medicine (ISICEM) in 2009, showed a 95% confidence interval (CI) of 37.8 mg/dL, exceeding the 30 mg/dL TGC range of 80-110 mg/dL, when using POC blood glucose meters (Table 2). Blood gas analyzers had the most accurate results with a 95% CI of 14.4 mg/dL, followed by laboratory values with a 95% CI of 21.6 mg/dL. Mixing methods had the worst accuracy with a 95% CI of 50.4 mg/dL, greatly exceeding the TGC range of 30 mg/dL. This study underpins the relationship between aimed target range width and required accuracy. When the 95% CI of a blood glucose meter exceeds the target range width, one needs to question the bluntness of the diagnostic tool.

Table 2.

95% Confidence Intervals (CI) for Different Glucose Measurement Methods.

Method of measurement	95% CI
Blood gas analyzers	0.8 mmol/L (14.4 mg/dL)
Laboratory	1.2 mmol/L (21.6 mg/dL)
HemoCue	1.1 mmol/L (19.8 mg/dL)
Strip point-of-care	2.1 mmol/L (37.8 mg/dL)
Mixed methods	2.8 mmol/L (50.4 mg/dL)
Tight glycemic control target range	1.7 mmol/L (30 mg/dL)

Adapted from Duncan Young et al³⁹ (ISICEM, 2009).

One has to take into account not only the target range width but also the absolute blood glucose value. Are we measuring in the hypoglycemic, normoglycemic, or hyperglycemic range? ISO15197:2003 standards for blood glucose meters prescribe a maximal deviation of 20% in 95% of measurements when blood glucose levels are above 75 mg/dL and a deviation of 15 mg/dL when below 75 mg/dL. Confirmation of compliance with these standards is executed by the manufacturers and does not necessarily apply in a hospital setting, let alone the critically ill patient population. Logically, most feared is the overestimation of blood glucose levels in the lower glycemic range, leading to unjustified increased dosing of insulin, and eventually to increasing numbers of true hypoglycemic episodes.

Vlasselaers et al investigated the accuracy of two older generation POC devices, HemoCue (HemoCue AB, Angelhölm, Sweden) and AccuCheck (Roche Diabetes Care Inc, United States) vs an arterial blood gas analyzer (ABL, Radiometer Medical, Brønshøj, Denmark) using arterial whole blood samples for all devices.²⁶ Initial analysis showed a very good correlation between the POC blood glucose meter and blood gas analyzer (r² = 0.97 for AccuCheck and 0.94 for HemoCue). But dividing the measurements into different glycemic ranges resulted in a dramatic drop of the correlation coefficient in the TGC (r² = 0.66 for AccuCheck and 0.56 for HemoCue) and hypoglycemic ranges (r² = 0.73 for AccuCheck and 0.78 for HemoCue). However, the lower correlation coefficients are at least partially explained by the narrower ranges of values, leading to decreased statistical power.

Another study with older generation POC blood glucose meters showed that less than 60% of the results by capillary (fingerstick) measurement fell within a 20% error range from the central laboratory reference method.⁴⁰ In the hypoglycemic range, the agreement was even as low as 26%. The use of arterial blood in the glucose meter resulted in better agreement with central laboratory measurement, especially in the hypoglycemic range (70% and 55%, respectively). Arterial blood gas analysis yielded the best agreement with 75% and 65% for the total and hypoglycemic ranges. Interestingly, they found a consistent overestimation with capillary measurements for all glycemic ranges. This implies that the use of POC devices with capillary blood can potentially lead to an increased number of hypoglycemic events, certainly when aiming for strict normoglycemia. Some POC devices tend to systematically overestimate blood gas values, while others underestimate levels in the low glycemic range and overestimate levels in the high glycemic range, which is a slightly better safety profile in the context of TGC.₄₁

As a first step to address these problems, corrective measures were introduced to compensate for the anemia. An increase in hematocrit is known to give lower glucose readings and vice versa.^30,31,42 This potentially masks hypoglycemia in anemic patients by measuring falsely elevated glucose levels. In 2009, Meynaar et al investigated the use of a correction factor (×1.086) after measuring glucose levels in arterial blood with POC blood glucose meter.⁴³ They compared against the standard central laboratory reference measurement, classically tested on serum. Using the ISO 15 197 limits, they found that in 9% of cases, glucose levels exceeded the acceptable range as compared with the central laboratory. By applying the correction factor, the difference improved to 6%. Capillary measurement, as classically used in POC devices, was not tested in this study.

chemistry techniques such as blood gas analyzers or central laboratory methods are considered less susceptible than biosensor technology in POC tests.⁴⁰ Interference with these tests can be caused by patient, pharmacological, and physiological factors. Glucose levels in the interstitial fluid can be affected by tissue perfusion, temperature, and local humoral factors.⁴⁴ POC device measurements are based on enzymatic reactions and therefore sensitive to pH fluctuations, as occurs frequently in ICU patients.⁴⁵ ICU patients are also often administered many different drugs, of which some may influence glucose level measurements. Tang et al investigated 30 different drugs and their effect on glucose readings from six different POC devices.^30,46 Interferences were found for ascorbic acid, acetaminophen, dopamine, and mannitol.

This body of research sparked the efforts by POC blood glucose meter manufacturers to improve their devices. Recent real-world studies, comparing newer generation POC glucose meters with central laboratory tests, showed that their accuracy is comparable in ICU and non-ICU settings, falling within the limits of CLSI quality standards. These newer generation POC glucose meters may be fit for BGC in critically ill patients.^47-49 A single-center trial in critically ill patients tested the accuracy of three “new” POC blood glucose meters in the setting of TGC. The FDA:2014 accuracy criteria were used with a maximum total allowable error of 10% and a maximal coefficient of variation (CV) of 3.9%. Arterial whole blood was used for blood glucose measurements in the POC devices and the blood gas analyzer was the reference methodology. All “new” meters met the FDA criterion of maximal 10% total allowable error: blood gas analyzer 0.0%, Freestyle Precision (Abbott Diabetes Care) 9.4%, Pro StatStrip Connectivity (Nova Biomedical) 3.7%, AccuCheck Inform II (Roche Diagnostics) 2.2%. The 95% CI was approximately 20 mg/dL for all POC blood glucose meters, compared with 7 mg/dL for the blood gas analyzer. Since the study by Vlasselaers et al in 2008, which was done in a similar patient population and the same context of TGC, the 95% CI of the POC blood glucose meters was basically halved. With a 95% CI of 20 mg/dL, the POC blood glucose meters may now be better suited for (tight) blood glucose management with a target range width of 30 mg/dL (80-110 mg/dL target range). Icodextrin did not interfere in any of the tested blood glucose meters and neither hematocrit nor oxygen tension could explain glucose level differences.

Blood Glucose Management Protocol

Apart from correct and accurate glucose measurement, a second important aspect for adequate BGM is the implementation of a clinically validated protocol.⁵⁰ In general, the choice of protocol appears to have a greater influence on glucose control measures than the glucose measurement method. Sensor inaccuracy can have an exponential impact on insulin dosing errors depending on the algorithm that is used. Protocols that implement more frequent measurements— or even near-continuous measurements—are bound to reduce the margin of error.⁵¹ Several BGM “systems” exist, from nurse-driven insulin administration based on intermittent measurements to fully autonomous computer-controlled looped systems, fed by near-continuous measurements.^52-56 In the original Leuven studies, an intuitive paper-based algorithm was used by the ICU nurses. This was later converted into a computer-based algorithm to calculate the most optimal insulin or glucose dose to achieve normoglycemia.^52,57,58 In order to clinically validate the newer computerized protocols, research groups take more and more advantage of simulation models and computer learning.^59,60 Simulation models have also been used to assess the required accuracy level of blood glucose meters. Van Herpe et al found that the mean absolute relative difference (MARD), a newer indicator of blood glucose meter accuracy, should be less than 7.1% for intermittent glucose measurement in order to avoid acute life-threatening situations and to minimize potentially life-threatening situations to <0.01%.⁵¹

Because of the heterogeneity in study protocols over the years, it is difficult to ascertain the best-standardized protocol for the ICU. ⁶¹ Simulation models can certainly aid in guiding future RCTs, but further research is required to clinically validate new protocols.

The Current Consensus

At this point, there is an international expert consensus among ICU staff to treat blood glucose values above 180 mg/dL in all ICU patients. The general aim is to keep blood glucose levels between 140 and 180 mg/dL, in order to have the necessary margin to avoid hypoglycemia. This can be achieved by frequent measurements, with a preference for arterial blood samples over capillary blood. Incorrect measurement is an important cause of hypoglycemia in critically ill patients. Using capillary blood in critically ill patients is less reliable because of peripheral edema. It often leads to an overestimation of blood glucose levels and should be avoided. The accuracy of blood glucose measurement devices should be checked periodically and preferentially, arterial blood gas analyzers are used. Arterial or venous blood samples are preferred. When hyperglycemia or hypoglycemia is detected, the use of a validated insulin dosing protocol leads to better BGC (Table 3).

Table 3.

Key Messages for the Current Consensus in Blood Glucose Management.

Key messages
Blood glucose management starts with an accurate blood glucose measurement.
There is no clinical consensus on accuracy levels.
Use only one method of measurement.
The method depends on chosen target range and accuracy.
Currently, levels <180 mg/dL or <150 mg/dL are targeted.
Accuracy in hypoglycemic ranges <80 mg/dL is essential.
Laboratorians need to work together with their intensive care unit physicians.
The blood gas analyzers remain gold standard.
New generation point-of-care (POC) blood glucose meters are not anymore affected by hematocrit, partial pressure of oxygen, and icodextrin.
However, new generation POC blood glucose meters may be an alternative for assay of glucose in whole blood of critically ill patients when using a clinically validated insulin dosing algorithm.
Accuracy of new generation POC blood glucose meters for capillary samples of critically ill patients may be sufficient in a context outside tight blood glucose control in less critically ill patients, when using a clinically validated insulin dosing algorithm.

Conclusion

Ever since the publication of the landmark study by Van den Berghe et al,¹ the benefits of good glycemic control have been internationally recognized. Methods of glucose measurement as well as therapeutic protocols have been well investigated during this time. Studies have shown a discrepancy between risk/benefit in tightly standardized single-center trials and the more heterogeneously designed multicenter trials.

In order to optimize BGC, there is a continued need for accurate blood glucose measurement devices. On the other hand, the implementation of a protocol-based approach to hyperglycemia or hypoglycemia in any ICU patient remains an important standard of practice. The optimal target range is yet to be determined and depends greatly on the accuracy of newer glucose measurement devices and the adherence to protocol setup.

Future research is aimed at fully closed-loop systems, with continuous blood glucose measurement and computer-controlled intervention, also known as the “artificial pancreas”.^62-68 A performant system could greatly reduce the significantly increased workload in the ICU. Of course, clinical validation of these systems would still be required to investigate the effect on clinical outcomes.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Gert-Jan Eerdekens

References

Van den Berghe

Wouters

Weekers

, et al. Intensive insulin therapy in critically ill patients. N Engl J Med. 2001;345(19):1359-1367.

Vanhorebeek

Langouche

Van den Berghe

Tight blood glucose control with insulin in the ICU: facts and controversies. Chest. 2007;132(1):268-278.

Van den Berghe

Wilmer

Hermans

, et al. Intensive insulin therapy in the medical ICU. N Engl J Med. 2006;354(5):449-461.

Gale

Sicoutris

Reilly

Schwab

Gracias

VH.

Poor glycemic control is associated with increased mortality in critically ill trauma patients. Am Surg. 2007;73(5):454-460.

Honiden

Inzucchi

SE.

Metabolic management during critical illness: glycemic control in the ICU. Semin Respir Crit Care Med. 2015;36(6):859-869.

Krinsley

Preiser

JC.

Is it time to abandon glucose control in critically ill adult patients?

Curr Opin Crit Care. 2019;25(4):299-306.

Carpenter

Gregg

Buchman

Coopersmith

CM.

Prevalence and impact of unknown diabetes in the ICU. Crit Care Med. 2015;43(12):e541-e550.

Krinsley

JS.

Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients. Mayo Clin Proc. 2003;78(12):1471-1478.

NICE-SUGAR Study Investigators, Finfer

Chittock

, et al. Intensive versus conventional glucose control in critically ill patients. N Engl J Med. 2009;360(13):1238-1297.

10.

Preiser

J-C

Devos

Ruiz-Santana

, et al. A prospective randomised multi-centre controlled trial on tight glucose control by intensive insulin therapy in adult intensive care units: the glucontrol study. Intensive Care Med. 2009;35(10):1738-1748.

11.

Brunkhorst

Engel

Bloos

, et al. Intensive insulin therapy and pentastarch resuscitation in severe sepsis. N Engl J Med. 2008;358(2):125-139.

12.

Arabi

Dabbagh

Tamim

, et al. Intensive versus conventional insulin therapy: a randomized controlled trial in medical and surgical critically ill patients. Crit Care Med. 2008;36(12):3190-3197.

13.

Del Carmen De La Rosa

Donado

Restrepo

, et al. Strict glycaemic control in patients hospitalised in a mixed medical and surgical intensive care unit: a randomised clinical trial. Crit Care. 2008;12(5):R120.

14.

Mesotten

Van den Berghe

Glycemic targets and approaches to management of the patient with critical illness. Curr Diab Rep. 2012;12(1):101-107.

15.

Mesotten

Preiser

Kosiborod

Glucose management in critically ill adults and children. Lancet Diabetes Endocrinol. 2015;3(9):723-733.

16.

Wiener

Larson

RJ.

Benefits and risks of tight glucose control in critically ill adults. JAMA. 2008;300(8):933-944.

17.

Karon

Meeusen

Bryant

SC.

Impact of glucose meter error on glycemic variability and time in target range during glycemic control after cardiovascular surgery. J Diabetes Sci Technol. 2015;10(2):336-342.

18.

Arnold

Paxton

McNorton

Szpunar

Edwin

SB.

The effect of a hypoglycemia treatment protocol on glycemic variability in critically ill patients. J Intensive Care Med. 2015;30(3):156-160.

19.

NICE-SUGAR Study Investigators, Finfer

Liu

, et al. Hypoglycemia and risk of death in critically ill patients. N Engl J Med. 2012;367(12):1108-1118.

20.

Hermanides

Bosman

Vriesendorp

, et al. Hypoglycemia is associated with intensive care unit mortality. Crit Care Med. 2010;38(6):1430-1434.

21.

American Diabetes Association. Standards of medical care in diabetes 2018. J Clin and Applied Res Educ. 2018;41(Suppl 1): S55-S64.

22.

Jacobi

Bircher

Krinsley

, et al. Guidelines for the use of an insulin infusion for the management of hyperglycemia in critically ill patients. Crit Care Med. 2012;40(12):3251-3276.

23.

Lonjaret

Claverie

Berard

, et al. Relative accuracy of arterial and capillary glucose meter measurements in critically ill patients. Diabetes Metab. 2012;38(3):230-235.

24.

Petersen

Graves

Tacker

Okorodudu

Mohammad

Cardenas

Jr.

Comparison of POCT and central laboratory blood glucose results using arterial, capillary, and venous samples from MICU patients on a tight glycemic protocol. Clin Chim Acta. 2008;396(1-2):10-13.

25.

Maruo

Oota

Tsurugi

, et al. Noninvasive near-infrared blood glucose monitoring using a calibration model built by a numerical simulation method: trial application to patients in an intensive care unit. Appl Spectrosc. 2006;60(12):1423-1431.

26.

Vlasselaers

Herpe

Milants

, et al. Blood glucose measurements in arterial blood of intensive care unit patients submitted to tight glycemic control: agreement between bedside tests. J Diabetes Sci Technol. 2008;2(6):932-938.

27.

Finfer

Wernerman

Preiser

, et al. Clinical review: consensus recommendations on measurement of blood glucose and reporting glycemic control in critically ill adults. Crit Care. 2013;17(3):229.

28.

Claerhout

De Prins

Mesotten

, et al. Performance of strip-based glucose meters and cassette-based blood gas analyzer for monitoring glucose levels in a surgical intensive care setting. Clin Chem Lab Med. 2016;54(1):169-180.

29.

Juneja

Pandey

Singh

Comparison between arterial and capillary blood glucose monitoring in patients with shock. Eur J Intern Med. 2011;22(3):241-244.

30.

Louie

Tang

Sutton

Lee

Kost

GJ.

Point-of-care glucose testing: effects of critical care variables, influence of reference instruments, and a modular glucose meter design. Arch Pathol Lab Med. 2000;124(2):257-266.

31.

Smith

Kilpatrick

ES.

Intra-operative blood glucose measurements: the effect of haematocrit on glucose test strips. Anaesthesia. 1994;49(2):129-132.

32.

Dungan

Chapman

Braithwaite

Buse

Glucose measurement: confounding issues in setting targets for inpatient management. Diabetes Care. 2007;30(2):403-439.

33.

Fekih Hassen

Ayed

Gharbi

Ben Sik Ali

Marghli

Elatrous

. Bedside capillary blood glucose measurements in critically ill patients: influence of catecholamine therapy. Diabetes Res Clin Pract. 2010;87(1):87-91.

34.

Pidcoke

Wade

Mann

, et al. Anemia causes hypoglycemia in intensive care unit patients due to error in single-channel glucometers: methods of reducing patient risk. Crit Care Med. 2010;38(2):471-476.

35.

Mann

Mora

Pidcoke

Wolf

Wade

CE.

Glycemic control in the burn intensive care unit: focus on the role of anemia in glucose measurement. J Diabetes Sci Technol. 2009;3(6):1319-1329.

36.

Inoue

Egi

Kotani

Morita

Accuracy of blood-glucose measurements using glucose meters and arterial blood gas analyzers in critically ill adult patients: systematic review. Crit Care. 2013;17(2):R48.

37.

Scott

Bruns

Boyd

Sacks

DB.

Tight glucose control in the intensive care unit: are glucose meters up to the task?

Clin Chem. 2009;55(1):18-20.

38.

Wilinska

Hovorka

Glucose control in the intensive care unit by use of continuous glucose monitoring: what level of measurement error is acceptable?

Clin Chem. 2014;60(12):1500-1509.

39.

Young

, et al. Tight Glucose Control: Yes or No? In: 29th International Symposium on Intensive Care and Emergency Medicine (ISICEM), Brussels, Belgium, 24-27 March 2009.

40.

Kanji

Buffie

Hutton

, et al. Reliability of point-of-care testing for glucose measurement in critically ill adults. Crit Care Med. 2005;33(12):2778-2785.

41.

Hoedemaekers

Klein Gunnewiek

Prinsen

Willems

Van der Hoeven

JG.

Accuracy of bedside glucose measurement from three glucometers in critically ill patients. Crit Care Med. 2008;36(11):3062-3066.

42.

Brunkhorst

Wahl

HG.

Blood glucose measurements in the critically ill: more than just a blood draw. Crit Care. 2006;10(6):178.

43.

Meynaar

van Spreuwel

Tangkau

, et al. Accuracy of AccuChek glucose measurement in intensive care patients. Crit Care Med. 2009;37(10):2691-2696.

44.

Holzinger

Warszawska

Kitzberger

Herkner

Metnitz

Madl

Impact of shock requiring norepinephrine on the accuracy and reliability of subcutaneous continuous glucose monitoring. Intensive Care Med. 2009;35(8):1383-1389.

45.

Heinemann

, Glucose Monitoring Study Group. Continuous glucose monitoring by means of the microdialysis technique: underlying fundamental aspects. Diabetes Technol Ther. 2003;5(4):545-561.

46.

Tang

Louie

Kost

GJ.

Effects of drugs on glucose measurements with handheld glucose meters and a portable glucose analyzer. Am J Clin Pathol. 2000;113(1):75-86.

47.

Schroeder

Giacherio

Gianchandani

Engoren

Shah

NH.

Postmarket surveillance of point-of-care glucose meters through analysis of electronic medical records. Clin Chem. 2016;62(5):716-724.

48.

Zhang

Isakow

Kollef

Scott

MG.

Performance of a modern glucose meter in ICU and general hospital inpatients: 3 years of real-world paired meter and central laboratory results. Crit Care Med. 2017;45(9):1509-1514.

49.

Dubois

Slingerland

Fokkert

, et al. Bedside glucose monitoring-is it safe? A new, regulatory-compliant risk assessment evaluation protocol in critically ill patient care settings. Crit Care Med. 2017;45(4):567-574.

50.

Kavanagh

McCowen

KC.

Glycemic control in the ICU. N Engl J Med. 2010;363(26):2540-2546.

51.

Van Herpe

De Moor

Van den Berghe

Mesotten

. Modeling of effect of glucose sensor errors on insulin dosage and glucose bolus computed by LOGIC-Insulin. Clin Chem. 2014;60(12):1510-1518.

52.

Dubois

Van Herpe

van Hooijdonk

, et al. Software-guided versus nurse-directed blood glucose control in critically ill patients: the LOGIC-2 multicenter randomized controlled clinical trial. Crit Care. 2017;21(1):212.

53.

Orford

Stow

Green

Corke

Safety and feasibility of an insulin adjustment protocol to maintain blood glucose concentrations within a narrow range in critically ill patients in an Australian level III adult intensive care unit. Crit Care Resusc. 2004;6(2):92-98.

54.

Adams

Hunter

Langley

Is nurse-managed blood glucose control in critical care as safe and effective as the traditional sliding scale method?

Intensive Crit Care Nurs. 2009;25(6):294-305.

55.

Eslami

Abu-Hanna

de Jonge

de Keizer

NF.

Tight glycemic control and computerized decision-support systems: a systematic review. Intensive Care Med. 2009;35(9):1505-1517.

56.

Righy Shinotsuka

Brasseur

Fagnoul

Vincent

Preiser

JC.

Manual versus Automated moNitoring Accuracy of GlucosE II (MANAGE II). Crit Care. 2016;20(1):380.

57.

Ward

Steel

Le Compte

, et al. Interface design and human factors considerations for model-based tight glycemic control in critical care. J Diabetes Sci Technol. 2014;6(1):125-134.

58.

Van den Berghe

. Intensive insulin therapy in the ICU—reconciling the evidence. Nat Rev Endocrinol. 2012;8(6):374-378.

59.

Lin

Razak

Pretty

, et al. A physiological Intensive Control Insulin-Nutrition-Glucose (ICING) model validated in critically ill patients. Comput Methods Programs Biomed. 2011;102(2):192-205.

60.

Chase

Desaive

Bohe

, et al. Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas. Crit Care. 2018;22(1):182.

61.

Van den Berghe

. How to compare adequacy of algorithms to control blood glucose in the intensive care unit? Crit Care. 2004;8(3):151-152.

62.

Chee

Fernando

Van Heerden

PV.

Closed-loop glucose control in critically ill patients using continuous glucose monitoring system (CGMS) in real time. IEEE Trans Inf Technol Biomed. 2003;7(1):43-53.

63.

van Steen

SCJ

Rijkenberg

Limpens

van der Voort

PHJ

Hermanides

DeVries

. The clinical benefits and accuracy of continuous glucose monitoring systems in critically ill patients-a systematic scoping review. Sensors (Basel). 2017;17(1):146.

64.

Wernerman

Desaive

Finfer

, et al. Continuous glucose control in the ICU: report of a 2013 round table meeting. Crit Care. 2014;18(3):226.

65.

Preiser

Lheureux

Thooft

Brimioulle

Goldstein

Vincent

JL.

Near-continuous glucose monitoring makes glycemic control safer in ICU patients. Crit Care Med. 2018;46(8):1224-1229.

66.

Yatabe

Yamazaki

Kitagawa

, et al. The evaluation of the ability of closed-loop glycemic control device to maintain the blood glucose concentration in intensive care unit patients. Crit Care Med. 2011;39(3):575-578.

67.

Okabayashi

Shima

Are closed-loop systems for intensive insulin therapy ready for prime time in the ICU?

Curr Opin Clin Nutr Metab Care. 2014;17(2):190-199.

68.

De Block

Gios

Verheyen

, et al. Randomized evaluation of glycemic control in the medical intensive care unit using real-time continuous glucose monitoring (REGIMEN Trial). Diabetes Technol Ther. 2015;17(12):889-898.

Accuracy of Blood Glucose Measurement and Blood Glucose Targets

Abstract

Background:

Methods:

Results:

Conclusion:

Keywords

Blood Glucose Control: The Clinical Trials

The Balancing Act: Controlling Hyperglycemia While Avoiding Hypoglycemia

Measurement of Blood Glucose Levels

Blood Glucose Management Protocol

The Current Consensus

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

References