Glycemic control in the critically ill: Less is more
====================================================

* Ghaith Alhatemi
* Haider Aldiwani
* Rafal Alhatemi
* Marwah Hussein
* Suzan Mahdai
* Berhane Seyoum

## ABSTRACT

Hyperglycemia is associated with poor clinical outcomes in critically ill patients. Initial clinical trials of intensive insulin therapy targeting blood glucose levels of 80 to 110 mg/dL showed improved outcomes, but subsequent trials found no benefits and even increased harm with this approach. Emerging literature has evaluated other glycemic indices including time-in-target blood glucose range, glycemic variability, and stress hyperglycemia ratio. These indices, while well described in observational studies, have not been addressed in the initial trials. Additionally, the patient’s pre existing diabetes status and preadmission diabetic control may modulate the outcomes of stringent glycemic control, with worse outcomes of hyperglycemia being observed in patients without diabetes and in those with well-controlled diabetes. Most medical societies recommend less stringent glucose control in the range of 140 to 180 mg/dL for critically ill patients.

KEY POINTS 
*   Hyperglycemia is associated with increased morbidity and mortality in critically ill patients and should be treated.

*   Enhancing the amount of time glucose levels are in the target range and minimizing glycemic variability have been associated with improved outcomes in critically ill patients.

*   Hypoglycemia has been independently associated with an increased risk of death in critically ill patients.

*   Although the optimal blood glucose target for patients in the intensive care unit is not known, a target of 140 to 180 mg/dL is the most acceptable.

Hyperglycemia has been associated with adverse clinical outcomes in critically ill patients, regardless of diabetes status.1–7 Proposed causes of stress hyperglycemia include excessive counterregulatory hormones (corticosteroid, glucagon, growth hormone, catecholamines) and release of cytokines tumor necrosis factor (TNF)-alpha and interleukin (IL)-1. These factors can promote a transient state of insulin resistance that can lead to decreased insulin action on suppressing gluconeogenesis and also to decreased uptake of insulin-mediated skeletal muscle glucose.8 Factors contributing to hyperglycemia in hospitalized patients include medications (steroids, catecholamines), parenteral nutrition, and intravenous medications diluted in dextrose.9

*See related editorial [page 189](http://www.ccjm.org/lookup/doi/10.3949/ccjm.89a.21127)*

Further, hyperglycemia itself induces production of inflammatory cytokines (IL-6, IL-8, and TNF-alpha) and reactive oxygen species.10 It also impairs the neutrophil functions of chemotaxis and bactericidal activity.11 Additionally, hyperglycemia and hyperinsulinemia have been shown to increase tissue procoagulant activity that may add to the procoagulant state.12 These mechanisms may explain the poor outcomes observed with hyperglycemia.

Initial single-center randomized clinical trials (RCTs) of intensive insulin therapy targeting blood glucose levels in the fasting range (80–110 mg/dL) (referred to as the Leuven trials) found significant mortality and morbidity benefit,13,14 and this strategy gained popularity. However, subsequent multicenter RCTs15–17 failed to replicate these findings, and the largest RCT, the Normoglycemia in Intensive Care Evaluation–Survival Using Glucose Algorithm Regulation (NICE-SUGAR) trial,17 reported evidence of harm with this intervention.

Other glycemic indices have shown independent impacts on outcomes in the intensive care unit (ICU). In fact, the time-in-range (TIR, the amount of time the glucose level is in the target range), glycemic variability, and the modulation effect of preexisting diabetes status, although thoroughly evaluated by observational studies, were not examined in the early RCTs. This may explain potential differences in outcomes between these trials.

This review will discuss findings from the major RCTs, metrics of glycemic control, and recommendations of professional medical societies for target blood glucose ranges in critically ill patients.

## METRICS OF GLYCEMIC CONTROL

### Hyperglycemia

In observational study results published from 2003 to 2009, hyperglycemia was generally associated with adverse clinical outcomes in critically ill patients in various settings (medical, surgical, trauma, and neurologic).1–7 For example, in one retrospective analysis,4 hyperglycemia had a graded effect on hospital mortality. In other trials,1,5–7 trauma patients with hyperglycemia had increased mortality rates, hospital length of stay, ICU length of stay, and incidences of nosocomial infection. Moreover, hyperglycemia was associated with worse neurologic outcomes and elevated intra cranial pressure in patients with severe traumatic brain injury, and early hyperglycemia was an independent predictor of worse scores on the Glasgow Coma Scale.3

The relationship between hyperglycemia and mortality in ICU patients is modulated by their diabetes status. Observational studies2,18–20 have shown that the greatest reduction in mortality associated with intensive insulin therapy (target goal 80–110 mg/dL) was seen in patients without diabetes. In Egi et al,18 multivariate logistic regression analysis showed greater reduction in odds of mortality (odds ratio 0.45) when 80–110 mg/dL was used in patients without diabetes compared with other blood glucose targets. In contrast, for patients with diabetes, the mortality benefit had a poor correlation. The cohorts of critically ill patients with diabetes were not identical. Thus, preadmission diabetic control as evidenced by hemoglobin A1c (HbA1c) levels might have a differential impact on the hyperglycemia-mortality relationship. For instance, in a retrospective observational study of patients with HbA1c levels obtained at admission,21 for patients with a low HbA1c level (< 7%), increases in mean blood glucose values were associated with increased mortality risk; the risk was decreased when the HbA1c was above 7%.21 This may signify that patients with poorly controlled diabetes may benefit from a less stringent glucose target.

In addition to mortality outcomes, early hyperglycemia (defined as elevated blood glucose on hospital day 1 or 2),5 hyperglycemia at admission,6,7 and worsening or highly variable hyperglycemia1 were associated with higher rates of infectious complications in critically ill patients. After correction for severity of illness and other variables including age, elevated glucose was an independent predictor of increased infectious morbidity in these studies.1,5–7

To study the complex interplay between acute and chronic hyperglycemia on mortality in hospitalized patients, Roberts et al22 developed the stress hyperglycemia ratio, calculated as the blood glucose level at admission divided by the estimated average glucose, which was inferred from the HbA1c as follows: the estimated average glucose equals HbA1c × 1.59, minus 2.59.23 In Roberts et al,22 the stress hyperglycemia ratio but not admission hyperglycemia was associated with adverse outcomes. These findings were corroborated by other cohort studies,24,25 demonstrating that the stress hyperglycemia ratio was independently associated with increased risk of death and additional complications.

### Time in the target glucose range

The TIR had been proposed as a “unifying” metric of glycemic control because it is affected by hyperglycemia, hypoglycemia, and glycemic variability. The Glucontrol study16 was the only RCT that explicitly reported TIR. A subsequent post hoc analysis of data from this study showed that a TIR greater than 50% for a glucose target of 140 to 180 mg/dL was independently associated with increased rate of survival.26 A series of single-center studies using the SPRINT (Specialized Relative Insulin Nutrition Tables) protocol, a tight glycemic control intervention, examined the effect of TIR (termed “cumulative time in band”) on organ failure and mortality in critically ill patients receiving intensive insulin therapy.27–29 Reduced organ failure, as evidenced by a reduction in the SOFA (Sequential Organ Failure Assessment) score, was associated with a TIR greater than 50%,27 while a TIR greater than 70% was independently associated with improved survival.29

A subsequent prospective study of patients after cardiac surgery showed improved outcomes in decreased duration of both mechanical ventilation and ICU length of stay in those with a TIR greater than 80%, regardless of diabetes status. The incidence of sternal wound infections was significantly higher in patients with a TIR below 80% vs patients with a TIR above 80%.30

The effect of diabetes status on TIR outcomes has been studied by Krinsley and Preiser.31 In their retrospective analysis of the prospectively collected data, and independent of severity of illness and ICU length of stay, a TIR greater than 80% for a blood glucose of 70 to 140 mg/dL was strongly associated with increased survival in critically ill patients without diabetes but not in patients with diabetes. One could argue that the design of the study did not include data on baseline glycemic control before ICU admission, and so it questions whether poorly controlled diabetes has any impact on the benefits of a high TIR.

A more recent landmark retrospective multicenter study by Lanspa et al32 published in 2019 sought to examine this effect and found that a TIR greater than 80% for a blood glucose target of 70 to 139 mg/dL was independently associated with reduced mortality in patients with or without diabetes. However, when diabetes status was stratified into well-controlled and poorly controlled disease (based on HbA1c), the TIR effect was not significant in patients with poorly controlled diabetes.32 This finding suggests that antecedent poor glucose control may potentially confound the effects of tight glycemic control if not taken into consideration.

### Glycemic variability

Glycemic variability is defined as the fluctuation of blood glucose or other parameters of glucose homeostasis over a given time. The most frequently used metrics for assessing short-term within-day glycemic variability are the following: 

*   Standard deviation of glucose

*   Coefficient of variation for glucose

*   Mean amplitude of glycemic excursions.33

Ryan et al34 proposed another metric for glycemic variability in type 1 diabetes, termed the glycemic lability index, based on the change in glucose level over a 4-week period. A discussion of the interpretation and reference values of these indices is beyond the scope of this review.

There is strong evidence that high glycemic variability is associated with increased short-term and long-term mortality and hospital length of stay in heterogeneous cohorts of critically ill patients,35–39 with 1 study36 showing a higher mortality rate with increasing glycemic variability in patients with sepsis when the glycemic lability index was divided into deciles. Increased rates of bacteremia,40 nosocomial infections,41 and surgical site infections42 have also been linked to increased glycemic variability. For example, Atamna et al40 found that increased glycemic variability (expressed as coefficient of variation for glucose) increased the risk of bacteremia in non-ICU patients hospitalized for acute infectious illnesses. Donati et al41 found that in critically ill patients, increased glycemic variability in all 3 indices noted above were significantly associated with infectious morbidity and mortality, with the highest quartile of the glycemic lability index having the strongest association with ICU-acquired infection. Subramaniam et al42 reported that postoperative glycemic variability in the first 24 hours after cardiac surgery carried the highest rate of a composite of postoperative adverse events, including superficial and deep sternal wound infections.

Several studies have evaluated the effects of antecedent diabetes status as well as hypoglycemia.20,43,44 Interestingly, when Krinsley et al20,43 stratified patients based on their prior diagnosis of diabetes, a high glycemic variability (using the coefficient of variation for glucose) was associated with increased mortality and shortened survival in acutely ill patients without diabetes but not in patients with diabetes. The landmark study by Lanspa et al44 used a standardized electronic insulin protocol to minimize interphysician variability in insulin titration. They found that even though the coefficient of variation was independently associated with 30-day mortality, this association was higher for patients without diabetes than for those with diabetes. Although these studies were adequately powered and their populations were stratified for diabetes state, their potential weakness is that the stratification was made based on either chart review20,43 or the International Classification of Diseases (ICD)-9 codes44 without including the HbA1c. Thus, diabetes diagnoses could have been missed. In addition, the effect of glycemic variability was not studied in patients with well-controlled vs poorly controlled diabetes, based on HbA1c values, as was done for the TIR.

The effect of glycemic variability on mortality outcomes, though potentially confounded by hypoglycemia, was also proven to be a strong independent predictor of mortality when adjusting for hypoglycemia and disease severity.44,45 In fact, in 1 study,46 the risk of hypoglycemia was 3.2 times higher in patients with increased glycemic variability.

## HYPOGLYCEMIA: A COMPLICATING FACTOR

The American Diabetes Association defines hypoglycemia as a blood glucose level below 70 mg/dL and classifies it as follows: 

*   Level 1: 70 to ≥ 54 mg/dL

*   Level 2: < 54 mg/dL

*   Level 3: a clinical event characterized by altered mental or physical status requiring assistance for treatment of hypoglycemia.47

In observational studies, hypoglycemia has been independently associated with increased risk of death in critically ill patients.48–52 In RCTs, a pooled analysis of the NICE-SUGAR study53 and the study by Meyfroidt et al54 showed that hypoglycemia increased the odds of mortality. In one study,52 mild hypoglycemia (defined as < 70 mg/dL) was associated with increased mortality regardless of diabetes status and diagnosis of conditions (medical, surgical, or trauma). In a retrospective study, Bagshaw et al48 found that early hypoglycemia (defined as within 24 hours of ICU admission) and its severity were associated with increasing mortality in a dose-dependent fashion. Interestingly, mortality was higher in patients with 2 episodes of hypoglycemia than in those with only 1 episode.48 Saliba et al55 examined outcomes based on whether hypoglycemia was induced by medication (iatrogenic) or was spontaneous during the course of critical illness. When results were stratified based on the cause of hypoglycemia, they found that the effects on mortality rates were equally harmful and that the cause did not have a significant impact.55

## GLYCEMIC TARGETS IN CLINICAL STUDIES

### Single-center trials

In 2010, Meyfroidt et al54 published results of a retrospective analysis of data first published in 2001 by Van den Berghe et al.13 In that trial, 1,548 patients (mainly with cardiac disease) admitted to the surgical ICU were randomized to receive either intensive insulin therapy (glucose goal of 80–110 mg/dL) or hyperglycemia treatment only when it reached the renal threshold (180–220 mg/dL). Reductions in mortality, critical illness polyneuropathy, acute renal failure, transfusion requirement, and bloodstream infections were more significant in the intensive insulin therapy group than in the “tolerating-hyperglycemia” group. However, hypoglycemia was more frequent in the intensive treatment cohort.13

In 2006, Van den Berghe et al14 published results from a similar trial in 1,200 exclusively medical ICU patients. The insulin infusion protocols and nutritional strategies were the same as in the study of surgical patients. Results showed that intensive insulin therapy did not decrease hospital mortality rates. However, the group had significant reductions in length of ICU and hospital stay, mechanical ventilation duration, and acute renal failure. As in the first trial, hypoglycemia was significantly more prevalent in the intensive insulin treatment group.14

### Multicenter trials

Subsequent multicenter RCTs failed to confirm the mortality benefits of intensive insulin therapy reported by Van den Berghe et al13,14 and Meyfroidt et al.54 The Efficacy of Volume Substitution and Insulin Therapy in Severe Sepsis study (VISEP)15 was conducted in medical and surgical ICU patients with sepsis, with results published in 2008. One year later, results were published from the Glucontrol study,16 conducted in a similar population. However, both studies were terminated prematurely due to increased hypoglycemia in the intensive therapy arm in VISEP15 and a high rate of unintended protocol violations in Glucontrol.16

Enthusiasm for strict glycemic control was further reduced by the 2009 publication of results from the international multicenter NICE-SUGAR study,17 which randomized 6,104 patients. In NICE-SUGAR, the intensive insulin therapy cohort (glucose target 81–108 mg/dL) had higher 90-day mortality rates and a higher incidence of severe hypoglycemia (< 40 mg/dL) than the conventional therapy group (glucose target 144–180 mg/ dL). Moreover, there was no reported difference between the groups in ICU or hospital length of stay, duration of mechanical ventilation, or need for renal replacement therapy. In a 24-month follow-up study of NICE-SUGAR,56 no differences were detected in favorable neurologic outcomes or mortality in patients with traumatic brain injury.

## EXPLAINING DISCREPANCIES IN STUDY RESULTS

### Difference in blood glucose targets

The Leuven studies13,14 and VISEP15 used target glucose levels of 80 to 110 mg/dL (stringent) in the intervention groups and 180 to 200 mg/ dL (loose) in the control groups. In contrast, the Glucontrol study used 80 to 110 mg/dL for the intervention group (stringent) and 140 to 180 mg/dL (intermediate) for the controls,16 and the NICE-SUGAR study17 used 81 to 108 mg/dL (stringent) for the interventional arm and 144 to 180 mg/dL (intermediate) for the controls. Thus, comparisons between stringent and intermediate glucose targets have not been addressed by adequately powered RCTs.

In attempts to find an optimal blood glucose target, Yamada et al57 and Yatabe et al58 performed network meta-analyses of published RCTs comparing insulin regimens in critically ill adults with hyperglycemia. Unlike the standard pairwise meta-analysis, a network meta-analysis has the advantage of comparing the efficacy of more than 2 interventions, using direct and indirect or mixed comparisons for the intervention groups.59 Using a common comparator, indirect comparisons can examine intervention arms that had no prior direct head-to-head comparisons in clinical trials. The 2 meta-analyses57,58 divided study groups into 4 interventions based on different blood glucose targets: tight (80–100 mg/dL), moderate (110–140 mg/dL, 110–144 mg/dL), mild (140–180 mg/dL, 144–180 mg/dL), and loose (> 180 mg/dL). Results revealed no significant difference relevant to the mortality risk for any comparison. However, these findings should be interpreted with caution, as the validity of indirect and mixed comparisons is built on the assumption that there are no differences between trials other than the intervention or treatment (in this case, a target blood glucose value), which is clearly a limitation given the methodologic differences of the key trials.

### Differences in other glycemic control metrics and diabetes status

The TIR, glycemic variability, preexisting diabetes status, and preadmission glycemic control play important modifying roles on the benefits of stringent insulin therapy on mortality outcomes, as discussed above. Apart from the Glucontrol trial that reported TIR and glycemic variability,16 earlier RCTs based comparisons solely on the blood glucose target, which can potentially confound the results.

### Differences in methods of glucose measurement

Inaccurate glucose measurement can lead to insulin dosing errors that can cause hypoglycemia. A review article by Inoue et al60 found that the first Leuven trial13 used precise blood-gas analyzers, which are more accurate than traditional point-of-care capillary glucose meters. Subsequent trials—medical Leuven,14 VISEP,15 Glucontrol,16 and NICE-SUGAR17—used both arterial and capillary analyzers. The point-of-care glucose meters, while having the advantage of ease of use and rapidity, can be affected by anemia,61 arterial oxygen tension,62 and the patient’s medications,63 especially given the outdated glucose monitors used in these studies.

Continuous glucose monitoring was not available at the time of the initial RCTs. This technology can offer a significant benefit in improving glycemic control,64,65 using a wide range of metrics such as TIR, time above range, and time below range, which can provide more precise data on glycemic control than conventional intermittent glucose monitoring.66 Clinical trials evaluating continuous glucose monitoring in hospitalized patients have been mainly confined to the intravascular route,67,68 and thus, minimally invasive devices have not been thoroughly studied. We believe that use of continuous glucose monitoring can probably provide more objective information on optimal blood glucose targets for future trials, especially when combined with validated computerized insulin protocols.

### Differences in insulin administration protocols

The Leuven trials13,14 and VISEP15 used a strict algorithm for insulin titration. In contrast, the NICE-SUGAR17 trial protocol was less standardized, allowing physicians to use their discretion and thus introducing interclinician variability in insulin administration, which can jeopardize TIR and increase glycemic variability.

In a multicenter international RCT published in 2017,69 a clinically validated computer algorithm for insulin infusion was compared with a nurse-driven protocol. Results showed that the computerized protocol achieved higher quality of blood glucose control as evidenced by lower hypoglycemia rates, high TIR, and low glycemic variability than the nurse-driven protocol. We hypothesize that a standardized computer-based insulin protocol can minimize interclinician variability and enhance compliance of the treating team.

## WHAT DO MEDICAL SOCIETIES RECOMMEND?

Several medical societies have guidelines on blood glucose targets for insulin therapy (Table 1).70–72

View this table:
[TABLE 1](http://www.ccjm.org/content/89/4/191/T1)

TABLE 1 
Recommendations for blood glucose targets for insulin therapy

The American Diabetes Association,70 citing the NICE-SUGAR trial results,17 recommends that insulin therapy be started for persistent hyperglycemia (> 180 mg/dL) with a target glucose range of 140 to 180 mg/dL in most critically ill patients, and notes that more aggressive goals (110–140 mg/dL) may be more appropriate for specific groups of patients (eg, postsurgical patients or patients with cardiac surgery) if these targets can be achieved without significant hypoglycemia. On the other hand, glucose concentrations above 180 mg/dL may be acceptable in terminally ill patients, in patients with severe comorbid conditions, and in inpatient care settings where frequent glucose monitoring or close nursing supervision is not feasible.70

The American College of Physicians71 recommends targeting a blood glucose range of 140 to 200 mg/dL in surgical and medical ICU patients, avoiding targets below 140 mg/dL due to likely increased harm.

Guidelines of the Society of Critical Care Medicine72 suggest a blood glucose value of 150 mg/dL or greater to trigger the use of insulin therapy, with the goal of maintaining a glucose level below 150 mg/dL for most critically ill patients and maintaining the glucose level absolutely below 180 mg/dL.

## TAKE-HOME MESSAGE

The optimal blood glucose target for patients in the ICU remains unknown, but a target of 140 to 180 mg/dL is the most acceptable for critically ill patients. We believe that future studies investigating the optimal target for ICU patients should do the following: 

*   Include other glycemic metrics

*   Take into account preadmission diabetes diagnosis and premorbid glycemic control (based on the HbA1c)

*   Use accurate blood glucose monitoring methods combined with a standardized validated insulin algorithm.

This will enable studies to shed light on appropriate glycemic targets and may lead to a more individualized approach for the critically ill patient rather than a universal approach.

## DISCLOSURES

The authors report no relevant financial relationships which, in the context of their contributions, could be perceived as a potential conflict of interest.

*   Copyright © 2022 The Cleveland Clinic Foundation. All Rights Reserved.

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