Impact of glucocorticoids on insulin resistance in the critically ill

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Abstract

Glucocorticoids (GCs) have been shown to reduce insulin sensitivity in healthy individuals. Widely used in critical care to treat a variety of inflammatory and allergic disorders, they may inadvertently exacerbate stress-hyperglycaemia. This research uses model-based methods to quantify the reduction in insulin sensitivity from GCs in critically ill patients, and thus their impact on glycaemic control. A model-based measure of insulin sensitivity (SI) was used to quantify changes between two matched cohorts of 40 intensive care unit (ICU) patients. Patients in one cohort received GC treatment, while patients in the control cohort did not. All patients were admitted to the Christchurch hospital ICU between 2005 and 2007 and spent at least 24 h on the SPRINT glycaemic control protocol.

A 31% reduction in whole-cohort median insulin sensitivity was seen between the control cohort and patients receiving glucocorticoids with a median dose equivalent to 200 mg/d of hydrocortisone per patient. Comparing percentile patients as a surrogate for matched patients, reductions in median insulin sensitivity of 20%, 25%, and 21% were observed for the 25th-, 50th- and 75th-percentile patients, respectively. These cohort and percentile patient reductions are less than or equivalent to the 30–62% reductions reported in healthy subjects especially when considering the fact that the GC doses in this study are 1.3–4.0 times larger than those in studies of healthy subjects. This reduced suppression of insulin sensitivity in critically ill patients could be a result of saturation due to already increased levels of catecholamines and cortisol common in critically illness. Virtual trial simulation showed that reductions in insulin sensitivity of 20–30% associated with glucocorticoid treatment in the ICU have limited impact on glycaemic control levels within the context of the SPRINT protocol.

Introduction

Hyperglycaemia is prevalent in critical care [1], [2], [3], [4], [5]. Increased secretion of counter-regulatory hormones stimulates endogenous glucose production and reduces effective insulin sensitivity [3], [4], [6]. Studies by Van den Berghe et al. [5], [7], Krinsley [8] and Chase et al. [2] have shown that tight glucose control can reduce ICU mortality by 18–45%. Glucocorticoids are used in critical care to treat a variety of inflammatory and allergic disorders, but may exacerbate stress-hyperglycaemia through their side effect of reducing insulin sensitivity and may thus indirectly impact clinical outcome.

Studies have shown that glucocorticoids (GCs) increase insulin resistance (reduce insulin sensitivity) in healthy individuals [9], [10], [11], [12], [13]. However, there is a lack of data about whether this effect is equally valid, or equally large, for critically ill patients. Insulin resistance, defined by relatively low insulin-mediated glucose disposal, is common and can be extreme in critically ill patients, which makes tight glycaemic control (TGC) in intensive care unit (ICU) patients difficult. Treatment with GCs may therefore make this task even harder if they yield significant (further) reductions of insulin sensitivity. Model-based methods can readily quantify changes in the insulin resistance of critically ill patients where typical methods of assessing this metric may be difficult to apply.

Several studies have reported 30–62% decreases in insulin sensitivity of healthy subjects after short-term administration of dexamethasone (2 or 6 mg/d) [9], [10], [11], [12]. Pagano et al. [13] documented a similar change with prednisone (15 mg/d). The mechanisms and pathways underlying these dramatic reductions in insulin sensitivity are not yet fully understood. Metabolic adaptations, including enhanced endogenous glucose production (EGP), increased plasma insulin concentrations, and reduced whole-body glucose disposal were also reported in these studies.

The primary hypothesis of this research is that insulin sensitivity is reduced by glucocorticoids in critically ill patients, but potentially to a lesser extent than in healthy individuals. Therefore, the aim of this research is to use model-based methods to quantify the effect of glucocorticoid therapy on insulin sensitivity of ICU patients and its impact on the resulting TGC interventions. These results will, for matched cohorts, enable assessment of whether GC therapy in the critically ill is detrimental to achieving tight glycaemic control, and thus potentially to patient outcome.

Section snippets

Subjects

This research was conducted as a retrospective study using records from 80 patients admitted to the Christchurch ICU between 2005 and 2007. A model-based measure of insulin sensitivity (SI) was used to quantify changes between two matched, critically ill cohorts.

A cohort of 40 patients, who each spent 24 h or more on the SPRINT glycaemic control protocol [2] and received glucocorticoid therapy during this time, was selected from the available records. These patients had received treatment with

Overall cohort analysis

Insulin sensitivity in patients receiving glucocorticoids was lower than control patients in an overall cohort comparison. Median insulin sensitivity was reduced 31% from 3.49 × 10−4 to 2.40 × 10−4 L/mU min (p < 0.001). Fig. 2 shows the CDFs for both cohorts. There is a clear separation between the control cohort and the steroid cohort (while receiving steroids) distributions at all likelihood values.

The CDF of insulin sensitivity of the steroid cohort is also shown for periods when the patients were

Discussion

Glucocorticoids cause significantly increased insulin resistance (significantly lower insulin sensitivity, SI) in healthy individuals [9], [10], [11], [12], [13]. The aim of this research was to determine to what extent this effect occurs in critically ill patients, who are already relatively insulin resistant due to their condition, and how it may affect TGC.

In this study, a whole-cohort 31% reduction in median insulin sensitivity was seen between patients receiving glucocorticoids (during

Conclusions

This research used model-based methods to show that glucocorticoids cause less of a reduction in the insulin sensitivity of critically ill patients than in healthy individuals. Both the percentile patient and cohort analyses point to reductions in insulin sensitivity associated with glucocorticoid treatment of 20–30%. These cohort and percentile patient reductions are less than or equivalent to the 30–62% reductions reported in healthy subjects especially when considering the fact that the GC

Conflict of interest

All authors declare no conflicts of interest.

Acknowledgement

Financial support: New Zealand Tertiary Education Commission.

References (39)

  • C.G. Perry et al.

    Glucocorticoids and insulin sensitivity: dissociation of insulin's metabolic and vascular actions

    J. Clin. Endocrinol. Metab.

    (2003)
  • H. Larsson et al.

    Short-term dexamethasone treatment increases plasma leptin independently of changes in insulin sensitivity in healthy women

    J. Clin. Endocrinol. Metab.

    (1996)
  • N. Nicod et al.

    Metabolic adaptations to dexamethasone-induced insulin resistance in healthy volunteers

    Obes. Res.

    (2003)
  • G. Pagano et al.

    An in vivo and in vitro study of the mechanism of prednisone-induced insulin resistance in healthy subjects

    J. Clin. Invest.

    (1983)
  • H. Derendorf et al.

    Receptor-based pharmacokinetic–pharmacodynamic analysis of corticosteroids

    J. Clin. Pharmacol.

    (1993)
  • J.C. Melby

    Clinical pharmacology of systemic corticosteroids

    Ann. Rev. Pharmacol. Toxicol.

    (1977)
  • B.P Schimmer et al.

    Adrenocorticotropic hormone: adrenocortical steroids and their synthetic analogs: inhibitors of the synthesis and actions of adrenocortical hormones

  • D.C. Deibert et al.

    Epinephrine-induced insulin resistance in man

    J. Clin. Invest.

    (1980)
  • E.J. Henriksen et al.

    Angiotensin converting enzyme inhibitors and modulation of skeletal muscle insulin resistance

    Diabetes Obes. Metab.

    (2003)
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