Open Access

The effect of diabetes mellitus on the association between measures of glycaemiccontrol and ICU mortality: a retrospective cohort study

  • Marjolein K Sechterberger1Email author,
  • Robert J Bosman2,
  • Heleen M Oudemans-van Straaten2,
  • Sarah E Siegelaar1,
  • Jeroen Hermanides3,
  • Joost BL Hoekstra1 and
  • J Hans De Vries1
Critical Care201317:R52

DOI: 10.1186/cc12572

Received: 30 September 2012

Accepted: 12 March 2013

Published: 19 March 2013

Abstract

Introduction

In critical illness, four measures of glycaemic control are associated with ICUmortality: mean glucose concentration, glucose variability, the incidence ofhypoglycaemia (≤ 2.2 mmol/l) or low glucose (2.3 to 4.7 mmol/l). Underlyingdiabetes mellitus (DM) might affect these associations. Our objective was to studywhether the association between these measures of glycaemic control and ICUmortality differs between patients without and with DM and to explore the cutoffvalue for detrimental low glucose in both cohorts.

Methods

This retrospective database cohort study included patients admitted betweenJanuary 2004 and June 2011 to a 24-bed medical/surgical ICU in a teachinghospital. We analysed glucose and outcome data from 10,320 patients: 8,682 withoutDM and 1,638 with DM. The cohorts were subdivided into quintiles of mean glucoseand quartiles of glucose variability. Multivariable regression models were used toexamine the independent association between the four measures of glycaemic controland ICU mortality, and for defining the cutoff value for detrimental lowglucose.

Results

Regarding mean glucose, a U-shaped relation was observed in the non-DM cohort withan increased ICU mortality in the lowest and highest glucose quintiles (odds ratio= 1.4 and 1.8, P < 0.001). No clear pattern was found in the DMcohort. Glucose variability was related to ICU mortality only in the non-DMcohort, with highest ICU mortality in the upper variability quartile (odds ratio =1.7, P < 0.001). Hypoglycaemia was associated with ICU mortality inboth cohorts (odds ratio non-DM = 2.5, P < 0.001; odds ratio DM = 4.2,P = 0.001), while low-glucose concentrations up to 4.9 mmol/l wereassociated with an increased risk of ICU mortality in the non-DM cohort and up to3.5 mmol/l in the DM cohort.

Conclusion

Mean glucose and high glucose variability are related to ICU mortality in thenon-DM cohort but not in the DM cohort. Hypoglycaemia (≤ 2.2 mmol/l) wasassociated with ICU mortality in both. The cutoff value for detrimental lowglucose is higher in the non-DM cohort (4.9 mmol/l) than in the DM cohort (3.5mmol/l). While hypoglycaemia (≤ 2.2 mmol/l) should be avoided in bothgroups, DM patients seem to tolerate a wider glucose range than non-DMpatients.

Introduction

Hyperglycaemia, hypoglycaemia and increased glucose variability in critically illpatients are independently associated with ICU mortality [16]. In the last decade many clinical triallists have attempted to improvemortality rates through intensive insulin therapy. Unfortunately, these trials haveproduced conflicting data, with some of the studies showing lower and others highermortality with strict glucose control, the latter possibly due to an increased incidenceof hypoglycaemia [712]. There is consensus about the importance to avoid hypoglycaemia and many ICUshave therefore increased their lower glucose limit [13]. However, there is no consensus about the optimal target glucose range. In aprevious database cohort study, we found an optimal mean glucose range of 6.7 to 8.4mmol/l in a medical cohort and 7.0 to 9.4 mmol/l in a surgical cohort [14]. We additionally found that glucose concentrations that were low but abovehypoglycaemic levels (between 2.3 and 4.7 mmol/l) were associated with increased ICUmortality [3]. Thus, in addition to the mean glucose concentration, glucose variability andhypoglycaemia, a fourth measure of glycaemic control - low glucose (2.3 to 4.7 mmol/l) -is associated with ICU mortality in the critically ill.

Underlying diabetes mellitus (DM) might affect the abovementioned associations. In arecent review we examined the current literature on glycaemic control and mortality indiabetic ICU patients and we found that, despite patients with DM having an increasedrisk of developing complications when admitted to the ICU, their risk of mortality isnot increased [15]. In addition, ICU patients with DM have lower mortality in the higher meanglucose range compared with those without DM, although varying cutoff values were used [1619]. Some studies found the opposite, with higher mortality rates for DM patientsin the low-normal mean glucose range. However, these findings were unadjusted resultsonly [18, 20] and this relation was not significant after adjustment for severity ofdisease [16]. Furthermore, high glucose variability in ICU patients with DM seems to beless harmful than in patients without DM [21, 22] although data are limited. Lastly, hypoglycaemia is associated with mortalityin patients with and without DM [3, 4, 23], while the risk of hypoglycaemia is higher in patients with DM [4, 24]. Altogether, some of the abovementioned findings are inconsistent and none ofthe reviewed studies evaluated all four measures of glycaemic control concomitantly.

The objective of this study was to determine whether the association between measures ofglycaemic control - mean glucose, glucose variability (measured as the mean absoluteglucose (MAG) change), the occurrence of hypoglycaemia (≤ 2.2 mmol/l) or lowglucose (2.3 to 4.7 mmol/l) - and ICU mortality differs between patients without andwith underlying DM in a large cohort of critically ill patients admitted to a generalICU of a teaching hospital in the Netherlands. We also explored the cutoff value fordetrimental low glucose in both populations.

Materials and methods

Design and setting

The current study was conducted as a single-centre retrospective database cohortstudy in a 24-bed mixed surgical/medical ICU in a teaching hospital (Onze LieveVrouwe Gasthuis, Amsterdam, the Netherlands). All data were collected prospectively.All beds were equipped with a clinical information system (MetaVision;i MDsoft, Tel Aviv, Israel) from which clinical and laboratorydata were extracted. The nurse-to-patient ratio was on average 1:2, depending on theseverity of disease. According to national guidelines this research is exempt fromethical approval because it is a retrospective study. The requirement for informedconsent was waived because all data were anonymous and collected retrospectively.

Glucose regulation protocol

A glucose regulation protocol, with a target blood glucose concentration of 4.0 to7.0 mmol/l, was implemented in 2001 after the publication of the study by van denBerghe and colleagues [7]. The glucose regulation sliding scale algorithm was connected to theclinical information system and fully computerised with an integrated decisionsupport module controlling the algorithm [25]. The glucose regulation protocol has been reported previously [2, 3, 14]. In April 2009, following the publication of the Normoglycaemia inIntensive Care Evaluation - Survival Using Glucose Algorithm Regulation investigatorsin 2009 [11], a new target blood glucose concentration of 5.0 to 9.0 mmol/l wasinstituted. To date, this new target blood glucose range is maintained in routineintensive care management.

Cohort and data collection

Relevant data were extracted from the clinical information system concerning patientsadmitted to the ICU between January 2004 and June 2011. Readmissions, patients with awithholding care policy, and patients with < 3 glucose values during ICU admissionwere excluded. The assignment of each patient's diabetic status on ICU admission wasbased on the use of oral glucose-lowering drugs and/or insulin therapy. Demographicvariables, admission diagnosis, glucose values, the occurrence of hypoglycaemia andICU and hospital mortality rates were assessed. Severity of disease was assessedusing the Acute Physiology and Chronic Health Evaluation (APACHE) II score onadmission [26]. For each subsequent day of ICU admission, the Sequential Organ FailureAssessment score was assessed as a measurement of severity of disease [27]. The maximal Sequential Organ Failure Assessment score was determined forthe patient's entire stay in the ICU [28].

Glucose measurements

Glucose was measured from blood samples obtained from an arterial catheter using theAccu-chek (Roche/Hitachi, Basel, Switzerland). Results were automatically stored inthe clinical information system. For each patient, mean glucose during admission wascalculated from all glucose values measured during ICU admission. As markers forglucose variability, the MAG change [2] and the standard deviation were calculated per patient. Hypoglycaemia wasdefined as one or more glucose values ≤ 2.2 mmol/l, which is in accordance withprevious trials [7, 11]. Although our blood glucose target range in the initial years was between4.0 and 7.0 mmol/l, we later found an association between the presence of a glucosevalue ≤ 4.7 mmol/l and ICU mortality [3]. Low glucose was therefore defined as the presence of at least one glucosevalue between 2.3 and 4.7 mmol/l.

Statistical analyses

Continuous data are presented as mean (standard deviation) or median (interquartilerange), as appropriate, and compared using Student's t test or theMann-Whitney rank-sum test, respectively. Categorical data are presented aspercentages and compared using the chi-square test. In accordance with our previousstudies, mean glucose and glucose variability (MAG change) were categorised intoequally sized quintiles [14] and quartiles [2] and were plotted against ICU mortality for the DM and non-DM cohortsseparately.

The independent association between mean glucose and ICU mortality was examined usingmultivariable logistic regression analysis calculating odds ratios (ORs) with 95%confidence intervals (CIs). The quintile with the lowest mortality incidence was usedas a reference. Based on clinical relevance and prognostic scoring, we adjusted fordemographics (age, sex), severity of disease (using the APACHE II score),hypoglycaemia (≤ 2.2 mmol/l) and cardiothoracic surgery as the admissioncategory. Cardiothoracic surgery was included as a covariate for several reasons: agenerally lower mortality in this group compared with other surgical patients, arelatively low APACHE II score, a relatively short length of ICU stay and severaldifferent demographic and physiological characteristics of this group from thegeneral ICU population, which could be reflected in differences in mean glucoseconcentration and glucose variability [29]. In an alternative model, adjustment was made for the occurrence ofglucose values ≤ 4.7 mmol/l, which is also independently associated withmortality [3, 30].

A second multivariable regression model was used to assess the independentassociation between glucose variability (MAG change) and ICU mortality, the quartilewith lowest mortality incidence used as a reference. In this model the same potentialconfounders were used including the variable mean glucose. Furthermore, to assess theassociation between hypoglycaemia (≤ 2.2 mmol/l) and low glucose (2.3 to 4.7mmol/l) and ICU mortality, unadjusted and adjusted ORs with 95% CIs were calculated,the latter using a third multivariable regression model adjusted for age, sex,severity of disease, cardiothoracic surgery and sepsis as admission diagnoses.

In both cohorts, we also assessed the cutoff value for detrimental low glucose, byperforming the latter analysis for different blood glucose cutoff values.Additionally, when we adjusted the logistic regression models for the change intarget glucose range in the studied period, no change in our results was observed(data not shown). All statistical analyses were performed in SPSS 18.0 (SPSS Inc,Chicago, IL, USA).

Results

From 11,901 ICU admissions, 10,320 patients were selected for analyses after excluding842 readmissions, 105 patients with a withholding care policy, and 714 patients with< 3 glucose measurements. The remaining cohort consisted of 8,682 (84.2%) patientswho did not have DM at the time of ICU admission (non-DM cohort) and 1,638 (15.8%)patients who had DM at the time of ICU admission (DM cohort). The percentage of medicaland surgical ICU admissions in the entire cohort was 26% and 74%. The non-DM:DM ratiowithin these groups was 9:1 in patients with a medical ICU admission diagnosis and 4:1in patients with a surgical ICU admission diagnosis. Table 1illustrates patient characteristics of the entire study population as well as thedifferences between the non-DM cohort and the DM cohort.
Table 1

Characteristics, glucose and treatment variables for patients without/withdiabetes mellitus and the total cohort

 

No diabetes

(n= 8,682)

Diabetes

(n= 1,638)

P valueª

Total cohort

(n= 10,320)

Age (years)

65 ± 13

68 ± 10

< 0.001

65 ± 13

Male sex

5804 (67)

1,032 (63)

0.003

6,836 (66)

Body mass index (kg/m2)

27 ± 14

29 ± 5

< 0.001

27 ± 13

APACHE II score on admission

16 (13 to 21)

16 (13 to 20)

0.006

16 (13 to 21)

Maximum SOFA score during admissionb

6 (5 to 8)

6 (5 to 7)

0.09

6 (5 to 8)

ICU stay (hours)

26 (20 to 66)

23 (19 to 49)

< 0.001

25 (20 to 64)

Died in the ICU

622 (7)

73 (5)

< 0.001

695 (7)

Died in the hospital

994 (11)

144 (9)

0.001

1,138 (11)

Medical admissions

2,444 (28)

266 (16)

< 0.001

2,710 (26)

Surgical admissions

6,238 (72)

1,372 (84)

< 0.001

7,610 (74)

   Cardiothoracic surgery patients

4,877 (56)

1,214 (74)

< 0.001

6,091 (59)

APACHE II admission category

    

   Cardiovascular

5,776 (67)

1,338 (82)

< 0.001

7114 (69)

   Sepsis

628 (7)

93 (6)

0.02

721 (7)

   After cardiac arrest

534 (6)

37 (2)

< 0.001

571 (6)

   Gastrointestinal

474 (5)

43 (3)

< 0.001

517 (5)

   Haematological

18 (0)

1 (0)

0.205

19 (0)

   Renal

60 (1)

9 (1)

0.519

69 (1)

   Metabolic

81(1)

14 (1)

0.761

95 (1)

   Neurological

266 (3)

12 (1)

< 0.001

278 (3)

   Respiratory

845 (10)

91 (6)

< 0.001

936 (9)

Glucose values per patient

12 (7 to 27)

14 (11 to 28)

< 0.001

13 (8 to 28)

Overall glucose (mmol/l)

8.0 ± 1.7

8.0 ± 1.6

0.577

8.0 ± 1.6

Morning glucose (mmol/l)

7.6 ± 2.0

7.0 ± 2.0

< 0.001

7.5 ± 2.0

Mean absolute glucose change (mmol/l/hour)

0.6 (0.4 to 0.8)

0.8 (0.6 to 1.0)

< 0.001

0.7 (0.4 to 0.9)

Standard deviation (mmol/l)

1.7 (1.3 to 2.3)

2.1 (1.6 to 2.7)

< 0.001

1.8 (1.4 to 2.4)

Incidence hypoglycaemia ≤ 2.2 mmol/lc

310 (4)

57 (4)

0.856

367 (4)

Incidence glucose value 2.3 to 4.7 mmol/lc

3,715 (43)

901 (55)

< 0.001

4,616 (45)

Use of insulin

6,686 (77)

1,610 (98)

< 0.001

8,296 (80)

Insulin dose (IU/hour)

2.2 (1.7 to 3.1)

2.8 (2.0 to 4.0)

< 0.001

2.3 (1.8 to 3.3)

Use of vasopressor drugs

8,020 (92)

1,551 (95)

0.001

9,571 (93)

Use of corticosteroids

8,561 (99)

1,636 (100)

< 0.001

10,197 (99)

Mechanical ventilationd

8,039 (93)

1,539 (94)

0.050

9,578 (93)

Continuous veno-venous haemofiltration

690 (8)

116 (7)

0.231

806 (8)

Data presented as mean ± standard deviation, n (%) or median(interquartile range). APACHE, Acute Physiology and Chronic Health Evaluation;SOFA, Sequential Organ Failure Assessment. aBased on Student's t test or the Mann-Whitney rank-sum test (continuous data), or the chi-squaretest (categorical data), comparing patients with and without diabetes.bMaximum score during admission, calculated from the totalindividual scores calculated each ICU day. cPatients who experienced atleast one hypoglycaemia or glucose value between 2.3 and 4.7 mmol/l.dIn the first 24 hours of ICU admission.

Association between mean glucose concentration and ICU mortality

Figure 1 demonstrates the quintiles of mean glucose ranges percohort (non-DM cohort: < 6.8, 6.8 to 7.3, 7.3 to 7.9, 7.9 to 8.9, > 8.9 mmol/l; DMcohort: < 6.9, 6.9 to 7.4, 7.4 to 8.0, 8.0 to 8.9, > 8.9 mmol/l) and correspondingICU mortality rates. This resulted in a U-shaped relationship between mean glucoseand ICU mortality in the non-DM cohort, with high ICU mortality in the lowest andhighest glucose quintile (11.8% and 7.7%). Multivariable logistic regression analysisin the non-DM cohort showed that mean glucose values in the lowest and highestquintiles were associated with a significantly higher OR for ICU mortality comparedwith the quintile with the lowest ICU mortality (Figure 2).This was supported by a significant nonlinear relationship between mean glucose andICU mortality (P for trend < 0.001). When we adjusted the logisticregression model for the occurrence of glucose values ≤ 4.7 mmol/l, the OR forICU mortality in the lowest quintile no longer reached significance in the non-DMcohort (OR = 1.3, 95% CI = 0.9 to 1.8, P = 0.17). The increased ICUmortality in the non-DM cohort in the lower part of the U-curve therefore seems to bedue to the relation between glucose values ≤ 4.7 mmol/l and ICU mortality. Incontrast, no clear pattern was found in the DM cohort in unadjusted (Figure 1B) or multivariate analysis (data not shown).
https://static-content.springer.com/image/art%3A10.1186%2Fcc12572/MediaObjects/13054_2012_Article_1703_Fig1_HTML.jpg
Figure 1

ICU mortality per quintile of mean glucose in the nondiabetes mellitus anddiabetes mellitus cohorts. ICU mortality (%) per quintile of meanglucose in (A) the nondiabetes mellitus cohort and (B) thediabetes mellitus cohort. Numbers above bars indicate the number of deaths permean glucose quintile.

https://static-content.springer.com/image/art%3A10.1186%2Fcc12572/MediaObjects/13054_2012_Article_1703_Fig2_HTML.jpg
Figure 2

Odds ratio for ICU mortality per quintile of mean glucose in the nondiabetesmellitus cohort. All odds ratios (ORs) were calculated per quintile ofmean glucose and adjusted for age, sex, Acute Physiology and Chronic HealthEvaluation II admission score, cardiothoracic surgery as admission diagnosisand the occurrence of hypoglycaemia (≤ 2.2 mmol/l). *P <0.05. CI, confidence interval.

Association between glucose variability and ICU mortality

The ranges of MAG change per quartile (non-DM cohort: < 0.37, 0.37 to 0.56, 0.56to 0.82, > 0.82 mmol/l/hour; DM cohort: < 0.56, 0.56 to 0.76, 0.76 to 1.03, > 1.03mmol/l/hour) and corresponding ICU mortality per cohort are shown in Figure 3. This resulted in a linear relationship in the non-DM cohort,with the highest mortality rate seen in the upper MAG quartile (13.4%). Multivariablelogistic regression analysis for the non-DM cohort is displayed in Figure 4; the OR for ICU mortality was highest in the upper MAG changequartile (OR = 1.69, P = 0.001). This was supported by a significantrelationship between MAG quartiles and ICU mortality (P for trend = 0.004).In contrast, in the DM cohort no clear pattern was found in unadjusted (Figure 3B) or multivariate analysis (data not shown).
https://static-content.springer.com/image/art%3A10.1186%2Fcc12572/MediaObjects/13054_2012_Article_1703_Fig3_HTML.jpg
Figure 3

ICU mortality per mean absolute glucose change quartile in non-diabetesmellitus and diabetes mellitus cohorts. ICU mortality (%) per meanabsolute glucose change (MAG) quartile in (A) the nondiabetes mellituscohort and (B) the diabetes mellitus cohort. Numbers above bars indicatenumber of deaths per mean absolute glucose change quartile.

https://static-content.springer.com/image/art%3A10.1186%2Fcc12572/MediaObjects/13054_2012_Article_1703_Fig4_HTML.jpg
Figure 4

Odds ratio for ICU mortality over mean absolute glucose quartiles in thenondiabetes mellitus cohort. All odds ratios (ORs) were calculated perquartile of mean absolute glucose (MAG) change and adjusted for age, sex, AcutePhysiology and Chronic Health Evaluation II admission score, mean glucose,cardiothoracic surgery as admission diagnosis and the occurrence ofhypoglycaemia (≤ 2.2 mmol/l). *P < 0.05. CI, confidenceinterval.

Association between hypoglycaemia and low glucose and ICU mortality

The percentage of patients who experienced at least one episode of hypoglycaemia(≤ 2.2 mmol/l) was similar in both cohorts (Table 1). Lowglucose (2.3 to 4.7 mmol/l) occurred more frequently in the DM cohort. The increasein glucose target range as introduced in 2009 decreased the percentage of patientswho experienced both hypoglycaemia (before 3.3%; after 0.3%) and low glucose (before36.3%; after 8.4%).

ICU mortality rates for hypoglycaemia were 29.7% and 21.1% in the non-DM and DMcohorts, respectively. Unadjusted ORs of hypoglycaemia (≤ 2.2 mmol/l) for ICUmortality in the occurrence of hypoglycaemia were 6.2 (95% CI = 4.8 to 8.1, P < 0.001) in the non-DM cohort and 6.6 (95% CI = 3.3 to 13.1, P <0.001) in the DM cohort. In logistic regression analysis, adjusted for potentialconfounders (see above), the OR of hypoglycaemia for ICU mortality was stillsignificant in both cohorts (non-DM cohort: OR = 2.5, 95% CI = 1.8 to 3.4, P < 0.001; DM cohort: OR = 4.2, 95% CI = 1.8 to 10.1, P = 0.001).

ICU mortality rates for low glucose (2.3 to 4.7 mmol/l) were 13.1% and 5.2% in thenon-DM and DM cohorts, respectively. The OR of low glucose for ICU mortality wassignificant in the non-DM cohort (unadjusted OR = 5.3, 95% CI = 4.4 to 6.4, P < 0.001; adjusted OR = 1.5, 95% CI = 1.2 to 1.9, P < 0.001). Whenexploring the cutoff value for detrimental low glucose in the non-DM cohort, we foundthat lowest blood glucose concentrations up to 4.9 mmol/l were associated with anincreased risk for ICU mortality (adjusted OR = 1.3, 95% CI = 1.1 to 1.7, P = 0.01). In contrast, when exploring the cutoff value for detrimental lowglucose in the DM cohort, we found that lowest blood glucose concentrations up to 3.5mmol/l were associated with an increased risk of ICU mortality (adjusted OR = 2.1,95% CI = 1.2 to 3.7, P = 0.01). With glucose values between 3.5 and 4.7mmol/l, no significant effect on the OR for ICU mortality was found. Poissonregression analysis, which we used in a previous study to adjust for daily SequentialOrgan Failure Assessment score over time [3], amounted to similar results (data not shown).

Discussion

In this retrospective database cohort study evaluating the association of four measuresof glycaemic control and ICU mortality concomitantly, we found striking differencesbetween the non-DM cohort and the DM cohort. In the non-DM cohort, ICU mortality wassignificantly related to all four measures of glycaemic control: mean glucose, glucosevariability, the occurrence of hypoglycaemia (≤ 2.2 mmol/l) and low glucoseconcentrations up to 4.9 mmol/l. In contrast, in the DM cohort, only the occurrence ofhypoglycaemia (≤ 2.2 mmol/l) and low-glucose concentrations up to 3.5 mmol/l weresignificantly associated with ICU mortality, while mean glucose and glucose variabilitywere not. The presence of DM thus seems to affect the association between glucosecontrol and ICU mortality.

Our findings support the results of previous studies that have focused on understandingthe association between the presence of DM at ICU admission, glycaemia, and ICUmortality [7, 8, 1619, 31, 32]. In all these studies, a stronger association between hyperglycaemia and ICUmortality was found in patients without DM, in comparison with patients with DM.

Hypoglycaemia has been found to be a risk factor of mortality in patients without andwith DM in the literature [3, 4, 7, 8, 30, 33, 34]. Of note, different cutoff values were used to define hypoglycaemia, rangingfrom ≤ 2.2 mmol/l [4, 35] up to ≤ 4.7 mmol/l [3, 33]. We also found a significant independent association between hypoglycaemia(≤ 2.2 mmol/l) and ICU mortality, in both the non-DM and DM cohorts. However, theassociation between low glucose (2.3 and 4.7 mmol/l) and ICU mortality was onlysignificant in the non-DM cohort, not in the DM cohort. When exploring the cutoff valuefor detrimental low glucose in the present cohort, we found that lowest blood glucoseconcentrations up to 4.9 mmol/l were associated with an increased risk of ICU mortalityin the non-DM cohort, and 3.5 mmol/l in the DM cohort. The cutoff value in the non-DMcohort is in line with our previous study, in which we found that lowest glucose valuesup to 4.7 mmol/l were associated with significant increased ICU mortality [3]. Furthermore, this cutoff value is supported by the finding that the highermortality in the lower half of the U-shaped curve (< 6.8 mmol/l) in the non-DM cohortis mainly determined by the occurrence of glucose values ≤ 4.7 mmol/l and less bythe glucose range between 4.7 and 6.8 mmol/l. The cutoff value for detrimental lowglucose we found in our DM cohort (≤ 3.5 mmol/l) is also in line with theliterature [23, 30]. Both studies found that glucose concentrations ≤ 3.9 mmol/l weresignificantly associated with mortality in a subgroup of DM patients. Altogether, we canconclude that the cutoff value for detrimental low glucose is lower in the DM populationthan in the non-DM population.

The association between glucose variability and ICU mortality in patients without andwith DM was studied previously [22]. In this observational study of 4,084 patients (including 942 DM patients), astrong association of glucose variability - expressed as the coefficient of variation(standard deviation/mean glucose level) - with mortality was found in patients withoutDM, while, in concordance with our study, no association was found in patients with DM [22]. Of note, this measure of glucose variability does not take order and timeinto account.

Several explanations can be considered for the different associations between glycaemiccontrol and ICU mortality in patients without and with pre-existing DM. We previouslysuggested that adaptation to hyperglycaemia might be a key mechanism [15]. Acute hyperglycaemia and inflammation induce oxidative stress, which causesendothelial damage [36]. In patients without DM, cellular adaptation mechanisms will be activated forthe first time in the acute care setting, whereas patients with DM could already haveadapted to these insults during their years with DM and therefore better tolerateepisodes of hyperglycaemia in an acute care setting. In addition, cellular adaptation torecurrent hypoglycaemia is also a well-established phenomenon [3739]. Although speculative, adaptation to low glucose will already be present inpatients with DM and might explain why patients with DM can withstand relatively lowglucose values better.

Our results should be viewed in light of the study's strengths and limitations.Strengths of our study include the large number of ICU patients and that glucose valueswere captured automatically, which prevents transcription errors. Furthermore, this isthe first study examining all four markers of glycaemic control in a non-DM cohort and aDM cohort simultaneously. Also, we used a time-based metric for glucose variability andwe explored multiple cutoff values for hypoglycaemia. Potential limitations of the studyare that it is a single-centre study and retrospective in design, and thus ispotentially subject to systematic error and bias. However, all data were prospectivelycollected and independently measured. Moreover, the findings are robust and internallyconsistent.

As in all studies in this field, our definition for a patient's diabetic status may benonrepresentative. Unfortunately, glycosylated haemoglobin testing was not performedbefore ICU admission and we were unable to make a distinction between type 1 and type 2DM patients. In addition, we were not able to distinguish between diabetes patients withgood and poor chronic control, who may become hyperglycaemic due to acute illness.Whether this might affect the optimal glucose target for the DM cohort remainsunknown.

Another limitation was that we were not able to distinguish between spontaneous(illness-related) and treatment-induced hypoglycaemia or variability. However, otherstudies could make this distinction. Finfer and colleagues reported that patients whohad encountered severe or moderate hypoglycaemia while not being treated with insulinwere at an increased mortality risk [23]. But they also demonstrated that, although to a lesser extent,insulin-induced hypoglycaemia was associated with an increased risk for ICU death. Incontrast, Kosiborod and colleagues only reported a high risk for mortality in patientshospitalised with acute myocardial infarction who developed hypoglycaemia spontaneously.Iatrogenic hypoglycaemia after insulin therapy was not associated with higher mortalityrisk [40].

Furthermore, in our cohort, most patients were admitted for cardiothoracic surgery; wecorrected for this potential confounder in our regression analyses and still foundsignificantly increased ICU mortality in the lowest and highest mean glucose quintilesand in the highest glucose variability quartile in the non-DM cohort. Moreover, the highamount of cardiothoracic surgery patients in the studied cohort may also havecontributed to the high administration level of corticosteroids. In our hospital, as inmany European hospitals (but not in most North American cardiac surgical centres),corticosteroid administration during cardiac surgery is part of routine care. Allpatients who were in shock or had sepsis or systemic inflammatory response syndrome alsoreceived corticosteroids. This could possibly limit the external validity of thissingle-centre study.

In our analyses of glucose variability, we did not correct for the frequency of glucosemeasurements during ICU admission. However, we did correct for severity of disease,which in itself is clearly correlated with the frequency of glucose measurements and ICUmortality. Furthermore, the concern that the frequency of blood glucose measurements mayinfluence the relation between the MAG and ICU mortality has been previously discussed [41]. MAG is independent of the number of measurements, as long as blood glucosekeeps changing at a constant rate. The MAG only increases when there is actually moreglucose variability. The possibility to capture variability, if there is any, increaseswhen the number of glucose measurements is increased. However, this can be said for allmeasures of glucose variability and this is not unique for the MAG change.

A limitation of our correction for severity of disease is the use of the APACHE IIscore. Although the validation of the use of APACHE II score to predict mortality incardiac surgery patients is lacking, this adjustment is the best available method [29]. Finally, because of the observational nature of the study, no proof ofcausation can be derived from the abovementioned associations between glycaemic controland ICU mortality.

Conclusion

This retrospective database cohort study shows that the presence of DM affects theassociation between three out of four measures of glycaemic control and ICU mortality.Mean glucose and high glucose variability were associated with ICU mortality in thenon-DM cohort but not in the DM cohort, whereas hypoglycaemia (≤ 2.2 mmol/l) wasassociated with ICU mortality in both. We additionally found a higher cutoff value fordetrimental low glucose in our non-DM cohort (4.9 mmol/l) than the DM cohort (3.5mmol/l). Glucose concentrations ≤ 4.9 mmol/l should therefore be avoided in thenon-DM cohort, while DM patients seem to tolerate a wider glucose range. Further studiesshould examine whether new technologies - that is, continuous glucose monitoringtechnology - could be of use for clinicians to improve glycaemic control.

Key messages

  • The presence of DM affects the association between three out of fourmeasures of glycaemic control and ICU mortality.

  • Mean glucose relates to ICU mortality by a U-shaped curve in thenon-DM population, whereas no clear association was found in the DM population.

  • High glucose variability is only related to ICU mortality in thenon-DM cohort.

  • The occurrence of hypoglycaemia (≤ 2.2 mmol/l) is related toICU mortality in both populations and should undoubtedly be avoided.

  • The cutoff value for detrimental low glucose in the non-DM population(4.9 mmol/l) seems to be higher than in the DM population (3.5 mmol/l).

Abbreviations

APACHE: 

Acute Physiology and Chronic Health Evaluation

CI: 

confidence interval

DM: 

diabetes mellitus

MAG: 

mean absolute glucose

OR: 

odds ratio.

Declarations

Authors’ Affiliations

(1)
Department of Internal Medicine, Academic Medical Center
(2)
Department of Intensive Care Medicine, Onze Lieve Vrouwe Gasthuis
(3)
Department of Anesthesiology, Academic Medical Center

References

  1. Dungan KM, Braithwaite SS, Preiser JC: Stress hyperglycaemia. Lancet 2009, 373: 1798-1807. 10.1016/S0140-6736(09)60553-5PubMed CentralView ArticlePubMedGoogle Scholar
  2. Hermanides J, Vriesendorp TM, Bosman RJ, Zandstra DF, Hoekstra JB, Devries JH: Glucose variability is associated with intensive care unit mortality. Crit Care Med 2010, 38: 838-842. 10.1097/CCM.0b013e3181cc4be9View ArticlePubMedGoogle Scholar
  3. Hermanides J, Bosman RJ, Vriesendorp TM, Dotsch R, Rosendaal FR, Zandstra DF, Hoekstra JB, Devries JH: Hypoglycemia is associated with intensive care unit mortality. Crit Care Med 2010, 38: 1430-1434. 10.1097/CCM.0b013e3181de562cView ArticlePubMedGoogle Scholar
  4. Krinsley JS, Grover A: Severe hypoglycemia in critically ill patients: risk factors and outcomes. Crit Care Med 2007, 35: 2262-2267. 10.1097/01.CCM.0000282073.98414.4BView ArticlePubMedGoogle Scholar
  5. Krinsley JS: Glycemic variability: a strong independent predictor of mortality in criticallyill patients. Crit Care Med 2008, 36: 3008-3013. 10.1097/CCM.0b013e31818b38d2View ArticlePubMedGoogle Scholar
  6. Siegelaar SE, Holleman F, Hoekstra JB, Devries JH: Glucose variability; does it matter? Endocr Rev 2010, 31: 171-182. 10.1210/er.2009-0021View ArticlePubMedGoogle Scholar
  7. Van den Berghe G, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P, Bouillon R: Intensive insulin therapy in the critically ill patients. N Engl J Med 2001, 345: 1359-1367. 10.1056/NEJMoa011300View ArticlePubMedGoogle Scholar
  8. Van den Berghe G, Wilmer A, Hermans G, Meersseman W, Wouters PJ, Milants I, Van WE, Bobbaers H, Bouillon R: Intensive insulin therapy in the medical ICU. N Engl J Med 2006, 354: 449-461. 10.1056/NEJMoa052521View ArticlePubMedGoogle Scholar
  9. Brunkhorst FM, Engel C, Bloos F, Meier-Hellmann A, Ragaller M, Weiler N, Moerer O, Gruendling M, Oppert M, Grond S, Olthoff D, Jaschinski U, John S, Rossaint R, Welte T, Schaefer M, Kern P, Kuhnt E, Kiehntopf M, Hartog C, Natanson C, Loeffler M, Reinhart K: Intensive insulin therapy and pentastarch resuscitation in severe sepsis. N Engl J Med 2008, 358: 125-139. 10.1056/NEJMoa070716View ArticlePubMedGoogle Scholar
  10. Preiser JC, Devos P, Ruiz-Santana S, Melot C, Annane D, Groeneveld J, Iapichino G, Leverve X, Nitenberg G, Singer P, Wernerman J, Joannidis M, Stecher A, Chiolero R: A prospective randomised multi-centre controlled trial on tight glucose control byintensive insulin therapy in adult intensive care units: the Glucontrol study. Intensive Care Med 2009, 35: 1738-1748. 10.1007/s00134-009-1585-2View ArticlePubMedGoogle Scholar
  11. Finfer S, Chittock DR, Su SY, Blair D, Foster D, Dhingra V, Bellomo R, Cook D, Dodek P, Henderson WR, Hebert PC, Heritier S, Heyland DK, McArthur C, McDonald E, Mitchell I, Myburgh JA, Norton R, Potter J, Robinson BG, Ronco JJ: Intensive versus conventional glucose control in critically ill patients. N Engl J Med 2009, 360: 1283-1297.View ArticlePubMedGoogle Scholar
  12. Marik PE, Preiser JC: Toward understanding tight glycemic control in the ICU: a systematic review andmetaanalysis. Chest 2010, 137: 544-551. 10.1378/chest.09-1737View ArticlePubMedGoogle Scholar
  13. Sechterberger MK, Siegelaar SE, Devries JH: In-hospital hyperglycemia: quo vadis? Diabetes Technol Ther 2011, 13: 1081-1084. 10.1089/dia.2011.0177View ArticlePubMedGoogle Scholar
  14. Siegelaar SE, Hermanides J, Oudemans-van Straaten HM, van der Voort PH, Bosman RJ, Zandstra DF, Devries JH: Mean glucose during ICU admission is related to mortality by a U-shaped curve insurgical and medical patients: a retrospective cohort study. Crit Care 2010, 14: R224. 10.1186/cc9369PubMed CentralView ArticlePubMedGoogle Scholar
  15. Siegelaar SE, Hoekstra JB, Devries JH: Special considerations for the diabetic patient in the ICU; targets for treatmentand risks of hypoglycaemia. Best Pract Res Clin Endocrinol Metab 2011, 25: 825-834. 10.1016/j.beem.2011.03.004View ArticlePubMedGoogle Scholar
  16. Egi M, Bellomo R, Stachowski E, French CJ, Hart GK, Hegarty C, Bailey M: Blood glucose concentration and outcome of critical illness: the impact ofdiabetes. Crit Care Med 2008, 36: 2249-2255. 10.1097/CCM.0b013e318181039aView ArticlePubMedGoogle Scholar
  17. Falciglia M, Freyberg RW, Almenoff PL, D'Alessio DA, Render ML: Hyperglycemia-related mortality in critically ill patients varies with admissiondiagnosis. Crit Care Med 2009, 37: 3001-3009. 10.1097/CCM.0b013e3181b083f7PubMed CentralView ArticlePubMedGoogle Scholar
  18. Graham BB, Keniston A, Gajic O, Trillo Alvarez CA, Medvedev S, Douglas IS: Diabetes mellitus does not adversely affect outcomes from a critical illness. Crit Care Med 2010, 38: 16-24. 10.1097/CCM.0b013e3181b9eaa5View ArticlePubMedGoogle Scholar
  19. Rady MY, Johnson DJ, Patel BM, Larson JS, Helmers RA: Influence of individual characteristics on outcome of glycemic control inintensive care unit patients with or without diabetes mellitus. Mayo Clin Proc 2005, 80: 1558-1567. 10.4065/80.12.1558View ArticlePubMedGoogle Scholar
  20. Krinsley JS: Glycemic control, diabetic status, and mortality in a heterogeneous population ofcritically ill patients before and during the era of intensive glycemicmanagement: six and one-half years experience at a university-affiliated communityhospital. Semin Thorac Cardiovasc Surg 2006, 18: 317-325. 10.1053/j.semtcvs.2006.12.003View ArticlePubMedGoogle Scholar
  21. Egi M, Bellomo R, Stachowski E, French CJ, Hart G: Variability of blood glucose concentration and short-term mortality in criticallyill patients. Anesthesiology 2006, 105: 244-252. 10.1097/00000542-200608000-00006View ArticlePubMedGoogle Scholar
  22. Krinsley JS: Glycemic variability and mortality in critically ill patients: the impact ofdiabetes. J Diabetes Sci Technol 2009, 3: 1292-1301.PubMed CentralView ArticlePubMedGoogle Scholar
  23. Finfer S, Liu B, Chittock DR, Norton R, Myburgh JA, McArthur C, Mitchell I, Foster D, Dhingra V, Henderson WR, Ronco JJ, Bellomo R, Cook D, McDonald E, Dodek P, Hebert PC, Heyland DK, Robinson BG: Hypoglycemia and risk of death in critically ill patients. N Engl J Med 2012, 367: 1108-1118.View ArticlePubMedGoogle Scholar
  24. Vriesendorp TM, van SS, Devries JH, de JE, Rosendaal FR, Schultz MJ, Hoekstra JB: Predisposing factors for hypoglycemia in the intensive care unit. Crit Care Med 2006, 34: 96-101. 10.1097/01.CCM.0000194536.89694.06View ArticlePubMedGoogle Scholar
  25. Rood E, Bosman RJ, van der Spoel JI, Taylor P, Zandstra DF: Use of a computerized guideline for glucose regulation in the intensive care unitimproved both guideline adherence and glucose regulation. J Am Med Inform Assoc 2005, 12: 172-180.PubMed CentralView ArticlePubMedGoogle Scholar
  26. Knaus WA, Draper EA, Wagner DP, Zimmerman JE: APACHE II: a severity of disease classification system. Crit Care Med 1985, 13: 818-829. 10.1097/00003246-198510000-00009View ArticlePubMedGoogle Scholar
  27. Vincent JL, Moreno R, Takala J, Willatts S, De MA, Bruining H, Reinhart CK, Suter PM, Thijs LG: The SOFA (Sepsis-related Organ Failure Assessment) score to describe organdysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems ofthe European Society of Intensive Care Medicine. Intensive Care Med 1996, 22: 707-710. 10.1007/BF01709751View ArticlePubMedGoogle Scholar
  28. Moreno R, Vincent JL, Matos R, Mendonca A, Cantraine F, Thijs L, Takala J, Sprung C, Antonelli M, Bruining H, Willatts S: The use of maximum SOFA score to quantify organ dysfunction/failure in intensivecare. Results of a prospective, multicentre study. Working Group on Sepsis relatedProblems of the ESICM. Intensive Care Med 1999, 25: 686-696. 10.1007/s001340050931View ArticlePubMedGoogle Scholar
  29. Kramer AA, Zimmerman JE: Predicting outcomes for cardiac surgery patients after intensive care unitadmission. Semin Cardiothorac Vasc Anesth 2008, 12: 175-183. 10.1177/1089253208323413View ArticlePubMedGoogle Scholar
  30. Krinsley JS, Schultz MJ, Spronk PE, Harmsen RE, van Braam HF, van der Sluijs JP, Melot C, Preiser JC: Mild hypoglycemia is independently associated with increased mortality in thecritically ill. Crit Care 2011, 15: R173. 10.1186/cc10322PubMed CentralView ArticlePubMedGoogle Scholar
  31. Krinsley JS, Meyfroidt G, Van den Berghe G, Egi M, Bellomo R: The impact of premorbid diabetic status on the relationship between the threedomains of glycemic control and mortality in critically ill patients. Curr Opin Clin Nutr Metab Care 2012, 15: 151-160. 10.1097/MCO.0b013e32834f0009View ArticlePubMedGoogle Scholar
  32. Van den Berghe G, Wilmer A, Milants I, Wouters PJ, Bouckaert B, Bruyninckx F, Bouillon R, Schetz M: Intensive insulin therapy in mixed medical/surgical intensive care units: benefitversus harm. Diabetes 2006, 55: 3151-3159. 10.2337/db06-0855View ArticlePubMedGoogle Scholar
  33. Egi M, Bellomo R, Stachowski E, French CJ, Hart GK, Taori G, Hegarty C, Bailey M: Hypoglycemia and outcome in critically ill patients. Mayo Clin Proc 2010, 85: 217-224. 10.4065/mcp.2009.0394PubMed CentralView ArticlePubMedGoogle Scholar
  34. Meyfroidt G, Keenan DM, Wang X, Wouters PJ, Veldhuis JD, Van den Berghe G: Dynamic characteristics of blood glucose time series during the course of criticalillness: effects of intensive insulin therapy and relative association withmortality. Crit Care Med 2010, 38: 1021-1029. 10.1097/CCM.0b013e3181cf710eView ArticlePubMedGoogle Scholar
  35. Van den Berghe G, Schetz M, Vlasselaers D, Hermans G, Wilmer A, Bouillon R, Mesotten D: Clinical review: Intensive insulin therapy in critically ill patients: NICE-SUGARor Leuven blood glucose target? J Clin Endocrinol Metab 2009, 94: 3163-3170. 10.1210/jc.2009-0663View ArticlePubMedGoogle Scholar
  36. Brownlee M: Biochemistry and molecular cell biology of diabetic complications. Nature 2001, 414: 813-820. 10.1038/414813aView ArticlePubMedGoogle Scholar
  37. Boyle PJ, Nagy RJ, O'Connor AM, Kempers SF, Yeo RA, Qualls C: Adaptation in brain glucose uptake following recurrent hypoglycemia. Proc Natl Acad Sci USA 1994, 91: 9352-9356. 10.1073/pnas.91.20.9352PubMed CentralView ArticlePubMedGoogle Scholar
  38. Heller SR, Cryer PE: Reduced neuroendocrine and symptomatic responses to subsequent hypoglycemia after1 episode of hypoglycemia in nondiabetic humans. Diabetes 1991, 40: 223-226. 10.2337/diabetes.40.2.223View ArticlePubMedGoogle Scholar
  39. McCrimmon RJ: Update in the CNS response to hypoglycemia. J Clin Endocrinol Metab 2012, 97: 1-8. 10.1210/jc.2011-1927View ArticlePubMedGoogle Scholar
  40. Kosiborod M, Inzucchi SE, Goyal A, Krumholz HM, Masoudi FA, Xiao L, Spertus JA: Relationship between spontaneous and iatrogenic hypoglycemia and mortality inpatients hospitalized with acute myocardial infarction. JAMA 2009, 301: 1556-1564. 10.1001/jama.2009.496View ArticlePubMedGoogle Scholar
  41. Harmsen RE, Spronk PE, Schultz MJ, Abu-Hanna A: May frequency of blood glucose measurement be blurring the association betweenmean absolute glucose change per hour and mortality? Crit Care Med 2011, 39: 224-225.View ArticlePubMedGoogle Scholar

Copyright

© Sechterberger et al.; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), whichpermits unrestricted use, distribution, and reproduction in any medium, provided theoriginal work is properly cited.