Admission hyperglycemia and adverse clinical outcomes in critically ill patients: A prospective, observational study

Background: Admission hyperglycemia is known to cause increase in in-hospital mortality, increased length of intensive care unit (ICU) stay, increased morbidity across critically ill patients. In patients with vascular disease (myocardial infarction, stroke, etc.), this has been extensively studied. We planned to study the prevalence of admission hyperglycemia and its association with adverse outcomes in all critically ill patients. Methods: In an observational, prospective study, 200 critically ill inpatients admitted to the medicine ICU were included. The patients were stratified into known diabetes, newly detected diabetes, and stress hyperglycemia. Baseline clinical and laboratory parameters were collected, and Acute Physiology and Chronic Health Evaluation (APACHE)-II, Sequential Organ Failure Assessment (SOFA), and Simplified Acute Physiology (SAP II) scores were calculated. Data regarding clinical outcomes (discharge or in-hospital death) were also collected. Results:   The prevalence of admission hyperglycemia and of stress hyperglycemia was found to be 11.99% and 1.51%, respectively. The newly detected diabetes had higher admission hyperglycemia and glycosylated hemoglobin. The prognostic scores – APACHE-II, SAP II, and SOFA scores – were worse among patients who died in the newly detected diabetes and the stress hyperglycemia group but not in the known diabetes group.   The odds of death increased by 3.5 times with 1-day increase in the ICU. Conclusion: Our study concluded that the patients with newly detected diabetes and stress hyperglycemia had more severe illness as compared to the known diabetics.

Keywords

Admission hyperglycemia - clinical outcomes - critically ill patients - diabetes mellitus - hyperglycemia - mortality - stress hyperglycemia

Introduction

Hyperglycemia is often multifactorial in critically ill patients. Severe hyperglycemia results in endothelial dysfunction, cytokine release, platelet activation, mitochondrial dysfunction, etc., and has been associated with an adverse outcome in a variety of settings in patients without history of diabetes.[[1]] Admission hyperglycemia includes the spectrum of stress hyperglycemia as well diabetic hyperglycemia. Elevated glucose levels on admission are associated with poor outcomes in patients with acute myocardial infarction (AMI), acute stroke, congestive cardiac failure, cardiogenic shock, atrial fibrillation, postangioplasty, cardiovascular surgery, trauma, acute exacerbation of chronic obstructive pulmonary disease, sepsis, etc.[[2]],[[3]] Hyperglycemia leads to an increased in-hospital mortality, especially so in critically ill patients without a previously recognized diagnosis of diabetes.

Most observational and retrospective studies have reported that hyperglycemia in patients with severe disease is associated with an increased risk of complications, longer intensive care unit (ICU) stay, and higher mortality rates. In evaluating admission hyperglycemia as a risk factor for adverse outcomes in critically ill patients, it is important to address the issue of illness severity. There have been many observational studies in the literature that have studied the incidence and effect on clinical outcomes of admission hyperglycemia on various cohorts of cardiovascular diseases (AMI, STEMI with angioplasty, atrial fibrillation, etc.), stroke, vascular thrombectomy, sepsis, trauma, etc., However, there have been only a few studies that have studied admission hyperglycemia on clinical outcomes of all the types of critically patients admitted to the ICU.[[2]],[[3]],[[4]] Moreover, there are hardly any studies that have tried to establish the relationship between admission hyperglycemia and various prognostic scoring systems in critically ill patients.[[5]]

Hence, we aimed to assess the incidence of admission hyperglycemia among the critically ill patients admitted to our ICU. We also intended to assess the generalizability of association between admission hyperglycemia and adverse clinical outcomes and also relationship between admission hyperglycemia and various prognostic scores in critically ill patients. If we are able to demonstrate an association in some of these patients, then it would pave a way to develop targeted interventions to treat those populations.

Patients and Methods

Setting and design

The prospective, observational study was carried out among the inpatients admitted to the Department of Medicine, Mahatma Gandhi institute of Medical Sciences (MGIMS), a 920-bedded rural teaching hospital situated in Central India. Every year, more than 11,000 patients are admitted to the department of medicine, of which about 25% are admitted to the medicine intensive care unit (MICU) for some critical illness. The department of medicine has 26-bedded MICU and 8-bedded cardiac ICU.

Study subjects

This study was carried out among the inpatients admitted to the ICU in the Department of Medicine, MGIMS, for any critical illness. The study was carried out over a period from December 2015 to December 2017. All consecutive patients, more than 18 years of age, who were admitted to the MICU due to any reasons, were included in the study. Patients with hyperglycemic crisis (diabetic ketoacidosis or hyperosmolar hyperglycemic states) were excluded. All the included patients were followed until discharge or death.

Study procedures

The study investigator identified the patient to be included in the study. Clinical and demographic data were collected at baseline by the study investigator, which included a detailed medical history, history of diabetes mellitus, and details of medications used. In-hospital data regarding diagnosis and reason for admission, corticosteroids and vasopressor therapy, mechanical ventilation support, total days of admission, total days in the ICU, and outcome were collected. Physiological and laboratory data were collected for the calculation of severity of illness using three scores, namely Acute Physiology and Chronic Health Evaluation (APACHE)-II, Sequential Organ Failure Assessment (SOFA), and Simplified Acute Physiology (SAP) II scores.[[6]],[[7]],[[8]]

Supine height (cm) and weight (kg) as measured routinely on the ICU admission were used to calculate body mass index (BMI), expressed as weight (kg)/height[[2]] (m), and the BMI was classified according to the World Health Organization definitions.[[9]] Patients were investigated for admission glucose (hexokinase assay), complete blood count (Coulter), blood urea, serum creatinine, serum sodium, serum potassium, pH, bicarbonate levels, serum bilirubin, C-reactive protein (enzymatic colorimetric assay), serum lactate (turbidimetric method), and glycosylated hemoglobin (HbA1c, high-performance liquid chromatography), which was measured within 24 h of ICU admission.

Consistent with the American Diabetes Association[[10]] recommendations and previous studies,[[3]],[[4]] hyperglycemia was defined as casual (nonfasting) blood glucose of >200 mg/dL on the day of admission to the ICU. We considered normoglycemia as admission glucose >60 mg/dL but <200 mg/dL.

We stratified patients in three groups: (1) stress hyperglycemia patients who had raised blood sugar on admission, but whose HbA1c value <5.6%; (2) known case of diabetes mellitus patients who had a history of diabetes mellitus and on medication oral hypoglycemic agents (OHA) or insulin to control blood sugar; and (3) newly diagnosed diabetes patients, whose HbA1c value >6.5% and random blood sugar (RBS) during the hospital stay were deranged and need blood sugar-lowering agent to control in the normal limit.

Statistical analysis

All data were collected on a structured pro forma by the study investigator and transferred to Microsoft Excel. These data were then transferred electronically to statistical software STATA version 13, StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP which was used for analysis. All the parametric quantitative data were expressed in terms of means ± standard deviation; nonparametric quantitative variables were expressed as median and interquartile ranges, and all categorical variables were presented as numbers (percentages). Mann–Whitney U-test or Kruskal–Wallis test was used to analyze continuous nonparametric data; continuous parametric data were analyzed using student's t-test or analysis of variance (ANOVA) when appropriate. Categorical data were analyzed by Chi-square test. Descriptive statistics were computed to assess the study sample's characteristics. Differences between those with hyperglycemia of known diabetes, newly detected diabetes with hyperglycemia, and stress hyperglycemia were assessed by ANOVA. The level of significance was taken as <0.05.

Multiple logistic regression was used to estimate adjusted, stratum-specific odds ratios (ORs). Modifiers of the association (OR) of hyperglycemia and death were included as interaction terms in these models. ORs with 95% confidence intervals (CIs) of the associated patient conditions were presented. The primary outcome of the study was in-hospital mortality. In addition, the adjusted ORs and 95% CIs for mortality were estimated through a stepwise model selection of a multivariable regression model adjusted by controlling the cofounding variables, such as age, sex, and comorbidities with the 95% CI.

Results

During the study period, a total of 2318 patients were admitted in the MICU for various reasons. After exclusion of 138 patients, as they were below 18 years of age, we identified 278 patients (11.99%) who had raised blood sugars at the time of admission. After excluding patients with diabetic ketoacidosis and hyperosmolar hyperglycemic status [[Figure 1]]. 200 patients were included in the study. Of these 200 patients included in the study, 82 (41%) patients were known case of diabetes mellitus; 70 (35%) were nondiabetic, and 48 (24%) were newly diagnosed diabetes. The prevalence of admission hyperglycemia in our study was 11.99% and the prevalence of newly detected diabetes was 2.07%. About 1.51% of patients had stress hyperglycemia at presentation.

Figure 1: Study flowchart depicting the flow of patients in the study

[[Table 1]] shows the clinicodemographic characteristics of the study population. The study population had a mean age of 57.32 ± 13.24 years. The known case of diabetes had a mean age (61.44 ± 10.82 years) significantly greater than the recently detected and stress hyperglycemia patients (F (2, 196) = 6.67; P = 0.0016). More than half of the study population was males (57/5%) and approximately three-quarters were smokers (72.5%). The history of alcohol intake was higher among stress hyperglycemia (7.5%) as compared to known diabetics and recently detected diabetics. Most of the study population was tachycardic on admission (heart rate (HR) mean = 106.44 ± 29.32) with normal systolic blood pressure (mean = 123.58 ± 45.79) and diastolic blood pressure (mean = 67.43 ± 33.64). There were 93 (45.5%) patients who were suffering with vascular diseases (cardiovascular and cerebrovascular disease); 16 (8%) with respiratory cause (chronic obstructive airway disease, pneumonia); 14 (7%) with kidney diseases (chronic kidney disease); 26 (13%) with liver cause (cirrhosis of liver); 38 (19%) with sepsis; 9 (4.5%) with malignancy; and remaining 4 (2%) were due to rheumatological disorders.

Table 1: Clinicodemographic characteristics of the patients in the study

Mean RBS on admission of the study population was 280.09 ± 73.73 mg/dL, with newly diagnosed diabetics having slightly higher RBS on admission (300.06 ± 64.91 mg/dL). RBS remained more than 290 mg/dL in all the patients 24 h after admission but was significantly higher in newly detected diabetics (311.44 ± 64.61) as compared to known diabetics and patients with stress hyperglycemia (F (2, 196) = 6.51; P = 0.0018). The HbA1c in newly detected diabetics was significantly higher (8.79 ± 2.11) as compared to known diabetics (7.18 ± 1.64).

The clinical and biochemical parameters were similar in patients with known diabetics, newly diagnosed diabetics, and stress hyperglycemia. This was very well reflected in the critically ill scores which were also similar for the three groups. The mean APACHE-II, SAP II, and SOFA scores were 20.43 ± 8.54, 5.86 ± 3.85, and 50.62 ± 18.68, respectively. About 11 (5.5%) study patients had APACHE-II score >5 predicting approximately 85% mortality. According to the SAP II score, a total of 47 patients (23.5%) had a SAP II score >64 predicting more than 75% mortality.

The mean hospital stay was about 8.09 ± 5.84 days in the study patients which was comparable for all three groups. Similarly, the mean number of days in the ICU was 4.97 ± 3.65 days. There were a total of 20 deaths (10%) among the study patients.

We compared RBS on admission, APACHE-II score, SAP II score, and SOFA score in all the three groups of patients (known diabetics, newly detected diabetes, and stress hyperglycemia) with respect to their outcomes (discharge or death) [[Table 2]]. We found statistically significant difference in discharge and death in APACHE-II (P = 0.010), SOFA (P = 0.002), SAPS II (P = 0.009) scores in total 200 admission hyperglycemia patients in the study. In patients who were known case of diabetes, there was no statistically significant difference in discharge and death in APACHE-II (P = 0.11), SOFA (P = 0.27), and SAPS II scores (P = 0.28). Among patients with newly detected diabetes, we found statistically significant difference in discharge and death in APACHE-II (P = 0.014), SOFA (P = 0.0001), and SAPS II (P = 0.009). Further, there was statistically significant difference in discharge and death in APACHE-II (P = 0.010), SOFA (P = 0.002), and SAPS II scores (P = 0.009) in patients with stress hyperglycemia.

Table 2: Comparison between RBS (on admission) and prognostic scores between discharged and patients who died in all 3 groups

A multivariate logistic regression [[Table 3]] to identify the predictors of mortality revealed that days in hospital (OR = 0.33, CI = 0.18–0.61, P = 0.000) and days in ICU (OR = 3.54, CI = 1.85-6.77, P = 0.000) were statistically significant. With 1 day of increase in stay in the ICU, the odds of death increased by about 3.5 times. The RBS on admission or HbA1c did not predict mortality.

Table 3: Multivariate logistic regression

Discussion

In this cohort of patents admitted in a rural teaching hospital, we examined the prevalence of admission hyperglycemia and the relationship between admission hyperglycemia and clinical outcomes, such as increased morbidity and in-hospital mortality.

We established the prevalence of admission hyperglycemia to be 11.99% from our study. About 1.51% presented with stress hyperglycemia at admission. Various studies have reported a prevalence of admission hyperglycemia ranging from 10% to 40%. Freire et al. who carried out observational cohort study of admission hyperglycemia and other risk factor as the predictors of hospital mortality in the MICU population found 10.2% prevalence of admission hyperglycemia.[[11]] Sung et al. who carried out prospective cohort study admission hyperglycemia is predictive of outcome in critically ill trauma patients found 25% prevalence of admission hyperglycemia.[[12]] Whitcomb et al. who carried out retrospective cohort study on the impact of admission hyperglycemia on hospital mortality in various ICU populations found 27.4% prevalence of admission hyperglycemia.[[2]] Williams et al. who carried out study effect of admission hyperglycemia on mortality and costs in acute ischemic stroke found 40% prevalence of admission hyperglycemia.[[13]]

The HbA1c in newly detected diabetics was significantly higher as compared to known diabetic patients (8.79 ± 2.11 vs. 7.18 ± 1.64). The relationship between glucose levels and mortality among ICU patients has been subject of previous investigation mostly in studies with a subgroup of diagnosis who are admitted to the ICU (e.g., myocardial infarction, stroke) or largely in smaller studies.[[14]] In the literature, HbA1c is an independent predictive factor for hospital mortality of diabetic patients with sepsis and without diabetes undergoing vascular surgery.[[15]] We offer a data set that included a substantial number of patients from MICU representing subgroups of hyperglycemia which has repeatedly been shown to be a risk factor as well as in those in which association is not clear. Our data in combination with previously published scientific evidence strongly suggest that the association between admission hyperglycemia and mortality may not be generalizable to all critically ill patients but only a subgroup with vascular disease.

In our study, among patients with admission hyperglycemia, there was statistically significant difference in APACHE-II, SOFA, and SAPS II scores between the patients who recovered and those who died (P ≤ 0.05). Similarly, there was statistically significant difference in patients with admission hyperglycemia in these scores and outcome between newly diagnosed and nondiabetic cases (P ≤ 0.05). However, in known case of diabetes, it was not statistically significantly associated (P ≥ 0.05). It is noted in the literature that even a modest degree of hyperglycemia occurring after critical care unit admission was associated with a substantial increase in hospital mortality in patients.[[16]],[[17]] Previously undiagnosed and untreated diabetes leads to a greater risk of vascular damage. Hyperglycemia might not cause obvious symptoms or signs for years, thus leading to delays in treatment. However, cardiovascular risk is known to increase even in the early stages of impaired glucose tolerance and might develop years before a confirmed diagnosis of diabetes. In the study of Whitcomb et al., the association between hyperglycemia on ICU admission and in-hospital mortality was not uniform in the study population; hyperglycemia was an independent risk factor only in patients without diabetic history in the cardiac, cardiothoracic, and neurosurgical ICUs.[[2]] The concept of “diabetes paradox” which suggests that in patients admitted to ICUs, the presence of diabetes as a comorbidity is not independently associated with increased risk of mortality.[[18]]

Although admission hyperglycemia has been associated with increased in-hospital mortality, its association with severity of illness is not widely studied. We had included the prognostic scores such as APACHE-II, SAP II, and SOFA scores in our study. We found that these prognostic scores were significantly higher in the patients in the newly detected diabetics and stress hyperglycemia patients who died. There was no significant difference in the diabetic patients. Whitcomb et al.[[2]] studied APACHE-III score, and among nondiabetics, unadjusted ORs for mortality comparing hyperglycemics to normoglycemics were significantly elevated in the cardiac, cardiothoracic, and nonsurgical ICUs.

There are some studies showing that admission hyperglycemia is not a predictor of adverse outcome. According to Freire et al., conventional factor of disease severity but not the highest glucose value during the first 24 of the ICU admission predicts hospital mortality.[[11]] Ligtenberg et al. in their retrospective study elaborated that the mean glucose level was not an independent risk factor for mortality in mixed ICU patients.[[17]] Rezvanfar et al. observed that whereas time-averaged hyperglycemia is a useful assessment for glucose control in critically ill patients, it has no priority to admission glucose and mean fasting glucose for outcome prediction.[[19]] In diabetic patients admission hyperglycaemia more closely related to underlying state of diabetic control and cannot be specifically linked to cytokines release, and hence diabetic patients are protected from acute glucose toxicity.[[20]] Based on these studies, admission hyperglycemia is associated with worse outcomes in patients without diabetes; however, this finding cannot be extended to individuals with diabetes.

Better glycemic control improves immune system and lowers the predisposition to and severity of infection, morbidity, and mortality. An intensivist should pay attention to blood sugar level during the ICU stay. The mean blood sugar levels during hospitalization persist significantly associated with mortality in nondiabetic patients more than in diabetic patients. However, when we consider total patients both diabetic and nondiabetic, there also increases mortality due to admission blood sugar. These findings in our study give direction for future studies to aid in the management of patients admitted in the ICU with hyperglycemia. The admission hyperglycaemia was found to be as interdependently associated with poor clinical outcome. It is a matter of future study whether strict control of blood sugar during hospitalization would improve the outcomes of hyperglycemic patients admitted in the ICU. There are some recent studies showed that strict blood sugar control level was found to be associated with higher incidence of hypoglycemia as well as increased mortality.[[21]]

Our study has many inherent methodology strengths, which provides credibility to the study. Our study is one of the few studies, which has included all the subgroup diagnosis of critically ill patients and adjusted for severity of illness. All consecutive patients presented in the MICU were included in this study, eliminating selection bias. The persons assessing clinical outcome and those estimating admission hyperglycemia levels were different. This study was conducted in a tertiary care center with rural background. Only few studies were conducted in such rural setup. There are a few limitations to our study. Our sample of patients may not represent all the critically ill patients with admission hyperglycemia as in this study we enrolled patients admitted only in the MICU. Critically ill patients admitted in the surgical, pediatrics, orthopedic, and maternal ICUs were not evaluated. Many studies in the literature have taken blood sugars >140 mg/dL as increased blood sugars and >200 mg/dL as severely raised blood sugars. In our study, we only considered patients with >200 mg/dL and hence would have missed out on the spectrum of mild-to-moderate elevated blood sugars and underestimated the prevalence of admission hyperglycemia and stress hyperglycemia. Ours being a cross-sectional study, we did not follow-up the patients. Like all observational studies, we cannot rule out the possibility that unmeasured confounders might be predictive of the prevalence of admission hyperglycemia and its correlation with prognostics factors, outcome–recovery, and disease specificity.

Conclusion

Our study concluded that the patients with newly detected diabetes and tress hyperglycemia had more severe illness as compared to the known diabetics.   The odds of death increased by 3.5 times with 1-day increase in the ICU stay. These findings are significant in light of all subgroups of critically ill patients being evaluated in our study which suggests that more interventions and tighter control of blood glucose may be needed in patients without diabetes.

Authors' contributions

All authors conributed to conceiving, conducting and reporting of the study. They all reviewed and approved the final version of the article.

Compliance with ethical principles

Ethical approval was granted by the ethics committee of Mahatma Ghandi Institute of Medical Sciences and all participants provided informed consent.

Conflict of Interest

There are no conflicts of interest.

Financial support and sponsorship

Nil.

• References

• 1 van Vught LA, Wiewel MA, Hoogendijk AJ, Frencken JF, Scicluna BP, Klein Klouwenberg PM, et al. The host response in patients with sepsis developing intensive care unit-acquired secondary infections. Am J Respir Crit Care Med 2017;196:458-70.
• 2 Whitcomb BW, Pradhan EK, Pittas AG, Roghmann MC, Perencevich EN. Impact of admission hyperglycemia on hospital mortality in various intensive care unit populations. Crit Care Med 2005;33:2772-7.
• 3 Umpierrez GE, Isaacs SD, Bazargan N, You X, Thaler LM, Kitabchi AE. Hyperglycemia: An independent marker of in-hospital mortality in patients with undiagnosed diabetes. J Clin Endocrinol Metab 2002;87:978-82.
• 4 Vanhorebeek I, Langouche L, van den Berghe G. Intensive insulin therapy in the intensive care unit: Update on clinical impact and mechanisms of action. Endocr Pract 2006;12 Suppl 3:14-22.
• 5 Leite SA, Locatelli SB, Niece SP, Oliveira AR, Tockus D, Tosin T. Impact of hyperglycemia on morbidity and mortality, length of hospitalization and rates of re-hospitalization in a general hospital setting in Brazil. Diabetol Metab Syndr 2010;2:49.
• 6 Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: A severity of disease classification system. Crit Care Med 1985;13:818-29.
• 7 Le Gall JR, Lemeshow S, Saulnier F. A new simplified acute physiology score (SAPS II) based on a European/North American multicenter study. JAMA 1993;270:2957-63.
• 8 Vincent JL, Moreno R, Takala J, Willatts S, de Mendonça A, Bruining H, et al. The SOFA (Sepsis-Related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med 1996;22:707-10.
• 9 Pi-Sunyer FX, Becker DM, Bouchard C, Carleton R, Colditz G, Dietz W, et al. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: Executive summary. Expert panel on the identification, evaluation, and treatment of overweight in adults. Am J Clin Nutr 1998;68:899-917.
• 10 Chamberlain JJ, Rhinehart AS, Shaefer CF Jr., Neuman A. Diagnosis and management of diabetes: Synopsis of the 2016 American Diabetes Association Standards of Medical Care in Diabetes. Ann Intern Med 2016;164:542-52.
• 11 Freire AX, Bridges L, Umpierrez GE, Kuhl D, Kitabchi AE. Admission hyperglycemia and other risk factors as predictors of hospital mortality in a medical ICU population. Chest 2005;128:3109-16.
• 12 Sung J, Bochicchio GV, Joshi M, Bochicchio K, Tracy K, Scalea TM. Admission hyperglycemia is predictive of outcome in critically ill trauma patients. J Trauma 2005;59:80-3.
• 13 Williams LS, Rotich J, Qi R, Fineberg N, Espay A, Bruno A, et al. Effects of admission hyperglycemia on mortality and costs in acute ischemic stroke. Neurology 2002;59:67-71.
• 14 O'Sullivan CJ, Hynes N, Mahendran B, Andrews EJ, Avalos G, Tawfik S, et al. Haemoglobin A1c (HbA1C) in non-diabetic and diabetic vascular patients. Is HbA1C an independent risk factor and predictor of adverse outcome? Eur J Vasc Endovasc Surg 2006;32:188-97.
• 15 Gornik I, Gornik O, Gasparović V. HbA1c is outcome predictor in diabetic patients with sepsis. Diabetes Res Clin Pract 2007;77:120-5.
• 16 Krinsley JS. Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients. Mayo Clin Proc 2003;78:1471-8.
• 17 Ligtenberg JJ, Meijering S, Stienstra Y, van der Horst IC, Vogelzang M, Nijsten MW, et al. Mean glucose level is not an independent risk factor for mortality in mixed ICU patients. Intensive Care Med 2006;32:435-8.
• 18 Krinsley JS, Fisher M. The diabetes paradox: Diabetes is not independently associated with mortality in critically ill patients. Hosp Pract (1995) 2012;40:31-5.
• 19 Rezvanfar MR, Dalvandy M, Emami AR, Rafiee M, Eshratee B. Hyperglycemia and mortality in critically ill patients. Pak J Med Sci 2009;25:232-7.
• 20 Vanhorebeek I, Gunst J, Derde S, Derese I, Boussemaere M, Güiza F, et al. Insufficient activation of autophagy allows cellular damage to accumulate in critically ill patients. J Clin Endocrinol Metab 2011;96:E633-45.
• 21 NICE-SUGAR Study Investigators; Finfer S, Chittock DR, Su SY, Blair D, Foster D, et al. Intensive versus conventional glucose control in critically ill patients. N Engl J Med 2009;360:1283-97.

Publikationsverlauf

Eingereicht: 20. Mai 2020

Angenommen: 26. Juli 2020

Artikel online veröffentlicht:
06. Juli 2022