Hypoglycemia is associated with intensive care unit mortality

Accuracy of a Continuous Glucose Monitor in the Intensive Care Unit: A Proposed Accuracy Standard and Calibration Protocol for Inpatient Use

Background and Aims: Guidelines now recommend inpatient continuous glucose monitor (CGM) use with confirmatory blood glucose measurements. However, the Food and Drug Administration has not yet officially approved CGM for inpatient use in large part because its accuracy has not been established in this setting. We tested the accuracy of the Dexcom G6 (G6) in 28 adults on an insulin infusion in a medical-surgical intensive care unit with 1064 matched CGM and arterial point-of-care pairs. Methods: The participants were on average 57.29 (SD 2.39) years, of whom 13 had a prior diagnosis of diabetes and 14 were admitted for a surgical diagnosis. The first 19 participants received the G6 without calibration and had a mean absolute relative difference (MARD) of 13.19% (IQR 5.11, 19.03) across 659 matched pairs, which just meets the critical care expert recommendation of MARD <14%. We then aimed to improve accuracy for the subsequent 9 participants using a calibration protocol. Results: The MARD for calibrated participants was 9.65% (3.03, 13.33), significantly lower than for uncalibrated participants (P < 0.001). Calibration also demonstrated excellent safety with 100% of values within the Clarke Error Grid zones A and B compared with 99.07% without calibration. Our protocol achieved the lowest MARD and safest CEG profile in the critical care setting and well exceeds the critical care expert recommendations. Our large sample of heterogenous critically ill patients also reached comparable accuracy to the MARD of 9% for G6 in outpatients. We believe our calibration protocol will allow G6 to be used with sufficient accuracy in inpatients.

Acute-to-chronic glycemic ratio as an outcome predictor in ischemic stroke in patients with and without diabetes mellitus

OBJECTIVE

Elevated plasma glucose levels are common in patients suffering acute ischemic stroke (AIS), and acute hyperglycemia has been defined as an independent determinant of adverse outcomes. The impact of acute-to-chronic glycemic ratio (ACR) has been analyzed in other diseases, but its impact on AIS prognosis remains unclear. The main aim of this study was to assess whether the ACR was associated with a 3-month poor prognosis in patients with AIS.

RESEARCH, DESIGN AND METHODS

Retrospective analysis of patients admitted for AIS in Hospital del Mar, Barcelona. To estimate the chronic glucose levels (CGL) we used the formula eCGL= [28.7xHbA1c (%)]-46.7. The ACR (glycemic at admission / eCGL) was calculated for all subjects. Tertile 1 was defined as: 0.28-0.92, tertile 2: 0.92-1.13 and tertile 3: > 1.13. Poor prognosis at 3 months after stroke was defined as mRS score 3-6.

RESULTS

2.774 subjects with AIS diagnosis were included. Age, presence of diabetes, previous disability (mRS), initial severity (NIHSS) and revascularization therapy were associated with poor prognosis (p values < 0.05). For each 0.1 increase in ACR, there was a 7% increase in the risk of presenting a poor outcome. The 3rd ACR tertile was independently associated with a poor prognosis and mortality. In the ROC curves, adding the ACR variable to the classical clinical model did not increase the prediction of AIS prognosis (0.786 vs. 0.781).

CONCLUSIONS

ACR was positively associated with a poor prognosis and mortality at 3-months follow-up after AIS. Subjects included in the 3rd ACR tertile presented a higher risk of poor prognosis and mortality. Baseline glucose or ACR did not add predictive value in comparison to only using classical clinical variables.

Relationship between time-weighted average glucose and mortality in critically ill patients: a retrospective analysis of the MIMIC-IV database

Blood glucose management in intensive care units (ICU) remains a controversial topic. We assessed the association between time-weighted average glucose (TWAG) levels and ICU mortality in critically ill patients in a real-world study. This retrospective study included critically ill patients from the Medical Information Mart for Intensive Care IV database. Glycemic distance is the difference between TWAG in the ICU and preadmission usual glycemia assessed with glycated hemoglobin at ICU admission. The TWAG and glycemic distance were divided into 4 groups and 3 groups, and their associations with ICU mortality risk were evaluated using multivariate logistic regression. Restricted cubic splines were used to explore the non-linear relationship. A total of 4737 adult patients were included. After adjusting for covariates, compared with TWAG ≤ 110 mg/dL, the odds ratios (ORs) of the TWAG > 110 mg/dL groups were 1.62 (95% CI 0.97-2.84, p = 0.075), 3.41 (95% CI 1.97-6.15, p < 0.05), and 6.62 (95% CI 3.6-12.6, p < 0.05). Compared with glycemic distance at - 15.1-20.1 mg/dL, the ORs of lower or higher groups were 0.78 (95% CI 0.50-1.21, p = 0.3) and 2.84 (95% CI 2.12-3.82, p < 0.05). The effect of hyperglycemia on ICU mortality was more pronounced in non-diabetic and non-septic patients. TWAG showed a U-shaped relationship with ICU mortality risk, and the mortality risk was minimal at 111 mg/dL. Maintaining glycemic distance ≤ 20.1 mg/dL may be beneficial. In different subgroups, the impact of hyperglycemia varied.

Malglycemia in the critical care setting. Part II: Relative and absolute hypoglycemia

INTRODUCTION

The relationship between critical care mortality and hypoglycemia, both relative (>30% below average preadmission glycemia) and absolute (blood glucose (BG) <70 mg/dL (<10 mmol/L)) requires further definition.

METHODS

We assessed the risk-adjusted relationship between hospital mortality with relative hypoglycemia using the Glycemic Ratio (GR), and with absolute hypoglycemia using BG in a retrospective cohort investigation (n = 4790).

RESULTS

Relative hypoglycemia excursions below GR 0.7 with a of 24-h non-exposure period between excursions in those with HbA1c ≥ 8% were independently associated with mortality (n = 373, OR 2.49, 95% CI 1.54-4.04, p = 0.0002) but not those with HbA1c < 8% (n = 4417, OR 0.98 95% CI 0.89-1.08, p = 0.70). Hours below GR 0.7 (1.0037, 0.9995-1.0080, 0.0846) or minimum GR (0.0896, 0.0030-2.6600, 0.1632) were not independently associated with outcome. Absolute hypoglycemia occurred across the HbA1c spectrum in a U-shaped pattern. There was no difference in mortality associated with exposure to BG < 70 mg/dL for HbA1c ≥ 6.5% vs <6.5% (29.7% vs 24.3%, p = 0.77). Hours below 70 mg/dL demonstrated strongest association with outcome, while minimum BG, and excursions below 70 mg/dL were also independently associated.

CONCLUSIONS

Relative hypoglycemia represented by excursions below GR 0.7 in those with HbA1c ≥ 8% occurred commonly and was independently associated with mortality. Absolute hypoglycemia had similar association with mortality regardless of HbA1c.

Glycemic variability and mortality in oncologic intensive care units

OBJECTIVE

This study aimed to investigate the association between glycemic variability and mortality in patients admitted to oncologic intensive care units.

METHODS

A retrospective cohort study was conducted using a convenience sample of 30 medical records of patients over 18 years of age of both sexes. Glycemic variability was measured using the standard deviation and general amplitude. Statistical analysis was performed using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The significance level (α) was set at 5% with a confidence interval (CI) of 95%.

RESULTS

The study included 14 male patients (46.67%) with a mean age of 60±15 years. A total of 1503 blood glucose samples were collected. The AUC analysis for the standard deviation did not show a statistically significant result (p=.966; 95% CI=[0.283, 0.726]). In contrast, the general amplitude had a statistically significant association with mortality (p=.049; 95% CI=[0.514, 0.916]).

CONCLUSIONS

This study found that glycemic variability measured by the general amplitude was significantly associated with patient mortality in oncologic intensive care units. These findings suggest that monitoring glycemic variability may be an important factor in the management of critically ill patients in oncologic intensive care units.

Prognostic Value of Serum Glucose Level in Critically Ill Septic Patients on Admission to Pediatric Intensive Care Unit

Background

Sepsis is one of the major causes of admission to the pediatric intensive care unit (PICU), as well as a primary cause of poor outcomes. Glycemic variation may occur because of sepsis resulting in either hypoglycemia or hyperglycemia. Measuring the random blood glucose (RBG) level of patients presenting with sepsis in PICU is an easy way to assess their prognosis.

Objectives

A prospective study was done from February 2023 to June 2023 to evaluate the relation between the outcome of pediatric septic patients and blood glucose level upon PICU admission.

Patients and methods

One hundred three children diagnosed with sepsis underwent clinical assessment upon admission to the PICU and initial labs including blood glucose levels were done. Pediatric Sequential Organ Failure Assessment (pSOFA) was calculated for every patient. The outcome of sepsis including length of stay, review of body systems, and mortality was documented.

Results

Hypoglycemic patients had the highest percentage of non-survivors (20.4%). They had a higher pSOFA score with a median of 11 (interquartile range-IQR 7-15), shorter PICU stay with a median of 2 (IQR 1-6) days, lower RBG with a median of 95 (45-120), a higher percentage of ventilation (55.1%), and a higher percentage of inotropic support (87.8%) with statistical significance with p-value (< 0.001, < 0.001, 0.001, < 0.001, 0.002), respectively.

Conclusion

Critically ill patients with abnormal random blood sugar (RBS) had a higher possibility of non-survival particularly those with hypoglycemia. Accordingly, RBS measurement is a rapid and cheap method that could be used in any emergency and as an early indicator to detect outcome.

How to cite this article

Mohamed AO, Abd El-Megied MA, Hosni YA. Prognostic Value of Serum Glucose Level in Critically Ill Septic Patients on Admission to Pediatric Intensive Care Unit. Indian J Crit Care Med 2023;27(10):754-758.

Association of the time in targeted blood glucose range of 3.9-10 mmol/L with the mortality of critically ill patients with or without diabetes

Purpose

The relationship between the TIR and mortality may be influenced by the presence of diabetes and other glycemic indicators. The purpose of this study was to investigate the relationship between TIR and in-hospital mortality in diabetic and non-diabetic patients in ICU.

Methods

A total of 998 patients with severe diseases in the ICU were selected for this retrospective analysis. The TIR is defined as the percentage of time spent in the target blood glucose range of 3.9-10.0 mmol/L within 24 h. The relationship between TIR and in-hospital mortality in diabetic and non-diabetic patients was analyzed. The effect of glycemic variability was also analyzed.

Results

The binary logistic regression model showed that there was a significant association between the TIR and the in-hospital death of severely ill non-diabetic patients. Furthermore, TIR≥70% was significantly associated with in-hospital death (OR = 0.581, P = 0.003). The study found that the coefficient of variation (CV) was significantly associated with the mortality of severely ill diabetic patients (OR = 1.042, P = 0.027).

Conclusions

Both diabetic and non-diabetic critically ill patients should control blood glucose fluctuations and maintain blood glucose levels within the target range, it may be beneficial in reducing mortality.

Type 1 and other types of diabetes mellitus in the perioperative period. What the anaesthetist should know

Diabetes mellitus is often treated as a uniform disease in the perioperative period. Type 2 diabetes is most commonly encountered, and only a minority of surgical patients have been diagnosed with another type of diabetes. Patients with a specific type of diabetes can be particularly prone to perioperative glycaemic dysregulation. In addition, certain type-related features and pitfalls should be taken into account in the operating theatre. In this narrative review, we discuss characteristics of types of diabetes other than type 2 diabetes relevant to the anaesthetist, based on available literature and data from our clinic.

Association of body mass index and hypoglycemia with mortality rates among sepsis patients: A retrospective sub-analysis of the FORECAST study

Aim

Hypoglycemia at admission is associated with high mortality in sepsis patients. However, the influence of body mass index (BMI) on this association remains unknown. Therefore, this study assesses the association of hypoglycemia at admission with mortality in patients with sepsis according to BMI.

Methods

This was a secondary analysis of a multicenter, prospective cohort study of 59 intensive care units in Japan. We included 1184 patients (age ≥16 years) with severe sepsis and excluded those with missing data on glucose level, BMI, or survival at discharge. The initial blood glucose level of <70 mg/dL was defined as hypoglycemia. Patients were assigned to the hypoglycemia or non-hypoglycemia group as per BMI category (<18.5 [low], 18.5-24.9 [normal], and ≥25 [high] kg/m²). The main outcome was in-hospital mortality. Multivariate logistic regression models were used to evaluate BMI category-by-hypoglycemia interactions.

Results

Overall, 1103 patients, including 65 with hypoglycemia, were analyzed. In the normal BMI group, patients with hypoglycemia had a higher in-hospital mortality rate (18/38, 47.4%) than those without (119/584, 20.4%). There was a significant interaction between normal BMI and hypoglycemia affecting in-hospital mortality; however, this effect was not observed for other BMI categories (odds ratio, 2.32; 95% confidence interval, 1.05-5.07; p-value for interaction = 0.0476).

Conclusion

The relationship between patients with sepsis and hypoglycemia on admission may differ according to BMI. Hypoglycemia on admission may be associated with high mortality in patients with normal BMI, but not in those with low or high BMI.

Software Packages and Tools for the Analysis of Continuous Glucose Monitoring Data

The advancement of technology in the field of glycemic control has led to the widespread use of continuous glucose monitoring (CGM), which can be nowadays obtained from wearable devices equipped with a minimally invasive sensor, that is, transcutaneous needle type or implantable, and a transmitter that sends information to a receiver or smart device for data storage and display. This work aims to review the currently available software packages and tools for the analysis of CGM data. Based on the purposes of this work, 12 software packages have been identified from the literature, published until December 2021, namely: GlyCulator, EasyGV (Easy Glycemic Variability), CGM-GUIDE^© (Continuous Glucose Monitoring Graphical User Interface for Diabetes Evaluation), GVAP (Glycemic Variability Analyzer Program), Tidepool, CGManalyzer, cgmanalysis, GLU, CGMStatsAnalyser, iglu, rGV, and cgmquantify. Comparison of available software packages and tools has been done in terms of main characteristics (i.e., publication year, presence of a graphical user interface, availability, open-source code, number of citations, programming language, supported devices, supported data format and organization of the data structure, documentation, presence of a toy example, video tutorial, data upload and download, measurement-units conversion), preprocessing procedures, data display options, and computed metrics; also, each of the computed metrics has been analyzed in terms of its adherence to the American Diabetes Association (ADA) 2017 international consensus on CGM data analysis and the ADA 2019 international consensus on time in range. Eventually, the agreement between metrics computed by different software and tools has been investigated. Based on such comparison, usability and complexity of data management, as well as the possibility to perform customized or patients-group analyses, have been discussed by highlighting limitations and strengths, also in relation to possible different user categories (i.e., patients, clinicians, researchers). The information provided could be useful to researchers interested in working in the diabetic research field as to clinicians and endocrinologists who need tools capable of handling CGM data effectively.

Outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study

BACKGROUND

Medical emergency teams (METs) have been implemented to reduce hospital mortality by the early recognition and treatment of potentially life-threatening conditions. The objective of this study was to establish a clinically useful association between clinical variables and mortality risk, among patients assessed by the MET, and further to design an easy-to-use risk score for the prediction of death within 30 days.

METHODS

Observational retrospective register study in a tertiary university hospital in Sweden, comprising 2,601 patients, assessed by the MET from 2010 to 2015. Patient registry data at the time of MET assessment was analysed from an epidemiological perspective, using univariable and multivariable analyses with death within 30 days as the outcome variable. Predictors of outcome were defined from age, gender, type of ward for admittance, previous medical history, acute medical condition, vital parameters and laboratory biomarkers. Identified factors independently associated with mortality were then used to develop a prognostic risk score for mortality.

RESULTS

The overall 30-day mortality was high (29.0%). We identified thirteen factors independently associated with 30-day mortality concerning; age, type of ward for admittance, vital parameters, laboratory biomarkers, previous medical history and acute medical condition. A MET risk score for mortality based on the impact of these individual thirteen factors in the model yielded a median (range) AUC of 0.780 (0.774-0.785) with good calibration. When corrected for optimism by internal validation, the score yielded a median (range) AUC of 0.768 (0.762-0.773).

CONCLUSIONS

Among clinical variables available at the time of MET assessment, thirteen factors were found to be independently associated with 30-day mortality. By applying a simple risk scoring system based on these individual factors, patients at higher risk of dying within 30 days after the MET assessment may be identified and treated earlier in the process.

Association between dysglycemia and the Charlson Comorbidity Index among hospitalized patients with diabetes

AIM

Inpatient dysglycemia has been linked to short-term mortality, but longer-term mortality data are lacking. Our aim was to evaluate the association between inpatient dysglycemia and one-year mortality risk.

METHODS

Retrospective chart review of adults with diabetes hospitalized between 2015 and 2019. The Charlson Comorbidity Index (CCI) was used to estimate 1-year mortality risk, stratified into low (CCI ≤ 5) and high risk (CCI ≥6). Simple and multivariable logistic regression was used to evaluate the association between dysglycemic measures and high mortality risk.

RESULTS

Among 22,639 unique admissions, BG ≥ 180, ≥300, ≤70, <54 and <40 mg/dL were associated with adjusted odds of 1.43 (95 % CI, 1.33, 1.54), 1.58 (95 % CI, 1.48, 1.68), 2.16 (95 % CI, 2.01, 2.32), 2.58 (95 % CI, 2.32, 2.86), and 2.56 (95 % CI, 2.19, 2.99) for high mortality risk, respectively. Older age and Black race were positively associated with hyperglycemia and hypoglycemia. Myocardial infarction, congestive heart failure (CHF), and moderate to severe liver disease were most strongly associated with hyperglycemia, while renal disease, CHF, peripheral vascular disease, and peptic ulcer disease were most strongly associated with hypoglycemia.

CONCLUSIONS

Inpatient hypoglycemia and hyperglycemia were both positively associated with higher one-year mortality risk, with stronger magnitude of association observed for hypoglycemia. The association appears to be mediated mainly by presence of diabetes-related complications.

Targeting Predialysis Glucose up to 180 mg/dl Reduces Glycemic Variability in End Stage Diabetic Nephropathy

Context

Glycemic variability plays a major role in the development as well as the progression of cardiovascular disease in diabetes.

Aims

We compared the mean plasma glucose and glycemic variability (GV) parameters on and off hemodialysis (HD) in patients with End-Stage Diabetic Nephropathy (ESDN) and End-Stage Renal Disease (ESRD).

Settings and Design

Cross-sectional study.

Methods and Material

We included 23 ESDN and 6 ESRD patients who underwent continuous glucose monitoring (CGM) (iPro2) for 6 days and a glucose-free dialysate for 4 hours thrice weekly. EasyGV software was used to calculate the variability parameters {mean glucose, Time in range (TIR), Time above and below range (TAR/TBR), CV (Coefficient of Variation) and MAGE}.

Statistical Analysis Used

The quantitative data variables were expressed by using mean and SD. Unpaired t-test was used to compare the two groups. P value <0.05 was considered significant.

Results

In the ESDN group, TIR was significantly lower whereas TAR and TBR were significantly higher on HD day. MAGE (101.88 ± 40.5 v/s 89.46 ± 30.0, P < 0.007) and CV (29.41% v/s 21.67%) were higher on HD day. Subjects with pre-HD glucose values ≥180 mg/dl (Group B, n = 24) had a rapid drop with a delayed higher rise in glucose values than those with pre-HD glucose values <180 mg/dl (Group A, n = 27). Ten patients had 13 episodes of hypoglycemia. The CGM parameters were not different in the ESRD group.

Conclusions

Targeting a pre- HD glucose value <180 mg/dl could be a good strategy to prevent larger fluctuation during and post HD.

Accuracy and Stability of a Subcutaneous Flash Glucose Monitoring System in Critically Ill Patients

BACKGROUND

Flash glucose monitoring (FGM) systems can reduce glycemic variability and facilitate blood glucose management within the target range. However, in critically ill patients, only small (n < 30) studies have examined the accuracy of FGM and none have assessed the stability of FGM accuracy. We evaluated the accuracy and stability of FGM in critically ill patients.

METHOD

This was a single-center, retrospective observational study. We included a total of 116 critically ill patients who underwent FGM for glycemic control. The accuracy of FGM was assessed as follows using blood gas glucose values as a reference: (1) numerical accuracy using the mean absolute relative difference, (2) clinical accuracy using consensus error grid analysis, and (3) stability of accuracy assessing 14-day trends in consensus error grid distribution.

RESULTS

FGM sensors remained in situ for a median of 6 [4, 11] days. We compared 2014 pairs of measurements between the sensor and blood gas analysis. Glucose values from the sensor were consistently lower, with a mean absolute relative difference of 13.8% (±16.0%), than those from blood gas analysis. Consensus error grid analysis demonstrated 99.4% of the readings to be in a clinically acceptable accuracy zone. The accuracy of FGM was stable across the 14 days after device insertion.

CONCLUSIONS

FGM had acceptable reliability and accuracy to arterial blood gas analysis in critically ill patients. In addition, the accuracy of FGM persisted for at least 14 days. Our study promotes the potential usefulness of FGM for glycemic monitoring in critically ill patients.

Relative Hypoglycemia and Lower Hemoglobin A1c-Adjusted Time in Band Are Strongly Associated With Increased Mortality in Critically Ill Patients

OBJECTIVES

To determine the associations of relative hypoglycemia and hemoglobin A1c-adjusted time in blood glucose (BG) band (HA-TIB) with mortality in critically ill patients.

DESIGN

Retrospective cohort investigation.

SETTING

University-affiliated adult medical-surgical ICU.

PATIENTS

Three thousand six hundred fifty-five patients with at least four BG tests and hemoglobin A1c (HbA1c) level admitted between September 14, 2014, and November 30, 2019.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patients were stratified for HbA1c bands of <6.5%; 6.5-7.9%; greater than or equal to 8.0% with optimal affiliated glucose target ranges of 70-140, 140-180, and 180-250 mg/dL, respectively. HA-TIB, a new glycemic metric, defined the HbA1c-adjusted time in band. Relative hypoglycemia was defined as BG 70-110 mg/dL for patients with HbA1c ≥ 8.0%. Further stratification included diabetes status-no diabetes (NO-DM, n = 2,616) and preadmission treatment with or without insulin (DM-INS, n = 352; DM-No-INS, n = 687, respectively). Severity-adjusted mortality was calculated as the observed:expected mortality ratio (O:EMR), using the Acute Physiology and Chronic Health Evaluation IV prediction of mortality. Among NO-DM, mortality and O:EMR, decreased with higher TIB 70-140 mg/dL (p < 0.0001) and were lowest with TIB 90-100%. O:EMR was lower for HA-TIB greater than or equal to 50% than less than 50% and among all DM-No-INS but for DM-INS only those with HbA1 greater than or equal to 8.0%.Among all patients with hba1c greater than or equal to 8.0% And no bg less than 70 mg/dl, mortality was 18.0% For patients with relative hypoglycemia (bg, 70-110 mg/dl) (p < 0.0001) And was 0.0%, 12.9%, 13.0%, And 34.8% For patients with 0, 0.1-2.9, 3.0-11.9, And greater than or equal to 12.0 Hours of relative hypoglycemia (p < 0.0001).

CONCLUSIONS

These findings have considerable bearing on interpretation of previous trials of intensive insulin therapy in the critically ill. Moreover, they suggest that BG values in the 70-110 range may be deleterious for patients with HbA1c greater than or equal to 8.0% and that the appropriate target for BG should be individualized to HbA1c levels. These conclusions need to be tested in randomized trials.

Admission Blood Glucose Is Associated With the 30-Days Mortality in Septic Patients: A Retrospective Cohort Study

Background: Sepsis, as one of the severe diseases, is frequently observed in critically ill patients, especially concurrent with diabetes. Whether admission blood glucose is associated with the prognosis, and outcome of septic patients is still debatable.

Methods: We retrospectively reviewed and analyzed the demographic characteristics of septic patients in the Medical Information Mart for Intensive Care III (MIMIC III, version 1.4) between June 2001 and October 2012. The Chi-square and Fisher's exact tests were used for the comparison of qualitative variables among septic patients with different glucose levels and the 30-day mortality in septic patients with diabetes or not. Univariate and stepwise multivariate Cox regression analyses were used to determine the risk factors for 30-day mortality. Kaplan-Meier analysis was conducted to reveal the different 30-day survival probabilities in each subgroup.

Results: A total of 2,948 septic patients (910 cases with diabetes, 2,038 cases without diabetes) were ultimately included in the study. The 30-day mortality was 32.4% (956/2,948 cases) in the overall population without any difference among diabetic and non-diabetic septic patients (p = 1.000). Admission blood glucose levels <70 mg/dl were only observed to be significantly associated with the 30-day mortality of septic patients without diabetes (hazard ratio (HR) = 2.48, p < 0.001). After adjusting for confounders, age >65 years (HR = 1.53, p = 0.001), the Sequential Organ Failure Assessment (SOFA) score >5 (HR = 2.26, p < 0.001), lactic acid >2 mmol/L (Lac, HR = 1.35, p = 0.024), and platelet abnormality (<100 k/ul: HR = 1.49; >300 k/ul: HR = 1.36, p < 0.001) were the independent risk factors for 30-day mortality in septic patients with diabetes. In non-diabetes population, age >65 years (HR = 1.53, p < 0.001), non-White or non-Black patients (HR = 1.30, p = 0.004), SOFA score >5 (HR = 1.56, p < 0.001), blood glucose <70 mg/dl (HR = 1.91, p = 0.003), anion gap (AG) >2 mmol/L (HR = 1.60, p < 0.001), Lac (HR = 1.61, p < 0.001), urea nitrogen >21 mg/dl (HR = 1.45, p = 0.001), alanine aminotransferase (ALT, HR = 1.31, p = 0.009), total bilirubin >1.2 mg/dl (HR = 1.20, p = 0.033), and low hemoglobin (HR = 1.34, p = 0.001) were the independent risk factors for 30-day mortality.

Conclusions: Our results indicate admission blood glucose, especially in terms of <70 mg/dl, is the key signaling in predicting the worse 30-day survival probability of septic patients without diabetes, which could help clinicians to make a more suitable and precise treatment modality in dealing with septic patients.

The obesity paradox and hypoglycemia in critically ill patients

BACKGROUND

A high body mass index (BMI) has been associated with decreased mortality in critically ill patients. This association may, in part, relate to the impact of BMI on glycemia. We aimed to study the relationship between BMI, glycemia and hospital mortality.

METHODS

We included all patients with a recorded BMI from four large international clinical databases (n = 259,177). We investigated the unadjusted association of BMI with average glucose levels, mortality and hypoglycemia rate. We applied multivariate analysis to investigate the impact of BMI on hypoglycemia rate, after adjusting for glycemia-relevant treatments (insulin, dextrose, corticosteroids, enteral and parenteral nutrition) and key physiological parameters (previous blood glucose level, blood lactate, shock state, SOFA score).

RESULTS

We analyzed 5,544,366 glucose measurements. On unadjusted analysis, increasing BMI was associated with increasing glucose levels (average increase of 5 and 10 mg/dL for the 25-30, 30-35 kg/m2 BMI groups compared to normal BMI (18.5-25 kg/m2) patients). Despite greater hyperglycemia, increasing BMI was associated with lower hospital mortality (average decrease of 2% and 3.25% for the 25-30, 30-35 kg/m2 groups compared to normal BMI patients) and lower hypoglycemia rate (average decrease of 2.5% and 3.5% for the 25-30, 30-35 kg/m2 groups compared to normal BMI patients). Increasing BMI was significantly independently associated with reduced hypoglycemia rate, with odds ratio (OR) 0.72 and 0.65, respectively (95% CIs 0.67-0.77 and 0.60-0.71, both p < 0.001) when compared with normal BMI. Low BMI patients showed greater hypoglycemia rate, with OR 1.6 (CI 1.43-1.79, p < 0.001). The association of high BMI and decreased mortality did not apply to diabetic patients. Although diabetic patients had higher rates of hypoglycemia overall and higher glucose variability (p < 0.001), they also had a reduced risk of hypoglycemia with higher BMI levels (p < 0.001).

CONCLUSIONS

Increasing BMI is independently associated with decreased risk of hypoglycemia. It is also associated with increasing hyperglycemia and yet with lower mortality. Lower risk of hypoglycemia might contribute to decreased mortality and might partly explain the obesity paradox. These associations, however, were markedly modified by the presence of diabetes.

Individualised versus conventional glucose control in critically-ill patients: the CONTROLING study-a randomized clinical trial

Purpose

Hyperglycaemia is an adaptive response to stress commonly observed in critical illness. Its management remains debated in the intensive care unit (ICU). Individualising hyperglycaemia management, by targeting the patient’s pre-admission usual glycaemia, could improve outcome.

Methods

In a multicentre, randomized, double-blind, parallel-group study, critically-ill adults were considered for inclusion. Patients underwent until ICU discharge either individualised glucose control by targeting the pre-admission usual glycaemia using the glycated haemoglobin A1c level at ICU admission (IC group), or conventional glucose control by maintaining glycaemia below 180 mg/dL (CC group). A non-commercial web application of a dynamic sliding-scale insulin protocol gave to nurses all instructions for glucose control in both groups. The primary outcome was death within 90 days.

Results

Owing to a low likelihood of benefit and evidence of the possibility of harm related to hypoglycaemia, the study was stopped early. 2075 patients were randomized; 1917 received the intervention, 942 in the IC group and 975 in the CC group. Although both groups showed significant differences in terms of glycaemic control, survival probability at 90-day was not significantly different (IC group: 67.2%, 95% CI [64.2%; 70.3%]; CC group: 69.6%, 95% CI [66.7%; 72.5%]). Severe hypoglycaemia (below 40 mg/dL) occurred in 3.9% of patients in the IC group and in 2.5% of patients in the CC group (p = 0.09). A post hoc analysis showed for non-diabetic patients a higher risk of 90-day mortality in the IC group compared to the CC group (HR 1.3, 95% CI [1.05; 1.59], p = 0.018).

Conclusion

Targeting an ICU patient’s pre-admission usual glycaemia using a dynamic sliding-scale insulin protocol did not demonstrate a survival benefit compared to maintaining glycaemia below 180 mg/dL.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00134-021-06526-8.

Hypoglycemia and mortality in sepsis patients: A systematic review and meta-analysis

BACKGROUND

Hypoglycemia frequently occurs in patients with sepsis. The status of prognosis of sepsis patients varies with the cause of hypoglycemia.

OBJECTIVE

A meta-analysis was performed to obtain a reliable basis for assessing the severity of disease in sepsis patients.

METHODS

A search of electronic databases was performed. The random-effects model was employed to calculate the overall odds ratio (OR) and 95% CI.

RESULTS

Five cohort studies were included. Decreased blood glucose level was associated with an increased risk of death [OR:1.68; 95% CI (1.12-2.53)]. Incidents of mortality were analyzed based on the causative factor of hypoglycemia. Patients with spontaneous hypoglycemia showed a significantly higher mortality rate than the control subjects[OR 1.65; 95% CI (1.20-2.28); p = 0.002].

CONCLUSION

In the early stages of sepsis, the occurrence of spontaneous hypoglycemia may be associated with the severity of the disease.

Admission Blood Glucose in the Emergency Department is Associated with Increased In-Hospital Mortality in Nontraumatic Critically Ill Patients

BACKGROUND

Abnormal admission blood glucose was reported as a useful predictor of outcome in critically ill patients.

OBJECTIVES

To identify patients at higher risk, this study aimed to evaluate the relationship between admission blood glucose levels and patient mortality during the management of nontraumatic critically ill patients in the emergency department (ED).

METHODS

In this prospective, single-center observational study in a German university ED, all adult patients admitted to the resuscitation room of the ED were included between September 1, 2014 and August 31, 2015. Directly after resuscitation room admission, blood samples for admission blood glucose were taken, and adult patients were divided into groups according to predefined cut-offs between the admission blood glucose. Study endpoint was in-hospital mortality.

RESULTS

During the study period, 532 patients were admitted to the resuscitation room. The data of 523 patients (98.3%) were available for analysis. The overall in-hospital mortality was 34.2%. In comparison with an in-hospital mortality of 25.2% at an admission blood glucose of 101-136 mg/dL (n = 107), admission blood glucose of ≤ 100 mg/dL (n = 25, odds ratio [OR] 6.30, 95% confidence interval [CI] 2.44-16.23, p < 0.001), 272-361 mg/dL (n = 63, OR 2.53, 95% CI 1.31-4.90, p = 0.007), and ≥ 362 mg/dL (n = 44, OR 2.96, 95% CI 1.42-6.18, p = 0.004) were associated with a higher mortality.

CONCLUSIONS

Abnormal admission blood glucose is associated with a high in-hospital mortality. Admission blood glucose is an inexpensive and rapidly available laboratory parameter that may predict mortality and help to identify critically ill patients at risk in a general nontraumatic critically ill ED patient cohort. The breakpoint for in-hospital mortality may be an admission blood glucose ≤ 100 and ≥ 272 mg/dL.

The paradox of the glycemic gap: Does relative hypoglycemia exist in critically ill patients?

BACKGROUND & AIMS

Elevated glycemic gap, as the differences between measured glucose and hemoglobin A1c (HbA1c)-derived average glucose (ADAG) levels, is a marker of stress-induced hyperglycemia and is a predictor of mortality in critically ill patients. Whether low glycemic gaps are associated with outcomes in critically ill patients remains unclear. We investigated the association of different glycemic gaps on mortality in critically ill patients.

METHODS

Totally 935 patients admitted to intensive care units (ICUs) were enrolled retrospectively after the exclusion of patients with absolute hypoglycemia, extreme hyperglycemia, and incomplete glycemic records. Patients were divided into 3 groups according to their glycemic gaps (<-29.7, -29.7-40, ≧40 mg/dL) at the time of ICU admission. The patients were followed for 1 year or until death.

RESULTS

Patients with low glycemic gap (glycemic gap < -29.7 mg/dL), which implied relative hypoglycemia, had lower serum glucose levels, higher HbA1c levels, and greater disease severity. Compared with medium group (glycemic gap -29.7-40 mg/dL), both the low and the high glycemic gap (glycemic gap ≧40 mg/dL) groups had significantly greater 30-day (log-rank p = 0.0464) and 1-year mortality (log-rank p = 0.0016). However, only the low glycemic gap group was independently associated with greater in-hospital mortality after adjusting for comorbidities (adjusted OR 1.78, 95% CI 1.00-3.16, p = 0.048).

CONCLUSION

This study revealed the presence of a U-shaped relationship between the glycemic gap and mortality in critically ill patients. Low glycemic gaps suggested relative hypoglycemia at the time of ICU admission, and were associated independently with greater in-hospital mortality.

Heparin-based blood purification attenuates organ injury in baboons with Streptococcus pneumoniae pneumonia

Bacterial pneumonia is a major cause of morbidity and mortality worldwide despite the use of antibiotics, and novel therapies are urgently needed. Building on previous work, we aimed to 1) develop a baboon model of severe pneumococcal pneumonia and sepsis with organ dysfunction and 2) test the safety and efficacy of a novel extracorporeal blood filter to remove proinflammatory molecules and improve organ function. After a dose-finding pilot study, 12 animals were inoculated with Streptococcus pneumoniae [5 × 10⁹ colony-forming units (CFU)], given ceftriaxone at 24 h after inoculation, and randomized to extracorporeal blood purification using a filter coated with surface-immobilized heparin sulfate (n = 6) or sham treatment (n = 6) for 4 h at 30 h after inoculation. For safety analysis, four uninfected animals also underwent purification. At 48 h, necropsy was performed. Inoculated animals developed severe pneumonia and septic shock. Compared with sham-treated animals, septic animals treated with purification displayed significantly less kidney injury, metabolic acidosis, hypoglycemia, and shock (P < 0.05). Purification blocked the rise in peripheral blood S. pneumoniae DNA, attenuated bronchoalveolar lavage (BAL) CCL4, CCL2, and IL-18 levels, and reduced renal oxidative injury and classical NLRP3 inflammasome activation. Purification was safe in both uninfected and infected animals and produced no adverse effects. We demonstrate that heparin-based blood purification significantly attenuates levels of circulating S. pneumoniae DNA and BAL cytokines and is renal protective in baboons with severe pneumococcal pneumonia and septic shock. Purification was associated with less severe acute kidney injury, metabolic derangements, and shock. These results support future clinical studies in critically ill septic patients.

Time in blood glucose range 70 to 180 mg/dL and survival rate in critically ill patients: A retrospective cohort study

Background

While time in targeted blood glucose range (TIR) 70–140 mg/dL is a known factor associated with mortality in critically ill patients, it remains unclear whether TIR is associated with 28-day mortality under the glycemic control with a less tight target glucose range of 70–180 mg/dL. We aimed to examine whether TIR 70–180 mg/dL was associated with 28-day mortality.

Methods

This is a retrospective cohort study using data from a tertiary care center in Japan collected from January 2016 through October 2019. We included adult patients (aged ≥20 years) admitted to the ICU. We excluded patients 1) with diabetic ketoacidosis patients, 2) discharged within 48 hours, 3) with repeated ICU admissions. We calculated TIR 70–180 mg/dL using the measured blood glucose values (≥3 times per day). The primary outcome was 28-day mortality. We examined the association between TIR and 28-day mortality using a logistic regression and Cox proportional hazard models with a stratification by glycosylated hemoglobin (HbA1c) level of 6.5%. Additionally, we repeated the analyses using the TIR category to assess the optimal TIR. For the sensitivity analysis, we repeated the primary analysis using TIR during the first three days from ICU admission.

Results

Of 1,230 patients, the median age was 72 years, 65% were male, and 250 patients (20%) had HbA1c ≥6.5% on admission. In patients with HbA1c <6.5%, TIR <80% was associated with an increased risk of 28-day mortality, with an adjusted odds ratio (OR) of 1.88 (95%CI: 1.36–2.61). Likewise, when using 10% incremental TIR as a categorical variable, lower TIR was associated with a worse 28-day mortality compared with TIR ≥90% (e.g., adjusted OR of TIR <60%, 3.62 [95%CI 2.36–5.53]). Similar associations were found in the analyses using Cox proportional hazards model and using TIR during the first three days. By contrast, in patients with HbA1c ≥6.5%, there was no consistent association of TIR with 28-day mortality.

Conclusions

We found that lower TIR 70–180 mg/dL was associated with a higher 28-day mortality in critically ill patients with HbA1c <6.5%, whereas there was no consistent association in patients with HbA1c ≥6.5%.

The Interaction of Acute and Chronic Glycemia on the Relationship of Hyperglycemia, Hypoglycemia, and Glucose Variability to Mortality in the Critically Ill

OBJECTIVES

To determine the relationship between preadmission glycemia, reflected by hemoglobin A1c level, glucose metrics, and mortality in critically ill patients.

DESIGN

Retrospective cohort investigation.

SETTING

University affiliated adult medical-surgical ICU.

PATIENTS

The investigation included 5,567 critically ill patients with four or more blood glucose tests and hemoglobin A1c level admitted between October 11, 2011 and November 30, 2019. The target blood glucose level was 90-120 mg/dL for patients admitted before September 14, 2014 (n = 1,614) and 80-140 mg/dL or 110-160 mg/dL for patients with hemoglobin A1c less than 7% or greater than or equal to 7% (n = 3,953), respectively, subsequently.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patients were stratified by hemoglobin A1c: less than 6.5.(n = 4,406), 6.5-7.9% (n = 711), and greater than or equal to 8.0% (n = 450). Increasing hemoglobin A1c levels were associated with significant increases in mean glycemia, glucose variability, as measured by coefficient of variation, and hypoglycemia (p for trend < 0.0001, < 0.0001, and 0.0010, respectively). Among patients with hemoglobin A1c less than 6.5%, mortality increased as mean glycemia increased; however, among patients with hemoglobin A1c greater than or equal to 8.0%, the opposite relationship was observed (p for trend < 0.0001 and 0.0027, respectively). Increasing glucose variability was independently associated with increasing mortality only among patients with hemoglobin A1c less than 6.5%. Hypoglycemia was independently associated with higher mortality among patients with hemoglobin A1c less than 6.5% and 6.5-7.9% but not among those with hemoglobin A1c greater than or equal to 8.0%. Mean blood glucose 140-180 and greater than or equal to 180 mg/dL were independently associated with higher mortality among patients with hemoglobin A1c less than 6.5% (p < 0.0001 for each). Among patients with hemoglobin A1c greater than or equal to 8.0% treated in the second era, mean blood glucose greater than or equal to 180 mg/dL was independently associated with decreased risk of mortality (p = 0.0358).

CONCLUSIONS

Preadmission glycemia, reflected by hemoglobin A1c obtained at the onset of ICU admission, has a significant effect on the relationship of ICU glycemia to mortality. The different responses to increasing mean glycemia support a personalized approach to glucose control practices in the ICU.

Incidence and Impact of Dysglycemia in Patients with Sepsis Under Moderate Glycemic Control

ABSTRACT

Glycemic control strategies for sepsis have changed significantly over the last decade, but their impact on dysglycemia and its associated outcomes has been poorly understood. In addition, there is controversy regarding the detrimental effects of hyperglycemia in sepsis. To evaluate the incidence and risks of dysglycemia under current strategy, we conducted a preplanned subanalysis of the sepsis cohort in a prospective, multicenter FORECAST study. A total of 1,140 patients with severe sepsis, including 259 patients with pre-existing diabetes, were included. Median blood glucose levels were approximately 140 mg/dL at 0 h and 72 h indicating that blood glucose was moderately controlled. The rate of initial and late hyperglycemia was 27.3% and 21.7%, respectively. The rate of early hypoglycemic episodes during the initial 24 h was 13.2%. Glycemic control was accompanied by a higher percentage of initial and late hyperglycemia but not with early hypoglycemic episodes, suggesting that glycemic control was targeted at excess hyperglycemia. In nondiabetic patients, late hyperglycemia (hazard ratio, 95% confidence interval; p-value: 1.816, 1.116-2.955, 0.016) and early hypoglycemic episodes (1.936, 1.180-3.175, 0.009) were positively associated with in-hospital mortality. Further subgroup analysis suggested that late hyperglycemia and early hypoglycemic episodes independently, and probably synergistically, affect the outcomes. In diabetic patients, however, these correlations were not observed. In conclusion, a significantly high incidence of dysglycemia was observed in our sepsis cohort under moderate glycemic control. Late hyperglycemia in addition to early hypoglycemia was associated with poor outcomes at least in nondiabetic patients. More sophisticated approaches are necessary to reduce the incidence of these serious complications.

Glycemic indices predict outcomes after aneurysmal subarachnoid hemorrhage: a retrospective single center comparative analysis

Although hyperglycemia is associated with worse outcomes after aneurysmal subarachnoid hemorrhage (aSAH), there is no consensus on the optimal glucose control metric, acceptable in-hospital glucose ranges, or suitable insulin regimens in this population. In this single-center retrospective cohort study of aSAH patients, admission glucose, and hospital glucose mean (MHG), minimum (MinG), maximum (MaxG), and variability were compared. Primary endpoints (mortality, complications, and vasospasm) were assessed using multivariate logistic regressions. Of the 217 patients included, complications occurred in 83 (38.2%), 124 (57.1%) had vasospasm, and 41 (18.9%) died. MHG was independently associated with (p < 0.001) mortality, MaxG (p = 0.017) with complications, and lower MinG (p = 0.015) with vasospasm. Patients with MHG ≥ 140 mg/dL had 10 × increased odds of death [odds ratio (OR) = 10.3; 95% CI 4.6–21.5; p < 0.0001] while those with MinG ≤ 90 mg/dL had nearly 2× increased odds of vasospasm (OR = 1.8; 95% CI 1.01–3.21; p = 0.0422). While inpatient insulin was associated with increased complications and provided no mortality benefit, among those with MHG ≥ 140 mg/dL insulin therapy resulted in lower mortality (OR = 0.3; 95% CI 0.1–0.9; p = 0.0358), but no increased complication risk. While elevated MHG and MaxG are highly associated with poorer outcomes after aSAH, lower MinG is associated with increased vasospasm risk. Future trials should consider initiating insulin therapy based on MHG rather than other hyperglycemia measures.

Vildagliptin vs. insulin treatment alone in diabetic acute coronary syndrome patients

BACKGROUND

Vildagliptin, an oral antidiabetic of the dipeptidyl peptidase-4 (DPP-4) inhibitor drugs, exhibits an overall low risk of hypoglycemia with less frequent hypoglycemic events in type 2 diabetes mellitus (T2DM) patients than other antidiabetic drugs. We hypothesized that among hospitalized acute coronary syndrome (ACS) patients, the addition of vildagliptin to subcutaneous insulin therapy would reduce the risk of hypoglycemic events.

METHODS

One hundred ACS T2DM adult patients naive to DPP-4 inhibitors were enrolled during admission to the ICCU. Patients were divided into two randomized controlled groups: a subcutaneous rapid-acting insulin-only therapy group and an oral vildagliptin plus subcutaneous insulin group. The trial was open label with no placebo arm. Mean glucose values, insulin values given for correction per hospitalization, and the number of hypoglycemic events (glucose < 70 mg/dL) were documented.

RESULTS

Eight hypoglycemia events occurred in the insulin-only group and none in the insulin plus DPP-4 inhibitor group (P < 0.001). Patients with acute myocardial infarction experienced a higher number of hypoglycemic events compared with unstable angina diagnosed patients. No significant differences were found regarding glucose level (P = 0.462) and administered insulin units (P = 0.639).

CONCLUSIONS

In T2DM patients, the addition of DPP-4 inhibitors to routine subcutaneous insulin therapy may significantly reduce hypoglycemic events while maintaining acceptable recommended ranges of glucose. Further studies on a larger scale are required to verify these results and to support that DPP-4 inhibitors added to today's standard insulin-only treatment in hospitalized diabetic ACS patients may improve overall glycemic control and provide a potential treatment option in this challenging clinical setting.

Electronic Glycemic Management System and Endocrinology Service Improve Value in Cardiac Surgery

BACKGROUND

Postoperative glycemic control improves cardiac surgery outcomes but insulin protocols are limited by complexity and inflexibility. We sought to evaluate the effect of implementing an electronic glycemic management system (eGMS) in conjunction with a cardiac surgery endocrinology consult service on glycemic control and outcomes after cardiac surgery.

METHODS

All patients with a calculated preoperative risk of mortality who underwent cardiac surgery before and after implementation of an eGMS and an endocrinology consult service were identified. Glycemic control and surgical outcomes were compared using univariate analysis, and multivariate regression was used to model the risk-adjusted effects of the interventions on glycemic control, surgical outcomes, and resource utilization. The health care-related value added by the interventions was calculated by dividing risk-adjusted outcomes by total hospital costs.

RESULTS

A total of 2612 patients were identified, with 1263 patients in the preimplementation cohort and 1349 in the postimplementation cohort. Multivariate regression demonstrated fewer postoperative hyperglycemic events (odds ratio [OR] 0.8, 95% CI, 0.65-0.99) after protocol implementation without an increase in hypoglycemic events (OR 0.96, 95% CI, 0.71-1.3). Average day-weighted mean glucose decreased from 144 to 138 mg/dL (P < .001). The improved glycemic control correlated with a risk-adjusted decrease in composite morbidity or mortality (OR 0.61, 95% CI, 0.47-0.79). Although hospital costs increased after implementation, the protocol increased health care-related value by 38%.

CONCLUSION

Implementation of a protocol consisting of an eGMS paired with a cardiac surgery-specific endocrinology consult service was associated with improved glycemic control and reduced morbidity. Despite higher costs health care-related value increased as a result of eGMS implementation.

Accuracy of Blood Glucose Measurement and Blood Glucose Targets

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

An Artificial Neural Network-based Predictive Model to Support Optimization of Inpatient Glycemic Control

Background: Achieving glycemic control in critical care patients is of paramount importance, and has been linked to reductions in mortality, intensive care unit (ICU) length of stay, and morbidities such as infection. The myriad of illnesses and patient conditions render maintenance of glycemic control very challenging in this setting. Materials and Methods: This study involved collection of continuous glucose monitoring (CGM) data, and other associated measures, from the electronic medical records of 127 patients for the first 72 h of ICU care who upon admission to the ICU had a diagnosis of type 1 (n = 8) or type 2 diabetes (n = 97) or a glucose value >150 mg/dL (n = 22). A neural network-based model was developed to predict a complete trajectory of glucose values up to 135 min ahead of time. Model accuracy was validated using data from 15 of the 127 patients who were not included in the model training set to simulate model performance in real-world health care settings. Results: Predictive models achieved an improved accuracy and performance compared with previous models that were reported by our research team. Model error, expressed as mean absolute difference percent, was 10.6% with respect to interstitial glucose values (CGM) and 15.9% with respect to serum blood glucose values collected 135 min in the future. A Clarke Error Grid Analysis of model predictions with respect to the reference CGM and blood glucose measurements revealed that >99% of model predictions could be regarded as clinically acceptable and would not lead to inaccurate insulin therapy or treatment recommendations. Conclusion: The noted clinical acceptability of these models illustrates their potential utility within a clinical decision support system to assist health care providers in the optimization of glycemic management in critical care patients.

Liraglutide for perioperative management of hyperglycaemia in cardiac surgery patients: a multicentre randomized superiority trial

AIMS

Most cardiac surgery patients, with or without diabetes, develop perioperative hyperglycaemia, for which intravenous insulin is the only therapeutic option. This is labour-intensive and carries a risk of hypoglycaemia. We hypothesized that preoperative administration of the glucagon-like peptide-1 receptor agonist liraglutide reduces the number of patients requiring insulin for glycaemic control during cardiac surgery.

MATERIALS AND METHODS

In this randomized, blinded, placebo-controlled, parallel-group, balanced (1:1), multicentre randomized, superiority trial, adult patients undergoing cardiac surgery in four Dutch tertiary hospitals were randomized to receive 0.6 mg subcutaneous liraglutide on the evening before surgery and 1.2 mg after induction of anaesthesia or matching placebo. Blood glucose was measured hourly and controlled using an insulin-bolus algorithm. The primary outcome was insulin administration for blood glucose >8.0 mmol/L in the operating theatre. Research pharmacists used centralized, stratified, variable-block, randomization software. Patients, care providers and study personnel were blinded to treatment allocation.

RESULTS

Between June 2017 and August 2018, 278 patients were randomized to liraglutide (139) or placebo (139). All patients receiving at least one study drug injection were included in the intention-to-treat analyses (129 in the liraglutide group, 132 in the placebo group). In the liraglutide group, 55 (43%) patients required additional insulin compared with 80 (61%) in the placebo group and absolute difference 18% (95% confidence interval 5.9-30.0, P = 0.003). Dose and number of insulin injections and mean blood glucose were all significantly lower in the liraglutide group. We observed no difference in the incidence of hypoglycaemia, nausea and vomiting, mortality or postoperative complications.

CONCLUSIONS

Preoperative liraglutide, compared with placebo, reduces insulin requirements while improving perioperative glycaemic control during cardiac surgery.

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

PURPOSE OF REVIEW

To summarize the advances in literature that support the best current practices regarding glucose control in the critically ill.

RECENT FINDINGS

There are differences between patients with and without diabetes regarding the relationship of glucose metrics during acute illness to mortality. Among patients with diabetes, an assessment of preadmission glycemia, using measurement of Hemoglobin A1c (HgbA1c) informs the choice of glucose targets. For patients without diabetes and for patients with low HgbA1c levels, increasing mean glycemia during critical illness is independently associated with increasing risk of mortality. For patients with poor preadmission glucose control the appropriate blood glucose target has not yet been established. New metrics, including stress hyperglycemia ratio and glycemic gap, have been developed to describe the relationship between acute and chronic glycemia.

SUMMARY

A 'personalized' approach to glycemic control in the critically ill, with recognition of preadmission glycemia, is supported by an emerging literature and is suitable for testing in future interventional trials.

Impact of blood glucose abnormalities on outcomes and disease severity in patients with severe sepsis: An analysis from a multicenter, prospective survey of severe sepsis

Background

Dysglycemia is frequently observed in patients with sepsis. However, the relationship between dysglycemia and outcome is inconsistent. We evaluate the clinical characteristics, glycemic abnormalities, and the relationship between the initial glucose level and mortality in patients with sepsis.

Methods

This is a retrospective sub-analysis of a multicenter, prospective cohort study. Adult patients with severe sepsis (Sepsis-2) were divided into groups based on blood glucose categories (<70 (hypoglycemia), 70–139, 140–179, and ≥180 mg/dL), according to the admission values. In-hospital mortality and the relationship between pre-existing diabetes and septic shock were evaluated.

Results

Of 1158 patients, 69, 543, 233, and 313 patients were categorized as glucose levels <70, 70–139, 140–179, ≥180 mg/dL, respectively. Both the Acute Physiological and Chronic Health Evaluation II and Sequential Organ Failure Assessment (SOFA) scores on the day of enrollment were higher in the hypoglycemic patients than in those with 70–179 mg/dL. The hepatic SOFA scores were also higher in hypoglycemic patients. In-hospital mortality rates were higher in hypoglycemic patients than in those with 70–139 mg/dL (26/68, 38.2% vs 43/221, 19.5%). A significant relationship between mortality and hypoglycemia was demonstrated only in patients without known diabetes. Mortality in patients with both hypoglycemia and septic shock was 2.5-times higher than that in patients without hypoglycemia and septic shock.

Conclusions

Hypoglycemia may be related to increased severity and high mortality in patients with severe sepsis. These relationships were evident only in patients without known diabetes. Patients with both hypoglycemia and septic shock had an associated increased mortality rate.

Glucose Management Technologies for the Critically Ill

Hyperglycemia is common in the intensive care unit (ICU) both in patients with and without a previous diagnosis of diabetes. The optimal glucose range in the ICU population is still a matter of debate. Given the risk of hypoglycemia associated with intensive insulin therapy, current recommendations include treating hyperglycemia after two consecutive glucose >180 mg/dL with target levels of 140-180 mg/dL for most patients. The optimal method of sampling glucose and delivery of insulin in critically ill patients remains elusive. While point of care glucose meters are not consistently accurate and have to be used with caution, continuous glucose monitoring (CGM) is not standard of care, nor is it generally recommended for inpatient use. Intravenous insulin therapy using paper or electronic protocols remains the preferred approach for critically ill patients. The advent of new technologies, such as electronic glucose management, CGM, and closed-loop systems, promises to improve inpatient glycemic control in the critically ill with lower rates of hypoglycemia.

Metformin Use and Metformin-associated Lactic Acidosis in Intensive Care Unit Patients with Diabetes

Metformin is a very potent anti-diabetic drug that has become the drug of choice for the treatment of type 2 diabetes. In addition to its glucose-lowering properties, it also reduces all-cause mortality through its anti-inflammatory and cardioprotective effects. Although metformin-associated lactic acidosis (MALA) is a very rare event, the mortality associated with it is close to 50%. As it is excreted through the kidney, MALA is frequently seen in patients on metformin with risk factors for developing acute kidney injury. Metformin increases the plasma lactate level in a concentration-dependent manner by inhibiting mitochondrial respiration, usually in the presence of a secondary event that disrupts lactate production or clearance. The incidence of acute kidney injury is very high in critically ill patients contributed by circulatory defects as well as contrast-induced nephropathy, the incidence of which is also high in this subset of the population. Because of this potential risk, metformin is frequently discontinued in diabetic patients admitted to the intensive care unit. Blood glucose variability and hypoglycemia, however, are both related to poor intensive care unit (ICU) outcomes and in order to prevent this in diabetic patients admitted to ICU, oral hypoglycemic agents are frequently switched to intravenous or subcutaneous insulin regimens, which allows for closer monitoring and better blood glucose control.

Comparison of perioperative glucose regulation in patients with type 1 vs type 2 diabetes mellitus: A retrospective cross-sectional study

BACKGROUND

Most perioperative diabetes mellitus (DM) guidelines do not distinguish between patients with type 1 (DM1) and type 2 (DM2). We hypothesised that similar treatment of DM1 and DM2 patients leads to differences in their perioperative glucose control.

METHODS

We performed a retrospective cross-sectional study, of all DM patients undergoing surgery between May 2013 and November 2015 in a Dutch university hospital. We compared DM1 with DM2 patients, treated according to the same perioperative glucose protocol. Our primary outcome was the incidence of hyperglycaemia (glucose ≥10 mmol/L). Secondary outcomes were short-term glycaemic control (glucose before surgery and peak glucose perioperatively), long-term glycaemic control (HbA1c in 90 days before and after surgery) and the incidence of hypoglycaemia (glucose <4 mmol/L).

RESULTS

We included 2259 patients with DM, 216 (10%) of which had DM1. The calculated incidences in our population were 7 out of 1000 patients with DM1 and 69 out of 1000 patients with DM2. Compared to those with DM2, patients with DM1 were younger, had a lower BMI, a higher glucose concentration before surgery, and a higher perioperative peak glucose concentration (11.0 [8.2-14.7] vs 9.4 [7.7-11.7], P < 0.001). The incidence of the primary endpoint, perioperative hyperglycaemia, was significantly higher in DM1 compared to DM2 patients (63% vs 43%, P < 0.001). Hypoglycaemia occurred more often in the DM1 population (7.1% vs 1.3%, P < 0.001).

CONCLUSION

Providing similar perioperative treatment to patients with DM1 and DM2 is associated with poorer short-term and long-term glycaemic control in DM1 throughout the perioperative period as well as an increased risk of hypoglycaemia.

Hypoglycemia but Not Hyperglycemia Is Associated with Mortality in Critically Ill Patients with Diabetes

BACKGROUND

Both severe hyperglycemia (> 200 mg/dL) and hypoglycemia (≤70 mg/dL) are known to be associated with increased mortality in critically ill patients. Therefore, we investigated associations of a single episode of blood glucose deviation (concentration either ≤70 mg/dL and/or > 200 mg/dL) during an intensive care unit (ICU) stay with mortality in these patients.

METHODS

A total of 4,986 patients (age 65 ± 15 years; 39% female; 14% type 2 diabetes [T2DM] based on medical records) admitted to a German ICU in a tertiary care hospital were investigated retrospectively. The intra-ICU and long-term mortality of patients between 4 and 7 years after their ICU submission were assessed.

RESULTS

A total 62,659 glucose measurements were analyzed. A single glucose deviation was associated with adverse outcomes compared to patients without a glucose deviation, represented by both intra-ICU mortality (22 vs. 10%; OR 2.62; 95% CI 2.23-3.09; p < 0.001) and long-term mortality (HR 2.01; 95% CI 1.81-2.24; p < 0.001). In patients suffering from T2DM hypoglycemia (30 vs. 13%; OR 2.94; 95% CI 2.28-3.80; p < 0.001) but not hyperglycemia (16 vs. 14%; OR 1.05; 95% CI 0.68-1.62; p = 0.84) was associated with mortality.

CONCLUSION

In patients with dia-betes, hypo- but not hyperglycemia was associated with increased mortality, whereas in patients without diabetes, both hyper- and hypoglycemia were associated with adverse outcome. Blood glucose concentration might need differential approaches depending on concomitant diseases.

Are point-of-care measurements of glycated haemoglobin accurate in the critically ill?

INTRODUCTION

Critically ill patients with type 2 diabetes mellitus (T2DM) and chronic hyperglycaemia may benefit from a more liberal approach to glucose control than patients with previously normal glucose tolerance. It may therefore be useful to rapidly determine HbA1c concentrations. Point-of-care (POC) analysers offer rapid results but may be less accurate than laboratory analysis.

AIM(S)

The aim of this study was to determine agreement between POC and laboratory HbA1c testing in critically ill patients with T2DM.

METHODS

Critically ill patients with T2DM had concurrent laboratory, capillary-, and arterial-POC HbA1c measurements performed. Data are presented as mean (standard deviation) or median [interquartile range]. Measurement agreement was assessed by Lin's concordance correlation coefficient, Bland-Altman 95% limits of agreement, and classification by Cohen's kappa statistic.

RESULTS

HbA1c analysis was performed for 26 patients. The time to obtain a result from POC analysis took a median of 9 [7, 10] minutes. Laboratory analysis took a median of 328 [257, 522] minutes from the time of test request to the time of report. Lin's correlation coefficient showed almost perfect agreement (0.99%) for arterial- vs capillary-POC and both POC methods vs arterial laboratory analysis. Bland-Altman plots showed a mean difference of 2.0 (3.7) with 95% limits of agreement of -5.4 to 9.3 for capillary vs laboratory, 1.6 (3.4) and -5.1 to 8.4 for arterial vs laboratory, and -0.137 (2.6) and -5.2 to 4.9 for capillary vs arterial. Patient classification as having inadequately controlled diabetes (>53 mmol/mol) showed 100% agreement across all tests.

CONCLUSIONS

HbA1c values can be accurately and rapidly obtained using POC testing in the critically ill.

Intensive glucose control for critically ill patients: an updated meta-analysis

This meta-analysis aims to update the evidence for the effects of intensive glucose control (IGC) on the outcomes among critically ill patients. We performed a systematic literature review from inception through December, 2017 by two independent authors by searching PubMed, EMBASE and Cochrane Library. Randomized clinical trials of the effects of IGC compared with conventional glucose control were selected. Random-effect models were applied to calculate summary relative risks (RRs) for the related outcomes. Of 4247 records identified, we abstracted data from 27 relevant trials for meta-analysis. Compared with patients receiving conventional glucose control (controls), patients with IGC did not have significantly decreased risk of short-term mortality (in-hospital mortality or intensive care unit (ICU) mortality) (RR 0.99, 95% CI 0.92-1.06) or 3- to 6-month mortality (RR 1.02, 95% CI 0.97-1.08). These results remained constant among different study settings including surgical ICUs, medical ICUs or mixed ICUs. Similarly, we also found that patients with IGC did not have significantly lower risk of sepsis (RR 1.00, 95% CI 0.89-1.11) or new need for dialysis (RR 0.97, 95% CI 0.84-1.11). However, patients with IGC had almost 4-fold increase in risk of hypoglycemia (RR 4.86, 95% CI 3.16-7.46). In conclusion, in this updated meta-analysis of published trials, critically ill patients receiving IGC were found to be at neutral risk for short-term or 3- 6-month mortality, risk of sepsis or new need for dialysis, but at higher risk of hypoglycemia.

Factors Influencing Variations in Hospitalization for Diabetes with Hypoglycemia

Many studies have explored risk factors associated with Hypoglycemia (HG) and examined the variation in healthcare utilization among HG patients. However, most of these studies failed to integrate a comprehensive list of personal risk factors in their investigations. This empirical study employed the Behavioral Model (BM) of health care utilization as a framework to investigate diabetes' hospitalizations with HG. The national inpatient sample with all non-pregnant adult patients admitted to hospitals' emergency departments and diagnosed with HG from 2012 to 2014 was used. Personal factors were grouped as predictors of the length of stay and the total charges incurred for hospitalization. High-risk profiles of hospitalized HG patients were identified. The analysis shows the need for care factors are the most influential predictors for lengthy hospitalization. The predisposing factors have a limited influence, while enabling factors influence the variation in hospital total charges. The presence of renal disease and diabetes mellitus (DM) complications played a key role in predicting hospital utilization. Furthermore, age, socio-economic status (SES), and the geographical location of the patients were also found to be vital factors in determining the variability in utilization among HG patients. Findings provide practical applications for targeting the high-risk HG patients for interventions.

ESPEN guideline on clinical nutrition in the intensive care unit

Following the new ESPEN Standard Operating Procedures, the previous guidelines to provide best medical nutritional therapy to critically ill patients have been updated. These guidelines define who are the patients at risk, how to assess nutritional status of an ICU patient, how to define the amount of energy to provide, the route to choose and how to adapt according to various clinical conditions. When to start and how to progress in the administration of adequate provision of nutrients is also described. The best determination of amount and nature of carbohydrates, fat and protein are suggested. Special attention is given to glutamine and omega-3 fatty acids. Particular conditions frequently observed in intensive care such as patients with dysphagia, frail patients, multiple trauma patients, abdominal surgery, sepsis, and obesity are discussed to guide the practitioner toward the best evidence based therapy. Monitoring of this nutritional therapy is discussed in a separate document.

Continuous glucose monitoring system can improve the quality of glucose control and glucose variability compared with point-of-care measurement in critically ill patients: A randomized controlled trial

BACKGROUND

The purpose of this study was to determine whether subcutaneous continuous glucose monitoring systems (CGMS) could improve glucose management in critically ill patients compared with frequent and conventional point-of-care (POC) glucose measurements.

METHODS

A total of 144 patients with an expected length of stay in the ICU of at least 72 hours and with an admission glucose or two random glucose values of >10.0 mmol/L within 24 hours after admission, were randomly assigned to the CGMS group (n = 74) or the conventional group (C group, n = 70). Both groups used the same insulin algorithm to reach the same glucose target range (8.0-10.0 mmol/L).

RESULTS

Time in range (TIR, 8.0-10.0 mmol/L), which is our primary outcome measure, was higher in the CGMS group than in the C group (51.5% vs. 29.0%, P < .001). Glucose variability (coefficient of variation, CV; standard deviation, SD; glucose lability index, and GLI) was improved by CGMS (all P < .05). Mean glucose level (MGL) (9.6 vs. 10.3 mmol/L, P = .156) and the proportion of patients with hypoglycemia did not differ between CGMS (5.4%) and C (5.7%) (P = 1.000). However, duration of hypoglycemia was reduced in the CGMS group (15 vs. 28 minutes, P = .032). Clinical outcomes were similar between groups except for the fewer usage of CRRT and lower peak plasma urea nitrogen level in the CGMS group.

CONCLUSION

The use of CGMS, compared with POC glucose measurement, could improve the TIR, GV and duration of hypoglycemia.

FATORES DE RISCO ASSOCIADOS À HIPOGLICEMIA E ANÁLISE DE EVENTOS ADVERSOS EM UMA TERAPIA INTENSIVA

RESUMO Objetivos: avaliar os fatores preditivos associados à ocorrência de hipoglicemia grave e analisar os eventos adversos relacionados ao uso de insulina e hipoglicemiantes orais em pacientes internados em uma unidade de terapia intensiva. Método: trata-se de um estudo de coorte desenvolvido em um hospital de grande porte no município do Rio de Janeiro. O processo de identificação de hipoglicemia ocorreu por meio da revisão diária e prospectiva de prontuários baseada no critério de rastreamento “glicose 50 ≤ mg/dL”. Resultados: foram avaliados 355 pacientes, seguidos durante toda a internação na unidade de terapia intensiva e 16 eventos de hipoglicemia relacionados ao uso de insulina foram confirmados, ocorridos em 10 pacientes, o que correspondeu a uma incidência de 2,8% e uma taxa de incidência de 0,6 eventos de hipoglicemia por 100 pacientes-dia. Os fatores de risco associados à hipoglicemia encontrados no estudo foram: presença de doença hepática (OR=3,06; IC 95%=1,22-7,66), sepse (OR=3,53; IC 95%=1,53-8,18) e ocorrência de evento adverso (OR=3,89; IC 95%=2,05-7,41). O aumento em um ponto no escore de gravidade APACHE (OR=1,15; IC 95%=1,09-1,20) e a ocorrência de hipoglicemia (OR=7,46; IC 95%=3,88-14,33) implicaram em aumento da chance de óbito na UTI. Conclusão: este estudo enfatiza o impacto da hipoglicemia na mortalidade em terapia intensiva e os fatores preditivos para sua ocorrência, bem como analisa os eventos adversos relacionados à insulina.

Therapeutic effect of intensive glycemic control therapy in patients with traumatic brain injury: A systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Hyperglycemia is associated with dismal outcomes in patients with traumatic brain injury (TBI), which is frequently treated with insulin therapy. In this study, a systematic review and meta-analysis of the published randomized controlled trials (RCTs) was performed to assess the safety and efficacy of intensive glycemic control (IGC) versus conventional glycemic control (CGC) for patients following TBI.

METHODS

Databases, including PubMed, Embase, and the Cochran database, were retrieved up to January 2018. The outcomes evaluated in this study included mortality, neurological outcome, infection rate, hypoglycemia episode, and length of stay (LOS) in intensive care unit (ICU). The enrolled trials were analyzed using the Review Manager 5.3 software.

RESULTS

A total of 7 randomized controlled trials (RCTs) involving 1013 cases were enrolled in this study, and the results indicated no significant difference in 6-month mortality (risk ratio [RR], 0.92; 95% confidence interval [CI] 0.76-1.10; P = .34). Subsequently, IGC was associated with a better neurological outcome (RR, 1.22; 95% CI 1.05-1.43; P = .01), lower infection rate (RR, 0.65; 95% CI 0.51-0.82; P = .0003) and shorter LOS in ICU (mean difference [MD] = -1.37; 95%CI = -2.11, -0.63; P = .0003). In addition, IGC would also increase the risk of hypoglycemia episode (RR, 4.53; 95% CI 2.18-9.42; P < .001).

CONCLUSIONS

IGC plays a protective role in improving neurological outcome, decreasing infection rate and reducing the LOS in ICU. However, IGC therapy can also remarkably increase the risk of hypoglycemia, but it will not affect the mortality in TBI patients.