Coefficient of glucose variation is independently associated with mortality in critically ill patients receiving intravenous insulin. Crit Care. 2014;18:R86. [PMID: 24886864 PMCID: PMC4075237 DOI: 10.1186/cc13851]

Glucose evaluation and management in the ICU (GEM-ICU): Protocol for a bi-centre cohort study

INTRODUCTION

Hyperglycaemia is common in intensive care unit (ICU) patients. Glycaemic monitoring and effective glycaemic control with insulin are crucial in the ICU to improve patient outcomes. However, glycaemic control and insulin use vary between ICU patients and hypo- and hyperglycaemia occurs. Therefore, we aim to provide contemporary data on glycaemic control and management, and associated outcomes, in adult ICU patients. We hypothesise that the occurrence of hypoglycaemia in acutely admitted ICU patients is lower than that of hyperglycaemia.

METHODS

We will conduct a bi-centre cohort study of 300 acutely admitted adult ICU patients. Routine data will be collected retrospectively at baseline (ICU admission) and daily during ICU stay up to a maximum of 30 days. The primary outcome will be the number of patients with hypoglycaemia during their ICU stay. Secondary outcomes will be occurrence of severe hypoglycaemia, occurrence of hyperglycaemia, time below blood glucose target range, time above target range, all-cause mortality at Day 30, number of days alive without life support at Day 30 and number of days alive and out of hospital at Day 30. Process outcomes include the number of in-ICU days, glucose measurements (number of measurements and method) and use of insulin (including route of administration and dosage). All statistical analyses will be descriptive.

CONCLUSIONS

This cohort study will provide a contemporary overview of glucose evaluation and management practices in adult ICU patients and, thus, highlight potential areas for improvement through future clinical trials in this area.

Simultaneous assessment of stress hyperglycemia ratio and glycemic variability to predict mortality in patients with coronary artery disease: a retrospective cohort study from the MIMIC-IV database

BACKGROUND

Stress hyperglycemia and glycemic variability (GV) can reflect dramatic increases and acute fluctuations in blood glucose, which are associated with adverse cardiovascular events. This study aimed to explore whether the combined assessment of the stress hyperglycemia ratio (SHR) and GV provides additional information for prognostic prediction in patients with coronary artery disease (CAD) hospitalized in the intensive care unit (ICU).

METHODS

Patients diagnosed with CAD from the Medical Information Mart for Intensive Care-IV database (version 2.2) between 2008 and 2019 were retrospectively included in the analysis. The primary endpoint was 1-year mortality, and the secondary endpoint was in-hospital mortality. Levels of SHR and GV were stratified into tertiles, with the highest tertile classified as high and the lower two tertiles classified as low. The associations of SHR, GV, and their combination with mortality were determined by logistic and Cox regression analyses.

RESULTS

A total of 2789 patients were included, with a mean age of 69.6 years, and 30.1% were female. Overall, 138 (4.9%) patients died in the hospital, and 404 (14.5%) patients died at 1 year. The combination of SHR and GV was superior to SHR (in-hospital mortality: 0.710 vs. 0.689, p = 0.012; 1-year mortality: 0.644 vs. 0.615, p = 0.007) and GV (in-hospital mortality: 0.710 vs. 0.632, p = 0.004; 1-year mortality: 0.644 vs. 0.603, p < 0.001) alone for predicting mortality in the receiver operating characteristic analysis. In addition, nondiabetic patients with high SHR levels and high GV were associated with the greatest risk of both in-hospital mortality (odds ratio [OR] = 10.831, 95% confidence interval [CI] 4.494-26.105) and 1-year mortality (hazard ratio [HR] = 5.830, 95% CI 3.175-10.702). However, in the diabetic population, the highest risk of in-hospital mortality (OR = 4.221, 95% CI 1.542-11.558) and 1-year mortality (HR = 2.013, 95% CI 1.224-3.311) was observed in patients with high SHR levels but low GV.

CONCLUSIONS

The simultaneous evaluation of SHR and GV provides more information for risk stratification and prognostic prediction than SHR and GV alone, contributing to developing individualized strategies for glucose management in patients with CAD admitted to the ICU.

Real-world data analysis for the association of glucose control and mortality in critically ill patients

Existing results regarding the usage of glycemic control in critically ill patients for reduced morbidity and mortality have been based on clinical studies but could not be reproduced in large prospective studies. Current guidelines for glycemic control suggest a target blood glucose of 140-180 mg/dL, with lower targets being appropriate for some patients. The current study aims to provide additional evidence to this area, through the usage of real-world retrospective data of everyday clinical practice. We have used the large, credentialed access database MIMIC-IV to assess the effect of glycemic control to patient mortality. Glycemic control has been characterized by the percentage of time that the glucose measurements fall within pre-specified glucose bands. Results from logistic regression and survival analysis are reported, along with visualizations based on methods from the machine learning literature, which all suggest that increased time in low and high glucose values is related to increased ICU mortality and decreased survival.

Glucometrics in the first week of critical illness and its association with mortality

OBJECTIVE

Evaluation of glucometrics in the first week of ICU stay and its association with outcomes.

DESIGN

Prospective observational study.

SETTING

Mixed ICU of teaching hospital.

PATIENTS

Adults initiated on insulin infusion for 2 consecutive blood glucose (BG) readings ≥180mg/dL.

MAIN VARIABLES OF INTEREST

Glucometrics calculated from the BG of first week of admission: hyperglycemia (BG>180mg/dL) and hypoglycemia (BG<70mg/dL) episodes; median, standard deviation (SD) and coefficient of variation (CV) of BG, glycemic lability index (GLI), time in target BG range (TIR). Factors influencing glucometrics and the association of glucometrics to patient outcomes analyzed.

RESULTS

A total of 5762 BG measurements in 100 patients of median age 55 years included. Glucometrics: hyperglycemia: 2253 (39%), hypoglycemia: 28 (0.48%), median BG: 169mg/dL (162-178.75), SD 31mg/dL (26-38.75), CV 18.6% (17.1-22.5), GLI: 718.5 [(mg/dL)²/h]/week (540.5-1131.5) and TIR 57% (50-67). Diabetes and higher APACHE II score were associated with higher SD and CV, and lower TIR. On multivariate regression, diabetes (p=0.009) and APACHE II score (p=0.016) were independently associated with higher SD. Higher SD and CV were associated with less vasopressor-free days; lower TIR with more blood-stream infections (BSI). Patients with higher SD, CV and GLI had a higher 28-day mortality. On multivariate analysis, GLI alone was associated with a higher mortality (OR 2.99, p=0.04).

CONCLUSIONS

Glycemic lability in the first week in ICU patients receiving insulin infusion is associated with higher mortality. Lower TIR is associated with more blood stream infections.

What, why and how to monitor blood glucose in critically ill patients

Critically ill patients are prone to high glycemic variations irrespective of their diabetes status. This mandates frequent blood glucose (BG) monitoring and regulation of insulin therapy. Even though the most commonly employed capillary BG monitoring is convenient and rapid, it is inaccurate and prone to high bias, overestimating BG levels in critically ill patients. The targets for BG levels have also varied in the past few years ranging from tight glucose control to a more liberal approach. Each of these has its own fallacies, while tight control increases risk of hypoglycemia, liberal BG targets make the patients prone to hyperglycemia. Moreover, the recent evidence suggests that BG indices, such as glycemic variability and time in target range, may also affect patient outcomes. In this review, we highlight the nuances associated with BG monitoring, including the various indices required to be monitored, BG targets and recent advances in BG monitoring in critically ill patients.

Glycemic variability and all-cause mortality in a large prospective southern European cohort of patients with differences in glycemic status

Background

Few studies have analyzed the relationship between glucose variability (GV) and adverse health outcomes in patients with differences in glycemic status. The present study tests the hypothesis that GV predicts all-cause mortality regardless of glycemic status after simple adjustment (age and sex) and full adjustment (age, sex, cardiovascular disease, hypertension, use of aspirin, statins, GLP-1 receptor agonists, SGLT-2 inhibitors and DPP-4 inhibitors, baseline FPG and average HbA1c).

Methods

Prospective cohort study with 795 normoglycemic patients, 233 patients with prediabetes, and 4,102 patients with type 2 diabetes. GV was measured using the coefficient of variation of fasting plasma glucose (CV-FPG) over 12 years of follow-up. The outcome measure was all-cause mortality.

Results

A total of 1,223 patients (657 men, 566 women) died after a median of 9.8 years of follow-up, with an all-cause mortality rate of 23.35/1,000 person-years. In prediabetes or T2DM patients, the fourth quartile of CV-FPG exerted a significant effect on all-cause mortality after simple and full adjustment. A sensitivity analysis excluding participants who died during the first year of follow-up revealed the following results for the highest quartile in the fully adjusted model: overall, HR (95%CI) = 1.54 (1.26–1.89); dysglycemia (prediabetes and T2DM), HR = 1.41 (1.15–1.73); T2DM, HR = 1.36 (1.10–1.67).

Conclusion

We found CV-FPG to be useful for measurement of GV. It could also be used for the prognostic stratification of patients with dysglycemia.

Effect of high-protein vs. high-fat snacks before lunch on glycemic variability in prediabetes: A study protocol for a randomized controlled trial

Background

China has the largest number of patients with Type 2 Diabetes Mellitus (T2DM), and it tends to increasingly grow in the future, putting an enormous burden on disease control and prevention in China. While glycemic variability (GV) came to be an important indicator of blood glucose control in diabetic patients, studies suggested that premeal snacks may help blood glucose control, but there are still some problems to be researched. Therefore, we designed this trial to evaluate which kind of premeal snacks would lead to better effects on GV under two diet patterns in pre-diabetes subjects and to evaluate assessments of acceptability and compliance, behavior, and metabolism changes in individuals will be described.

Methods and analysis

The study is a single-center, open-label, multiparallel group, randomized controlled trial. A total of 32 male and female volunteers will be randomized into 4 groups in a single allocated ratio of soy milk (powder) snack, milk (powder) snack, almonds snack, and placebo control with 250 ml of water taken 30 min before lunch, respectively. The study consists of two intervention periods over 11 days. The first intervention period under habitual diet conditions from D3 to D6 (4 days), during which all subjects are asked to maintain their habitual eating and daily activities similar to the run-in period. The second intervention consists of prelunch snacks with standard meals. We will examine both the effect of GV and various metabolic and behavioral outcomes potentially associated with the interventions. At the end of this study, we will assess the acceptability and maintainability of the intervention through interviews.

Clinical trial registration

Chinese Clinical Trial Registry, identifier ChiCTR2200058935.

Impact of short-term glycemic variability on risk of all-cause mortality in type 2 diabetes patients with well-controlled glucose profile by continuous glucose monitoring: A prospective cohort study

AIMS

To investigate the association between short-term glycemic variability (GV) and all-cause mortality in type 2 diabetes with well-controlled glucose profile by continuous glucose monitoring (CGM).

METHODS

In this prospective study, 1839 diabetes patients who reached percentage of time in the target glucose range of 3.9-10 mmol/L > 70%, percentage of time above range of 10 mmol/L < 25% and percentage of time below range of 3.9 mmol/L < 4% on CGM were enrolled and were classified into five groups by coefficient of variation for glucose (%CV) level: ≤20%, 20-25%, 25-30%, 30-35%, and > 35%. Cox proportional hazard models were used to estimate hazard ratios (HRs) of all-cause mortality risk associated with the different %CV categories.

RESULTS

At baseline, participants had mean age of 60.9 years and mean HbA_1c of 7.3% (56 mmol/mol). A total of 165 deaths were identified during a median follow-up of 6.9 years. In multivariate Cox regression analysis, HRs associated with %CV categories were 1.00, 1.16 (95% CI 0.78-1.73), 1.38 (95% CI 0.89-2.15), 1.33 (95% CI 0.77-2.29) and 2.26 (95% CI 1.13-4.52) for all-cause mortality.

CONCLUSIONS

Greater %CV was associated with increased risk for all-cause mortality even among patients with seemingly well-controlled glucose status.

Glycaemic Variability and Hyperglycaemia as Prognostic Markers of Major Cardiovascular Events in Diabetic Patients Hospitalised in Cardiology Intensive Care Unit for Acute Heart Failure

(1) Background: Hyperglycaemia and hypoglycaemia are both emerging risk factors for cardiovascular disease. Nevertheless, the potential effect of glycaemic variability (GV) on mid-term major cardiovascular events (MACE) in diabetic patients presenting with acute heart failure (AHF) remains unclear. This study investigates the prognostic value of GV in diabetic patients presenting with acute heart failure (AHF). (2) Methods: this was an observational study including consecutive patients with diabetes and AHF between January 2015 and November 2016. GV was calculated using standard deviation of glycaemia values during initial hospitalisation in the intensive cardiac care unit. MACE, including recurrent AHF, new-onset myocardial infarction, ischaemic stroke and cardiac death, were recorded. The predictive effects of GV on patient outcomes were analysed with respect to baseline characteristics and cardiac status. (3) Results: In total, 392 patients with diabetes and AHF were enrolled. During follow-up (median (interquartile range) 29 (6−51) months), MACE occurred in 227 patients (57.9%). In total, 92 patients died of cardiac causes (23.5%), 107 were hospitalised for heart failure (27.3%), 19 had new-onset myocardial infarction (4.8%) and 9 (2.3%) had an ischaemic stroke. Multivariable logistic regression analysis showed that GV > 50 mg/dL (2.70 mmol/L), age > 75 years, reduced left ventricular ejection fraction (LVEF < 30%) and female gender were independent predictors of MACE: hazard ratios (HR) of 3.16 (2.25−4.43; p < 0.001), 1.54 (1.14−2.08; p = 0.005), 1.47 (1.06−2.07; p = 0.02) and 1.43 (1.05−1.94; p = 0.03), respectively. (4) Conclusions: among other well-known factors of HF, a GV cut-off value of >50 mg/dL was the strongest independent predictive factor for mid-term MACE in patients with diabetes and AHF.

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.

Preoperative Carbohydrate Drink Intake Increases Glycemic Variability in Patients with Type 2 Diabetes Mellitus in Total Joint Arthroplasty: A Prospective Randomized Trial

BACKGROUND

Preoperative carbohydrate treatment attenuates insulin resistance and improves metabolism to an anabolic state. Despite these benefits, impaired glycemic control and aspiration risk related to gastroparesis represent concerns for patients with diabetes undergoing surgery. This randomized controlled trial investigated the effects of oral carbohydrate therapy on perioperative glucose variability, metabolic responses, and gastric volume in diabetic patients undergoing elective total hip or knee arthroplasty.

METHODS

Fifty diabetic patients scheduled to undergo elective total knee or hip arthroplasty during August 2019-October 2020 were randomly assigned to a control or carbohydrate therapy (CHO) group. CHO group of patients received a 400-mL carbohydrate drink 2-3 h before anesthesia; control group of patients underwent overnight fasting from midnight, one night before surgery. Blood glucose levels were measured before intake of the carbohydrate drink, before spinal anesthesia, preoperatively, immediately postoperatively, and 1 h postoperatively. Insulin level and gastric volume were measured before spinal anesthesia.

RESULTS

The glucose variability of patients in the CHO group was significantly higher than that of those in the control group (16.5 vs. 10.1%, P = 0.008). Similarly, insulin resistance was higher in the CHO group than in the control group (8.5 vs. 2.7, P < 0.001). The gastric volume did not differ significantly between the groups (61.3 vs. 15.2 ml, P = 0.082).

CONCLUSIONS

Preoperative oral carbohydrate therapy increases glucose variability and insulin resistance in diabetic patients. Therefore, carbohydrate beverages should be cautiously administered to diabetic patients, considering metabolic and safety aspects. Trial registration number ClinicalTrials.gov (No. NCT04013594).

Impact of Comorbidities on Beneficial Effect of Lactated Ringers vs. Saline in Sepsis Patients

Background: Lactated Ringers reduced mortality more than saline in sepsis patients but increased mortality more than saline in traumatic brain injury patients.

Method: This prospective cohort study was conducted in a medical intensive care unit (ICU) in central Taiwan. We applied standard sepsis evaluation protocol and identified heart, lung, liver, kidney, and endocrine comorbidities. We also evaluated resuscitation response with central venous pressure, central venous oxygen saturation, and serum lactate level simultaneously. Propensity-score matching and Cox regression were used to estimate mortality. The competing risk model compared the lengths of hospital stays with the subdistribution hazard ratio (SHR).

Results: Overall, 938 patients were included in the analysis. The lactated Ringers group had a lower mortality rate (adjusted hazard ratio, 0.59; 95% CI 0.43-0.81) and shorter lengths of hospital stay (SHR, 1.39; 95% C.I. 1.15-1.67) than the saline group; the differences were greater in patients with chronic pulmonary disease and small and non-significant in those with chronic kidney disease, moderate to severe liver disease and cerebral vascular disease. The resuscitation efficacy was the same between fluid types, but serum lactate levels were significantly higher in the lactated Ringers group than in the saline group (0.12 mg/dl/h; 95% C.I.: 0.03, 0.21), especially in chronic liver disease patients. Compared to the saline group, the lactated Ringers group achieved target glucose level earlier in both diabetes and non-diabetes patients.

Conclusion: Lactate Ringer's solution provides greater benefits to patients with chronic pulmonary disease than to those with chronic kidney disease, or with moderate to severe liver disease. Comorbidities are important in choosing resuscitation fluid types.

Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions

Clinical decision-making is based on knowledge, expertise, and authority, with clinicians approving almost every intervention-the starting point for delivery of "All the right care, but only the right care," an unachieved healthcare quality improvement goal. Unaided clinicians suffer from human cognitive limitations and biases when decisions are based only on their training, expertise, and experience. Electronic health records (EHRs) could improve healthcare with robust decision-support tools that reduce unwarranted variation of clinician decisions and actions. Current EHRs, focused on results review, documentation, and accounting, are awkward, time-consuming, and contribute to clinician stress and burnout. Decision-support tools could reduce clinician burden and enable replicable clinician decisions and actions that personalize patient care. Most current clinical decision-support tools or aids lack detail and neither reduce burden nor enable replicable actions. Clinicians must provide subjective interpretation and missing logic, thus introducing personal biases and mindless, unwarranted, variation from evidence-based practice. Replicability occurs when different clinicians, with the same patient information and context, come to the same decision and action. We propose a feasible subset of therapeutic decision-support tools based on credible clinical outcome evidence: computer protocols leading to replicable clinician actions (eActions). eActions enable different clinicians to make consistent decisions and actions when faced with the same patient input data. eActions embrace good everyday decision-making informed by evidence, experience, EHR data, and individual patient status. eActions can reduce unwarranted variation, increase quality of clinical care and research, reduce EHR noise, and could enable a learning healthcare system.

American Association of Clinical Endocrinology Clinical Practice Guideline: The Use of Advanced Technology in the Management of Persons With Diabetes Mellitus

OBJECTIVE

To provide evidence-based recommendations regarding the use of advanced technology in the management of persons with diabetes mellitus to clinicians, diabetes-care teams, health care professionals, and other stakeholders.

METHODS

The American Association of Clinical Endocrinology (AACE) conducted literature searches for relevant articles published from 2012 to 2021. A task force of medical experts developed evidence-based guideline recommendations based on a review of clinical evidence, expertise, and informal consensus, according to established AACE protocol for guideline development.

MAIN OUTCOME MEASURES

Primary outcomes of interest included hemoglobin A1C, rates and severity of hypoglycemia, time in range, time above range, and time below range.

RESULTS

This guideline includes 37 evidence-based clinical practice recommendations for advanced diabetes technology and contains 357 citations that inform the evidence base.

RECOMMENDATIONS

Evidence-based recommendations were developed regarding the efficacy and safety of devices for the management of persons with diabetes mellitus, metrics used to aide with the assessment of advanced diabetes technology, and standards for the implementation of this technology.

CONCLUSIONS

Advanced diabetes technology can assist persons with diabetes to safely and effectively achieve glycemic targets, improve quality of life, add greater convenience, potentially reduce burden of care, and offer a personalized approach to self-management. Furthermore, diabetes technology can improve the efficiency and effectiveness of clinical decision-making. Successful integration of these technologies into care requires knowledge about the functionality of devices in this rapidly changing field. This information will allow health care professionals to provide necessary education and training to persons accessing these treatments and have the required expertise to interpret data and make appropriate treatment adjustments.

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.

Glycemic Variability With Insulin Glargine Versus Detemir in Hospitalized Patients With Diabetes

BACKGROUND

Prior research has demonstrated increased mortality with increasing glycemic variability (GV) in hospitalized patients with diabetes.

OBJECTIVE

We aimed to compare glycemic variability (GV) of insulin glargine to detemir in the inpatient setting.

METHODS

This single-center, retrospective, cohort study evaluated noncritically ill patients with diabetes on long-acting insulin at a large academic medical institution between 2010 and 2017. This study was reviewed and approved by the Institutional Review Board. The formulary transitioned from insulin glargine to detemir in December 2013; therefore, patients were compared before and after transition. The primary endpoint was to compare coefficient of variation (CV), a measure of GV, between detemir and glargine. Secondary endpoints included GV measured by standard deviation (SD), CV within 72 hours of long-acting insulin initiation, length-of-stay (LOS), in-hospital mortality, and comparison between subgroups.

RESULTS

2334 patients were included in the study, and there were 1167 in each group. CV was significantly less variable with detemir compared to glargine (33.7% versus 34.8%, difference = 1.09, p = 0.02) and remained significant after controlling for confounders. Similarly, SD was significantly less with detemir (p = 0.048). CV within 72 hours, LOS, and in-hospital mortality were not statistically different. Lastly, GV was higher in medical patients compared to surgical.

CONCLUSION

Insulin detemir exhibited less GV than insulin glargine, although the small difference is unlikely to be clinically significant. Application of this data will aid in formulary decisions and support the use of either agent within the hospital setting.

Identifying Glycemic Variability in Diabetes Patient Cohorts and Evaluating Disease Outcomes

Glycemic variability (GV) is an obstacle to effective blood glucose control and an autonomous risk factor for diabetes complications. We, therefore, explored sample data of patients with diabetes mellitus who maintained better amplitude of glycemic fluctuations and compared their disease outcomes with groups having poor control. A retrospective study was conducted using electronic data of patients having hemoglobin A1C (HbA1c) values with five recent time points from Think Whole Person Healthcare (TWPH). The control variability grid analysis (CVGA) plot and coefficient of variability (CV) were used to identify and cluster glycemic fluctuation. We selected important variables using LASSO. Chi-Square, Fisher’s exact test, Bonferroni chi-Square adjusted residual analysis, and multivariate Kruskal–Wallis tests were used to evaluate eventual disease outcomes. Patients with very high CV were strongly associated (p < 0.05) with disorders of lipoprotein (p = 0.0014), fluid, electrolyte, and acid–base balance (p = 0.0032), while those with low CV were statistically significant for factors influencing health status such as screening for other disorders (p = 0.0137), long-term (current) drug therapy (p = 0.0019), and screening for malignant neoplasms (p = 0.0072). Reducing glycemic variability may balance alterations in electrolytes and reduce differences in lipid profiles, which may assist in strategies for managing patients with diabetes mellitus.

Critical illness myopathy precedes hyperglycaemia and high glucose variability

BACKGROUND

Critical Illness Myopathy (CIM) is a serious ICU complication, and dysglycaemia is widely regarded as a risk factor. Although glucose variability (GV) has been independently linked to ICU mortality, an association with CIM has not been investigated. This study examines the relationship between CIM and GV.

METHODS

Retrospective investigation including ICU patients with SOFA ≥8, mechanical ventilation, and CIM diagnostics. Glucose readings were collected every 6 h throughout the first week of treatment, when CIM is thought to develop. GV was measured using standard deviation (SD), coefficient of variability (CV), mean absolute glucose (MAG), mean amplitude of glycaemic excursions (MAGE), and mean of daily difference (MODD).

RESULTS

74 patients were included, and 50 (67.6%) developed CIM. Time on glycaemic target (70-179 mg/dL), caloric and insulin intakes, mean, maximum and minimum blood glucose values were similar for all patients until the 5th day, after which CIM patients exhibited higher mean and maximum glucose levels. Significantly higher GV in CIM patients were observed on day 5 (SD, CV, MAG, MAGE), day 6 (MODD), and day 7 (SD, CV, MAG).

CONCLUSIONS

CIM patients developed transient increases in GV and hyperglycaemia only late in the first week, suggesting that myopathy precedes dysglycaemia.

Glycemic variability: adverse clinical outcomes and how to improve it?

Glycemic variability (GV), defined as an integral component of glucose homoeostasis, is emerging as an important metric to consider when assessing glycemic control in clinical practice. Although it remains yet no consensus, accumulating evidence has suggested that GV, representing either short-term (with-day and between-day variability) or long-term GV, was associated with an increased risk of diabetic macrovascular and microvascular complications, hypoglycemia, mortality rates and other adverse clinical outcomes. In this review, we summarize the adverse clinical outcomes of GV and discuss the beneficial measures, including continuous glucose monitoring, drugs, dietary interventions and exercise training, to improve it, aiming at better addressing the challenging aspect of blood glucose management.

Dynamic properties of glucose complexity during the course of critical illness: a pilot study

Methods to control the blood glucose (BG) levels of patients in intensive care units (ICU) improve the outcomes. The development of continuous BG levels monitoring devices has also permitted to optimize these processes. Recently it was shown that a complexity loss of the BG signal is linked to poor clinical outcomes. Thus, it becomes essential to decipher this relation to design efficient BG level control methods. In previous studies the BG signal complexity was calculated as a single index for the whole ICU stay. Although, these approaches did not grasp the potential variability of the BG signal complexity. Therefore, we setup this pilot study using a continuous monitoring of central venous BG levels in ten critically ill patients (EIRUS platform, Maquet Critical CARE AB, Solna, Sweden). Data were processed and the complexity was assessed by the detrended fluctuation analysis and multiscale entropy (MSE) methods. Finally, recordings were split into 24 h overlapping intervals and a MSE analysis was applied to each of them. The MSE analysis on time intervals revealed an entropy variation and allowed periodic BG signal complexity assessments. To highlight differences of MSE between each time interval we calculated the MSE complexity index defined as the area under the curve. This new approach could pave the way to future studies exploring new strategies aimed at restoring blood glucose complexity during the ICU stay.

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.

Higher glycemic variability within the first day of ICU admission is associated with increased 30-day mortality in ICU patients with sepsis

Background

High glycemic variability (GV) is common in critically ill patients; however, the prevalence and mortality association with early GV in patients with sepsis remains unclear.

Methods

This retrospective cohort study was conducted in a medical intensive care unit (ICU) in central Taiwan. Patients in the ICU with sepsis between January 2014 and December 2015 were included for analysis. All of these patients received protocol-based management, including blood sugar monitoring every 2 h for the first 24 h of ICU admission. Mean amplitude of glycemic excursions (MAGE) and coefficient of variation (CoV) were used to assess GV.

Results

A total of 452 patients (mean age 71.4 ± 14.7 years; 76.7% men) were enrolled for analysis. They were divided into high GV (43.4%, 196/452) and low GV (56.6%, 256/512) groups using MAGE 65 mg/dL as the cut-off point. Patients with high GV tended to have higher HbA1c (6.7 ± 1.8% vs. 5.9 ± 0.9%, p < 0.01) and were more likely to have diabetes mellitus (DM) (50.0% vs. 23.4%, p < 0.01) compared with those in the low GV group. Kaplan–Meier analysis showed that a high GV was associated with increased 30-day mortality (log-rank test, p = 0.018). The association remained strong in the non-DM (log-rank test, p = 0.035), but not in the DM (log-rank test, p = 0.254) group. Multivariate Cox proportional hazard regression analysis identified that high APACHE II score (adjusted hazard ratio (aHR) 1.045, 95% confidence interval (CI) 1.013–1.078), high serum lactate level at 0 h (aHR 1.009, 95% CI 1.003–1.014), having chronic airway disease (aHR 0.478, 95% CI 0.302–0.756), high mean day 1 glucose (aHR 1.008, 95% CI 1.000–1.016), and high MAGE (aHR 1.607, 95% CI 1.008–2.563) were independently associated with increased 30-day mortality. The association with 30-day mortality remained consistent when using CoV to assess GV.

Conclusions

We found that approximately 40% of the septic patients had a high early GV, defined as MAGE > 65 mg/dL. Higher GV within 24 h of ICU admission was independently associated with increased 30-day mortality. These findings highlight the need to monitor GV in septic patients early during an ICU admission.

Effect of Adding Insulin Glargine on Glycemic Control in Critically Ill Patients Admitted to Intensive Care Units: A Prospective Randomized Controlled Study

OBJECTIVE

We aimed to examine the effects of adding a longer-acting insulin glargine to existing glucose control on reducing blood-glucose fluctuations in an intensive care unit (ICU).

METHODS

A total of 110 patients randomly received adjuvant insulin glargine 15 IU/day (glargine) or placebo (control), in addition to daily infusion of insulin to maintain glucose levels at a target of 140-180 mg/dL. End points were mean and variance of blood glucose and frequency of hypoglycemia, hyperglycemia, ICU stay, and mortality. Data were analyzed with repeated-measures ANOVA and Mann-Whitney U test.

RESULTS

Average daily glucose level was significantly less in the glargine group than controls (P<0.0001), while there was no difference in daily variance in blood glucose between the two groups. The duration of glucose concentrations being within the target range was identical between the glargine and control groups (16.6±4.9 vs 16.4±4.6 hours/day, P=0.844) during the 7 days of admission. The frequency of hypoglycemia was greater in the glargine group and total duration of hyperglycemia (>180 mg/dL) much longer among controls (P<0.001). Similar mortality rates were observed in both groups, while ICU length of stay was 2 days shorter in the glargine group.

CONCLUSION

Addition of insulin glargine to routine protocols more effectively reduces glucose levels and decreases incidence of hyperglycemic episodes and regular insulin usage. This adjustment may be associated with decreases in duration of ICU stay or increases in hypoglycemic events.

Glycemic Variability: An Independent Predictor of Mortality and the Impact of Age in Pediatric Intensive Care Unit

Objective: To compare the ability of different indices of glycemic variability (GV) in the prognostic evaluation of critically ill children and investigate whether heterogeneity of glucose control exists within this population group. Methods: We conducted a retrospective study of the GV data collected from patients admitted to the pediatric intensive care unit, Children's Hospital of Chongqing Medical University between January 2016 and December 2016. We calculated the mean glucose level (MGL) and four indices of GV, namely, standard deviation (SD), coefficient of variation (CV), mean amplitude of glycemic excursion (MAGE), and glycemic lability index (GLI). The 28-day mortality was considered as the primary endpoint. Results: Survivors and non-survivors showed significant differences in terms of the SD, CV, MAGE, and GLI (P < 0.05, for all). However, GLI was superior to the other indices and showed an independent association with ICU mortality (odds ratio [OR], 1.082; 95% confidence interval [CI], 1.031-1.135; P < 0.01). Sub-group analysis disaggregated by quartiles of MGL and GV revealed that younger subjects (age ≤ 36 months) had significantly higher mortality in the lowest quartile of the MGL and in the highest quartile of GV; the older children (age > 36 months) experienced significantly higher mortality in the highest quartiles of MGL and GV. Conclusion: GV is closely associated with mortality, and among all glucose parameters evaluated, GLI was found to be the strongest predictor of outcomes. This paper is the first report of age being a potentially important modifier of the association between GV, MGL, and mortality in critically ill children.

Percentage of Time in Range 70 to 139 mg/dL Is Associated With Reduced Mortality Among Critically Ill Patients Receiving IV Insulin Infusion

BACKGROUND

In addition to hyperglycemia, hypoglycemia, and glycemic variability, reduced time in targeted blood glucose range (TIR) is associated with increased risk of death in critically ill patients. This relation between TIR and mortality may be confounded by diabetic status and antecedent glycemic control.

METHODS

This study retrospectively analyzed critically ill patients managed with the same IV insulin protocol at multiple centers. The percentage of TIR between 70 and 139 mg/dL was calculated. Patients with diabetic ketoacidosis, patients who had < 10 blood glucose readings, and patients with repeat admissions were excluded. The highest recorded glycosylated hemoglobin value in the preceding 3 months or up to 1 month following admission were used as a surrogate for the patient's preexisting glucose control. Stratified regression analyses were performed for 30-day mortality, with covariates of age, sex, TIR ≥ 80%, Acute Physiology Score, and Charlson Comorbidity Index.

RESULTS

A total of 9,028 patients, 53.2% of whom had diabetes, were studied. Median TIR was 84.1% for nondiabetic patients and 64.5% for patients with diabetes. Mortality was lower in those with TIR > 80% compared with those with TIR ≤ 80% (12.4% vs 19.2%; P < .001). TIR > 80% was independently associated with reduced mortality in nondiabetic patients (OR, 0.52; P < .001), patients with diabetes (OR, 0.69; P = .001), and patients with well-controlled disease (OR, 0.50; P < .001) but not in patients with poorly controlled disease (OR, 0.86; P = .40).

CONCLUSIONS

TIR was independently associated with mortality in critically ill patients, particularly those with good antecedent glucose control.

Nutrition delivery, workload and performance in a model-based ICU glycaemic control system

BACKGROUND AND OBJECTIVE

Hyperglycaemia is commonplace in the adult intensive care unit (ICU), and has been associated with increased morbidity and mortality. Effective glycaemic control (GC) can reduce morbidity and mortality, but has proven difficult. STAR is a model-based GC protocol that uniquely maintains normoglycaemia by changing both insulin and nutrition interventions, and has been proven effective in controlling blood glucose (BG) in the ICU. However, most ICU GC protocols only change insulin interventions, making the variable nutrition aspect of STAR less clinically desirable. This paper compares the performance of STAR modulating only insulin, with three simpler alternative nutrition protocols in clinically evaluated virtual trials.

METHODS

Alternative nutrition protocols are fixed nutrition rate (100% caloric goal), CB (Cahill et al. best) stepped nutrition rate (60%, 80% and 100% caloric goal for the first 3 days of GC, and 100% thereafter) and SLQ (STAR lower quartile) stepped nutrition rate (65%, 75% and 85% caloric goal for the first 3 days of GC, and 85% thereafter). Each nutrition protocol is simulated with the STAR insulin protocol on a 221 patient virtual cohort, and GC performance, safety and total intervention workload are assessed.

RESULTS

All alternative nutrition protocols considerably reduced total intervention workload (14.6-19.8%) due to reduced numbers of nutrition changes. However, only the stepped nutrition protocols achieved similar GC performance to the current variable nutrition protocol. Of the two stepped nutrition protocols, the SLQ nutrition protocol also improved GC safety, almost halving the number of severe hypoglycaemic cases (5 vs. 9, P = 0.42).

CONCLUSIONS

Overall, the SLQ nutrition protocol was the best alternative to the current variable nutrition protocol, but either stepped nutrition protocol could be adapted by STAR to reduce workload and make it more clinically acceptable, while maintaining its proven performance and safety.

Evaluation of preoperative oral carbohydrate administration on insulin resistance in off-pump coronary artery bypass patients: A randomised trial

BACKGROUND

In fasting cardiac surgery patients, preoperative carbohydrate (CHO) drink intake attenuated insulin resistance and improved cardiac metabolism, although its beneficial effects were not evident after cardiac surgery possibly due to cardiopulmonary bypass-related extreme systemic inflammation.

OBJECTIVE

We aimed to evaluate whether preoperative CHO intake affected insulin resistance and free-fatty acid (FFA) concentrations in off-pump coronary revascularisation.

DESIGN

A randomised controlled trial.

SETTING

Primary care in a university hospital in Korea from January 2015 to July 2016.

PATIENTS

Sixty patients who underwent elective multi-vessel off-pump coronary revascularisation were randomised into two groups. Three patients were excluded from analysis and 57 patients completed study.

INTERVENTION

The CHO group received oral CHO (400 ml) the prior evening and 2 to 3 h before surgery, and the control group was fasted from food and water according to standard protocol.

MAIN OUTCOME MEASURES

Insulin resistance was assessed twice, after anaesthetic induction and after surgery via short insulin tolerance test. FFA, C-reactive protein and creatine kinase-myocardial band concentrations were determined serially for 48 h after surgery.

RESULTS

Insulin sensitivity was greater (P = 0.002) and plasma FFA concentrations were lower (P = 0.001) after anaesthetic induction in the CHO group compared with the Control group, although there were no intergroup differences after surgery. The postoperative peak creatine kinase-myocardial band concentration was significantly lower in the CHO group compared with the Control group [8.8 (5.4 to 18.2) vs. 6.4 (3.5 to 9.7) ng ml, P = 0.031].

CONCLUSION

A preoperative CHO supplement significantly reduced insulin resistance and FFA concentrations compared with fasting at the beginning of the surgery, but these benefits were lost after off-pump coronary revascularisation. Despite their transient nature, these beneficial effects resulted in less myocardial injury, mandating further studies focused on the impact of preoperative CHO on myocardial ischaemia and cardiac function after coronary revascularisation.

TRIAL REGISTRATION

Clinicaltrials.gov identifier: NCT 02330263.

Volume-Based vs Rate-Based Enteral Nutrition in the Intensive Care Unit: Impact on Nutrition Delivery and Glycemic Control

BACKGROUND

Underfeeding with enteral nutrition (EN) is prevalent in intensive care units (ICUs) and associated with negative outcomes. This study evaluated the impact of volume-based EN (VBEN) vs rate-based EN (RBEN) on delivery of prescribed energy and protein, and glycemic control (GC).

METHODS

This retrospective study included adult patients who require mechanical ventilation within 48 hours of ICU admission and with an RBEN (n = 85) or VBEN (n = 86) order for ≥3 consecutive days during the first 12 ICU days.

RESULTS

Patients receiving VBEN, vs RBEN, received more prescribed energy (RBEN, 67.6%; VBEN, 79.6%; P < .001) and protein (RBEN, 68.6%; VBEN, 79.3%; P < .001). Multiple linear regression analyses confirmed VBEN was significantly associated with an 8.9% increase in energy (P = .002) and 7.7% increase in protein (P = .004) received, after adjusting for age, Acute Physiology and Chronic Health Evaluation II score, duration of and initiation day for EN, and ICU admission location. Presence of hyperglycemia (P = .40) and glycemic variability (GV) (P = .99) were not different between the 2 groups. After adjusting for age, body mass index, diabetes history, primary diagnosis, and percent of days receiving corticosteroids, GC outcomes (presence of hyperglycemia, P = .27; GV, P = .67) remained unrelated to EN order type in multivariable regression models.

CONCLUSION

VBEN, compared with RBEN, was associated with increased energy and protein delivery without adversely affecting GC. These results suggest VBEN is an effective, safe strategy to enhance EN delivery in the ICU.

Update on glucose in critical care

The aim of this review is to summarize recent developments on the mechanisms involved in stress hyperglycemia associated with critical illness. Different aspects of the consequences of stress hyperglycemia as well as the therapeutic approaches tested so far are discussed: the physiological regulations of blood glucose, the mechanisms underlying stress hyperglycemia, the clinical associations, and the results of the prospective trials and meta-analyses to be taken into consideration when interpreting the available data. Current recommendations, challenges, and technological hopes for the future are be discussed.

Dysglycemia in the critically ill patient: current evidence and future perspectives

Dysglycemia in critically ill patients (hyperglycemia, hypoglycemia, glycemic variability and time in range) is a biomarker of disease severity and is associated with higher mortality. However, this impact appears to be weakened in patients with previous diabetes mellitus, particularly in those with poor premorbid glycemic control; this phenomenon has been called "diabetes paradox". This phenomenon determines that glycated hemoglobin (HbA1c) values should be considered in choosing glycemic control protocols on admission to an intensive care unit and that patients' target blood glucose ranges should be adjusted according to their HbA1c values. Therefore, HbA1c emerges as a simple tool that allows information that has therapeutic utility and prognostic value to be obtained in the intensive care unit.

Effects of preoperative oral carbohydrate administration on patient well-being and satisfaction in thyroid surgery

Background

Although the positive effects of preoperative oral carbohydrate administration on clinical outcomes followingmajor surgery have been reported continuously, there are few investigations of them in minor surgical patients. Thepresent study was designed to examine the effects of preoperative oral carbohydrate administration on patient well-beingand satisfaction in patients undergoing thyroidectomy.

Methods

Fifty adults aged 20–65 years and scheduled for elective thyroidectomy in first schedule in the morning wereallocated to one of two groups. The Control group (n = 25) was requested to obey traditional preoperative fasting aftermidnight prior to the day of surgery. The Carbohydrate group (n = 25) also fasted overnight but drank 400 ml of carbohydrate-richdrink 2 hours before induction of anesthesia. Patient well-being (thirst, hunger, mouth dryness, nauseaand vomiting, fatigue, anxiety and sleep quality) and satisfaction were assessed just before the operating room admission(preoperative) and 6 hours following surgery (postoperative). Other secondary outcomes including oral Schirmer’s testand plasma glucose concentrations were also evaluated.

Results

The two groups were homogenous in patient characteristics. Seven parameters representing patient well-beingevaluated on NRS (0–10) and patient satisfaction scored on a 5-point scale were not statistically different between thetwo groups preoperatively and postoperatively. There were no statistically significant differences in secondary outcomes.

Conclusions

Preoperative oral carbohydrate administration does not appear to improve patient well-being and satisfactioncompared with midnight fasting in patients undergoing thyroidectomy in first schedule in the morning.

Diabetes-Specific Formulae Versus Standard Formulae as Enteral Nutrition to Treat Hyperglycemia in Critically Ill Patients: Protocol for a Randomized Controlled Feasibility Trial

Background

During critical illness, hyperglycemia is prevalent and is associated with adverse outcomes. While treating hyperglycemia with insulin reduces morbidity and mortality, it increases glycemic variability and hypoglycemia risk, both of which have been associated with an increase in mortality. Therefore, other interventions which improve glycemic control, without these complications should be explored. Nutrition forms part of standard care, but the carbohydrate load of these formulations has the potential to exacerbate hyperglycemia. Specific diabetic-formulae with a lesser proportion of carbohydrate are available, and these formulae are postulated to limit glycemic excursions and reduce patients’ requirements for exogenous insulin.

Objective

The primary outcome of this prospective, blinded, single center, randomized controlled trial is to determine whether a diabetes-specific formula reduces exogenous insulin administration. Key secondary outcomes include the feasibility of study processes as well as glycemic variability.

Methods

Critically ill patients will be eligible if insulin is administered whilst receiving exclusively liquid enteral nutrition. Participants will be randomized to receive a control formula, or a diabetes-specific, low glycemic index, low in carbohydrate study formula. Additionally, a third group of patients will receive a second diabetes-specific, low glycemic index study formula, as part of a sub-study to evaluate its effect on biomarkers. This intervention group (n=12) will form part of recruitment to a nested cohort study with blood and urine samples collected at randomization and 48 hours later for the first 12 participants in each group with a secondary objective of exploring the metabolic implications of a change in nutrition formula. Data on relevant medication and infusions, nutrition provision and glucose control will be collected to a maximum of 48 hours post randomization. Baseline patient characteristics and anthropometric measures will be recorded. A 28-day phone follow-up will explore weight and appetite changes as well as blood glucose control pre and post intensive care unit (ICU) discharge.

Results

Recruitment commenced in February 2015 with an estimated completion date for data collection by May 2018. Results are expected to be available late 2018.

Conclusions

This feasibility study of the effect of diabetes-specific formulae on the administration of insulin in critically ill patients and will inform the design of a larger, multi-center trial.

Trial Registration

Australian New Zealand Clinical Trial Registry (ANZCTR):12614000166673; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12614000166673 (Archived by WebCite at http://www.webcitation.org/6xs0phrVu)

Nutrition delivery of a model-based ICU glycaemic control system

BACKGROUND

Hyperglycaemia is commonplace in the adult intensive care unit (ICU), associated with increased morbidity and mortality. Effective glycaemic control (GC) can reduce morbidity and mortality, but has proven difficult. STAR is a proven, effective model-based ICU GC protocol that uniquely maintains normo-glycaemia by changing both insulin and nutrition interventions to maximise nutrition in the context of GC in the 4.4-8.0 mmol/L range. Hence, the level of nutrition it provides is a time-varying estimate of the patient-specific ability to take up glucose.

METHODS

First, the clinical provision of nutrition by STAR in Christchurch Hospital, New Zealand (N = 221 Patients) is evaluated versus other ICUs, based on the Cahill et al. survey of 158 ICUs. Second, the inter- and intra- patient variation of nutrition delivery with STAR is analysed. Nutrition rates are in terms of percentage of caloric goal achieved.

RESULTS

Mean nutrition rates clinically achieved by STAR were significantly higher than the mean and best ICU surveyed, for the first 3 days of ICU stay. There was large inter-patient variation in nutrition rates achieved per day, which reduced overtime as patient-specific metabolic state stabilised. Median intra-patient variation was 12.9%; however, the interquartile range of the mean per-patient nutrition rates achieved was 74.3-98.2%, suggesting patients do not deviate much from their mean patient-specific nutrition rate. Thus, the ability to tolerate glucose intake varies significantly between, rather than within, patients.

CONCLUSIONS

Overall, STAR's protocol-driven changes in nutrition rate provide higher nutrition rates to hyperglycaemic patients than those of 158 ICUs from 20 countries. There is significant inter-patient variability between patients to tolerate and uptake glucose, where intra-patient variability over stay is much lower. Thus, a best nutrition rate is likely patient specific for patients requiring GC. More importantly, these overall outcomes show high nutrition delivery and safe, effective GC are not exclusive and that restricting nutrition for GC does not limit overall nutritional intake compared to other ICUs.

Hypoglycemia Reduction Strategies in the ICU

PURPOSE OF REVIEW

We reviewed the strategies associated with hypoglycemia risk reduction among critically ill non-pregnant adult patients.

RECENT FINDINGS

Hypoglycemia in the ICU has been associated with increased mortality in a number of studies. Insulin dosing and glucose monitoring rules, response to impending hypoglycemia, use of computerization, and attention to modifiable factors extrinsic to insulin algorithms may affect the risk for hypoglycemia. Recurring use of intravenous (IV) bolus doses of insulin in insulin-resistant cases may reduce reliance upon higher IV infusion rates. In order to reduce the risk for hypoglycemia in the ICU, caregivers should define responses to interruption of continuous carbohydrate exposure, incorporate transitioning strategies upon initiation and interruption of IV insulin, define modifications of antihyperglycemic therapy in the presence of worsening renal function or chronic kidney disease, and anticipate the effects traceable to other medications and substances. Institutional and system-wide quality improvement efforts should assign priority to hypoglycemia prevention.

Variability in Glycemic Control with Temperature Transitions during Therapeutic Hypothermia

Purpose

Patients treated with therapeutic hypothermia (TH) and continuous insulin may be at increased risk of hyperglycemia or hypoglycemia, particularly during temperature transitions. This study aimed to evaluate frequency of glucose excursions during each phase of TH and to characterize glycemic control patterns in relation to survival.

Methods

Patients admitted to a tertiary care hospital for circulatory arrest and treated with both therapeutic hypothermia and protocol-based continuous insulin between January 2010 and June 2013 were included. Glucose measures, insulin, and temperatures were collected through 24 hours after rewarming.

Results

24 of 26 patients experienced glycemic excursions. Hyperglycemic excursions were more frequent during initiation versus remaining phases (36.3%, 4.3%, 2.5%, and 4.0%, p = 0.002). Hypoglycemia occurred most often during rewarming (0%, 7.7%, 23.1%, and 3.8%, p = 0.02). Patients who experienced hypoglycemia had higher insulin doses prior to rewarming (16.2 versus 2.1 units/hr, p = 0.03). Glucose variation was highest during hypothermia and trended higher in nonsurvivors compared to survivors (13.38 versus 9.16, p = 0.09). Frequency of excursions was also higher in nonsurvivors (32.3% versus 19.8%, p = 0.045).

Conclusions

Glycemic excursions are common and occur more often in nonsurvivors. Excursions differ by phase but risk of hypoglycemia is increased during rewarming.

Association of In-Hospital Mortality and Dysglycemia in Septic Patients

Background

The associations between dysglycemia and mortality in septic patients with and without diabetes are yet to be confirmed. Our aim was to analyze the association of diabetes and sepsis mortality, and to examine how dysglycemia (hyperglycemia, hypoglycemia and glucose variability) affects in-hospital mortality of patients with suspected sepsis in emergency department (ED) and intensive care units.

Methods

Clinically suspected septic patients admitted to ED were included, and stratified into subgroups according to in-hospital mortality and the presence of diabetes. We analyzed patients’ demographics, comorbidities, clinical and laboratory parameters, admission glucose levels and severity of sepsis. Odds ratio of mortality was assessed after adjusting for possible confounders. The correlations of admission glucose and CoV (blood glucose coefficients of variation) and mortality in diabetes and non-diabetes were also tested.

Results

Diabetes was present in 58.3% of the patients. Diabetic patients were older, more likely to have end-stage renal disease and undergoing hemodialysis, but had fewer malignancies, less sepsis severity (lower Mortality in Emergency Department Sepsis Score), less steroid usage in emergency department, and lower in-hospital mortality rate (aOR:0.83, 95% CI 0.65–0.99, p = 0.044). Hyperglycemia at admission (glucose≥200 mg/dL) was associated with higher risks of in-hospital mortality among the non-diabetes patients (OR:1.83 vs. diabetes, 95% CI 1.20–2.80, p = 0.005) with the same elevated glucose levels at admission. In addition, CoV>30% resulted in higher risk of death as well (aOR:1.88 vs. CoV between 10 and 30, 95%CI 1.24–2.86 p = 0.003).

Conclusions

This study indicates that while diabetes mellitus seems to be a protective factor in sepsis patients, hyper- or hypoglycemia status on admission, and increased blood glucose variation during hospital stays, were independently associated with increased odds ratio of mortality.

Higher glucose variability in type 1 than in type 2 diabetes patients admitted to the intensive care unit: A retrospective cohort study

PURPOSE

Although the course of disease of type 1 and type 2 diabetes differs, the distinction is rarely made when patients are admitted to the intensive care unit (ICU). Here, we report patient- and admission-related characteristics in relation to glycemic measures of patients with type 1 and type 2 diabetes admitted to the ICU.

MATERIALS AND METHODS

A retrospective chart review was performed of 1574 patients with diabetes admitted between 2004 and 2011 to our ICU. Glycemic measures included mean glucose, the incidence of hypoglycemia and hyperglycemia, percentage of glucose values in/below/above target, and glucose variability. The ICU and hospital mortality were secondary outcomes.

RESULTS

We classified 2% (n=27) of patients as having type 1 diabetes and 98% (n=1547) as having type 2 diabetes. Patients with type 1 diabetes were significantly younger, had a lower body mass index, and were more frequently admitted to the ICU for medical diagnoses. No differences in glycemic measures were found, apart from a 20% higher glucose variability in the type 1 diabetes group.

CONCLUSIONS

Patients with type 1 diabetes showed a higher glucose variability, but overall glycemic control was not different between patients with type 1 and type 2 diabetes. Very few diabetes patients admitted to the ICU have type 1 diabetes.

Glucose Control in the ICU: A Continuing Story

In the present era of near-continuous glucose monitoring (CGM) and automated therapeutic closed-loop systems, measures of accuracy and of quality of glucose control need to be standardized for licensing authorities and to enable comparisons across studies and devices. Adequately powered, good quality, randomized, controlled studies are needed to assess the impact of different CGM devices on the quality of glucose control, workload, and costs. The additional effects of continuing glucose control on the general floor after the ICU stay also need to be investigated. Current algorithms need to be adapted and validated for CGM, including effects on glucose variability and workload. Improved collaboration within the industry needs to be encouraged because no single company produces all the necessary components for an automated closed-loop system. Combining glucose measurement with measurement of other variables in 1 sensor may help make this approach more financially viable.

Glucose management in the intensive care unit: are we looking for the right sweet spot?

In a recently published issue of Critical Care Medicine, Kar and colleagues investigated glucose management of critically ill patients with type 2 diabetes. In this commentary, we discuss the challenges of investigating glucose control in the critically ill, why so many internally valid studies in this field lead to conflicting results, and the obstacles preventing investigators from reaching a conclusive answer.

Liberal Glycemic Control in Critically Ill Patients With Type 2 Diabetes: An Exploratory Study

OBJECTIVES

The optimal blood glucose target in critically ill patients with preexisting diabetes and chronic hyperglycemia is unknown. In such patients, we aimed to determine whether a " liberal" approach to glycemic control would reduce hypoglycemia and glycemic variability and appear safe.

DESIGN

Prospective, open-label, sequential-period exploratory study.

SETTING

Medical-surgical ICU.

PATIENTS

During sequential 6-month periods, we studied 83 patients with preexisting type 2 diabetes and chronic hyperglycemia (glycated hemoglobin, ≥ 7.0% at ICU admission).

INTERVENTION

During the "standard care" period, 52 patients received insulin to treat blood glucose concentrations greater than 10 mmol/L whereas during the "liberal" period, 31 patients received insulin to treat blood glucose concentrations greater than 14 mmol/L.

MEASUREMENTS AND MAIN RESULTS

Time-weighted mean glucose concentrations and the number and duration of moderate (< 4.0 mmol/L) and severe (≤ 2.2 mmol/L) hypoglycemic episodes were recorded, with moderate and severe hypoglycemic episodes grouped together. Glycemic variability was assessed by calculating the coefficient of variability for each patient. Safety was evaluated using clinical outcomes and plasma concentrations of markers of inflammation, glucose-turnover, and oxidative stress. Mean glucose (TWglucoseday 0-7, standard care: 9.3 [1.8] vs liberal: 10.3 [2.1] mmol/L; p = 0.02) and nadir blood glucose (4.4 [1.5] vs 5.5 [1.6] mmol/L; p < 0.01) were increased during the liberal period. There was a signal toward reduced risk of moderate-severe hypoglycemia (relative risk: liberal compared with standard care: 0.47 [95% CI, 0.19-1.13]; p = 0.09). Ten patients (19%) during the standard period and one patient (3%) during the liberal period had recurrent episodes of moderate-severe hypoglycemia. Liberal therapy reduced glycemic variability (coefficient of variability, 33.2% [12.9%] vs 23.8% [7.7%]; p < 0.01). Biomarker data and clinical outcomes were similar.

CONCLUSIONS

In critically ill patients with type 2 diabetes and chronic hyperglycaemia, liberal glycemic control appears to attenuate glycemic variability and may reduce the prevalence of moderate-severe hypoglycemia.

miR-1273g-3p participates in acute glucose fluctuation-induced autophagy, dysfunction, and proliferation attenuation in human umbilical vein endothelial cells

Acute glucose fluctuations (AGF) often cause high mortality among critically ill patients, but the mechanisms induced by AGF are not clear. Recent studies suggest that endothelial dysfunction is a key factor that leads to high mortality among critically ill patients. Our goal is to evaluate the phenomenon and mechanisms of endothelial dysfunction induced by AGF. In this study, the functions of human umbilical vein endothelial cells (HUVECs) were compared after treatment with sustained high glucose (SHG), AGF in two groups (AGF1 fluctuations between 5 and 16 mM and AGF2 fluctuations between 5 and 25 mM), and normal glucose levels as a control group (CTR). The medium of the groups was changed every 4 h. The influence of AGF on wound healing was also tested on C57BL/6 mice. The results show that cell proliferation, angiogenesis, and migration functions were injured in the SHG and both AGF groups. AGF2 group shows the worse condition in vitro. In vivo, the wound healing was delayed after the AGF treatment. Furthermore, the markers of apoptosis and autophagy were analyzed. We observed that the autophagy changed in all treatment groups, but apoptosis showed no change. To get to know the mechanism of dysfunction and autophagy, we performed the microRNA chip assay and real-time PCR and found miR-1273g-3p remarkably changed in AGF2 group. After the mimic and inhibitor of miR-1273g-3p were transfected during the AGF2 treatment, we found that the dysfunction and autophagy were partially enhanced by miR-1273g-3p mimic and reversed by miR-1273g-3p inhibitor in AGF2 group. Thus, we conclude that AGF can induce more dysfunction and autophagy, and miR-1273g-3p is also an important factor that leads to the injury.

Dysglycemia and Glucose Control During Sepsis

Sepsis predisposes to disordered metabolism and dysglycemia; the latter is a broad term that includes hyperglycemia, hypoglycemia, and glycemic variability. Dysglycemia is a marker of illness severity. Large randomized controlled trials have provided considerable insight into the optimal blood glucose targets for critically ill patients with sepsis. However, it may be that the pathophysiologic consequences of dysglycemia are dynamic throughout the course of a septic insult and also altered by premorbid glycemia. This review highlights the relevance of hyperglycemia, hypoglycemia, and glycemic variability in patients with sepsis with an emphasis on a rational approach to management.