Hyperglycemia-related mortality in critically ill patients varies with admission diagnosis

IMPROVING GLYCEMIC CONTROL SAFELY IN CRITICAL CARE PATIENTS: A COLLABORATIVE SYSTEMS APPROACH IN NINE HOSPITALS

OBJECTIVE

Safely improve glycemic control in the critical care units of nine hospitals.

METHODS

Critical care adult inpatients from nine hospitals with ≥4 point-of-care blood glucose (BG) readings over ≥2 days were targeted by collaborative improvement efforts to reduce hyper- and hypoglycemia. Balanced glucometric goals for each hospital were set targeting improvement from baseline or goals deemed desirable from Society of Hospital Medicine (SHM) benchmarking data. Collaborative interventions included standardized insulin infusion protocols, hypoglycemia prevention bundles, audit and feedback, education, and measure-vention (coupling measurement of patients "off protocol" with concurrent interventions to correct suboptimal care).

RESULTS

All sites improved glycemic control. Six reached prespecified levels of improvement of the day-weighted mean BG. The day-weighted mean BG for the cohort decreased by 7.7 mg/dL (95% confidence interval [CI], 7.0 mg/dL to 8.4 mg/dL) to 151.3 mg/dL. Six of nine sites showed improvement in the percent intensive care unit (ICU) days with severe hyperglycemia (any BG >299 mg/dL). ICU severe hyperglycemic days declined from 8.6 to 7.2% for the cohort (relative risk, 0.84; 95% CI, 0.80 to 0.88). Patient days with any BG <70 mg/dL were reduced by 0.4% (95% CI, 0.06% to 0.6%), from 4.5 to 4.1%, for a small but statistically significant reduction in hypoglycemia. Seven of nine sites showed improvement.

CONCLUSION

Multihospital improvements in ICU glycemic control, severe hyperglycemia, and hypoglycemia are feasible. Balanced goals for glycemic control and hypoglycemia in the ICU using SHM benchmarks and metrics enhanced successful improvement efforts with good staff acceptance and sustainability.

ABBREVIATIONS

BG = blood glucose CMI = case-mix index CY = calendar year DKA = diabetic ketoacidosis EMR = electronic medical record GBMF = Gordon and Betty Moore Foundation ICU = intensive care unit IIP = insulin infusion protocol SHM = Society of z Hospital Medicine.

Prognostic value of blood glucose in emergency room and glycosylated hemoglobin in patients who have suffered an acute cerebro-vascular event

BACKGROUND AND OBJECTIVE

Stress hyperglycemia has been associated with a worse prognosis in patients hospitalized in critical care units. The aim of this study is to evaluate the impact of blood glucose and glycosylated hemoglobin (HbA1c) levels on the mortality of patients suffering a acute cerebro-vascular event, and to determine if this relationship depends on the presence of diabetes.

MATERIAL AND METHODS

A retrospective analysis of 255 patients admitted to the ER for stroke was performed. Venous plasma glucose levels in the emergency room and HbA1c levels within the first 48hours were analyzed. The presence of diabetes was defined in terms of the patients' medical history, as well as their levels of fasting plasma glucose and HbA1c. Mortality was assessed within the first 30 months after the onset of the acute event.

RESULTS

28.2% of patients had diabetes. Higher mortality was observed in patients who had been admitted with plasma glucose levels≥140mg/dl (hazard ratio [HR]=2.22, 95% CI: 1.18-4.16, P=.013) after adjusting for various factors. This relationship was not confirmed in diabetic patients (HR=2.20, 95% CI: 0.66-7.40, P=.201) and was in non-diabetics (HR=2.55, 95% CI: 1.11-5.85, P=.027). In diabetics, HbA1c≥7% was not associated with poor prognosis (HR=0.68, 95% CI: 0.23-1.98, P=.475), whereas non-diabetics with admission levels of HbA1c falling within the pre-diabetes range (5.7% -6.4%) had a higher mortality (HR=2.62, 95% CI: 1.01-6.79, P=.048).

CONCLUSION

Admission hyperglycemia is associated with a worse prognosis in patients without diabetes admitted for stroke, but this relationship was not seen in diabetics. In non-diabetic patients, HbA1c levels in the pre-diabetes range is associated with higher mortality.

Blood glucose on admission and mortality in patients with venous thromboembolism

AIMS

Evaluate association between admission blood glucose (ABG) and mortality in patients with or without diabetes mellitus (DM) hospitalized for venous thromboembolism (VTE).

METHODS

Observational data derived from the electronic records of hospitalized patients ≥18years, admitted for VTE (including deep vein thrombosis and pulmonary embolism) between January 2011 and December 2013. ABG levels were classified to categories: ≤70 (low), 70-110 (normal), 111-140 (mildly elevated), 141-180mg/dl (moderately elevated) and>180mg/dl (markedly elevated). Main outcome was all-cause mortality at the end of follow-up. We had complete follow-up data at 12months for all patients; median follow-up time was 1126days.

RESULTS

Cohort included 567 patients, 137 with (mean age 73, 45% male), and 430 without DM (mean age 65, 40% male). There was a significant interaction between DM, ABG and mortality (p≤0.05). In patients without DM there was a significant association between ABG and mortality: [hazard ratios 1.6, 2.3, and 4.7 respectively for mildly, moderately and markedly elevated ABG (p≤0.01)]. A significant association between ABG and mortality persisted following multivariable analysis only in patients with markedly elevated ABG (HR=2.3 95% CI 1.2-4.5). Similar results were evident in patients with deep vein thrombosis or pulmonary embolism. In patients with DM there was no significant association between ABG and mortality.

CONCLUSION

In patients without DM hospitalized for VTE, markedly elevated ABG is associated with increased mortality.

Liraglutide as an Alternative to Insulin for Glycemic Control in Intensive Care Unit: A Randomized, Open-label, Clinical Study

Background:

Intravenous insulin is the cornerstone in the management of hyperglycemia in the Intensive Care Unit (ICU). We studied the efficacy of liraglutide compared with insulin in the ICU.

Materials and Methods:

In this prospective, open-labeled, randomized study, we included 120 patients (15–65 years, either sex) admitted to ICU with capillary blood glucose (CBG) between 181 and 300 mg/dl. We excluded patients with secondary diabetes and APACHE score >24. The patients were divided into two groups (n = 60) based on the CBG: Group 1 (181–240) and Group 2 (241–300). They were randomized further into four subgroups (n = 30) to receive insulin (Groups 1A and 2A), liraglutide (Group 1B), and insulin with liraglutide (Group 2B). The primary outcome was the ability to achieve CBG below 180 mg/dL at the end of 24 h. The secondary outcomes include mortality at 1 month and hospital stay. Data and results were analyzed using Mann-Whitney U-test, paired t- test, and Chi-square tests.

Results:

The mean age of the patients (93M and 27F) was 57.1 ± 13.9 years, hospital stay (16.9 ± 7.5 days), and CBG was 240.5 ± 36.2 mg/dl. The primary outcome was reached in 26, 27, 25, and 28 patients of Groups 1A, 2A, 1B, and 2B, respectively. The 30-day mortality and hospital stay were similar across all the four groups. Hypoglycemia was common with insulin and gastrointestinal side effects were more common with liraglutide (P < 0.001).

Conclusion:

Liraglutide is a viable alternative to insulin for glycemic control in the ICU. Further studies with a larger number of patients are required to confirm our findings.

Hyperglycemia and glycemic variability are associated with the severity of sepsis in nondiabetic subjects

PURPOSE

The purpose was to compare glucose variability (GV) obtained via continuous glucose monitoring between nondiabetic sepsis patients and healthy subjects and to seek associations between GV and sepsis severity in nondiabetic sepsis patients.

METHODS

Nondiabetic sepsis inpatients and healthy controls received a 72-hour continuous glucose monitoring (iPro2, Medtronic) postadmission and post-oral glucose tolerance test, respectively. The mean glucose level (MGL) along with GV represented by standard deviation (SD) and the mean amplitude of glycemic excursion (MAGE) were calculated at 24 and 72 hours. Sepsis severity was evaluated with the Sepsis-related Organ Failure Assessment Score (SOFA). MGL and GV in patients with SOFA ≥9 and <9 were compared.

RESULTS

Thirty nondiabetic sepsis and 10 healthy subjects were recruited. No differences were found between groups except for higher patient age in sepsis patients. The MGL and MAGE_72h of sepsis patients were significantly higher than those of healthy subjects. MGL and GV_24h were higher in patients with SOFA ≥9 than in patients with SOFA <9 (MGL_24h 195±17 vs 139±27, P<.001; SD_24h 32 [28, 36] vs 19 [5, 58], P=.02; and MAGE_24h 94 [58, 153] vs 54 [16, 179], P=.01).

CONCLUSION

Nondiabetic sepsis patients had higher MGL and GV values than healthy subjects. MGL and GV_24h were associated with sepsis severity.

Glycemic management in critically ill patients

Hyperglycemia associated with critical illness, also called “stress hyperglycemia” or “stress diabetes”, is a consequence of many pathophysiologic hormonal responses including increased catecholamines, cortisol, glucagon, and growth hormone. Alterations in multiple biochemical pathways result in increased hepatic and peripheral insulin resistance with an uncontrolled activation of gluconeogenesis and glycogenolysis. Hyperglycemia has a negative impact on the function of the immune system, on the host response to illness or injury, and on infectious and overall outcomes. The degree of glucose elevation is associated with increased disease severity. Large randomized controlled trials including the Van den Berghe study, the NICE-SUGAR trial, VISEP and GLUCONTROL have shown that the control of glucose levels in critically ill patients has implications on outcome and that both hyperglycemia and hypoglycemia are detrimental and should be avoided. Glucose variability has also been shown to be detrimental. Aggressive glucose control strategies have changed due to the concerns of hypoglycemia and therefore intermediate target glucose control strategies are most often adopted. Different patient populations may vary with regards to optimal glucose targets, timing and approach for glucose control, and with regards to the prognostic significance of glucose excursions and variability. Medical, surgical, and trauma patients may benefit at different rates from glucose control and the approach may need to be adapted to various medical settings and to correspond to the workflow of health providers. Effect modifiers for the success of insulin therapy for hyperglycemia include the methods of nutritional supplementation and exogenous glucose administration. Further research is required to improve insulin protocols for glucose control, to further define glucose targets, and to enhance the accuracy of glucose measuring technologies.

Establishment and Validation of GV-SAPS II Scoring System for Non-Diabetic Critically Ill Patients

BACKGROUND AND AIMS

Recently, glucose variability (GV) has been reported as an independent risk factor for mortality in non-diabetic critically ill patients. However, GV is not incorporated in any severity scoring system for critically ill patients currently. The aim of this study was to establish and validate a modified Simplified Acute Physiology Score II scoring system (SAPS II), integrated with GV parameters and named GV-SAPS II, specifically for non-diabetic critically ill patients to predict short-term and long-term mortality.

METHODS

Training and validation cohorts were exacted from the Multiparameter Intelligent Monitoring in Intensive Care database III version 1.3 (MIMIC-III v1.3). The GV-SAPS II score was constructed by Cox proportional hazard regression analysis and compared with the original SAPS II, Sepsis-related Organ Failure Assessment Score (SOFA) and Elixhauser scoring systems using area under the curve of the receiver operator characteristic (auROC) curve.

RESULTS

4,895 and 5,048 eligible individuals were included in the training and validation cohorts, respectively. The GV-SAPS II score was established with four independent risk factors, including hyperglycemia, hypoglycemia, standard deviation of blood glucose levels (GluSD), and SAPS II score. In the validation cohort, the auROC values of the new scoring system were 0.824 (95% CI: 0.813-0.834, P< 0.001) and 0.738 (95% CI: 0.725-0.750, P< 0.001), respectively for 30 days and 9 months, which were significantly higher than other models used in our study (all P < 0.001). Moreover, Kaplan-Meier plots demonstrated significantly worse outcomes in higher GV-SAPS II score groups both for 30-day and 9-month mortality endpoints (all P< 0.001).

CONCLUSIONS

We established and validated a modified prognostic scoring system that integrated glucose variability for non-diabetic critically ill patients, named GV-SAPS II. It demonstrated a superior prognostic capability and may be an optimal scoring system for prognostic evaluation in this patient group.

Premixed Insulin Analogue Compared with Basal-Plus Regimen for Inpatient Glycemic Control

BACKGROUND

No previous studies have investigated the use of a premixed insulin analogue in a hospital setting.

OBJECTIVE

To compare the efficacy and safety of treatment with premixed insulin analogue (insulin lispro mix 75/25, LM75/25) with the basal-plus regimen with insulin glargine in hospitalized patients with type 2 diabetes (T2D).

MATERIALS AND METHODS

A randomized clinical trial in hospitalized patients with T2D and glucose >140 mg/dL on admission was performed. A total of 54 patients were randomized to receive insulin LM75/25 or glargine. In both groups, a correction dose of lispro was administered before meals. Insulin dose was adjusted to obtain a mean blood glucose (BG) between 100 and 140 mg/dL.

RESULTS

Improvement in the mean BG after the first day of treatment was similar in both groups (P = 0.470). Glycemic control at the end of follow-up was similar between the group with insulin LM75/25 (131.3 ± 28.4 mg/dL) and insulin glargine (143.8 ± 32.5 mg/dL, P = 0.153). The aim of a BG concentration of <140 mg/dL was obtained in 72% of the patients in the premixed insulin analogue group and 56% of patients in the basal-plus group (P = 0.239). There was no difference in the frequency of hypoglycemia between groups (7 vs. 10, P = 0.529).

CONCLUSION

Results of this trial indicate that the use of a premixed insulin analogue is as effective and safe as the basal-plus regimen to achieve glycemic control.

In Silico Testing of an Artificial-Intelligence-Based Artificial Pancreas Designed for Use in the Intensive Care Unit Setting

BACKGROUND

Effective glucose control in the intensive care unit (ICU) setting has the potential to decrease morbidity and mortality rates which should in turn lead to decreased health care expenditures. Current ICU-based glucose controllers are mathematically derived, and tend to be based on proportional integral derivative (PID) or model predictive control (MPC). Artificial intelligence (AI)-based closed loop glucose controllers may have the ability to achieve control that improves on the results achieved by either PID or MPC controllers.

METHOD

We conducted an in silico analysis of an AI-based glucose controller designed for use in the ICU setting. This controller was tested using a mathematical model of the ICU patient's glucose-insulin system. A total of 126 000 unique 5-day simulations were carried out, resulting in 107 million glucose values for analysis.

RESULTS

For the 7 control ranges tested, with a sensor error of ±10%, the following average results were achieved: (1) time in control range, 94.2%, (2) time in range 70-140 mg/dl, 97.8%, (3) time in hyperglycemic range (>140 mg/dl), 2.1%, and (4) time in hypoglycemic range (<70 mg/dl), 0.09%. In addition, the average coefficient of variation (CV) was 11.1%.

CONCLUSIONS

This in silico study of an AI-based closed loop glucose controller shows that it may be able to improve on the results achieved by currently existing ICU-based PID/MPC controllers. If these results are confirmed in clinical testing, this AI-based controller could be used to create an artificial pancreas system for use in the ICU setting.

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.

Association between Blood Glucose Levels the Day after Targeted Temperature Initiation and Outcome in Traumatic Brain Injury: A Post-Hoc Analysis of the B-HYPO Study

We investigated associations between blood glucose levels and clinical outcomes in participants of the multi-center randomized controlled Brain-Hypothermia (B-HYPO) study. Patients with severe traumatic brain injury (TBI, Glasgow Coma Scale 4-8) were assigned to therapeutic hypothermia (TH, 32-34°C, n = 98) or fever control (35.5-37.0°C, n = 50) groups. TH patients were cooled as soon as possible for ≥72 h and rewarmed at a rate of <1°C/d. We recorded blood glucose (BG) levels on days 0, 1, and 3 after treatment initiation, and day 1 after rewarming. The Glasgow Outcome Scale was assessed at 6 months. Median BG levels decreased from day 0 to day 1 (163 vs. 132 mg/dL, p = 0.0062) in the fever control group. In contrast, a decrease was observed from day 1 to day 3 (157.5 vs. 126 mg/dL, p < 0.001) in the TH group. Day 1 BG was higher in the TH group compared with the fever control group (p = 0.0252). At day 0, BG levels were higher in non-survivors compared with survivors across all patients (p = 0.0035), the TH group (p = 0.0125), and the non-surgical group (p = 0.0236). Higher day 1 BG levels were observed in non-survivors compared with survivors across all patients (p = 0.0071), the fever control group (p = 0.0495), and the surgical group (p = 0.0364). In the TH group, the initial stress hyperglycemia was sustained the next day after TH induction. Day 1 BG predicted outcome in TBI patients with TH and fever control. Our findings indicate the significance of BG control particularly during TH treatment.

The association of admission blood glucose level with the clinical picture and prognosis in cardiogenic shock - Results from the CardShock Study

BACKGROUND

Critically ill patients often present with hyperglycemia, regardless of previous history of diabetes mellitus (DM). Hyperglycemia has been associated with adverse outcome in acute myocardial infarction and acute heart failure. We investigated the association of admission blood glucose level with the clinical picture and short-term mortality in cardiogenic shock (CS).

METHODS

Consecutively enrolled CS patients were divided into five categories according to plasma glucose level at the time of enrolment: hypoglycemia (glucose <4.0mmol/L), normoglycemia (4.0-7.9mmol/L), mild (8.0-11.9mmol/L), moderate (12.0-15.9mmol/L), and severe (≥16.0mmol/L) hyperglycemia. Clinical presentation, biochemistry, and short-term mortality were compared between the groups.

RESULTS

Plasma glucose level of 211 CS patients was recorded. Glucose levels were distributed equally between normoglycemia (26% of patients), mild (27%), moderate (19%) and severe (25%) hyperglycemia, while hypoglycemia (2%) was rare. Severe hyperglycemia was associated with higher blood leukocyte count (17.3 (5.8) E9/L), higher lactate level (4.4 (3.3-8.4) mmol/L) and lower arterial pH (7.23 (0.14)) compared with normoglycemia or mild to moderate hyperglycemia (p<0.001 for all). In-hospital mortality was highest among hypoglycemic (60%) and severely hyperglycemic (56%) patients, compared with 22% in normoglycemic group (p<0.01). Severe hyperglycemia was an independent predictor of in-hospital mortality (OR 3.7, 95% CI 1.19-11.7, p=0.02), when adjusted for age, gender, LVEF, lactate, and DM.

CONCLUSIONS

Admission blood glucose level has prognostic significance in CS. Mortality is highest among patients with severe hyperglycemia or hypoglycemia. Severe hyperglycemia is independently associated with high in-hospital mortality in CS. It is also associated with biomarkers of systemic hypoperfusion and stress response.

Survivors of intensive care with type 2 diabetes and the effect of shared care follow-up clinics: study protocol for the SWEET-AS randomised controlled feasibility study

BACKGROUND

Many patients who survive the intensive care unit (ICU) experience long-term complications such as peripheral neuropathy and nephropathy which represent a major source of morbidity and affect quality of life adversely. Similar pathophysiological processes occur frequently in ambulant patients with diabetes mellitus who have never been critically ill. Some 25 % of all adult ICU patients have diabetes, and it is plausible that ICU survivors with co-existing diabetes are at heightened risk of sequelae from their critical illness. ICU follow-up clinics are being progressively implemented based on the concept that interventions provided in these clinics will alleviate the burdens of survivorship. However, there is only limited information about their outcomes. The few existing studies have utilised the expertise of healthcare professionals primarily trained in intensive care and evaluated heterogenous cohorts. A shared care model with an intensivist- and diabetologist-led clinic for ICU survivors with type 2 diabetes represents a novel targeted approach that has not been evaluated previously. Prior to undertaking any definitive study, it is essential to establish the feasibility of this intervention.

METHODS

This will be a prospective, randomised, parallel, open-label feasibility study. Eligible patients will be approached before ICU discharge and randomised to the intervention (attending a shared care follow-up clinic 1 month after hospital discharge) or standard care. At each clinic visit, patients will be assessed independently by both an intensivist and a diabetologist who will provide screening and targeted interventions. Six months after discharge, all patients will be assessed by blinded assessors for glycated haemoglobin, peripheral neuropathy, cardiovascular autonomic neuropathy, nephropathy, quality of life, frailty, employment and healthcare utilisation. The primary outcome of this study will be the recruitment and retention at 6 months of all eligible patients.

DISCUSSION

This study will provide preliminary data about the potential effects of critical illness on chronic glucose metabolism, the prevalence of microvascular complications, and the impact on healthcare utilisation and quality of life in intensive care survivors with type 2 diabetes. If feasibility is established and point estimates are indicative of benefit, funding will be sought for a larger, multi-centre study.

TRIAL REGISTRATION

ANZCTR ACTRN12616000206426.

Usefulness of the plasma glucose concentration-to-HbA1c ratio in predicting clinical outcomes during acute illness with extreme hyperglycaemia

AIMS

To evaluate the correlation between the plasma glucose-to-glycated haemoglobin ratio (GAR) and clinical outcome during acute illness.

METHODS

This retrospective observational cohort study enrolled 661 patients who visited the emergency department of our hospital between 1 July 2008 and 30 September 2010 with plasma glucose concentrations>500mg/dL. Systolic blood pressure, heart rate, white blood cells, neutrophils, haematocrit, blood urea nitrogen, serum creatinine, liver function and plasma glucose concentration were recorded at the initial presentation to the emergency department. Data on glycated haemoglobin over the preceding 6 months were reviewed from our hospital database. The glucose-to-HbA_1c ratio (GAR) was calculated as the plasma glucose concentration divided by glycated haemoglobin.

RESULTS

The GAR of those who died was significantly higher than that of the survivors (81.0±25.9 vs 67.6±25.0; P<0.001). There was a trend towards a higher 90-day mortality rate in patients with higher GARs (log-rank test P<0.0001 for trend). On multivariate Cox regression analysis, the GAR was significantly related to 90-day mortality (hazard ratio [HR] for 1 standard deviation [SD] change: 1.41, 95% confidence interval [CI]: 1.22-1.63; P<0.001), but not to plasma glucose (HR: 0.89, 95% CI: 0.70-1.13; P=0.328). Rates of intensive care unit (ICU) admission and mechanical ventilator use were also higher in those with higher GARs.

CONCLUSION

GAR independently predicted 90-day mortality, ICU admission and use of mechanical ventilation. It was also a better predictor of patient outcomes than plasma glucose alone in patients with extremely high glucose levels.

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.

Inpatient Management of Diabetes Mellitus among Noncritically Ill Patients at University Hospital of Puerto Rico

OBJECTIVE

To describe the state of glycemic control in noncritically ill diabetic patients admitted to the Puerto Rico University Hospital and adherence to current standard of care guidelines for the treatment of diabetes.

METHODS

This was a retrospective study of patients admitted to a general medicine ward with diabetes mellitus as a secondary diagnosis. Clinical data for the first 5 days and the last 24 hours of hospitalization were analyzed.

RESULTS

A total of 147 noncritically ill diabetic patients were evaluated. The rates of hyperglycemia (blood glucose ≥180 mg/dL) and hypoglycemia (blood glucose <70 mg/dL) were 56.7 and 2.8%, respectively. Nearly 60% of patients were hyperglycemic during the first 24 hours of hospitalization (mean random blood glucose, 226.5 mg/dL), and 54.2% were hyperglycemic during the last 24 hours of hospitalization (mean random blood glucose, 196.51 mg/dL). The mean random last glucose value before discharge was 189.6 mg/dL. Most patients were treated with subcutaneous insulin, with basal insulin alone (60%) used as the most common regimen. The proportion of patients classified as uncontrolled receiving basal-bolus therapy increased from 54.3% on day 1 to 60% on day 5, with 40% continuing to receive only basal insulin. Most of the uncontrolled patients had their insulin dose increased (70.1%); however, a substantial proportion had no change (23.7%) or even a decrease (6.2%) in their insulin dose.

CONCLUSION

The management of hospitalized diabetic patients is suboptimal, probably due to clinical inertia, manifested by absence of appropriate modification of insulin regimen and intensification of dose in uncontrolled diabetic patients. A comprehensive educational diabetes management program, along with standardized insulin orders, should be implemented to improve the care of these patients.

The classification of hospitalized patients with hyperglycemia and its implication on outcome: results from a prospective observational study in Internal Medicine

The relevance of classifying hyperglycemic hospitalized subjects (HS) as known diabetes (D), newly discovered diabetes (ND), and stress hyperglycemia (SH) is unclear. The aim of this study was to determine the prevalence, in-hospital mortality, and length of stay (LOS) of three different phenotypes of HS. Fasting glucose ≥126 mg/dL (7 mmol/L) or random blood glucose ≥200 mg/dL (11.1 mmol/L) defined HS who were categorized into three groups: D; ND (no history of diabetes and HbA1c ≥48 mmol/mol); SH (no history of diabetes and HbA1c <48 mmol/mol). The end points of the study were in-hospital mortality and LOS. Of 1447 consecutive enrolled subjects, the prevalence of HS was 28.6 % (415/1447), of these 71.6 % had D, 21.2 % SH, and 7.2 % ND, respectively. In-hospital death was 3.9 % in normoglycemic and 6.0 % in hyperglycemic subjects. Individuals with SH had an increased risk of in-hospital death (7.9 %) (HR 2.17, 95 % CI 1.18-4.9; p = 0.039), while this was not observed for D and ND patients. The mean LOS was greater in ND and SH subjects. Hyperglycemia is common, and is associated with an increased risk of in-hospital mortality and extension of hospital stay. HbA1c along with clinical history is a useful tool to identify subgroups of hyperglycemic hospitalized subjects. Individuals with SH have a longer LOS, and a double risk of in-hospital mortality. Additionally, identifying previously unknown diabetes represents a remarkable opportunity for prevention of diabetes-related acute and chronic complications.

An Elevated Glycemic Gap is Associated with Adverse Outcomes in Diabetic Patients with Acute Myocardial Infarction

Acute hyperglycemia is a frequent finding in patients presenting to the emergency department (ED) with acute myocardial infarction (AMI). The prognostic role of hyperglycemia in diabetic patients with AMI remains controversial. We retrospectively reviewed patients' medical records to obtain demographic data, clinical presentation, major adverse cardiac events (MACEs), several clinical scores and laboratory data, including the plasma glucose level at initial presentation and HbA1c levels. The glycemic gap, which represents changes in serum glucose levels during the index event, was calculated from the glucose level upon ED admission minus the HbA1c-derived average glucose (ADAG). We enrolled 331 patients after the review of medical records. An elevated glycemic gap between admission serum glucose levels and ADAG were associated with an increased risk of mortality in patients. The glycemic gap showed superior discriminative power regarding the development of MACEs when compared with the admission glucose level. The calculation of the glycemic gap may increase the discriminative powers of established clinical scoring systems in diabetic patients presenting to the ED with AMI. In conclusion, the glycemic gap could be used as an adjunct parameter to assess the severity and prognosis of diabetic patients presenting with AMI. However, the usefulness of the glycemic gap should be further explored in prospective longitudinal studies.

Glycated Hemoglobin Testing to Identify Undiagnosed Diabetes Mellitus in the Inpatient Setting

BACKGROUND

Hyperglycemia is commonly seen in hospitalized patients. Glycated hemoglobin (HbA1c) correlates with the average blood glucose level over the previous 8 to 12 weeks. Thus, an HbA1c test offers a longitudinal view that reduces etiologic ambiguity of disease. Screening of HbA1c levels plays an important role in the diagnosis and management of diabetes mellitus in the outpatient setting but remains underused in the evaluation of hyperglycemia with undiagnosed diabetes in the inpatient setting. The underuse of the HbA1c test may be a missed opportunity for early diabetes detection in the hospital.

OBJECTIVE

To examine the use of HbA1c tests in identifying previously undiagnosed diabetes mellitus among patients with hyperglycemia in a rural inpatient setting.

METHODS

A retrospective review of medical records of hospitalized patients with hyperglycemia in a rural community teaching hospital in the Midwest. Descriptive and inferential statistical methods were used.

RESULTS

Medical records of 348 unique patients with hyperglycemia were reviewed. Fifty patients treated for hyperglycemia had medical records with no known history of diabetes (NKHD). Of the 50 patients with NKHD, 31 (62%) had an HbA1c test. Of the 31 patients tested, 6 (19%) had HbA1c levels consistent with the diagnosis of prediabetes, and 18 (58%) had levels consistent with diabetes. Seventeen (55%) of the 31 patients had a discharge diagnosis that included diabetes. Of the 19 patients with NKHD who did not have an HbA1c test, 2 (11%) received a discharge diagnosis that included diabetes.

CONCLUSION

Hospitalized patients with NKHD and hyperglycemia are more likely to receive an appropriate diagnosis if HbA1c is measured. Failing to fully use HbA1c tests in the inpatient setting constitutes a missed opportunity to distinguish transient hyperglycemia from chronic disease. The HbA1c level can elucidate the course of dys-glycemia and trigger mechanisms for timely intervention.

The prognostic significance of admission blood glucose levels in patients with urinary tract infection

AIMS

Evaluate the association between admission blood glucose (ABG) and short and long-term outcomes following hospitalization for urinary tract infection (UTI).

METHODS

Single center, retrospective cohort study of patients admitted to medical wards between January 1, 2011 and December 31, 2013 with a diagnosis of UTI. Patients were classified to those with diabetes mellitus (DM) and those without it. ABG levels were classified to categories: ≤70, 70-110, 111-199, ≥200mg/dl. Primary outcome was all-cause mortality within 30-days and 1-year. Secondary outcomes were hospital readmissions within 30-days and 1-year, and survival rates at end of follow-up.

RESULTS

Cohort included 3405 patients (median age, 78 years; 44% men), 1106 with DM and 2299 without it. Among patients without DM, compared with ABG between 70 and 110mg/dl (n=852, 37%), there was a significant association between ABG and all-cause mortality: hazard ratios (95% CI) with ABG ≤70mg/dl (n=13, 0.6%), 111-199mg/dl (n=1292, 56%), and ≥200mg/dl (n=142, 6%) were: 3.67 (0.89-15.14, p=0.07, 23% mortality (n=3)), 1.85 (1.29-2.64, p<0.001, 7% mortality (n=89)), and 2.94 (1.71-5.07, p<0.0001, 11% mortality (n=15)) at 30-days, and 3.8 (1.87-7.71, 38% mortality (n=5)), 1.35 (1 1.13-1.60, 7% mortality (n=215)), and 2.02 (1.50-2.71, 25% mortality (n=35)) at 1-year (all p<0.001). In patients with DM there was no significant association between ABG and mortality. There was no association between ABG and readmissions in both groups.

CONCLUSION

There is a significant association between ABG and short and long-term, all-cause mortality in patients without DM, but not in patients with DM, hospitalized for UTI.

Relationship between glycated hemoglobin, Intensive Care Unit admission blood sugar and glucose control with ICU mortality in critically ill patients

BACKGROUND AND AIMS

The association between hyperglycemia and mortality is believed to be influenced by the presence of diabetes mellitus (DM). In this study, we evaluated the effect of preexisting hyperglycemia on the association between acute blood glucose management and mortality in critically ill patients. The primary objective of the study was the relationship between HbA1c and mortality in critically ill patients. Secondary objectives of the study were relationship between Intensive Care Unit (ICU) admission blood glucose and glucose control during ICU stay with mortality in critically ill patients.

MATERIALS AND METHODS

Five hundred patients admitted to two ICUs were enrolled. Blood sugar and hemoglobin A1c (HbA1c) concentrations on ICU admission were measured. Age, sex, history of DM, comorbidities, Acute Physiology and Chronic Health Evaluation II score, sequential organ failure assessment score, hypoglycemic episodes, drug history, mortality, and development of acute kidney injury and liver failure were noted for all patients.

RESULTS

Without considering the history of diabetes, nonsurvivors had significantly higher HbA1c values compared to survivors (7.25 ± 1.87 vs. 6.05 ± 1.22, respectively, P < 0.001). Blood glucose levels in ICU admission showed a significant correlation with risk of death (P < 0.006, confidence interval [CI]: 1.004-1.02, relative risk [RR]: 1.01). Logistic regression analysis revealed that HbA1c increased the risk of death; with each increase in HbA1c level, the risk of death doubled. However, this relationship was not statistically significant (P: 0.161, CI: 0.933-1.58, RR: 1.2).

CONCLUSIONS

Acute hyperglycemia significantly affects mortality in the critically ill patients; this relation is also influenced by chronic hyperglycemia.

The Effect of Sustained Inflammation on Hepatic Mevalonate Pathway Results in Hyperglycemia

Control of plasma glucose level is essential to organismal survival. Sustained inflammation has been implicated in control of glucose homeostasis in cases of infection, obesity, and type 2 diabetes; however, the precise role of inflammation in these complex disease states remains poorly understood. Here, we find that sustained inflammation results in elevated plasma glucose due to increased hepatic glucose production. We find that sustained inflammation suppresses CYP7A1, leading to accumulation of intermediate metabolites at the branch point of the mevalonate pathway. This results in prenylation of RHOC, which is concomitantly induced by inflammatory cytokines. Subsequent activation of RHO-associated protein kinase results in elevated plasma glucose. These findings uncover an unexpected mechanism by which sustained inflammation alters glucose homeostasis.

The prevalence of hyperglycaemia and its relationship with mortality, readmissions and length of stay in an older acute surgical population: a multicentre study

BACKGROUND

The purpose of the study is to examine the prevalence of hyperglycaemia in an older acute surgical population and its effect on clinically relevant outcomes in this setting.

METHODS

Using Older Persons Surgical Outcomes Collaboration (OPSOC) multicentre audit data 2014, we examined the prevalence of admission hyperglycaemia, and its effect on 30-day and 90-day mortality, readmission within 30 days and length of acute hospital stay using logistic regression models in consecutive patients, ≥65 years, admitted to five acute surgical units in the UK hospitals in England, Scotland and Wales. Patients were categorised in three groups based on their admission random blood glucose: <7.1, between 7.1 and 11.1 and ≥11.1 mmol/L.

RESULTS

A total of 411 patients (77.25±8.14 years) admitted during May and June 2014 were studied. Only 293 patients (71.3%) had glucose levels recorded on admission. The number (%) of patients with a blood glucose <7.1, 7.1-11.1 and ≥11.1 mmol/L were 171 (58.4), 99 (33.8) and 23 (7.8), respectively. On univariate analysis, admission hyperglycaemia was not predictive of any of the outcomes investigated. Although the characteristics of those with no glucose level were not different from the included sample, 30-day mortality was significantly higher in those who had not had their admission glucose level checked (10.2% vs 2.7%), suggesting a potential type II error.

CONCLUSION

Despite current guidelines, nearly a third of older people with surgical diagnoses did not have their glucose checked on admission highlighting the challenges in prognostication and evaluation research to improve care of older frail surgical patients.

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.

Prevalence and Impact of Unknown Diabetes in the ICU

OBJECTIVES

Many patients with diabetes and their care providers are unaware of the presence of the disease. Dysglycemia encompassing hyperglycemia, hypoglycemia, and glucose variability is common in the ICU in patients with and without diabetes. The purpose of this study was to determine the impact of unknown diabetes on glycemic control in the ICU.

DESIGN

Prospective observational study.

SETTING

Nine ICUs in an academic, tertiary hospital and a hybrid academic/community hospital.

PATIENTS

Hemoglobin A1c levels were ordered at all ICU admissions from March 1, 2011 to September 30, 2013. Electronic medical records were examined for a history of antihyperglycemic medications or International Classification of Diseases, 9th Edition diagnosis of diabetes. Patients were categorized as having unknown diabetes (hemoglobin A1c > 6.5%, without history of diabetes), no diabetes (hemoglobin A1c < 6.5%, without history of diabetes), controlled known diabetes (hemoglobin A1c < 6.5%, with documented history of diabetes), and uncontrolled known diabetes (hemoglobin A1c > 6.5%, with documented history of diabetes).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A total of 15,737 patients had an hemoglobin A1c and medical record evaluable for the history of diabetes, and 5,635 patients had diabetes diagnosed by either medical history or an elevated hemoglobin A1c in the ICU. Of these, 1,460 patients had unknown diabetes, accounting for 26.0% of all patients with diabetes. This represented 41.0% of patients with an hemoglobin A1c > 6.5% and 9.3% of all ICU patients. Compared with patients without diabetes, patients with unknown diabetes had a higher likelihood of requiring an insulin infusion (44.3% vs 29.3%; p < 0.0001), a higher average blood glucose (172 vs 126 mg/dL; p < 0.0001), an increased percentage of hyperglycemia (19.7% vs 7.0%; blood glucose > 180 mg/dL; p < 0.0001) and hypoglycemia (8.9% vs 2.5%; blood glucose < 70 mg/dL; p < 0.0001), higher glycemic variability (55.6 vs 28.8, average of patient SD of glucose; p < 0.0001), and increased mortality (13.8% vs 11.4%; p = 0.01).

CONCLUSIONS

Patients with unknown diabetes represent a significant percentage of ICU admissions. Measurement of hemoglobin A1c at admission can prospectively identify a population that are not known to have diabetes but have significant challenges in glycemic control in the ICU.

The Emory University Perioperative Algorithm for the Management of Hyperglycemia and Diabetes in Non-cardiac Surgery Patients

Hyperglycemia is a frequent manifestation of critical and surgical illness, resulting from the acute metabolic and hormonal changes associated with the response to injury and stress (Umpierrez and Kitabchi, Curr Opin Endocrinol. 11:75-81, 2004; McCowen et al., Crit Care Clin. 17(1):107-24, 2001). The exact prevalence of hospital hyperglycemia is not known, but observational studies have reported a prevalence of hyperglycemia ranging from 32 to 60 % in community hospitals (Umpierrez et al., J Clin Endocrinol Metab. 87(3):978-82, 2002; Cook et al., J Hosp Med. 4(9):E7-14, 2009; Farrokhi et al., Best Pract Res Clin Endocrinol Metab. 25(5):813-24, 2011), and 80 % of patients after cardiac surgery (Schmeltz et al., Diabetes Care 30(4):823-8, 2007; van den Berghe et al., N Engl J Med. 345(19):1359-67, 2001). Retrospective and randomized controlled trials in surgical populations have reported that hyperglycemia and diabetes are associated with increased length of stay, hospital complications, resource utilization, and mortality (Frisch et al., Diabetes Care 33(8):1783-8, 2010; Kwon et al., Ann Surg. 257(1):8-14, 2013; Bower et al., Surgery 147(5):670-5, 2010; Noordzij et al., Eur J Endocrinol. 156(1):137-42, 2007; Mraovic et al., J Arthroplasty 25(1):64-70, 2010). Substantial evidence indicates that correction of hyperglycemia reduces complications in critically ill, as well as in general surgery patients (Umpierrez et al., J Clin Endocrinol Metab. 87(3):978-82, 2002; Clement et al., Diabetes Care 27(2):553-97, 2004; Pomposelli et al., JPEN J Parented Enteral Nutr. 22(2):77-81, 1998). This manuscript reviews the pathophysiology of stress hyperglycemia during anesthesia and the perioperative period. We provide a practical outline for the diagnosis and management of preoperative, intraoperative, and postoperative care of patients with diabetes and hyperglycemia.

Report on Racial Disparities in Hospitalized Patients with Hyperglycemia and Diabetes

CONTEXT

A higher prevalence of diabetes-related complications is reported in minority populations; however, it is not known if there are racial disparities in diabetes care and outcomes in hospitalized patients.

OBJECTIVE

Our objective was to determine the association between hyperglycemia, in patients with and without diabetes mellitus (non-DM), and complications among different racial groups.

DESIGN

This observational study compared the frequency of hyperglycemia (blood glucose ≥ 180 mg/dL; 10 mmol/L) and DM and hospital complications between Black and White patients hospitalized patients between January 2012 and December 2013.

SETTING AND PARTICIPANTS

Adults admitted to medical and surgery services in two academic hospitals were included in this study.

RESULTS

Among 35 866 patients, there were 14 387 Black (40.1%) and 21 479 White patients (59.9%). Blacks had a higher prevalence of hyperglycemia (42.3% vs 36.7%, P < .0001) and DM (34.5% vs 22.8%, P < .0001) and a higher admission rate and mean daily blood glucose (P < .001). Blacks also had higher rates of complications (22.2% vs 19.2%, P < .0001), both in patients with DM (24.7 vs 22.9%, P = .0413) and non-DM with hyperglycemia (41.2% vs 37.2%, P = .0019). Using sequential modelling adjusted for age, gender, body mass index, comorbidities, and insurance coverage, non-DM Blacks with normoglycemia (odds ratio, 1.22; 95% confidence interval, 1.10-1.35) and non-DM Blacks with hyperglycemia (odds ratio, 1.18; 95% confidence interval, 1.04-1.33) had higher number of complications compared to Whites.

CONCLUSIONS

Black patients have higher rates of hyperglycemia and diabetes, worse inpatient glycemic control, and greater frequency of hospital complications compared to Whites. Non-DM Blacks with hyperglycemia are a particularly vulnerable group. Further investigation is needed to better understand factors contributing the racial disparities in the hospital.

Diabetes and the Association of Postoperative Hyperglycemia With Clinical and Economic Outcomes in Cardiac Surgery

OBJECTIVE

The management of postoperative hyperglycemia is controversial and generally does not take into account pre-existing diabetes. We analyzed clinical and economic outcomes associated with postoperative hyperglycemia in cardiac surgery patients, stratifying by diabetes status.

RESEARCH DESIGN AND METHODS

Multicenter cohort study in 4,316 cardiac surgery patients operated on in 2010. Glucose was measured at 6-h intervals for 48 h postoperatively. Outcomes included cost, hospital length of stay (LOS), cardiac and respiratory complications, major infections, and death. Associations between maximum glucose levels and outcomes were assessed with multivariable regression and recycled prediction analyses.

RESULTS

In patients without diabetes, increasing glucose levels were associated with a gradual worsening of outcomes. In these patients, hyperglycemia (≥180 mg/dL) was associated with an additional cost of $3,192 (95% CI 1,972 to 4,456), an additional hospital LOS of 0.8 days (0.4 to 1.3), an increase in infections of 1.6% (0.5 to 2.8), and an increase in respiratory complications of 2.6% (0.0 to 5.3). However, among patients with insulin-treated diabetes, optimal outcomes were associated with glucose levels considered to be hyperglycemic (180 to 240 mg/dL). This level of hyperglycemia was associated with cost reductions of $6,225 (-12,886 to -222), hospital LOS reductions of 1.6 days (-3.7 to 0.4), infection reductions of 4.1% (-9.1 to 0.0), and reductions in respiratory complication of 12.5% (-22.4 to -3.0). In patients with non-insulin-treated diabetes, outcomes did not differ significantly when hyperglycemia was present.

CONCLUSIONS

Glucose levels <180 mg/dL are associated with better outcomes in most patients, but worse outcomes in patients with diabetes with a history of prior insulin use. These findings support further investigation of a stratified approach to the management of patients with stress-induced postoperative hyperglycemia based on prior diabetes status.

Glucose Levels in Patients With Acute Respiratory Failure Requiring Mechanical Ventilation

BACKGROUND

Recent studies suggest that patients with acute exacerbations of chronic obstructive pulmonary disease (COPD) frequently develop hyperglycemia, which has been linked to adverse outcomes.

METHODS

We retrospectively collected information about patient demographics, admission diagnosis, comorbidities, use of insulin, and glucose levels and related tests in 174 patients who required mechanical ventilation for acute respiratory failure.

RESULTS

These patients had a mean age of 57.8 ± 16.8 years, a mean Acute Physiology and Chronic Health Evaluation (APACHE II) score of 13.8 ± 6.1, and an overall mortality of 32.2%. The mean number of ventilator days was 7.5 ± 7.1. The mean highest glucose level was 239.3 ± 88.9 mg/dL in patients with COPD (n = 41) and 259.1 ± 131.7 mg/dL in patients without COPD (n =133). Patients with diabetes had higher glucose levels than patients without this diagnosis ( P < .05). Patients receiving corticosteroids did not have increased glucose levels ( P > .05). The mortality rate was higher in patients with glucose levels >140 mg/dL than in patients below 140 mg/dL (35.1% vs 10.5%, P < .05 unadjusted analysis).

CONCLUSION

In this study, hyperglycemia occurred in 89% of the patients with acute respiratory failure requiring mechanical ventilation. The most important risk factor for this was a premorbid diagnosis of diabetes.

GlycA is a Novel Marker of Inflammation Among Non-Critically Ill Hospitalized Patients with Type 2 Diabetes

GlycA is a nuclear magnetic resonance-derived signal that originates from oligosaccharide chains of acute phase proteins. The objective of this study is to characterize GlycA levels in hospitalized non-critically ill patients with type 2 diabetes. This study evaluated traditional and novel (GlycA) inflammatory markers among 121 patients who were stratified by admission diagnoses: congestive heart failure (CHF), cardiac non-CHF (CARD), infection (INF), and other (OTH). HbA1c was similar across groups (8.0-9.2%, p=0.20). Inflammatory markers were elevated but varied significantly across disease categories, with the highest values of interleukin-6 (IL-6), c-reactive protein (CRP), and GlycA in the INF group and the highest tumor necrosis factor-α and intracellular adhesion molecule-1 levels in CHF group. GlycA was associated with higher IL-6 and CRP, lower hemoglobin, and lower glomerular filtration rate. GlycA and other inflammatory markers were not significantly associated with admission glucose or HbA1c. Among hospitalized non-critically ill patients with type 2 diabetes, GlycA was highest in INF patients and was associated with IL-6 and CRP. None of the markers were significant predictors of glucose control.

Diabetes and infection: assessing the association with glycaemic control in population-based studies

Diabetes is a leading cause of morbidity and mortality. The global burden of diabetes is rising because of increased obesity and population ageing. Although preventive and treatment measures are well documented for macrovascular and microvascular complications, little such guidance exists for infections in people with diabetes, despite evidence suggesting greater susceptibility to infections, and worse outcomes. In particular, few studies have characterised the relation between glycaemic control and infectious disease, which we discuss in this Review. Some large population-based observational studies have reported strong associations between higher HbA1c and infection risks for both type 1 and type 2 diabetes. However, studies are contradictory, underpowered, or do not control for confounders. Evidence suggests that better glycaemic control might reduce infection risk, but further longitudinal studies with more frequent measures of HbA1c are needed. Older people (aged 70 years or older) with diabetes are at increased risk of complications, including infectious diseases. There is more uncertainty about appropriate glycaemic control targets in this age group, and evidence suggests that glycaemic control is often neglected. Robust evidence from cohorts with sufficient numbers of older people would help to develop clinically relevant guidelines and targets to reduce mortality, morbidity, and antibiotic use, and to improve quality of life.

Metabolic Correction in Patients Sample with Diabetes: Clinical Outcomes and Costs Reductions

Diabetes is a leading cause of mortality and morbidity worldwide. Diabetes complications produce profound impact on patient's quality of life and represent very significant economic cost to patients, their family, the government and society as a whole. Metabolic correction has been proposed as an efficient method to improve clinical outcomes and reduce costs in diabetes. Metabolic correction is a concept that supports health maintenance and promotes the healing processes by improving the body's biochemical-physiological mechanisms. This is done by helping activate the metabolic enzymes necessary to facilitate key physiological pathways. A group of 50 patients followed a simple metabolic correction strategy based on hydration, diet, and magnesium supplementation during a 6 months period. Outcomes measures included laboratory testing, anthropometric measures and medication use including its related costs. Patients had an average weight loss of 9.4 lbs (↓5.0%) from baseline at month 3 and 12 lbs (↓6.4%) at month 6. Waist circumference decreased on average 3.7 inches (↓9.0%) from baseline at month 3 and had further decrease to 5.5 inches (↓13.4%) from baseline at month 6. Laboratory testing of average triglycerides decreased from a baseline of 156.9 to 116.7 (↓25.6%) at month 3 and maintained a reduction of ↓24.2% by month 6. Total cholesterol concentration decreased from a baseline of 181.1 mg/dL to 173.9 (↓4.0%) in month 3 and to 171.1 (↓5.5%) at month 6. Average HgA1c decreased from baseline of 7.17 to 6.52 (↓9.1%) at month 3 and maintained 6.52 at months 6. The atherogenic index decreased from 4.18 at baseline to 3.85 at month 3 (↓7.9%) and then 3.47 (17.0%) at month 6. Medication use and cost was quantified in various ways. The average baseline monthly diabetes medication cost per patient of $124.10 was reduced to $ 78.23 (↓36.7% reduction) at month 3 and to $62.80 (↓49.4% reduction) at month 6. A simple and well structured metabolic correction program that includes a significant educational component, dietary modifications and dietary supplement intake was able to maintain or improve vital signs, anthopometric and laboratory measurements that correlate with improved clinical diabetes and cardiovascular health. This outcome was achieved while decreasing the use medications at month 3 and 6 at significant cost savings.

Relative Hyperglycemia, a Marker of Critical Illness: Introducing the Stress Hyperglycemia Ratio

CONTEXT

Hyperglycemia in hospitalized patients is associated with increased morbidity and mortality.

OBJECTIVE

We examined whether critical illness is more strongly associated with relative or absolute hyperglycemia.

DESIGN

The study was an observational cohort study.

PATIENTS AND SETTING

A total of 2290 patients acutely admitted to a tertiary hospital.

MAIN OUTCOME MEASURE

The relative hyperglycemia (stress hyperglycemia ratio [SHR]) was defined as admission glucose divided by estimated average glucose derived from glycosylated hemoglobin. The relationships between glucose and SHR with critical illness (in-hospital death or critical care) were examined.

RESULTS

In univariable analyses, SHR (odds ratio, 1.23 per 0.1 increment [95% confidence interval, 1.18-1.28]; P < .001) and glucose (odds ratio, 1.18 per mmol/L [1.13-1.23]; P < .001) were associated with critical illness. In multivariable analysis, the association was maintained for SHR (odds ratio, 1.20 per 0.1 increment [1.13-1.28]; P < .001), but not glucose (odds ratio, 1.03 per mmol/L [0.97-1.11]; P = .31). Background hyperglycemia affected the relationship between glucose (P = .002) and critical illness, but not SHR (P = .35) and critical illness. In patients with admission glucose ≤ 10 mmol/L, the odds ratio for critical illness was higher in the fourth (2.4 [1.4-4.2]; P = .001) and fifth (3.9 [2.3-6.8]; P < .001) SHR quintiles than in the lowest SHR quintile.

CONCLUSIONS

SHR controls for background glycemia and is a better biomarker of critical illness than absolute hyperglycemia. SHR identifies patients with relative hyperglycemia at risk of critical illness. Future studies should explore whether basing glucose-lowering therapy on relative, rather than absolute, hyperglycemia improves outcomes in hospitalized patients.

Comparison of Basal-Bolus and Premixed Insulin Regimens in Hospitalized Patients With Type 2 Diabetes

OBJECTIVE

Premixed insulin is a commonly prescribed formulation for the outpatient management of patients with type 2 diabetes. The safety and efficacy of premixed insulin formulations in the hospital setting is not known.

RESEARCH DESIGN AND METHODS

In a prospective, open-label trial, we randomized general medicine and surgery patients to receive a basal-bolus regimen with glargine once daily and glulisine before meals (n = 33) or premixed human insulin (30% regular insulin and 70% NPH insulin) twice daily (n = 39). Major outcomes included differences in daily blood glucose (BG) levels and frequency of hypoglycemic events (<70 mg/dL) between treatment groups.

RESULTS

At the first prespecified interim analysis, the study was stopped early because of an increased frequency of hypoglycemia >50% in patients treated with premixed human insulin. A total of 64% of patients treated with premixed insulin experienced one or more episodes of hypoglycemia compared with 24% in the basal-bolus group (P < 0.001). There were no differences in mean daily BG level after the first day of insulin treatment (175 ± 32 vs. 179 ± 43 mg/dL, P = 0.64) between groups. A BG target between 80 and 180 mg/dL before meals was achieved in 55.9% of BG readings in the basal-bolus group and 54.3% of BG readings in the premixed insulin group (P = 0.23). There was no difference in the length of hospital stay or mortality between treatment groups.

CONCLUSIONS

Inpatient treatment with premixed human insulin resulted in similar glycemic control but in significantly higher frequency of hypoglycemia compared with treatment with basal-bolus insulin regimen in hospitalized patients with diabetes.

Hyperglycemia grand rounds: descriptive findings of outcomes from a continuing education intervention to improve glycemic control and prevent hypoglycemia in the hospital setting

Hyperglycemia is common in the hospital in-patient setting and is associated with adverse outcomes. Healthcare professionals (HCPs) often fail to use best practices established to manage this condition or to coordinate care among team members.

OBJECTIVES

The objective of the Hyperglycemia Grand Rounds (HGR) continuing education initiative was to improve knowledge levels in a team setting, leading to improved clinical competence, evidence-based behaviors, and improved patient care.

METHODS

To achieve that goal, a four-module seminar series was presented to HCPs on-site in a "Grand Rounds" format at healthcare institutions across the United States. Outcomes data included satisfaction, learning, impact, and intent-to-implement measures at event time and at follow-up. At the site level, detailed questionnaires assessed skill gaps and expected outcomes from administrators at the time the modules were scheduled and the impact after modules were completed. Demographic information allowed identification of HCPs receiving maximum benefits; data on barriers to implementation are reported.

RESULTS

Seventy-eight percent of participants self-reported a positive impact on competence, performance, or patient outcomes. Forty percent of learners said they intended to make specific changes in practices. Eighty-two percent of administrators confirmed expected changes in their health system. The follow-up study concurred with the initial findings.

CONCLUSION

The HGR was an effective program in improving self-reported competence amongst attendees that could potentially lead to improved care. This descriptive report summarizes outcomes from 1 year of educational efforts to more than 2000 healthcare professionals.

Usefulness of Glycemic Gap to Predict ICU Mortality in Critically Ill Patients With Diabetes

Stress-induced hyperglycemia (SIH) has been independently associated with an increased risk of mortality in critically ill patients without diabetes. However, it is also necessary to consider preexisting hyperglycemia when investigating the relationship between SIH and mortality in patients with diabetes. We therefore assessed whether the gap between admission glucose and A1C-derived average glucose (ADAG) levels could be a predictor of mortality in critically ill patients with diabetes.We retrospectively reviewed the Acute Physiology and Chronic Health Evaluation II (APACHE-II) scores and clinical outcomes of patients with diabetes admitted to our medical intensive care unit (ICU) between 2011 and 2014. The glycosylated hemoglobin (HbA1c) levels were converted to the ADAG by the equation, ADAG = [(28.7 × HbA1c) - 46.7]. We also used receiver operating characteristic (ROC) curves to determine the optimal cut-off value for the glycemic gap when predicting ICU mortality and used the net reclassification improvement (NRI) to measure the improvement in prediction performance gained by adding the glycemic gap to the APACHE-II score.We enrolled 518 patients, of which 87 (17.0%) died during their ICU stay. Nonsurvivors had significantly higher APACHE-II scores and glycemic gaps than survivors (P < 0.001). Critically ill patients with diabetes and a glycemic gap ≥80 mg/dL had significantly higher ICU mortality and adverse outcomes than those with a glycemic gap <80 mg/dL (P < 0.001). Incorporation of the glycemic gap into the APACHE-II score increased the discriminative performance for predicting ICU mortality by increasing the area under the ROC curve from 0.755 to 0.794 (NRI = 13.6%, P = 0.0013).The glycemic gap can be used to assess the severity and prognosis of critically ill patients with diabetes. The addition of the glycemic gap to the APACHE-II score significantly improved its ability to predict ICU mortality.

Glucose management in critically ill adults and children

Blood glucose management in people with acute myocardial infarction and critical illness has always attracted controversy. Compared with the era before 2001 when no attention was given to blood glucose management, DIGAMI-1 in 1995 and the first Leuven study in 2001 showed improved outcomes with strict control of blood glucose, thereby suggesting a causal association between hyperglycaemia and mortality risk. These landmark trials have set the standard in clinical practice that excessive hyperglycaemia is not acceptable. Multicentre trials contradicted the benefits of tight control of patients' blood glucose and results showed that different standard operating procedures for blood glucose control (eg, blood glucose meters or algorithms), divergent concomitant feeding strategies, and varying patient populations are important confounders. The general consensus now is that excessive hyperglycaemia (>10 mmol/L) and severe hypoglycaemia (<2·2 mmol/L) should be avoided in critically ill adults. If adequate blood glucose meters and clinically validated protocols for insulin-dosing are available, targeting of blood glucose concentrations to less than 8 mmol/L (moderate glycaemic control), while avoiding mild hypoglycaemia (<3·9 mmol/L), is a reasonable strategy in adult patients who are critically ill. This recommendation is not based on findings from randomised controlled trials, but merely represents a very common, pragmatic approach by physicians at the bedside. As a result of the few properly validated technologies for tighter blood glucose control, targeting blood glucose concentrations to less than 6 mmol/L is not recommended, because its risk-to-benefit ratio becomes questionable. Because blood glucose control in the target of adult ranges does not improve patient outcomes for children in the intensive care unit, glucose management in this patient population should be limited to avoid excessive hyperglycaemia (>10 mmol/L).

Randomized Controlled Trial of Intensive Versus Conservative Glucose Control in Patients Undergoing Coronary Artery Bypass Graft Surgery: GLUCO-CABG Trial

OBJECTIVE

The optimal level of glycemic control needed to improve outcomes in cardiac surgery patients remains controversial.

RESEARCH DESIGN AND METHODS

We randomized patients with diabetes (n = 152) and without diabetes (n = 150) with hyperglycemia to an intensive glucose target of 100-140 mg/dL (n = 151) or to a conservative target of 141-180 mg/dL (n = 151) after coronary artery bypass surgery (CABG) surgery. After the intensive care unit (ICU), patients received a single treatment regimen in the hospital and 90 days postdischarge. Primary outcome was differences in a composite of complications, including mortality, wound infection, pneumonia, bacteremia, respiratory failure, acute kidney injury, and major cardiovascular events.

RESULTS

Mean glucose in the ICU was 132 ± 14 mg/dL (interquartile range [IQR] 124-139) in the intensive and 154 ± 17 mg/dL (IQR 142-164) in the conservative group (P < 0.001). There were no significant differences in the composite of complications between intensive and conservative groups (42 vs. 52%, P = 0.08). We observed heterogeneity in treatment effect according to diabetes status, with no differences in complications among patients with diabetes treated with intensive or conservative regimens (49 vs. 48%, P = 0.87), but a significant lower rate of complications in patients without diabetes treated with intensive compared with conservative treatment regimen (34 vs. 55%, P = 0.008).

CONCLUSIONS

Intensive insulin therapy to target glucose of 100 and 140 mg/dL in the ICU did not significantly reduce perioperative complications compared with target glucose of 141 and 180 mg/dL after CABG surgery. Subgroup analysis showed a lower number of complications in patients without diabetes, but not in patients with diabetes treated with the intensive regimen. Large prospective randomized studies are needed to confirm these findings.

COMPARISON OF BASAL INSULIN REGIMENS ON GLYCEMIC VARIABILITY IN NONCRITICALLY ILL PATIENTS WITH TYPE 2 DIABETES

OBJECTIVE

To evaluate the impact of different subcutaneous basal insulin regimens on glycemic variability (GV) and hospital complications in non-intensive care unit (ICU) patients with type 2 diabetes (T2D).

METHODS

This study is a post hoc analysis of 279 general medicine and surgery patients treated with either a "Basal Bolus" insulin regimen using glargine once daily and glulisine before meals or a "Basal Plus" regimen using glargine once daily plus correction doses of glulisine before meals for glucose >140 mg/dL. GV was calculated as mean delta (Δ) daily glucose, mean SD, and mean amplitude of glycemic excursions (MAGE).

RESULTS

Treatment with Basal Bolus and Basal Plus regimens resulted in similar mean daily glucose, hypoglycemia, length of stay (LOS), and hospital complications (all P>.05). There were no differences in GV between treatment groups by Δ change (72.5 ± 36 vs. 69.3 ± 34 mg/dL), SD (38.5 ± 18 vs. 37.1 ± 16 mg/dL) and MAGE (67.5 ± 34 vs. 66.1 ± 39 mg/dL) (all P>.05). Surgery patients treated with Basal Bolus had higher GV compared to those treated with Basal Plus (Δ daily glucose and SD: P = .02, MAGE: P = .009), but no difference in GV was found between treatment groups for the general medicine patients (P>.05). Patients with hypoglycemia events had higher GV compared to subjects without hypoglycemia (P<.05), but no association was found between GV and hospital complications (P>.05).

CONCLUSION

Treating hospitalized, non-ICU, diabetic patients with Basal Plus insulin regimen resulted in similar glucose control and GV compared to the standard Basal Bolus insulin regimen. Higher GV was not associated with hospital complications.

Glucose control in critical care

Glycemic control among critically-ill patients has been a topic of considerable attention for the past 15 years. An initial focus on the potentially deleterious effects of hyperglycemia led to a series of investigations regarding intensive insulin therapy strategies that targeted tight glycemic control. As knowledge accumulated, the pursuit of tight glycemic control among critically-ill patients came to be seen as counterproductive, and moderate glycemic control came to dominate as the standard practice in intensive care units. In recent years, there has been increased focus on the importance of hypoglycemic episodes, glycemic variability, and premorbid diabetic status as factors that contribute to outcomes among critically-ill patients. This review provides a survey of key studies on glucose control in critical care, and aims to deliver perspective regarding glycemic management among critically-ill patients.

Glycemic Variation in Tumor Patients with Total Parenteral Nutrition

Background:

Hyperglycemia is associated with poor clinical outcomes and mortality in several patients. However, studies evaluating hyperglycemia variation in tumor patients receiving total parenteral nutrition (TPN) are scarce. The aim of this study was to assess the relationship between glycemia and tumor kinds with TPN by monitoring glycemic variation in tumor patients.

Methods:

This retrospective clinical trial selected 312 patients with various cancer types, whose unique nutrition treatment was TPN during the monitoring period. All patients had blood glucose (BG) values assessed at least six times daily during the TPN infusion. The glycemic variation before and after TPN was set as the indicator to evaluate the factors influencing BG.

Results:

The clinical trial lasted 7.5 ± 3.0 days adjusted for age, gender, family cancer history and blood types. There were six cancer types: Hepatic carcinoma (HC, 21.8%), rectal carcinoma (17.3%), colon carcinoma (CC, 14.7%), gastric carcinoma (29.8%), pancreatic carcinoma (11.5%), and duodenal carcinoma (DC, 4.8%). The patients were divided into diabetes and nondiabetes groups. No statistical differences in TPN glucose content between diabetes and nondiabetes groups were found; however, the tumor types affected by BG values were obvious. With increasing BG values, DC, HC and CC were more represented than other tumor types in this sequence in diabetic individuals, as well as in the nondiabetic group. BG was inclined to be more easily influenced in the nondiabetes group. Other factors did not impact BG values, including gender, body mass index, and TPN infusion duration time.

Conclusions:

When tumor patients are treated with TPN, BG levels should be monitored according to different types of tumors, besides differentiating diabetes or nondiabetes patients. Special BG control is needed for DC, HC and CC in both diabetic and nondiabetic patients. If BG overtly increases, positive measurements are needed to control BG values. The ClinicalTrials.gov ID is NCT02024321.

Reporting on Glucose Control Metrics in the Intensive Care Unit

The 'diabetes of injury' typically associated with critical illness has recently been thoroughly revisited and much better characterised following major therapeutic advances. The occurrence of severe hyperglycaemia, moderate hypoglycaemia or high glycaemic variability has been associated with an increased mortality and rate of complications in large independent cohorts of acutely ill patients. Hence, current guidelines advocate the prevention and avoidance of each of these three dysglycaemic domains, and the use of a common metrics for a quantitative description of dysglycaemic events, such as the proportion of time spent in the target glycaemic range as a unifying variable. Using a common language will help to face the future challenges, including the definition of the most appropriate blood glucose (BG) target according to the category of admission, the time interval from the initial injury and the medical history. The clinical testing of technological improvements in the monitoring systems and the therapeutic algorithms should be assessed using the same metrics.