Organ failure and tight glycemic control in the SPRINT study

Threshold of hyperglycaemia associated with mortality in critically ill patients: a multicentre, prospective, observational study using continuous glucose monitoring

AIMS/HYPOTHESIS

Continuous glucose monitoring (CGM) provides comprehensive information on the exposure to dysglycaemia. This study aimed to investigate the threshold of hyperglycaemia related to mortality risk in critically ill patients using CGM technology.

METHODS

A total of 293 adult critically ill patients admitted to intensive care units of five medical centres were prospectively included between May 2020 and November 2021. Participants wore intermittently scanned CGM for a median of 12.0 days. The relationships between different predefined time above ranges (TARs), with the thresholds of hyperglycaemia ranging from 7.8 to 13.9 mmol/l (140-250 mg/dl), and in-hospital mortality risk were assessed by multivariate Cox proportional regression analysis. Time in ranges (TIRs) of 3.9 mmol/l (70 mg/dl) to the predefined hyperglycaemic thresholds were also assessed.

RESULTS

Overall, 66 (22.5%) in-hospital deaths were identified. Only TARs with a threshold of 10.5 mmol/l (190 mg/dl) or above were significantly associated with the risk of in-hospital mortality, after adjustment for covariates. Furthermore, as the thresholds for TAR increased from 10.5 mmol/l to 13.9 mmol/l (190 mg/dl to 250 mg/dl), the hazards of in-hospital mortality increased incrementally with every 10% increase in TARs. Similar results were observed concerning the associations between TIRs with various upper thresholds and in-hospital mortality risk. For per absolute 10% decrease in TIR 3.9-10.5 mmol/l (70-190 mg/dl), the risk of in-hospital mortality was increased by 12.1% (HR 1.121 [95% CI 1.003, 1.253]).

CONCLUSIONS/INTERPRETATION

A glucose level exceeding 10.5 mmol/l (190 mg/dl) was significantly associated with higher risk of in-hospital mortality in critically ill patients.

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.

Classification-based deep neural network vs mixture density network models for insulin sensitivity prediction problem

Model-based glycemic control (GC) protocols are used to treat stress-induced hyperglycaemia in intensive care units (ICUs). The STAR (Stochastic-TARgeted) glycemic control protocol - used in clinical practice in several ICUs in New Zealand, Hungary, Belgium, and Malaysia - is a model-based GC protocol using a patient-specific, model-based insulin sensitivity to describe the patient's actual state. Two neural network based methods are defined in this study to predict the patient's insulin sensitivity parameter: a classification deep neural network and a Mixture Density Network based method. Treatment data from three different patient cohorts are used to train the network models. Accuracy of neural network predictions are compared with the current model- based predictions used to guide care. The prediction accuracy was found to be the same or better than the reference. The authors suggest that these methods may be a promising alternative in model-based clinical treatment for patient state prediction. Still, more research is needed to validate these findings, including in-silico simulations and clinical validation trials.

Association between time in range 70-180 mg/dl in early stage and severity with in patients acute pancreatitis

BACKGROUND

It is not well understood whether glucose control in the early stage of acute pancreatitis(AP) is related to outcome. This study aimed to investigate the association between blood glucose time in range (TIR) of 70-180 mg/dL in the first 72 h(h) on admission and the progression of AP.

METHODS

Individuals admitted with AP to the Gastroenterology Department of the Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University between January 2017 and December 2021 were included and retrospectively evaluated. The percentage of TIR between 70 and 180 mg/dL in the first 72 h was calculated. According to the progress of AP at discharge, patients were divided into mild pancreatitis(MAP), and moderately severe acute pancreatitis (MSAP), or severe acute pancreatitis (SAP) groups. We examined the association between TIR or TIR ≥ 70% and AP severity using logistic regression models stratified by a glycosylated hemoglobin (HbA1c) level of 6.5%. Receiver operating characteristic (ROC) curves were generated to assess the ability of the TIR to predict MSAP or SAP.

RESULTS

A total of 298 individuals were included, of whom 35 developed MSAP or SAP. Logistic regression analyses indicated that TIR was independently associated with the incidence of more serious AP (odds ratio [OR] = 0.962, 95% CI = 0.941-0.983, p = 0.001). This association remained significant in individuals with HbA1c levels ≤ 6.5% (OR = 0.928, 95% CI = 0.888-0.969, p = 0.001). A TIR ≥ 70% was independently associated with reduced severity only in people with well-antecedent controls (OR = 0.238; 95% CI = 0.071-0.802; p = 0.020). TIR was not powerful enough to predict the severity of AP in both patients with poor antecedent glucose control (AUC = 0.641) or with HbA1c < 6.5% (AUC = 0.668).

CONCLUSIONS

TIR was independently associated with severity in patients with AP, particularly those with good antecedent glucose control.

Model-based subcutaneous insulin for glycemic control of pre-term infants in the neonatal intensive care unit

Hyperglycaemia is a common problem in neonatal intensive care units (NICUs). Achieving good control can result in better outcomes for patients. However, good control is difficult, where poor control and resulting hypoglycaemia reduces outcomes and confounds results. Clinically validated models can provide good control, and subcutaneous insulin delivery can provide more options for insulin therapy for clinicians. However, this combination has only been significantly utilised in adult outpatient diabetes, but could hold benefit for treating NICU infants. This research combines a well-validated NICU metabolic model with subcutaneous insulin kinetics models to assess the feasibility of a model-based approach. Clinical data from 12 very/extremely pre-mature infants was collected for an average study duration of 10.1 days. Blood glucose, interstitial and plasma insulin, as well as subcutaneous and local insulin were modelled, and patient-specific insulin sensitivity profiles were identified for each patient. Modelling error was low, where the cohort median [IQR] mean percentage error was 0.8 [0.3 3.4] %. For external validation, insulin sensitivity was compared to previous NICU cohorts using the same metabolic model, where overall levels of insulin sensitivity were similar. Overall, the combined system model accurately captured observed glucose and insulin dynamics, showing the potential for a model-based approach to glycaemic control using subcutaneous insulin in this cohort. The results justify further model validation and clinical trial research to explore a model-based protocol.

Feeding intolerance in critically ill patients with COVID-19

BACKGROUND & AIMS

Early reports suggest significant difficulty with enteral feeding in critically ill COVID-19 patients. This study aimed to characterize the prevalence, clinical manifestations, and outcomes of feeding intolerance in critically ill patients with COVID-19.

METHODS

We examined 323 adult patients with COVID-19 admitted to the intensive care units (ICUs) of Massachusetts General Hospital between March 11 and June 28, 2020 who received enteral nutrition. Systematic chart review determined prevalence, clinical characteristics, and hospital outcomes (ICU complications, length of stay, and mortality) of feeding intolerance.

RESULTS

Feeding intolerance developed in 56% of the patients and most commonly manifested as large gastric residual volumes (83.9%), abdominal distension (67.2%), and vomiting (63.9%). Length of intubation (OR 1.05, 95% CI 1.03-1.08), ≥1 GI symptom on presentation (OR 0.76, 95% CI 0.59-0.97), and severe obesity (OR 0.29, 95% CI 0.13-0.66) were independently associated with development of feeding intolerance. Compared to feed-tolerant patients, patients with incident feeding intolerance were significantly more likely to suffer cardiac, renal, hepatic, and hematologic complications during their hospitalization. Feeding intolerance was similarly associated with poor outcomes including longer ICU stay (median [IQR] 21.5 [14-30] vs. 15 [9-22] days, P < 0.001), overall hospitalization time (median [IQR] 30.5 [19-42] vs. 24 [15-35], P < 0.001) and in-hospital mortality (33.9% vs. 16.1%, P < 0.001). Feeding intolerance was independently associated with an increased risk of death (HR 3.32; 95% CI 1.97-5.6).

CONCLUSIONS

Feeding intolerance is a frequently encountered complication in critically ill COVID-19 patients in a large tertiary care experience and is associated with poor outcomes.

Estimating Enhanced Endogenous Glucose Production in Intensive Care Unit Patients with Severe Insulin Resistance

BACKGROUND

Critically ill ICU patients frequently experience acute insulin resistance and increased endogenous glucose production, manifesting as stress-induced hyperglycemia and hyperinsulinemia. STAR (Stochastic TARgeted) is a glycemic control protocol, which directly manages inter- and intra- patient variability using model-based insulin sensitivity (SI). The model behind STAR assumes a population constant for endogenous glucose production (EGP), which is not otherwise identifiable.

OBJECTIVE

This study analyses the effect of estimating EGP for ICU patients with very low SI (severe insulin resistance) and its impact on identified, model-based insulin sensitivity identification, modeling accuracy, and model-based glycemic clinical control.

METHODS

Using clinical data from 717 STAR patients in 3 independent cohorts (Hungary, New Zealand, and Malaysia), insulin sensitivity, time of insulin resistance, and EGP values are analyzed. A method is presented to estimate EGP in the presence of non-physiologically low SI. Performance is assessed via model accuracy.

RESULTS

Results show 22%-62% of patients experience 1+ episodes of severe insulin resistance, representing 0.87%-9.00% of hours. Episodes primarily occur in the first 24 h, matching clinical expectations. The Malaysian cohort is most affected. In this subset of hours, constant model-based EGP values can bias identified SI and increase blood glucose (BG) fitting error. Using the EGP estimation method presented in these constrained hours significantly reduced BG fitting errors.

CONCLUSIONS

Patients early in ICU stay may have significantly increased EGP. Increasing modeled EGP in model-based glycemic control can improve control accuracy in these hours. The results provide new insight into the frequency and level of significantly increased EGP in critical illness.

Impact of time in range during hospitalization on clinical outcomes in diabetic patients with toe amputation: a propensity score matching analysis

Purpose

In recent years, time in range (TIR), defined as a percentage within a target time range, has attracted much attention. This study was aimed to investigate the short-term effects of Time in Rang on diabetic patients undergoing toe amputation in a more specific and complete manner.

Methods

A retrospective analysis on patients with diabetic foot ulcer (DFU) treated by toe amputation or foot amputation at the First Affiliated Hospital of Wenzhou Medical University between January 2015 and December 2019 were evaluated. A 1:1 match was conducted between the TIR < 70% group and the TIR ≥ 70% group using the nearest neighbor matching algorithm. Data were analyzed using Chi-squared, Fisher’s exact, and Mann–Whitney U tests.

Results

Compared with patients in the TIR ≥ 70% group, patients in the TIR < 70% had a higher rate of re-amputation, and a higher rate of postoperative infection. Multivariate analysis revealed that smoking, lower extremity arterial disease and TIR < 70% were risk factors for surgery of re-amputation. The results of subgroup analysis found that the TIR < 70% was associated with a greater risk of re-amputation in patients with HbA1c < 7.5%, lower extremity arterial disease, and non-smokers.

Conclusions

TIR can be used as a short-term glycemic control indicator in patients with DFUs and should be widely accepted in clinical practice. However, a future multicenter prospective study is needed to determine the relationship between TIR and toe re-amputation in diabetic foot patients.

Relationship Between Glucose Time in Range in Diabetic and Non-Diabetic Patients and Mortality in Critically Ill Patients

Background: Shorter time spent in specific blood glucose ranges is associated with mortality benefit in critically ill patients. However, various time in range values are reported, each based on a specific blood glucose range. Objective: To evaluate relationship between percentage of time spent at various blood glucose ranges (TIR) and mortality in critically ill patients. Methods: Single-center, retrospective, cohort study that included adult patients admitted to ICU for at least one day. We evaluated the relationship between TIR at prespecified blood glucose ranges and hospital mortality in diabetic and non-diabetic patients Results: Of the 5287 patients included, 3705 (70.0%) were non-diabetic and 1582 were diabetic (29.9%). Diabetic patients had higher in-hospital mortality rate (15.8%) compared to non-diabetic patients (11.3%), p < 0.0001, and with higher incidence of hyperglycemia (77.8% vs. 39.4%) and hypoglycemia (14.3% vs. 10%) compared to non-diabetic patients, p < 0.0001. The highest median TIR for both diabetic [76% (49.1 − 97.8%)] and non-diabetic patients [100% (92.3--100%)] was at blood glucose range of 70-180 mg/dL. In non-diabetic cohort, the only optimal TIR of 40% at blood glucose range of 70-120 mg/dL was identified. Non-diabetic patients stratified into TIR 70-120 mg/dL > 40% reported significantly lower mortality (7.0%) rate compared to patients with TIR 70-120 mg/dL < 40% (15.7%), OR 0.52, 95% CI 0.27-0.97, adjusted-p = 0.03. In diabetic patients, no relationship was detected between TIR at all predefined glucose ranges and hospital mortality. Conclusion: Critically ill non-diabetic patients who spent at least 40% of time in blood glucose range of 70-120 mg/dL had improved survival. This association was not observed in diabetic patients.

Association of time in range with postoperative wound healing in patients with diabetic foot ulcers

Time in range (TIR) is a novel indicator of glycaemic control that has been reported to have an association with diabetic complications. The objective of the study was to explore the association of TIR with postoperative wound healing in patients with diabetic foot ulcers (DFUs). We retrospectively analysed the data of DFU patients who had undergone surgical treatment from 2015 to 2019. A 1:1 ratio in propensity score matching (PSM) was adopted to compare patients with TIR ≥50% with those <50%. Data were summarised using chi-squared, Fisher's exact, and Mann-Whitney U tests. Patients with TIR <50% underwent a higher rate of secondary surgery within a month (P = .032) and had a longer hospital stay (P = .045) with greater hospital charges (P < .001) than the TIR ≥50% group. Multivariate analysis revealed that TIR (P = .034), Wagner score (P = .009), diabetes treatment (P = .006), and type of surgery (P = .013) were independent risk factors for secondary surgery. Additionally, patient subgroups with TIR <50% and baseline HbA1c < 7.5% (P = .025), albumin level ≥ 30 g/L (P = .039), HDL < 1.16 (P = .021), or Wagner score ≥ 3 (P = .048) also experienced a higher incidence of secondary surgery. TIR was correlated with postoperative wound healing in patients with DFUs. Strict glycaemic targets should be established for surgical patients.

Estimating Increased EGP During Stress Response in Critically Ill Patients

BACKGROUND

Stress-induced hyperglycemia is frequently experienced by critically ill patients and the use of glycemic control (GC) has been shown to improve patient outcomes. For model-based approaches to GC, it is important to understand and quantify model parameter assumptions. This study explores endogenous glucose production (EGP) and the use of a population-based parameter value in the intensive care unit context.

METHOD

Hourly insulin sensitivity (SI) was fit to clinical data from 145 patients on the Specialized Relative Insulin and Nutrition Titration GC protocol for at least 24 hours. Constraint of SI at a lower bound was used to explore likely EGP variability due to stress response. Minimum EGP was estimated during times when the model SI was constrained, and time and duration of events were examined.

RESULTS

Constrained events occur for 1.6% of patient hours. About 70% of constrained events occur in the first 12 hours and most events (~80%) occur when there is no exogenous nutrition given. Enhanced EGP values ranged from 1.16 mmol/min (current population value) to 2.75 mmol/min, with most being below 1.5 mmol/min (21% increase).

CONCLUSION

The frequency of constrained events is low and the current population value of 1.16 mmol/min is sufficient for more than 98% of patient hours, however, some patients experience significantly raised EGP probably due to an extreme stress response early in patient stay.

Association of specialized enteral nutrition with glycemic control and clinical outcomes in critically ill patients: A meta-analysis of randomized controlled trials

OBJECTIVE

To evaluate the association of glycemic-control formulae (GCF) with measurements of glycemic control and clinical outcomes compared to standard enteral formulae (SF) in critically ill patients.

DATA SOURCES

MEDLINE, EMBASE, Scopus and the Cochrane Central Register of Controlled Trials were searched from inception up to January, 2021.

STUDY SELECTION

RCTs that assessed the effects of GCF relative to SF in adult critically ill patients.

DATA EXTRACTION

Measurements of glycemic control were the primary outcomes. Secondary outcomes included insulin requirements, mechanical ventilation (MV), length of intensive care unit (ICU) stay and mortality. Two authors independently extracted data and assessed risk of bias using the Cochrane's RoB 2 tool and the GRADE approach was used to assess the quality of evidence.

DATA SYNTHESIS

Ten studies (12 reports, 685 patients) were included. The use of GCFs was associated with lower blood glucose (WMD, -16.06 mg/dL; 95% CI -23.48 to -8.63; I² = 47%) and lower daily administered insulin (WMD, -7.20 IU; 95% CI -13.92 to -0.48; I² = 53%). Glycemic variability, measured by the coefficient of variation, was also associated with the use of GCFs (WMD, -6.84%; 95% CI, -13.57 to -0.11; I² = 95%). In contrast, analyses for length of ICU stay (WMD, -0.12, 95% CI -1.77 to 1.52; I² = 0%), duration of MV (WMD, -0.34 days; 95% CI, -1.72 to 1.04; I² = 0%) and mortality (RR, 1.13; 95% CI 0.82 to 1.56; I² = 0%) were not statistically significant. Quality of evidence ranged from low to very low, and only one study was judged as at low risk of bias.

CONCLUSIONS

In this meta-analysis, GCFs were significantly associated with lower insulin requirements and improved glycemic control. Although results for clinical outcomes were not statistically significant, there is insufficient evidence to confirm or exclude important differences due to serious imprecision in the effect estimates and overall low quality of evidence. The effects of GCFs on clinical outcomes require confirmation in larger randomized trials.

High Inter-Patient Variability in Sepsis Evolution: A Hidden Markov Model Analysis

BACKGROUND

Severe sepsis and septic shock are common in the intensive care unit (ICU) and contribute significantly to cost and mortality. Early treatment is critical but is confounded by the difficulty of real-time diagnosis. This study uses hidden Markov models (HMMs) to examine whether the time evolution of sepsis can add diagnostic accuracy or value using a proven set of bio-signals.

METHODS

Clinical data (N=36 patients; 6071 hours), including an hourly personalised insulin sensitivity metric. A two hidden state HMM is created to discriminate diagnosed cases (Severe Sepsis, Septic Shock) from controls (SIRS, Sepsis) states. Diagnostic performance is measured by ROC curves, likelihood ratios (LHRs), sensitivity/specificity, and diagnostic odds-ratios (DOR), for a best-case resubstitution estimate and a worst-case 80/20% repeated holdout analysis.

RESULTS

The HMM delivered near perfect results (95% Sensitivity; 96% Specificity) for best-case resubstitution estimates, but was comparatively poor (59% Sensitivity; 61% Specificity) for worst-case repeated holdout estimations. Adding the time evolution of sepsis did not add to the accuracy of diagnosis from using the signals alone without time history.

CONCLUSIONS

These potentially surprising results indicate significant inter-patient variability in the time evolution of sepsis, preventing effective diagnosis in the context of the bio-signals, data, and HMM topology used. Efforts for improved real-time, early sepsis diagnosis should concentrate on the robustness and efficacy of the bio-signals and data used, as well as the level of model complexity, to create more effective real-time classifiers.

Fifteen-minute Frequency of Glucose Measurements and the Use of Threshold Alarms: Impact on Mitigating Dysglycemia in Critically Ill Patients

BACKGROUND

The use of near-continuous blood glucose (BG) monitoring has the potential to improve glycemic control in critically ill patients. The MANAGE IDE trial evaluated the performance of the OptiScanner (OS) 5000 in a multicenter cohort of 200 critically ill patients.

METHODS

An Independent Group reviewed the BG run charts of all 200 patients and voted whether unblinded use of the OS, with alarms set at 90 and 130 to 150 mg/dL to alert the clinical team to impending hypoglycemia and hyperglycemia, respectively, would have eliminated episodes of dysglycemia: hypoglycemia, defined as a single BG <70 mg/dL; hyperglycemia, defined as >4 hours of BG >150 mg/dL; severe hyperglycemia, defined as >4 hours of BG >200 mg/dL and increased glucose variability (GV), defined as coefficient of variation (CV) >20%.

RESULTS

At least one episode of dysglycemia occurred in 103 (51.5%) of the patients, including 6 (3.0%) with hypoglycemia, 83 (41.5%) with hyperglycemia, 18 (9.0%) with severe hyperglycemia, and 40 (20.0%) with increased GV. Unblinded use of the OS with appropriate alarms would likely have averted 97.1% of the episodes of dysglycemia: hypoglycemia (100.0%), hyperglycemia (96.4%), severe hyperglycemia (100.0%), and increased GV (97.5%). Point accuracy of the OS was very similar to that of the point of care BG monitoring devices used in the trial.

CONCLUSION

Unblinded use of the OS would have eliminated nearly every episode of dysglycemia in this cohort of critically ill patients, thereby markedly improving the quality and safety of glucose control.

Insulin sensitivity in critically ill patients: are women more insulin resistant?

Background

Glycaemic control (GC) in intensive care unit is challenging due to significant inter- and intra-patient variability, leading to increased risk of hypoglycaemia. Recent work showed higher insulin resistance in female preterm neonates. This study aims to determine if there are differences in inter- and intra-patient metabolic variability between sexes in adults, to gain in insight into any differences in metabolic response to injury. Any significant difference would suggest GC and randomised trial design should consider sex differences to personalise care.

Methods

Insulin sensitivity (SI) levels and variability are identified from retrospective clinical data for men and women. Data are divided using 6-h blocks to capture metabolic evolution over time. In total, 91 male and 54 female patient GC episodes of minimum 24 h are analysed. Hypothesis testing is used to determine whether differences are significant (P < 0.05), and equivalence testing is used to assess whether these differences can be considered equivalent at a clinical level. Data are assessed for the raw cohort and in 100 Monte Carlo simulations analyses where the number of men and women are equal.

Results

Demographic data between females and males were all similar, including GC outcomes (safety from hypoglycaemia and high (> 50%) time in target band). Females had consistently significantly lower SI levels than males, and this difference was not clinically equivalent. However, metabolic variability between sexes was never significantly different and always clinically equivalent. Thus, inter-patient variability was significantly different between males and females, but intra-patient variability was equivalent.

Conclusion

Given equivalent intra-patient variability and significantly greater insulin resistance, females can receive the same benefit from safe, effective GC as males, but may require higher insulin doses to achieve the same glycaemia. Clinical trials should consider sex differences in protocol design and outcome analyses.

Insulin sensitivity in critically ill patients: are women more insulin resistant?

BACKGROUND

Glycaemic control (GC) in intensive care unit is challenging due to significant inter- and intra-patient variability, leading to increased risk of hypoglycaemia. Recent work showed higher insulin resistance in female preterm neonates. This study aims to determine if there are differences in inter- and intra-patient metabolic variability between sexes in adults, to gain in insight into any differences in metabolic response to injury. Any significant difference would suggest GC and randomised trial design should consider sex differences to personalise care.

METHODS

Insulin sensitivity (SI) levels and variability are identified from retrospective clinical data for men and women. Data are divided using 6-h blocks to capture metabolic evolution over time. In total, 91 male and 54 female patient GC episodes of minimum 24 h are analysed. Hypothesis testing is used to determine whether differences are significant (P < 0.05), and equivalence testing is used to assess whether these differences can be considered equivalent at a clinical level. Data are assessed for the raw cohort and in 100 Monte Carlo simulations analyses where the number of men and women are equal.

RESULTS

Demographic data between females and males were all similar, including GC outcomes (safety from hypoglycaemia and high (> 50%) time in target band). Females had consistently significantly lower SI levels than males, and this difference was not clinically equivalent. However, metabolic variability between sexes was never significantly different and always clinically equivalent. Thus, inter-patient variability was significantly different between males and females, but intra-patient variability was equivalent.

CONCLUSION

Given equivalent intra-patient variability and significantly greater insulin resistance, females can receive the same benefit from safe, effective GC as males, but may require higher insulin doses to achieve the same glycaemia. Clinical trials should consider sex differences in protocol design and outcome analyses.

Increased insulin resistance in intensive care: longitudinal retrospective analysis of glycaemic control patients in a New Zealand ICU

BACKGROUND

Critical care populations experience demographic shifts in response to trends in population and healthcare, with increasing severity and/or complexity of illness a common observation worldwide. Inflammation in critical illness impacts glucose-insulin metabolism, and hyperglycaemia is associated with mortality and morbidity. This study examines longitudinal trends in insulin sensitivity across almost a decade of glycaemic control in a single unit.

METHODS

A clinically validated model of glucose-insulin dynamics is used to assess hour-hour insulin sensitivity over the first 72 h of insulin therapy. Insulin sensitivity and its hour-hour percent variability are examined over 8 calendar years alongside severity scores and diagnostics.

RESULTS

Insulin sensitivity was found to decrease by 50-55% from 2011 to 2015, and remain low from 2015 to 2018, with no concomitant trends in age, severity scores or risk of death, or diagnostic category. Insulin sensitivity variability was found to remain largely unchanged year to year and was clinically equivalent (95% confidence interval) at the median and interquartile range. Insulin resistance was associated with greater incidence of high insulin doses in the effect saturation range (6-8 U/h), with the 75th percentile of hourly insulin doses rising from 4-4.5 U/h in 2011-2014 to 6 U/h in 2015-2018.

CONCLUSIONS

Increasing insulin resistance was observed alongside no change in insulin sensitivity variability, implying greater insulin needs but equivalent (variability) challenge to glycaemic control. Increasing insulin resistance may imply greater inflammation and severity of illness not captured by existing severity scores. Insulin resistance reduces glucose tolerance, and can cause greater incidence of insulin saturation and resultant hyperglycaemia. Overall, these results have significant clinical implications for glycaemic control and nutrition management.

Assessment of Glycemic Control Protocol (STAR) Through Compliance Analysis Amongst Malaysian ICU Patients

Purpose

This paper presents an assessment of an automated and personalized stochastic targeted (STAR) glycemic control protocol compliance in Malaysian intensive care unit (ICU) patients to ensure an optimized usage.

Patients and Methods

STAR proposes 1–3 hours treatment based on individual insulin sensitivity variation and history of blood glucose, insulin, and nutrition. A total of 136 patients recorded data from STAR pilot trial in Malaysia (2017–quarter of 2019*) were used in the study to identify the gap between chosen administered insulin and nutrition intervention as recommended by STAR, and the real intervention performed.

Results

The results show the percentage of insulin compliance increased from 2017 to first quarter of 2019* and fluctuated in feed administrations. Overall compliance amounted to 98.8% and 97.7% for administered insulin and feed, respectively. There was higher average of 17 blood glucose measurements per day than in other centres that have been using STAR, but longer intervals were selected when recommended. Control safety and performance were similar for all periods showing no obvious correlation to compliance.

Conclusion

The results indicate that STAR, an automated model-based protocol is positively accepted among the Malaysian ICU clinicians to automate glycemic control and the usage can be extended to other hospitals already. Performance could be improved with several propositions.

Risk and reward: extending stochastic glycaemic control intervals to reduce workload

Background

STAR is a model-based, personalised, risk-based dosing approach for glycaemic control (GC) in critically ill patients. STAR provides safe, effective control to nearly all patients, using 1–3 hourly measurement and intervention intervals. However, the average 11–12 measurements per day required can be a clinical burden in many intensive care units. This study aims to significantly reduce workload by extending STAR 1–3 hourly intervals to 1 to 4-, 5-, and 6-hourly intervals, and evaluate the impact of these longer intervals on GC safety and efficacy, using validated in silico virtual patients and trials methods. A Standard STAR approach was used which allowed more hyperglycaemia over extended intervals, and a STAR Upper Limit Controlled approach limited nutrition to mitigate hyperglycaemia over longer intervention intervals.

Results

Extending STAR from 1–3 hourly to 1–6 hourly provided high safety and efficacy for nearly all patients in both approaches. For STAR Standard, virtual trial results showed lower % blood glucose (BG) in the safe 4.4–8.0 mmol/L target band (from 83 to 80%) as treatment intervals increased. Longer intervals resulted in increased risks of hyper- (15% to 18% BG > 8.0 mmol/L) and hypo- (2.1% to 2.8% of patients with min. BG < 2.2 mmol/L) glycaemia. These results were achieved with slightly reduced insulin (3.2 [2.0 5.0] to 2.5 [1.5 3.0] U/h) and nutrition (100 [85 100] to 90 [75 100] % goal feed) rates, but most importantly, with significantly reduced workload (12 to 8 measurements per day). The STAR Upper Limit Controlled approach mitigated hyperglycaemia and had lower insulin and significantly lower nutrition administration rates.

Conclusions

The modest increased risk of hyper- and hypo-glycaemia, and the reduction in nutrition delivery associated with longer treatment intervals represent a significant risk and reward trade-off in GC. However, STAR still provided highly safe, effective control for nearly all patients regardless of treatment intervals and approach, showing this unique risk-based dosing approach, modulating both insulin and nutrition, to be robust in its design. Clinical pilot trials using STAR with different measurement timeframes should be undertaken to confirm these results clinically.

Individualizing Glycemic Control in the Critically Ill

Hyperglycemia is a common phenomenon in critically ill patients, even in those without diabetes. Two landmark studies established the benefits of tight glucose control (blood glucose target 80-110 mg/dL) in surgical and medical patients. Since then, literature has consistently demonstrated that both hyperglycemia and hypoglycemia are independently associated with increased morbidity and mortality in a variety of critically ill patients. However, tight glycemic control has subsequently come into question due to risks of hypoglycemia and increased mortality. More recently, strategies targeting euglycemia (blood glucose ≤180 mg/dL) have been associated with improved outcomes, although the risk of hypoglycemia remains. More complex targets (ie, glycemic variability and time within target glucose range) and the impact of individual patient characteristics (ie, diabetic status and prehospital glucose control) have more recently been shown to influence the relationship between glycemic control and outcomes in critically ill patients. Although our understanding has increased, the optimal glycemic target is still unclear and glucose management strategies may require adjustment for individual patient characteristics. As glucose management increases in complexity, we realize that traditional means of using meters and strips and paper insulin titration algorithms are potential limitations to our success. To achieve these complex goals for glycemic control, the use of continuous or near-continuous glucose monitoring combined with computerized insulin titration algorithms may be required. The purpose of this review is to discuss the evidence surrounding the various domains of glycemic control and the emerging data supporting the need for individualized glucose targets in critically ill patients.

Glycaemic Control in Critically Ill Adult Patients: Is intensive insulin therapy beneficial?

OBJECTIVES Glycaemic control with intensive insulin therapy and its impact on patient outcomes have always been contentious in an intensive care setting. This study aims to assess the patterns of glycaemic control in critically ill patients at a tertiary care institution in Trinidad and its relationship to outcomes. METHODS All adult patients admitted to a multidisciplinary intensive care unit (ICU) for a period of two years were enrolled for a retrospective chart review. Data collected included demographics, admission blood glucose, mean morning blood glucose (MBG), the trend of glucose control, number of hypoglycaemic episodes, admission Simplified Acute Physiology Score (SAPS) II, ICU and hospital length of stay, duration of mechanical ventilation, anaemia, renal replacement therapy and hospital outcome. RESULTS A total of 104 patients were studied. Four different patterns of insulin therapy were practised at the ICU. The median age of patients was 55.5 years, the mean SAPS II was 49.3, the mean predicted mortality was 45.5% and the overall observed mortality was 38.5%. The majority of admissions had cardiovascular illnesses (25%), followed by sepsis (20.2%). Patients with multiple hypoglycaemic episodes had an increased mortality (p<0.01). Patients had a better outcome with a higher MBG (>100 mg/dL) (p<0.05). There was a significant difference in mortality among the four patterns of glycaemic control (p<0.001). Admission blood glucose, length of time of mechanical ventilation, ICU length of stay and renal replacement therapy were not found to be associated with adverse outcomes. CONCLUSION Intensive insulin therapy (IIT) may not benefit ICU patients but can be probably associated with higher mortality. Avoidance of hypoglycaemia as well as persistent hyperglycaemia may lead to a better outcome in critically ill patients.

STAR-Liège Clinical Trial Interim Results: Safe and Effective Glycemic Control for All

While the benefits of glycemic control for critically ill patients are increasingly demonstrated, the ability to deliver safe, effective control to intermediate target ranges is widely debated due to the increased risk of hypoglycemia. This study analyzes interim clinical trial results of the fully computerized model-based Stochastic TARgeted (STAR) glycemic control framework at the University Hospital of Liège, Belgium. Patients with dysglycemia were randomly assigned to the full version of STAR, modulating both insulin and nutrition inputs, or STAR-IO, an insulin only version of STAR. Both arms target the normoglycemic 80-145 mg/dL (4.4-8.0 mmol/L) band. Results are further compared to retrospective data from 20 patients under the standard unit protocol targeting a higher 100-150 mg/dL (5.6-8.3 mmol/L) band. Much higher time in target band is provided under the full version of STAR, with similar safety and significantly lower incidence of mild hyperglycemia (blood glucose > 145 mg/dL or 8.0 mmol/L) and severe hyperglycemia (blood glucose > 180 mg/dL or 10.0 mmol/L). As a result, lower median blood glucose levels are safely and consistently achieved with lower glycemic variability, suggesting STAR's potential to improve clinical outcomes. These interim results show the possibility to achieve safe, effective control for all patients using STAR, and suggest glycemic control to lower targets could be beneficial.

Multi-input stochastic prediction of insulin sensitivity for tight glycaemic control using insulin sensitivity and blood glucose data

BACKGROUND

Glycaemic control in the intensive care unit is dependent on effective prediction of patient insulin sensitivity (SI). The stochastic targeted (STAR) controller uses a 2D stochastic model for prediction, with current SI as an input and future SI as an output.

METHODS

This paper develops an extension of the STAR 2D stochastic model into 3D by adding blood glucose (G) as an input. The performance of the 2D and 3D stochastic models is compared over a retrospective cohort of 65,269 data points across 1525 patients.

RESULTS

Under five-fold cross-validation, the 3D model was found to better match the expected potion of data points within, above and below various credible intervals, suggesting it provided a better representation of the underlying probability field. The 3D model was also found to provide an 18.1% narrower 90% credible interval on average, and a narrower 90% credible interval in 96.4% of cases, suggesting it provided more accurate predictions of future SI. Additionally, the 3D stochastic model was found to avoid the undesirable tendency of the 2D model to overestimate SI for patients with high G, and underestimate SI for patients with low G.

CONCLUSIONS

Overall, the 3D stochastic model is shown to provide clear potential benefits over the 2D model for minimal clinical cost or effort, though further exploration into whether these improvements in SI prediction translate into improved clinical outcomes is required.

3D kernel-density stochastic model for more personalized glycaemic control: development and in-silico validation

Background

The challenges of glycaemic control in critically ill patients have been debated for 20 years. While glycaemic control shows benefits inter- and intra-patient metabolic variability results in increased hypoglycaemia and glycaemic variability, both increasing morbidity and mortality. Hence, current recommendations for glycaemic control target higher glycaemic ranges, guided by the fear of harm. Lately, studies have proven the ability to provide safe, effective control for lower, normoglycaemic, ranges, using model-based computerised methods. Such methods usually identify patient-specific physiological parameters to personalize titration of insulin and/or nutrition. The Stochastic-Targeted (STAR) glycaemic control framework uses patient-specific insulin sensitivity and a stochastic model of its future variability to directly account for both inter- and intra-patient variability in a risk-based insulin-dosing approach.

Results

In this study, a more personalized and specific 3D version of the stochastic model used in STAR is compared to the current 2D stochastic model, both built using kernel-density estimation methods. Fivefold cross validation on 681 retrospective patient glycaemic control episodes, totalling over 65,000 h of control, is used to determine whether the 3D model better captures metabolic variability, and the potential gain in glycaemic outcome is assessed using validated virtual trials. Results show that the 3D stochastic model has similar forward predictive power, but provides significantly tighter, more patient-specific, prediction ranges, showing the 2D model over-conservative > 70% of the time. Virtual trial results show that overall glycaemic safety and performance are similar, but the 3D stochastic model reduced median blood glucose levels (6.3 [5.7, 7.0] vs. 6.2 [5.6, 6.9]) with a higher 61% vs. 56% of blood glucose within the 4.4–6.5 mmol/L range.

Conclusions

This improved performance is achieved with higher insulin rates and higher carbohydrate intake, but no loss in safety from hypoglycaemia. Thus, the 3D stochastic model developed better characterises patient-specific future insulin sensitivity dynamics, resulting in improved simulated glycaemic outcomes and a greater level of personalization in control. The results justify inclusion into ongoing clinical use of STAR.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas

There is considerable physiological and clinical evidence of harm and increased risk of death associated with dysglycemia in critical care. However, glycemic control (GC) currently leads to increased hypoglycemia, independently associated with a greater risk of death. Indeed, recent evidence suggests GC is difficult to safely and effectively achieve for all patients. In this review, leading experts in the field discuss this evidence and relevant data in diabetology, including the artificial pancreas, and suggest how safe, effective GC can be achieved in critically ill patients in ways seeking to mimic normal islet cell function. The review is structured around the specific clinical hurdles of: understanding the patient’s metabolic state; designing GC to fit clinical practice, safety, efficacy, and workload; and the need for standardized metrics. These aspects are addressed by reviewing relevant recent advances in science and technology. Finally, we provide a set of concise recommendations to advance the safety, quality, consistency, and clinical uptake of GC in critical care. This review thus presents a roadmap toward better, more personalized metabolic care and improved patient outcomes.

Performance of Stochastic Targeted Blood Glucose Control Protocol by virtual trials in the Malaysian intensive care unit

BACKGROUND AND OBJECTIVE

Blood glucose variability is common in healthcare and it is not related or influenced by diabetes mellitus. To minimise the risk of high blood glucose in critically ill patients, Stochastic Targeted Blood Glucose Control Protocol is used in intensive care unit at hospitals worldwide. Thus, this study focuses on the performance of stochastic modelling protocol in comparison to the current blood glucose management protocols in the Malaysian intensive care unit. Also, this study is to assess the effectiveness of Stochastic Targeted Blood Glucose Control Protocol when it is applied to a cohort of diabetic patients.

METHODS

Retrospective data from 210 patients were obtained from a general hospital in Malaysia from May 2014 until June 2015, where 123 patients were having comorbid diabetes mellitus. The comparison of blood glucose control protocol performance between both protocol simulations was conducted through blood glucose fitted with physiological modelling on top of virtual trial simulations, mean calculation of simulation error and several graphical comparisons using stochastic modelling.

RESULTS

Stochastic Targeted Blood Glucose Control Protocol reduces hyperglycaemia by 16% in diabetic and 9% in nondiabetic cohorts. The protocol helps to control blood glucose level in the targeted range of 4.0-10.0 mmol/L for 71.8% in diabetic and 82.7% in nondiabetic cohorts, besides minimising the treatment hour up to 71 h for 123 diabetic patients and 39 h for 87 nondiabetic patients.

CONCLUSION

It is concluded that Stochastic Targeted Blood Glucose Control Protocol is good in reducing hyperglycaemia as compared to the current blood glucose management protocol in the Malaysian intensive care unit. Hence, the current Malaysian intensive care unit protocols need to be modified to enhance their performance, especially in the integration of insulin and nutrition intervention in decreasing the hyperglycaemia incidences. Improvement in Stochastic Targeted Blood Glucose Control Protocol in terms of u_en model is also a must to adapt with the diabetic cohort.

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.

RePHILL: protocol for a randomised controlled trial of pre-hospital blood product resuscitation for trauma

OBJECTIVES

To describe the 'Resuscitation with Pre-HospItaL bLood products' trial (RePHILL) - a multi-centre randomised controlled trial of pre-hospital blood product (PHBP) administration vs standard care for traumatic haemorrhage.

BACKGROUND

PHBP are increasingly used for pre-hospital trauma resuscitation despite a lack of robust evidence demonstrating superiority over crystalloids. Provision of PHBP carries additional logistical and regulatory implications, and requires a sustainable supply of universal blood components.

METHODS

RePHILL is a multi-centre, two-arm, parallel group, open-label, phase III randomised controlled trial currently underway in the UK. Patients attended by a pre-hospital emergency medical team, with traumatic injury and hypotension (systolic blood pressure <90 mmHg or absent radial pulse) believed to be due to traumatic haemorrhage are eligible. Exclusion criteria include age <16 years, blood product receipt on scene prior to randomisation, Advanced Medical Directive forbidding blood product administration, pregnancy, isolated head injury and prisoners. A total of 490 patients will be recruited in a 1 : 1 ratio to receive either the intervention (up to two units of red blood cells and two units of lyophilised plasma) or the control (up to four boluses of 250 mL 0.9% saline). The primary outcome measure is a composite of failure to achieve lactate clearance of ≥20%/h over the first 2 hours after randomisation and all-cause mortality between recruitment and discharge from the primary receiving facility to non-acute care. Secondary outcomes include pre-hospital time, coagulation indices, in-hospital transfusion requirements and morbidity.

RESULTS

Pilot study recruitment began in December 2016. Approval to proceed to the main trial was received in June 2017. Recruitment is expected to continue until 2020.

CONCLUSIONS

RePHILL will provide high-quality evidence regarding the efficacy and safety of PHBP resuscitation for trauma.

Clinical Effectiveness of Intravenous Exenatide Infusion in Perioperative Glycemic Control after Coronary Artery Bypass Graft Surgery

Background

We aimed to assess the clinical effectiveness of intravenous exenatide compared to insulin in perioperative blood glucose control in coronary artery bypass grafting surgery patients.

Methods

Patients more than 18 yr old admitted for elective coronary artery bypass grafting were included in a phase II/III nonblinded randomized superiority trial. Current insulin use and creatinine clearance of less than 60 ml/min were exclusion criteria. Two groups were compared: the exenatide group, receiving exenatide (1-h bolus of 0.05 µg/min followed by a constant infusion of 0.025 µg/min), and the control group, receiving insulin therapy. The blood glucose target range was 100 to 139 mg/dl. The primary outcome was the proportion of patients who spent at least 50% of the study period within the target range. The consumption of insulin (Cinsulin) and the time to start insulin (Tinsulin) were compared between the two groups.

Results

In total, 53 and 51 patients were included and analyzed in the exenatide and control groups, respectively (age: 70 ± 9 vs. 68 ± 11 yr; diabetes mellitus: 12 [23%] vs. 10 [20%]). The primary outcome was observed in 38 (72%) patients in the exenatide group and in 41 (80%) patients in the control group (odds ratio [95% CI] = 0.85 [0.34 to 2.11]; P = 0.30). Cinsulin was significantly lower (60 [40 to 80] vs. 92 [63 to 121] U, P &lt; 0.001), and Tinsulin was significantly longer (12 [7 to 16] vs. 7 [5 to 10] h, P = 0.02) in the exenatide group.

Conclusions

Exenatide alone at the dose used was not enough to achieve adequate blood glucose control in coronary artery bypass grafting patients, but it reduces overall consumption of insulin and increases the time to initiation of insulin.

Continuous glucose monitoring in neonates: a review

Continuous glucose monitoring (CGM) is well established in the management of diabetes mellitus, but its role in neonatal glycaemic control is less clear. CGM has provided important insights about neonatal glucose metabolism, and there is increasing interest in its clinical use, particularly in preterm neonates and in those in whom glucose control is difficult. Neonatal glucose instability, including hypoglycaemia and hyperglycaemia, has been associated with poorer neurodevelopment, and CGM offers the possibility of adjusting treatment in real time to account for individual metabolic requirements while reducing the number of blood tests required, potentially improving long-term outcomes. However, current devices are optimised for use at relatively high glucose concentrations, and several technical issues need to be resolved before real-time CGM can be recommended for routine neonatal care. These include: 1) limited point accuracy, especially at low or rapidly changing glucose concentrations; 2) calibration methods that are designed for higher glucose concentrations of children and adults, and not for neonates; 3) sensor drift, which is under-recognised; and 4) the need for dynamic and integrated metrics that can be related to long-term neurodevelopmental outcomes. CGM remains an important tool for retrospective investigation of neonatal glycaemia and the effect of different treatments on glucose metabolism. However, at present CGM should be limited to research studies, and should only be introduced into routine clinical care once benefit is demonstrated in randomised trials.

Untangling glycaemia and mortality in critical care

Background

Hyperglycaemia is associated with adverse outcomes in the intensive care unit, and initial studies suggested outcome benefits of glycaemic control (GC). However, subsequent studies often failed to replicate these results, and they were often unable to achieve consistent, safe control, raising questions about the benefit or harm of GC as well as the nature of the association of glycaemia with mortality and clinical outcomes. In this study, we evaluated if non-survivors are harder to control than survivors and determined if glycaemic outcome is a function of patient condition and eventual outcome or of the glycaemic control provided.

Methods

Clinically validated, model-based, hour-to-hour insulin sensitivity (SI) and its hour-to-hour variability (%ΔSI) were identified over the first 72 h of therapy in 145 patients (119 survivors, 26 non-survivors). In hypothesis testing, we compared distributions of SI and %ΔSI in 6-hourly blocks for survivors and non-survivors. In equivalence testing, we assessed if differences in these distributions, based on blood glucose measurement error, were clinically significant.

Results

SI level was never equivalent between survivors and non-survivors (95% CI of percentage difference in medians outside ±12%). Non-survivors had higher SI, ranging from 9% to 47% higher overall in 6-h blocks, and this difference became statistically significant as glycaemic control progressed. %ΔSI was equivalent between survivors and non-survivors for all 6-hourly blocks (95% CI of difference in medians within ±12%) and decreased in general over time as glycaemic control progressed.

Conclusions

Whereas non-survivors had higher SI levels, variability was equivalent to that of survivors over the first 72 h. These results indicate survivors and non-survivors are equally controllable, given an effective glycaemic control protocol, suggesting that glycaemia level and variability, and thus the association between glycaemia and outcome, are essentially determined by the control provided rather than by underlying patient or metabolic condition.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-017-1725-y) contains supplementary material, which is available to authorized users.

Safety and Efficacy of Antiviral Therapy for Prevention of Cytomegalovirus Reactivation in Immunocompetent Critically Ill Patients: A Randomized Clinical Trial

IMPORTANCE

Latent cytomegalovirus (CMV) infection is present in more than half the adult population, and a viral reactivation (ie, when the virus becomes measurable in body fluids such as blood) can occur in up to one-third of these individuals during episodes of critical illness.

OBJECTIVE

To determine whether antiviral therapy is safe and effective for preventing CMV reactivation in a general population of critically ill patients.

DESIGN, SETTING, AND PARTICIPANTS

A single-center, open-label, randomized, controlled clinical trial recruited 124 CMV-seropositive patients undergoing mechanical ventilation for at least 24 hours in the intensive care unit between January 1, 2012, and January 31, 2014. The mean baseline Acute Physiology and Chronic Health Evaluation II score of all patients was 17.6.

INTERVENTIONS

Patients were randomized to receive anti-CMV prophylaxis with valacyclovir hydrochloride (n = 34) or low-dose valganciclovir hydrochloride (n = 46) for up to 28 days to suppress viral reactivation, or to a control group with no intervention (n = 44).

MAIN OUTCOMES AND MEASURES

Time to first CMV reactivation in blood within the 28-day follow-up period following initiation of the study drug.

RESULTS

Among the 124 patients in the study (46 women and 78 men; mean [SD] age, 56.9 [16.9] years), viral reactivation in the blood occurred in 12 patients in the control group, compared with 1 patient in the valganciclovir group and 2 patients in the valacyclovir group (combined treatment groups vs control: hazard ratio, 0.14; 95% CI 0.04-0.50). Although this trial was not powered to assess clinical end points, the valacyclovir arm was halted prematurely because of higher mortality; 14 of 34 patients (41.2%) had died by 28 days, compared with 5 of 37 (13.5%) patients in the control arm at the point of the decision to halt this arm. Other safety end points showed similar outcomes between groups.

CONCLUSIONS AND RELEVANCE

Antiviral prophylaxis with valacyclovir or low-dose valganciclovir suppresses CMV reactivation in patients with critical illness. However, given the higher mortality, a large-scale trial would be needed to determine the clinical efficacy and safety of CMV suppression.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT01503918.

Generalisability of a Virtual Trials Method for Glycaemic Control in Intensive Care

BACKGROUND

Elevated blood glucose (BG) concentrations (Hyperglycaemia) are a common complication in critically ill patients. Insulin therapy is commonly used to treat hyperglycaemia, but metabolic variability often results in poor BG control and low BG (hypoglycaemia).

OBJECTIVE

This paper presents a model-based virtual trial method for glycaemic control protocol design, and evaluates its generalisability across different populations.

METHODS

Model-based insulin sensitivity (SI) was used to create virtual patients from clinical data from three different ICUs in New Zealand, Hungary, and Belgium. Glycaemic results from simulation of virtual patients under their original protocol (self-simulation) and protocols from other units (cross simulation) were compared.

RESULTS

Differences were found between the three cohorts in median SI and inter-patient variability in SI. However, hour-to-hour intra-patient variability in SI was found to be consistent between cohorts. Self and cross-simulation results were found to have overall similarity and consistency, though results may differ in the first 24-48 h due to different cohort starting BG and underlying SI.

CONCLUSIONS AND SIGNIFICANCE

Virtual patients and the virtual trial method were found to be generalisable across different ICUs. This virtual trial method is useful for in silico protocol design and testing, given an understanding of the underlying assumptions and limitations of this method.

Computer-determined dosage of insulin in the management of neonatal hyperglycaemia (HINT2): protocol of a randomised controlled trial

INTRODUCTION

Neonatal hyperglycaemia is frequently treated with insulin, which may increase the risk of hypoglycaemia. Computer-determined dosage of insulin (CDD) with the STAR-GRYPHON program uses a computer model to predict an effective dose of insulin to treat hyperglycaemia while minimising the risk of hypoglycaemia. However, CDD models can require more frequent blood glucose testing than common clinical protocols. The aim of this trial is to determine if CDD using STAR-GRYPHON reduces hypoglycaemia in hyperglycaemic preterm babies treated with insulin independent of the frequency of blood glucose testing.

METHODS AND ANALYSIS

Design: Multicentre, non-blinded, randomised controlled trial.

SETTING

Neonatal intensive care units in New Zealand and Australia.

PARTICIPANTS

138 preterm babies ≤30 weeks' gestation or ≤1500 g at birth who develop hyperglycaemia (two consecutive blood glucose concentrations ≥10 mmol/L, at least 4 hours apart) will be randomised to one of three groups: (1) CDD using the STAR-GRYPHON model-based decision support system: insulin dose and frequency of blood glucose testing advised by STAR-GRYPHON, with a maximum testing interval of 4 hours; (2) bedside titration: insulin dose determined by medical staff, maximum blood glucose testing interval of 4 hours; (3) standard care: insulin dose and frequency of blood glucose testing determined by medical staff. The target range for blood glucose concentrations is 5-8 mmol/L in all groups. A subset of babies will have masked continuous glucose monitoring.

PRIMARY OUTCOME

is the number of babies with one or more episodes of hypoglycaemia (blood glucose concentration <2.6 mmol/L), during treatment with insulin.

ETHICS AND DISSEMINATION

This protocol has been approved by New Zealand's Health and Disability Ethics Committee: 14/STH/26. A data safety monitoring committee has been appointed to oversee the trial. Findings will be disseminated to participants and carers, peer-reviewed journals, guideline developers and the public.

TRIAL REGISTRATION NUMBER

12614000492651.

Effect of Fat-based versus Carbohydrate-based Enteral Feeding on Glycemic Control in Critically Ill Patients: A Randomized Clinical Trial

Background and Aims:

The aim of this study was to evaluate the preventive effects of high-fat enteral feeding on glycemic control and clinical outcomes in critically ill patients: a randomized clinical trial.

Materials and Methods:

This study was done on 42 normoglycemic patients admitted to Intensive Care Unit (ICU). Patients were randomly classified into three groups of 14 each. Control group (A) received carbohydrate-based diet (protein: 20%, fat: 30%, and carbohydrate: 50%), study groups received two types of high-fat diet; Group B (protein: 20%, fat: 45% including half of olive oil and half sunflower oil, and carbohydrate: 35%); and Group C (protein: 20%, fat: 45% including sunflower oil, and carbohydrate: 35%) in the first 48 h of admission.

Results:

Basal characteristics of participants were the same. After the feeding trial, there was no difference between the groups in mean plasma and capillary glucose levels and insulin requirements. Serum high density lipoprotein (HDL)-cholesterol level was increased significantly in Group B on day 10 compared to admission level (40.75 ± 5.58 vs. 43.56 ± 2.25, P = 0.05). We did not find any difference in organ failure involvement and mortality rate between groups. The number of ICU free days was significantly more in Group B compared to the control group (P = 0.04).

Conclusion:

High-fat diets have no preventive effect on stress hyperglycemia. High monounsaturated fat diet may increase serum HDL-cholesterol level and decrease the length of stay in ICU.

[Metabolic control in the critically ill patient an update: hyperglycemia, glucose variability hypoglycemia and relative hypoglycemia]

BACKGROUND

Metabolic changes of glucose in critically ill patients increase morbidity and mortality. The appropriate level of blood glucose has not been established so far and should be adjusted for different populations. However concepts such as glucose variability and relative hypoglycemia of critically ill patients are concepts that are changing management methods and achieving closer monitoring.

OBJECTIVES

The purpose of this review is to present new data about the management and metabolic control of patients in critical areas.

CONCLUSIONS

Currently glucose can no longer be regarded as an innocent element in critical patients; both hyperglycemia and hypoglycemia increase morbidity and mortality of patients. Protocols and better instruments for continuous measurement are necessary to achieve the metabolic control of our patients.

Double-Blind Randomized Clinical Trial Comparing Dopamine and Epinephrine in Pediatric Fluid-Refractory Hypotensive Septic Shock

OBJECTIVE

We compared efficacy of dopamine and epinephrine as first-line vasoactive therapy in achieving resolution of shock in fluid-refractory hypotensive cold septic shock.

DESIGN

Double-blind, pilot, randomized controlled study.

SETTING

Pediatric emergency and ICU of a tertiary care teaching hospital.

PATIENTS

Consecutive children 3 months to 12 years old, with fluid-refractory hypotensive septic shock, were enrolled between July 2013 and December 2014.

INTERVENTION

Enrolled children were randomized to receive either dopamine (in incremental doses, 10 to 15 to 20 μg/kg/min) or epinephrine (0.1 to 0.2 to 0.3 μg/kg/min) till end points of resolution of shock were achieved. After reaching maximum doses of test drugs, open-label vasoactive was started as per discretion of treating team. Primary outcome was resolution of shock within first hour of resuscitation. The study was registered (CTRI/2014/02/004393) and was approved by institute ethics committee.

MEASUREMENTS AND MAIN RESULTS

We enrolled 29 children in epinephrine group and 31 in dopamine group. Resolution of shock within first hour was achieved in greater proportion of children receiving epinephrine (n = 12; 41%) than dopamine (n = 4; 13%) (odds ratio, 4.8; 95% CI, 1.3-17.2; p = 0.019); the trend persisted even at 6 hours (48.3% vs 29%; p = 0.184). Children in epinephrine group had lower Sequential Organ Function Assessment score on day 3 (8 vs 12; p = 0.05) and more organ failure-free days (24 vs 20 d; p = 0.022). No significant difference in adverse events (16.1% vs 13.8%; p = 0.80) and mortality (58.1% vs 48.3%; p = 0.605) was observed between the two groups.

CONCLUSION

Epinephrine is more effective than dopamine in achieving resolution of fluid-refractory hypotensive cold shock within the first hour of resuscitation and improving organ functions.

Safety, efficacy and clinical generalization of the STAR protocol: a retrospective analysis

Background

The changes in metabolic pathways and metabolites due to critical illness result in a highly complex and dynamic metabolic state, making safe, effective management of hyperglycemia and hypoglycemia difficult. In addition, clinical practices can vary significantly, thus making GC protocols difficult to generalize across units.The aim of this study was to provide a retrospective analysis of the safety, performance and workload of the stochastic targeted (STAR) glycemic control (GC) protocol to demonstrate that patient-specific, safe, effective GC is possible with the STAR protocol and that it is also generalizable across/over different units and clinical practices.

Methods

Retrospective analysis of STAR GC in the Christchurch Hospital Intensive Care Unit (ICU), New Zealand (267 patients), and the Gyula Hospital, Hungary (47 patients), is analyzed (2011–2015). STAR Christchurch (BG target 4.4–8.0 mmol/L) is also compared to the Specialized Relative Insulin and Nutrition Tables (SPRINT) protocol (BG target 4.4–6.1 mmol/L) implemented in the Christchurch Hospital ICU, New Zealand (292 patients, 2005–2007). Cohort mortality, effectiveness and safety of glycemic control and nutrition delivered are compared using nonparametric statistics.

Results

Both STAR implementations and SPRINT resulted in over 86 % of time per episode in the blood glucose (BG) band of 4.4–8.0 mmol/L. Patients treated using STAR in Christchurch ICU spent 36.7 % less time on protocol and were fed significantly more than those treated with SPRINT (73 vs. 86 % of caloric target). The results from STAR in both Christchurch and Gyula were very similar, with the BG distributions being almost identical. STAR provided safe GC with very few patients experiencing severe hypoglycemia (BG < 2.2 mmol/L, <5 patients, 1.5 %).

Conclusions

STAR outperformed its predecessor, SPRINT, by providing higher nutrition and equally safe, effective control for all the days of patient stay, while lowering the number of measurements and interventions required. The STAR protocol has the ability to deliver high performance and high safety across patient types, time, clinical practice culture (Christchurch and Gyula) and clinical resources.

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.

Time in blood glucose range 70 to 140 mg/dl >80% is strongly associated with increased survival in non-diabetic critically ill adults

Introduction

Hyperglycemia, hypoglycemia and increased glucose variability are independently associated with increased risk of death in critically ill adults. The relationship between time in targeted blood glucose range (TIR) and mortality is not well described and may be a factor that has confounded the results of the major interventional trials of intensive insulin therapy.

Methods

We conducted a retrospective analysis of prospectively collected data involving 3,297 patients with intensive care unit (ICU) lengths of stay (LOS) of ≥1.0 day who were admitted between 1 January 2009 and 31 December 2013 to a single mixed medical-surgical ICU. We investigated the relationship between TIR 70 to 140 mg/dl with mortality and compared outcomes of non-diabetics (NON) and individuals with diabetes mellitus (DM), including stratifying by TIR above (TIR-hi) and below (TIR-lo) the median value for the NON and DM groups.

Results

There were 85,799 blood glucose (BG) values for the NON group and 32,651 for the DM group, and we found that 75.5% and 54.8%, respectively, were between 70 and 140 (P <0.0001). The median (interquartile range) TIR (%) values for the NON and DM groups were 80.6% (61.4% to 94.0%) and 55.0% (35.5% to 71.1%), respectively (P <0.0001). For the NON group, mortality was 8.47% and 15.71% for TIR-hi and TIR-lo, respectively (P <0.0001). For the DM group, mortality was 16.09% and 14.44% for TIR-hi and TIR-lo, respectively (P = NS). We observed similar relationships for the NON group when we stratified by ICU LOS or severity of illness, especially in the most severely ill patients. There was a cumulative interaction of indices of hypoglycemia, hyperglycemia or glucose variability with TIR. Multivariable analysis demonstrated, for the NON group, that TIR-hi was independently associated with increased survival (P =0.0019). For the NON group, the observed-to-expected mortality ratios for TIR-hi and TIR-lo, based on Acute Physiology and Chronic Health Evaluation IV methodology, were 0.53 and 0.78, respectively. In contrast, among those in the DM group, there was no clear relationship between TIR 70 to 140 mg/dl and survival.

Conclusions

Independently of ICU LOS and severity of illness, TIR 70 to 140 mg/dl >80% is strongly associated with survival in critically ill patients without diabetes. These findings have implications for the design of clinical protocols for glycemic control in critically ill patients as well for the design of future interventional trials of intensive insulin therapy.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-015-0908-7) contains supplementary material, which is available to authorized users.