Software-guided versus nurse-directed blood glucose control in critically ill patients: the LOGIC-2 multicenter randomized controlled clinical trial

Year in Review 2023: Noteworthy Literature in Cardiothoracic Critical Care

This article reviews noteworthy investigations and society recommendations published in 2023 relevant to the care of critically ill cardiothoracic surgical patients. We reviewed 3,214 articles to identify 18 publications that add to the existing literature across a variety of topics including resuscitation, nutrition, antibiotic management, extracorporeal membrane oxygenation (ECMO), neurologic care following cardiac arrest, coagulopathy and transfusion, steroids in pulmonary infections, and updated guidelines in the management of acute respiratory distress syndrome (ARDS).

Society of Critical Care Medicine Guidelines on Glycemic Control for Critically Ill Children and Adults 2024

RATIONALE

Maintaining glycemic control of critically ill patients may impact outcomes such as survival, infection, and neuromuscular recovery, but there is equipoise on the target blood levels, monitoring frequency, and methods.

OBJECTIVES

The purpose was to update the 2012 Society of Critical Care Medicine and American College of Critical Care Medicine (ACCM) guidelines with a new systematic review of the literature and provide actionable guidance for clinicians.

PANEL DESIGN

The total multiprofessional task force of 22, consisting of clinicians and patient/family advocates, and a methodologist applied the processes described in the ACCM guidelines standard operating procedure manual to develop evidence-based recommendations in alignment with the Grading of Recommendations Assessment, Development, and Evaluation Approach (GRADE) methodology. Conflict of interest policies were strictly followed in all phases of the guidelines, including panel selection and voting.

METHODS

We conducted a systematic review for each Population, Intervention, Comparator, and Outcomes question related to glycemic management in critically ill children (≥ 42 wk old adjusted gestational age to 18 yr old) and adults, including triggers for initiation of insulin therapy, route of administration, monitoring frequency, role of an explicit decision support tool for protocol maintenance, and methodology for glucose testing. We identified the best available evidence, statistically summarized the evidence, and then assessed the quality of evidence using the GRADE approach. We used the evidence-to-decision framework to formulate recommendations as strong or weak or as a good practice statement. In addition, "In our practice" statements were included when the available evidence was insufficient to support a recommendation, but the panel felt that describing their practice patterns may be appropriate. Additional topics were identified for future research.

RESULTS

This guideline is an update of the guidelines for the use of an insulin infusion for the management of hyperglycemia in critically ill patients. It is intended for adult and pediatric practitioners to reassess current practices and direct research into areas with inadequate literature. The panel issued seven statements related to glycemic control in unselected adults (two good practice statements, four conditional recommendations, one research statement) and seven statements for pediatric patients (two good practice statements, one strong recommendation, one conditional recommendation, two "In our practice" statements, and one research statement), with additional detail on specific subset populations where available.

CONCLUSIONS

The guidelines panel achieved consensus for adults and children regarding a preference for an insulin infusion for the acute management of hyperglycemia with titration guided by an explicit clinical decision support tool and frequent (≤ 1 hr) monitoring intervals during glycemic instability to minimize hypoglycemia and against targeting intensive glucose levels. These recommendations are intended for consideration within the framework of the patient's existing clinical status. Further research is required to evaluate the role of individualized glycemic targets, continuous glucose monitoring systems, explicit decision support tools, and standardized glycemic control metrics.

Our Scientific Journey through the Ups and Downs of Blood Glucose Control in the ICU

This article tells the story of our long search for the answer to one question: Is stress hyperglycemia in critically ill patients adaptive or maladaptive? Our earlier work had suggested the lack of hepatic insulin effect and hyperglycemia as jointly predicting poor outcome. Therefore, we hypothesized that insulin infusion to reach normoglycemia, tight glucose control, improves outcome. In three randomized controlled trials (RCTs), we found morbidity and mortality benefit with tight glucose control. Moving from the bed to the bench, we attributed benefits to the prevention of glucose toxicity in cells taking up glucose in an insulin-independent, glucose concentration gradient-dependent manner, counteracted rather than synergized by insulin. Several subsequent RCTs did not confirm benefit, and the large Normoglycemia in Intensive Care Evaluation-Survival Using Glucose Algorithm Regulation, or "NICE-SUGAR," trial found increased mortality with tight glucose control associated with severe hypoglycemia. Our subsequent clinical and mechanistic research revealed that early use of parenteral nutrition, the context of our initial RCTs, had been a confounder. Early parenteral nutrition (early-PN) aggravated hyperglycemia, suppressed vital cell damage removal, and hampered recovery. Therefore, in our next and largest "TGC-fast" RCT, we retested our hypothesis, without the use of early-PN and with a computer algorithm for tight glucose control that avoided severe hypoglycemia. In this trial, tight glucose control prevented kidney and liver damage, though with much smaller effect sizes than in our initial RCTs without affecting mortality. Our quest ends with the strong recommendation to omit early-PN for patients in the ICU, as this reduces need of blood glucose control and allows cellular housekeeping systems to play evolutionary selected roles in the recovery process. Once again, less is more in critical care.

Robust stability control for nonlinear time varying delay fractional order practical systems and application in Glucose-Insulin system

Diabetes Mellitus is a long-term and prevalent disease that 10% of the world population suffer ‎from. This study uses a state feedback controller to control blood glucose level in the delayed ‎fractional order model of this disease. Thus, first, a proper state feedback controller for ‎stabilizing the fractional order model with time-variant delays is presented. Then, stability and ‎stabilization of the fractional order models in the fractional order insulin-glucose model with ‎time-variant delays is presented. The results show that the insulin-glucose system with the ‎proposed controller is stabilized and the blood glucose concentration is controlled in a proper ‎time. Further studies might provide the opportunity for novel technologies in controlling and ‎treating diabetic patients.

Tight Blood-Glucose Control without Early Parenteral Nutrition in the ICU

BACKGROUND

Randomized, controlled trials have shown both benefit and harm from tight blood-glucose control in patients in the intensive care unit (ICU). Variation in the use of early parenteral nutrition and in insulin-induced severe hypoglycemia might explain this inconsistency.

METHODS

We randomly assigned patients, on ICU admission, to liberal glucose control (insulin initiated only when the blood-glucose level was >215 mg per deciliter [>11.9 mmol per liter]) or to tight glucose control (blood-glucose level targeted with the use of the LOGIC-Insulin algorithm at 80 to 110 mg per deciliter [4.4 to 6.1 mmol per liter]); parenteral nutrition was withheld in both groups for 1 week. Protocol adherence was determined according to glucose metrics. The primary outcome was the length of time that ICU care was needed, calculated on the basis of time to discharge alive from the ICU, with death accounted for as a competing risk; 90-day mortality was the safety outcome.

RESULTS

Of 9230 patients who underwent randomization, 4622 were assigned to liberal glucose control and 4608 to tight glucose control. The median morning blood-glucose level was 140 mg per deciliter (interquartile range, 122 to 161) with liberal glucose control and 107 mg per deciliter (interquartile range, 98 to 117) with tight glucose control. Severe hypoglycemia occurred in 31 patients (0.7%) in the liberal-control group and 47 patients (1.0%) in the tight-control group. The length of time that ICU care was needed was similar in the two groups (hazard ratio for earlier discharge alive with tight glucose control, 1.00; 95% confidence interval, 0.96 to 1.04; P = 0.94). Mortality at 90 days was also similar (10.1% with liberal glucose control and 10.5% with tight glucose control, P = 0.51). Analyses of eight prespecified secondary outcomes suggested that the incidence of new infections, the duration of respiratory and hemodynamic support, the time to discharge alive from the hospital, and mortality in the ICU and hospital were similar in the two groups, whereas severe acute kidney injury and cholestatic liver dysfunction appeared less prevalent with tight glucose control.

CONCLUSIONS

In critically ill patients who were not receiving early parenteral nutrition, tight glucose control did not affect the length of time that ICU care was needed or mortality. (Funded by the Research Foundation-Flanders and others; TGC-Fast ClinicalTrials.gov number, NCT03665207.).

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

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

Impact of tight blood glucose control within normal fasting ranges with insulin titration prescribed by the Leuven algorithm in adult critically ill patients: the TGC-fast randomized controlled trial

Background

It remains controversial whether critical illness-related hyperglycemia should be treated or not, since randomized controlled trials (RCTs) have shown context-dependent outcome effects. Whereas pioneer RCTs found improved outcome by normalizing blood glucose in patients receiving early parenteral nutrition (PN), a multicenter RCT revealed increased mortality in patients not receiving early PN. Although withholding early PN has become the feeding standard, the multicenter RCT showing harm by tight glucose control in this context has been criticized for its potentially unreliable glucose control protocol. We hypothesize that tight glucose control is effective and safe using a validated protocol in adult critically ill patients not receiving early PN.

Methods

The TGC-fast study is an investigator-initiated, multicenter RCT. Patients unable to eat, with need for arterial and central venous line and without therapy restriction, are randomized upon ICU admission to tight (80–110 mg/dl) or liberal glucose control (only initiating insulin when hyperglycemia >215 mg/dl, and then targeting 180–215 mg/dl). Glucose measurements are performed on arterial blood by a blood gas analyzer, and if needed, insulin is only administered continuously through a central venous line. If the arterial line is no longer needed, glucose is measured on capillary blood. In the intervention group, tight control is guided by the validated LOGIC-Insulin software. In the control arm, a software alert is used to maximize protocol compliance. The intervention is continued until ICU discharge, until the patient is able to eat or no longer in need of a central venous line, whatever comes first. The study is powered to detect, with at least 80% power and a 5% alpha error rate, a 1-day difference in ICU dependency (primary endpoint), and a 1.5% increase in hospital mortality (safety endpoint), for which 9230 patients need to be included. Secondary endpoints include acute and long-term morbidity and mortality, and healthcare costs. Biological samples are collected to study potential mechanisms of organ protection.

Discussion

The ideal glucose target for critically ill patients remains debated. The trial will inform physicians on the optimal glucose control strategy in adult critically ill patients not receiving early PN.

Trial registration

ClinicalTrials.gov NCT03665207. Registered on 11 September 2018.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06709-8.

Nurse led protocols for control of glycaemia in critically ill patients: A systematic review

BACKGROUND

Blood glucose control in critically ill patients is challenging and can affect clinical outcomes. Several manual as well as automated approaches have been proposed over the time, however nursing staff still covers the key-role for optimization of glycemia throughout adjustment of insulin infusion and administration.

AIM

Systematic review to compare the efficacy/the effects of nurse led insulin infusion protocols versus standard approaches in patients admitted in the intensive care unit.

METHODS

All relevant studies evaluating nurse directed protocols for insulin administration in critically ill adults. Data was independently extracted and collected through a dedicated electronic form. The following outcomes have been recorded: the number (or percentage) of glycaemia measurements within the target range; the number of hypo- and hyper-glycaemic events, separately; the mean glycaemia; the lowest and highest glycemia values recorded; the time to reach the glycaemia target; the ICU length of stay and the ICU and the long-term (>30 days) mortality. Statistical analysis was conducted on the summary statistics of the selected articles (eg, means, medians, proportions). Unpaired nonparametric continuous data were compared through the Mann-Whitney U-test.

RESULTS

Glycaemic control as well as ICU length of stay and mortality are similar in both patients' groups. Specifically, the group of patients treated with standard modalities include those treated with doctors led protocols, paper charts or software-based approaches.

CONCLUSION

Overall, nurse led insulin protocols can effectively control blood glucose level among critically ill patients.

Practical approach to clinical controversies in glycemic control for hospitalized surgical patients

The importance of glycemic management in surgical patient populations stems from an association between hyperglycemia and increased rates of surgical site infections, sepsis, and mortality. Various guidelines provide recommendations regarding target glucose concentrations, but all stress the importance of avoiding hypoglycemia as well. Within the surgical patient population, glycemic targets may vary further depending on the surgical service, such as cardiac surgery, neurosurgery, or reconstructive burn surgery. Glycemic management in critically ill surgical patients is achieved primarily through the use of intravenous insulin infusion protocols. These protocols can include fixed protocols, multiplication factor protocols, and computerized algorithms. In contrast, noncritically ill surgical patients are generally managed through the utilization of subcutaneous insulin with a combination of basal, bolus, and sliding scale insulin. Insulin protocols should be effective at maintaining glucose concentrations within the specified target range with minimal hypoglycemic events. Monitoring glucose concentrations while on either an intravenous or subcutaneous insulin protocol is essential. Point-of-care testing is the primary method for monitoring glucose concentrations in both critically ill and noncritically ill surgical patients and allows for adjustment of the insulin regimen. As patients move between units and to the outpatient setting, ensuring adequate follow-up is essential to maintaining control of hyperglycemia.

Artificial intelligence in critically ill diabetic patients: current status and future prospects

Recent years have witnessed increasing numbers of artificial intelligence (AI) based applications and devices being tested and approved for medical care. Diabetes is arguably the most common chronic disorder worldwide and AI is now being used for making an early diagnosis, to predict and diagnose early complications, increase adherence to therapy, and even motivate patients to manage diabetes and maintain glycemic control. However, these AI applications have largely been tested in non-critically ill patients and aid in managing chronic problems. Intensive care units (ICUs) have a dynamic environment generating huge data, which AI can extract and organize simultaneously, thus analysing many variables for diagnostic and/or therapeutic purposes in order to predict outcomes of interest. Even non-diabetic ICU patients are at risk of developing hypo or hyperglycemia, complicating their ICU course and affecting outcomes. In addition, to maintain glycemic control frequent blood sampling and insulin dose adjustments are required, increasing nursing workload and chances of error. AI has the potential to improve glycemic control while reducing the nursing workload and errors. Continuous glucose monitoring (CGM) devices, which are Food and Drug Administration (FDA) approved for use in non-critically ill patients, are now being recommended for use in specific ICU populations with increased accuracy. AI based devices including artificial pancreas and CGM regulated insulin infusion system have shown promise as comprehensive glycemic control solutions in critically ill patients. Even though many of these AI applications have shown potential, these devices need to be tested in larger number of ICU patients, have wider availability, show favorable cost-benefit ratio and be amenable for easy integration into the existing healthcare systems, before they become acceptable to ICU physicians for routine use.

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.

A prospective randomized trial comparing computerized columnar insulin dosing chart (the Atlanta protocol) versus the joint British diabetes societies for inpatient care protocol in management of hyperglycemia in patients with acute coronary syndrome admitted to cardiac care unit in Alexandria, Egypt

BACKGROUND

Hyperglycemia in acute coronary syndrome (ACS) is linked to raised morbidity and mortality. Insulin administration using insulin infusion protocols (IIP) is the preferred strategy to control hyperglycemia in critically ill patients. To date, no specific IIP has been identified as the most efficient for achieving glycemic control.

AIM

to compare glycemic achievements (safety) (primary objective), and coronary and other clinical outcomes (efficacy) (secondary objective) by hyperglycemia management in Cardiac Care Unit (CCU) using computerized Atlanta Protocol (Group (I)) versus paper-based Joint British Diabetes Societies (JBDS) For Inpatient Care Protocol (Group (II)).

PATIENTS AND METHODS

The study was done on 100 ACS patients admitted to Alexandria Main University hospital CCU with RBG >180 mg/dL. They were randomized into the 2 groups in a 1:1 ratio. CBG was measured hourly for 72 hours and was managed by IV insulin infusion.

RESULTS

Group (I) showed statistically significant less mean time for target BG achievement (3.52 ± 1.53hours), lower incidence of Level 1 hypoglycemia (2%) than Group (II) (4.76 ± 2.33 hours, 22%, p = 0.013, 0.002 respectively) and statistically significant less mean number of episodes above the glycemic target after its achievement than Group (II) (p < 0.001). Regarding Level 2 hypoglycemia the difference was not significant statistically.

CONCLUSION

Both protocols successfully maintained target BG level with low incidence of clinically significant hypoglycemia, however, the computerized Atlanta protocol achieved better glycemic outcomes. We recommend the use of the computerized Atlanta protocol in CCU rather than JBDS for Inpatient Care Protocol whenever this is feasible.

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.

Accuracy of Blood Glucose Measurement and Blood Glucose Targets

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Usability study of a new tool for nutritional and glycemic management in adult intensive care: Glucosafe 2

The new decision support tool Glucosafe 2 (GS2) is based on a mathematical model of glucose and insulin dynamics, designed to assist caregivers in blood glucose control and nutrition. This study aims to assess end-user acceptance and usability of this bedside decision support tool in an adult intensive care setting. Caregivers were first trained and then invited to trial GS2 prototype on bedside computers. Data for qualitative analysis were collected through semi-structured interviews from twenty users after minimum three trial days. Most caregivers (70%) rated GS2 as convenient and believed it would help improving adherence to current guidelines (85%). Moreover, most nurses (80%) believed that GS2 would be timesaving. Nurses' risk perceptions and manual data entry emerged as central barriers to use GS2 in routine practice. Issues emerged from the caregivers were compiled into a list of 12 modifications of the GS2 prototype to increase end-user acceptance and usability. This usability study showed that GS2 was considered by ICU caregivers as helpful in daily clinical practice, allowing time-saving and better standardization of ICU patient's care. Important issues were raised by the users with implications for the development and deployment of GS2. Integrating the technology into existing IT infrastructure may facilitate caregivers' acceptance. Further clinical studies of the performance and potential health outcomes are warranted.

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.

Blood glucose control in the intensive care unit: Where is the data?

Blood glucose control, including hyperglycemia correction, maintaining glucose at optimal level and avoiding hypoglycemia, is a challenge clinicians face every day in intensive care units (ICUs). If managed inadequately, its related mortality can increase. Prior to 2001, no relevant data from randomized, controlled studies assessing glucose control in the ICU were available. In the past 18 years, however, many clinical trials have defined criteria for managing abnormal blood glucose levels, as well as provided suggestions for glycemic monitoring. Point-of-care blood glucose monitors have become the preferred bedside technology to aid in glycemic management. In addition, in some institutions, continuous glucose monitoring is now available. Cost-effectiveness of adequate glycemic control in the ICU must be taken into consideration when addressing this complex issue. Newer types of glycemic monitoring may reduce nursing staff fatigue and shorten times for the treatment of hyperglycemia or hypoglycemia. There are a variety of glycemic care protocols available. However, not all ICU clinicians are aware of them. The following minireview describes some of these concepts.

Glycemic control outcomes of manual and computerized insulin titration protocols: a systematic review protocol

OBJECTIVE

The object of this systematic review is to determine the effectiveness of computerized insulin titration protocols compared to manual insulin titration protocols for glycemic control in hospitalized adult patients.

INTRODUCTION

Hyperglycemia is common during acute illness, and current recommendations for patients with altered glucose metabolism is the use of intravenous insulin therapy. Due to the narrow therapeutic index of insulin, euglycemia is difficult to achieve and requires frequent dose titrations and blood glucose checks. Dose titrations can be accomplished through the use of manual or computerized insulin titration protocols.

INCLUSION CRITERIA

This review will consider studies that compare manual and computerized insulin titration protocols for hospitalized adult patients requiring intravenous insulin therapy for hyperglycemia. Studies must have considered one or more glycemic control outcomes.

METHODS

This systematic review will use the JBI methodology for evidence of effectiveness. The search will be limited to studies published in English from 1984, as this was the approximate year that the first pilot study of a computerized titration protocol was implemented. The databases to be searched include: Cochrane Central Register of Controlled Trials, CINAHL, PubMed, Embase, Health Technology Assessments and Ovid Healthstar. The trial registers to be searched include: US National Library of Medicine (ClinicalTrials.gov). The search for unpublished studies will include ProQuest Dissertations and Theses, and MedNar. Retrieval of full-text studies, assessment of methodological quality and data extraction will be performed independently by two reviewers. Meta-analysis will be performed if possible, and a Grading of Recommendations, Assessment, Development and Evaluation (GRADE) Summary of Findings presented.

SYSTEMATIC REVIEW REGISTRATION NUMBER

PROSPERO CRD42019142776.

Glucose control in the ICU

PURPOSE OF REVIEW

Critically ill patients usually develop hyperglycemia, which is associated with adverse outcome. Controversy exists whether the relationship is causal or not. This review summarizes recent evidence regarding glucose control in the ICU.

RECENT FINDINGS

Despite promising effects of tight glucose control in pioneer randomized controlled trials, the benefit has not been confirmed in subsequent multicenter studies and one trial found potential harm. This discrepancy could be explained by methodological differences between the trials rather than by a different case mix. Strategies to improve the efficacy and safety of tight glucose control have been developed, including the use of computerized treatment algorithms.

SUMMARY

The ideal blood glucose target remains unclear and may depend on the context. As compared with tolerating severe hyperglycemia, tight glucose control is well tolerated and effective in patients receiving early parenteral nutrition when provided with a protocol that includes frequent, accurate glucose measurements and avoids large glucose fluctuations. All patient subgroups potentially benefit, with the possible exception of patients with poorly controlled diabetes, who may need less aggressive glucose control. It remains unclear whether tight glucose control is beneficial or not in the absence of early parenteral nutrition.

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.

Update on glucose in critical care

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

Hypoglycemia Prevention by Algorithm Design During Intravenous Insulin Infusion

PURPOSE OF REVIEW

This review examines algorithm design features that may reduce risk for hypoglycemia while preserving glycemic control during intravenous insulin infusion. We focus principally upon algorithms in which the assignment of the insulin infusion rate (IR) depends upon maintenance rate of insulin infusion (MR) or a multiplier.

RECENT FINDINGS

Design features that may mitigate risk for hypoglycemia include use of a mid-protocol bolus feature and establishment of a low BG threshold for temporary interruption of infusion. Computer-guided dosing may improve target attainment without exacerbating risk for hypoglycemia. Column assignment (MR) within a tabular user-interpreted algorithm or multiplier may be specified initially according to patient characteristics and medical condition with revision during treatment based on patient response. We hypothesize that a strictly increasing sigmoidal relationship between MR-dependent IR and BG may reduce risk for hypoglycemia, in comparison to a linear relationship between multiplier-dependent IR and BG. Guidelines are needed that curb excessive up-titration of MR and recommend periodic pre-emptive trials of MR reduction. Future research should foster development of recommendations for "protocol maxima" of IR appropriate to patient condition.

Critical Care Management of Stress-Induced Hyperglycemia

PURPOSE OF REVIEW

We discuss key studies that have set the scene for the debate on the efficacy and safety of tight glycemic control in critically ill patients, highlighting important differences among them, and describe the ensuing search towards strategies for safer glucose control.

RECENT FINDINGS

Differences in level of glycemic control, glucose measurement and insulin administration, expertise, and nutritional management may explain the divergent outcomes of the landmark studies on tight glycemic control in critical illness. Regarding strategies towards safer glucose control, several computerized algorithms have shown promise, but lack validation in adequately powered outcome studies. Real-time continuous glucose monitoring and closed loop blood glucose control systems are not up to the task yet due to technical challenges, though recent advances are promising. Alternatives for insulin have only been investigated in small feasibility studies. Severe hyperglycemia in critically ill patients generally is not tolerated anymore, but the optimal blood glucose target may depend on the specific patient and logistic context.

Informatics for the Modern Intensive Care Unit

Advanced informatics systems can help improve health care delivery and the environment of care for critically ill patients. However, identifying, testing, and deploying advanced informatics systems can be quite challenging. These processes often require involvement from a collaborative group of health care professionals of varied disciplines with knowledge of the complexities related to designing the modern and "smart" intensive care unit (ICU). In this article, we explore the connectivity environment within the ICU, middleware technologies to address a host of patient care initiatives, and the core informatics concepts necessary for both the design and implementation of advanced informatics systems.

Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them

Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care.