ArticleAnnals of intensive care2011
Pilot proof of concept clinical trials of Stochastic Targeted (STAR) glycemic control.
Article in Annals of intensive care, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Pilot study of the SPRINT glycemic control protocol in a Hungarian medical intensive care unit.Journal of diabetes science and technology · 2012Trial
- Second pilot trials of the STAR-Liege protocol for tight glycemic control in critically ill patients.Biomedical engineering online · 2012Trial
- Estimating Enhanced Endogenous Glucose Production in Intensive Care Unit Patients with Severe Insulin Resistance.Journal of diabetes science and technology · 2022Article
- Stochastic integrated model-based protocol for volume-controlled ventilation setting.Biomedical engineering online · 2022Article
- Model-based glycemic control in a Malaysian intensive care unit: performance and safety study.Medical devices (Auckland, N.Z.) · 2019Article
- Optimising mechanical ventilation through model-based methods and automation.Annual reviews in control · 2019Review
- Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas.Critical care (London, England) · 2018Review
- Hypoglycemia Prevention by Algorithm Design During Intravenous Insulin Infusion.Current diabetes reports · 2018Review
- 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.Biomedical engineering online · 2018Review
- Nutrition delivery of a model-based ICU glycaemic control system.Annals of intensive care · 2018Article
- Continuous Glucose Monitoring Measures Can Be Used for Glycemic Control in the ICU: An In-Silico Study.Journal of diabetes science and technology · 2018Article
- Untangling glycaemia and mortality in critical care.Critical care (London, England) · 2017Article
- A C-Peptide-Based Model of Pancreatic Insulin Secretion in Extremely Preterm Neonates in Intensive Care.Journal of diabetes science and technology · 2015Article
- The benefits of tight glycemic control in critical illness: Sweeter than assumed?Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2014Review
- Evolution of insulin sensitivity and its variability in out-of-hospital cardiac arrest (OHCA) patients treated with hypothermia.Critical care (London, England) · 2014Article
- Reducing the impact of insulin sensitivity variability on glycaemic outcomes using separate stochastic models within the STAR glycaemic protocol.Biomedical engineering online · 2014Article
- On the problem of patient-specific endogenous glucose production in neonates on stochastic targeted glycemic control.Journal of diabetes science and technology · 2013Review
- The future is now: software-guided intensive insulin therapy in the critically ill.Journal of diabetes science and technology · 2013Review
- Variability of insulin sensitivity during the first 4 days of critical illness: implications for tight glycemic control.Annals of intensive care · 2012Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionTight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. STAR (Stochastic TARgeted) is a flexible, model-based TGC approach directly accounting for intra- and inter- patient variability with a stochastically derived maximum 5% risk of blood glucose (BG) < 4.0 mmol/L. This research assesses the safety, efficacy, and clinical burden of a STAR TGC controller modulating both insulin and nutrition inputs in pilot trials.
methodsSeven patients covering 660 hours. Insulin and nutrition interventions are given 1-3 hourly as chosen by the nurse to allow them to manage workload. Interventions are calculated by using clinically validated computer models of human metabolism and its variability in critical illness to maximize the overlap of the model-predicted (5-95th percentile) range of BG outcomes with the 4.0-6.5 mmol/L band while ensuring a maximum 5% risk of BG < 4.0 mmol/L. Carbohydrate intake (all sources) was selected to maximize intake up to 100% of SCCM/ACCP goal (25 kg/kcal/h). Maximum insulin doses and dose changes were limited for safety. Measurements were made with glucometers. Results are compared to those for the SPRINT study, which reduced mortality 25-40% for length of stay ≥3 days. Written informed consent was obtained for all patients, and approval was granted by the NZ Upper South A Regional Ethics Committee.
resultsA total of 402 measurements were taken over 660 hours (~14/day), because nurses showed a preference for 2-hourly measurements. Median [interquartile range, (IQR)] cohort BG was 5.9 mmol/L [5.2-6.8]. Overall, 63.2%, 75.9%, and 89.8% of measurements were in the 4.0-6.5, 4.0-7.0, and 4.0-8.0 mmol/L bands. There were no hypoglycemic events (BG < 2.2 mmol/L), and the minimum BG was 3.5 mmol/L with 4.5% < 4.4 mmol/L. Per patient, the median [IQR] hours of TGC was 92 h [29-113] using 53 [19-62] measurements (median, ~13/day). Median [IQR] results: BG, 5.9 mmol/L [5.8-6.3]; carbohydrate nutrition, 6.8 g/h [5.5-8.7] (~70% goal feed median); insulin, 2.5 U/h [0.1-5.1]. All patients achieved BG < 6.1 mmol/L. These results match or exceed SPRINT and clinical workload is reduced more than 20%.
conclusionsSTAR TGC modulating insulin and nutrition inputs provided very tight control with minimal variability by managing intra- and inter- patient variability. Performance and safety exceed that of SPRINT, which reduced mortality and cost in the Christchurch ICU. The use of glucometers did not appear to impact the quality of TGC. Finally, clinical workload was self-managed and reduced 20% compared with SPRINT.
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Registered trials
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