ArticleJournal of diabetes science and technology2012
Stochastic targeted (STAR) glycemic control: design, safety, and performance.
Article in Journal of diabetes science and technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 120 citations in OpenAlex.
- Pilot study of a model-based approach to blood glucose control in very-low-birthweight neonates.BMC pediatrics · 2012Trial
- A digital twin for tracking and forecasting glycemia with septic patients in ICUs.npj metabolic health and disease · 2026Article
- Algorithm-guided insulin therapy in hospitalized patients: current evidence, implementation challenges, and future perspectives.Reviews in endocrine & metabolic disorders · 2026Review
- Determining Losses in Jet Injection Subcutaneous Insulin Delivery: A Model-Based Approach.Journal of diabetes science and technology · 2023Article
- Estimating Enhanced Endogenous Glucose Production in Intensive Care Unit Patients with Severe Insulin Resistance.Journal of diabetes science and technology · 2022Article
- Estimating Increased EGP During Stress Response in Critically Ill Patients.Journal of diabetes science and technology · 2021Article
- Insulin sensitivity in critically ill patients: are women more insulin resistant?Annals of intensive care · 2021Article
- Increased insulin resistance in intensive care: longitudinal retrospective analysis of glycaemic control patients in a New Zealand ICU.Therapeutic advances in endocrinology and metabolism · 2021Article
- Risk and reward: extending stochastic glycaemic control intervals to reduce workload.Biomedical engineering online · 2020Article
- Assessment of Glycemic Control Protocol (STAR) Through Compliance Analysis Amongst Malaysian ICU Patients.Medical devices (Auckland, N.Z.) · 2020Article
- 3D kernel-density stochastic model for more personalized glycaemic control: development and in-silico validation.Biomedical engineering online · 2019Article
- Interpretation of Retrospective BG Measurements.Journal of diabetes science and technology · 2018Article
- 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
- Safety, efficacy and clinical generalization of the STAR protocol: a retrospective analysis.Annals of intensive care · 2016Article
- Glucose Control in the ICU: A Continuing Story.Journal of diabetes science and technology · 2016Review
- Simulation and qualitative analysis of glucose variability, mean glucose, and hypoglycemia after subcutaneous insulin therapy for stress hyperglycemia.Theoretical biology & medical modelling · 2016Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 2 countries.
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 that directly accounts for intra- and interpatient variability with a stochastically derived maximum 5% risk of blood glucose (BG) below 72 mg/dl. This research assesses the safety, efficacy, and clinical burden of a STAR TGC controller modulating both insulin and nutrition inputs in virtual and clinical pilot trials.
methodsClinically validated virtual trials using data from 370 patients in the SPRINT (Specialized Relative Insulin and Nutrition Titration) study were used to design the STAR protocol and test its safety, performance, and required clinical effort prior to clinical pilot trials. Insulin and nutrition interventions were given every 1-3 h as chosen by the nurse to allow them to manage workload. Interventions were designed to maximize the overlap of the model-predicted (5-95(th) percentile) range of BG outcomes with the 72-117 mg/dl band and thus provide a maximum 5% risk of BG <72 mg/dl. Interventions were calculated using clinically validated computer models of human metabolism and its variability in critical illness. Carbohydrate intake (all sources) was selected to maximize intake up to 100% of the American College of Chest Physicians/Society of Critical Care Medicine (ACCP/SCCM) goal (25 kg/kcal/h). Insulin doses were limited (8 U/h maximum), with limited increases based on current rate (0.5-2.0 U/h). Initial clinical pilot trials involved 3 patients covering ~450 h. Approval was granted by the Upper South A Regional Ethics Committee.
resultsVirtual trials indicate that STAR provides similar glycemic control performance to SPRINT with 2-3 h (maximum) measurement intervals. Time in the 72-126 mg/dl and 72-145 mg/dl bands was equivalent for all controllers, indicating that glycemic outcome differences between protocols were only shifted in this range. Safety from hypoglycemia was improved. Importantly, STAR using 2-3 h (maximum) intervention intervals reduced clinical burden up to 30%, which is clinically very significant. Initial clinical trials showed glycemic performance, safety, and management of inter- and intrapatient variability that matched or exceeded the virtual trial results.
conclusionsIn virtual trials, STAR TGC provided tight control that maximized the likelihood of BG in a clinically specified glycemic band and reduced hypoglycemia with a maximum 5% (or lower) expected risk of light hypoglycemia (BG <72 mg/dl) via model-based management of intra- and interpatient variability. Clinical workload was self-managed and reduced up to 30% compared with SPRINT. Initial pilot clinical trials matched or exceeded these virtual results.
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