[en] Glycemic control (GC) has improved outcomes for intensive care unit (ICU) patients. However, the increased risk of hypoglycemia and glycemic variability due to inter- and intra- patient variability make safe, effective GC difficult. Stochastic TARgeted (STAR) GC framework is a unique, patient-specific, risk-based dosing protocol directly accounting for both inter- and intra- patient variability using a stochastic model of future patient variability. A new tri-variate (3D) stochastic model, developed and validated in virtual trials to provide more accurate future predictions of insulin sensitivity (SI), is clinically evaluated.
STAR-3D was implemented as standard care at the Christchurch Hospital ICU, New Zealand, between April 2019 and January 2021. In total, 567 patients (33276 hours) were treated. The overall median [IQR] BG achieved was 6.7 [6.0 7.8] mmol/L with 76% BG in the 4.4-8.0 mmol/L target band. Importantly, there were only 0.3% BG < 4.0 mmol/L (mild hypoglycemia) and no incidence of severe hypoglycemia (BG < 2.2 mmol/L). These outcomes were achieved with median [IQR] 4.0 [2.0 6.0] U/h insulin and median [IQR] nutrition delivery of 99 [80 100]% goal feed (GF). Similar safety and performance BG outcomes were obtained at a per-patient level, suggesting STAR-3D successfully provided safe, effective control for all patients, regardless of patient condition. Compared to the original version of STAR, STAR-3D provided improved safety and efficacy, while achieving higher nutrition delivery.
The new 3D stochastic model in STAR-3D provided higher safety and efficacy for all patients in this large clinical trial, despite using higher insulin rates than its predecessor to provide greater nutrition delivery. STAR-3D thus better captured patient-specific condition and variability to provide improved GC outcomes.
Disciplines :
Anesthesia & intensive care Endocrinology, metabolism & nutrition Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Uyttendaele, Vincent ; Université de Liège - ULiège > GIGA In silico - Model-based therap., Critic. Care Basic Sc.
Knopp, Jennifer L.
Desaive, Thomas ; Université de Liège - ULiège > Département d'astrophys., géophysique et océanographie (AGO) > Thermodynamique des phénomènes irréversibles
Chase, J. Geoffrey
Language :
English
Title :
STAR-3D Clinical Trial Results: Improved performance and safety
Publication date :
2021
Event name :
11th IFAC Symposium on Biological and Medical Systems BMS 2021
Event place :
Ghent, Belgium
Event date :
19-22 Septembre 2021
Audience :
International
Journal title :
IFAC-PapersOnLine
ISSN :
2405-8971
eISSN :
2405-8963
Publisher :
Elsevier, Kidlington, United Kingdom
Special issue title :
11th IFAC Symposium on Biological and Medical Systems BMS 2021
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