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

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dc.contributor.authorUyttendaele V
dc.contributor.authorShaw, Geoff
dc.contributor.authorDesaive T
dc.contributor.authorKnopp, Jennifer
dc.contributor.authorChase, Geoff
dc.date.accessioned2021-06-14T21:51:53Z
dc.date.available2021-06-14T21:51:53Z
dc.date.issued2020en
dc.date.updated2021-04-19T03:14:15Z
dc.description.abstractBackground: 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.en
dc.identifier.citationUyttendaele V, Knopp JL, Shaw GM, Desaive T, Chase JG (2020). Risk and reward: Extending stochastic glycaemic control intervals to reduce workload. BioMedical Engineering Online. 19(1). 26-.en
dc.identifier.doihttp://doi.org/10.1186/s12938-020-00771-6
dc.identifier.issn1475-925X
dc.identifier.urihttps://hdl.handle.net/10092/102038
dc.languageeng
dc.language.isoen
dc.publisherSpringer Science and Business Media LLCen
dc.rightsAll rights reserved unless otherwise stateden
dc.rights.urihttp://hdl.handle.net/10092/17651en
dc.subjectHumansen
dc.subjectModels, Statisticalen
dc.subjectRisk Assessmenten
dc.subjectStochastic Processesen
dc.subjectWorkloaden
dc.subjectGlycemic Controlen
dc.subjecthyperglycaemiaen
dc.subjectblood glucoseen
dc.subjectinsulin therapyen
dc.subjectinsulin sensitivityen
dc.subjectinsulin resistanceen
dc.subjecttrade-offen
dc.subject.anzsrc0903 Biomedical Engineeringen
dc.subject.anzsrcFields of Research::32 - Biomedical and clinical sciences::3202 - Clinical sciences::320212 - Intensive careen
dc.subject.anzsrcFields of Research::32 - Biomedical and clinical sciences::3202 - Clinical sciences::320208 - Endocrinologyen
dc.subject.anzsrcFields of Research::40 - Engineering::4003 - Biomedical engineering::400306 - Computational physiologyen
dc.titleRisk and reward: Extending stochastic glycaemic control intervals to reduce workloaden
dc.typeJournal Articleen
uc.collegeFaculty of Engineering
uc.departmentMechanical Engineering
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