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  • STAR-3D Clinical Trial Resu...
    Uyttendaele, Vincent; Knopp, Jennifer L.; Desaive, Thomas; Chase, J. Geoffrey

    IFAC-PapersOnLine, 2021, 2021-00-00, Letnik: 54, Številka: 15
    Journal Article, Web Resource

    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.