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STAR-3D Clinical Trial Results: Improved performance and safety

机译：Star-3D临床试验结果：提高性能和安全性

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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.
机译：血糖控制（GC）改善了重症监护单位（ICU）患者的结果。然而，由于患者间可变性和患者间变异性导致的低血糖和血糖变异的风险增加了安全，有效的GC困难。随机靶向（Star）GC框架是一种独特的患者特异性风险的计量协议，直接占使用未来患者变异性的随机模型的间接模型和内部患者的变异性。在虚拟试验中开发和验证的新的三变变（3D）随机模型，以提供更准确的未来胰岛素敏感性（SI）的预测，在临床上评估.STAR-3D在新西兰克赖斯特彻奇医院ICU实施标准护理，2019年4月至1月2021年。总共治疗了567名患者（33276小时）。实现的总中位数[IQR] BG为6.7 [6.0 7.8] mmol / L，4.4-8.0mmol / L靶带中的76％BG。重要的是，只有0.3％BG <4.0 mmol / L（轻度低血糖）和严重低血糖的发病率（Bg <2.2mmol / L）。通过中位数[IQR] 4.0 [2.0 6.0] U / H胰岛素和中位数[IQR]营养递送99 [80 100]％饲料（GF）来实现这些结果。在每位患者水平上获得了类似的安全性和性能BG结果，表明Star-3D为所有患者成功提供了安全，有效的控制，无论患者状况如何。与原始版本的星星，Star-3d提供了提高的安全性和疗效，同时实现了更高的营养交付。尽管使用更高的胰岛素，但Star-3d中的新型3D随机模型为所有患者提供了更高的安全性和功效。比其前身提供更大的营养交付。因此，Star-3D因此更好地捕获了患者特定的条件和可变性，以提供改进的GC结果。

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