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Development of blood glucose control for extremely premature infants

机译:极早产儿血糖控制的发展

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摘要

Extremely premature neonates often experience hyperglycaemia, which has been linked to increased mortality and worsened outcomes. Insulin therapy can assist in controlling blood glucose levels and promoting needed growth. This study presents the development of a model-based stochastic targeted controller designed to adapt insulin infusion rates to match the unique and changing metabolic state and control parameters of the neonate. Long-term usage of targeted BG control requires successfully forecasting variations in neonatal metabolic state, accounting for differences in clinical practices between units, and demonstrating robustness to errors that can occur in everyday clinical usage. Simulation studies were used to evaluate controller ability to target several common BG ranges and evaluate controller sensitivity to missed BG measurements and delays in control interventions on a virtual patient cohort of 25 infants developed from retrospective data. Initial clinical pilot trials indicated model performance matched expected performance from simulations. Stochastic targeted glucose control developed using validated patient-specific virtual trials can yield effective protocols for this cohort. Long-term trials show fundamental success, however clinical interface design appears as a critical factor to ensuring good compliance and thus good control.
机译:极早产的新生儿经常会发生高血糖症,这与死亡率增加和结果恶化有关。胰岛素疗法可帮助控制血糖水平并促进所需的生长。这项研究提出了一种基于模型的随机目标控制器的开发,该控制器旨在调整胰岛素的输注速度,以匹配新生儿独特且不断变化的代谢状态和控制参数。长期使用靶向BG控制剂需要成功地预测新生儿代谢状态的变化,解决单位之间临床实践的差异,并证明其对日常临床使用中可能发生的错误的鲁棒性。模拟研究用于评估针对多个常见BG范围的控制器能力,并评估控制器对错过的BG测量值的敏感性,以及根据回顾性数据对25名婴儿进行虚拟患者队列控制干预的延迟。初步的临床试验表明,模型性能与仿真结果相符。使用经过验证的针对特定患者的虚拟试验开发的随机靶向葡萄糖控制可以产生针对该队列的有效方案。长期试验显示出基本的成功,但是临床界面设计似乎是确保良好依从性并因此获得良好控制的关键因素。

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