控制导向模型包括高胰岛素血症诱导的1型糖尿病胰岛素抵抗

M. Moscoso-Vásquez, P. Colmegna, R. Sánchez-Peña
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引用次数: 0

摘要

胰岛素抵抗(IR)是由高血糖症(HG)和高胰岛素血症(HI)诱发的1型糖尿病(TIDM)患者健康并发症的重要危险因素。考虑到胰岛素作用受损与TIDM的闭环血糖控制的相关性,在本研究中,通过添加患者胰岛素水平(IOB)的估计值作为模型输入,增强了先前面向控制的线性参数变化(LPV)模型。该模型是基于UVA/Padova代谢模拟器的分布版本获得的,并允许包含活性胰岛素对患者胰岛素敏感性的影响$(\ mathm {S}_{\ mathm {I}})$,并通过使用先验患者信息来应对患者之间的差异。该模型的有效性是通过与之前的面向控制的LPV模型进行比较来评估的,而LPV模型又是对之前的表示的改进,就其与UVA/Padova模型的开环和闭环差异而言。硅结果证明了在控制器设计阶段包括胰岛素堆积效应的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Control-Oriented Model Including Hyperinsulinemia Induced Insulin Resistance in Type 1 Diabetes
Insulin Resistance (IR) is an important risk factor for health complications in subjects with Type 1 Diabetes Mellitus (TIDM) that is induced by Hyperglycemia (HG) and Hyperinsulinemia (HI) conditions, among other triggers. Considering the relevance of impaired insulin action in closed-loop glycemic control in TIDM, in this work, a previous controloriented Linear Parameter-Varying (LPV) model is augmented by adding the estimate of the patient’s Insulin On Board (IOB) as a model input. The model is obtained based on the distribution version of the UVA/Padova metabolic simulator, and allows to include the effect of active insulin on the patient’s insulin sensitivity $(\mathrm {S}_{\mathrm {I}})$ and cope with inter-patient variability by using a priori patient information. The efficacy of this model is evaluated in comparison with the previous control-oriented LPV model which in turn is an improvement of previous representations, in terms of their open- and closed-loop differences with respect to the UVA/Padova model. In silico results evidence the importance of including the effects of insulin stacking at the controller-design stage.
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