论文标题
甲状腺功能亢进治疗的建模和预测控制
Modeling and Predictive Control for the Treatment of Hyperthyroidism
论文作者
论文摘要
在这项工作中,我们提出了一种方法来确定抗甲状腺药物治疗甲状腺功能亢进症患者的剂量。我们建议通过模型预测控制(MPC)方案来确定剂量,而不是依靠通常在临床实践中进行的试验方法。为此,我们首先扩展了垂体 - 甲状腺反馈回路的数学模型,以便可以考虑甲咪唑的摄入量。其次,基于扩展模型,我们开发了一个MPC方案来确定合适的剂量。在数值模拟中,我们考虑了(i)患者受坟墓疾病影响并口服药物的情况,以及(ii)患有威胁生命的甲状腺毒性病的患者,通常会静脉内给予药物治疗。我们的概念研究表明,通过MPC方案确定药物剂量可能是当前应用反复试验方法的有前途替代方法。
In this work, we propose an approach to determine the dosages of antithyroid agents to treat hyperthyroid patients. Instead of relying on a trial-and-error approach as it is commonly done in clinical practice, we suggest to determine the dosages by means of a model predictive control (MPC) scheme. To this end, we first extend a mathematical model of the pituitary-thyroid feedback loop such that the intake of methimazole, a common antithyroid agent, can be considered. Second, based on the extended model, we develop an MPC scheme to determine suitable dosages. In numerical simulations, we consider scenarios in which (i) patients are affected by Graves' disease and take the medication orally and (ii) patients suffering from a life-threatening thyrotoxicosis, in which the medication is usually given intravenously. Our conceptual study suggests that determining the medication dosages by means of an MPC scheme could be a promising alternative to the currently applied trial-and-error approach.