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Computational evaluation of the dynamic minimal model for the root causes of hypoglycemia

机译：动态最小模型对低血糖症根源的计算评估

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This research is an attempt to validate how glu-cose-insulin dynamic mathematical model facilitate to identify the root causes for hypoglycaemia. The purpose is to determine whether increased insulin sensitivity or increased insulin secretion causes post- prandial hypoglycemic (PPH) response, by linking experimental patient data with dynamic mathematical model. For this purpose two groups, as hypoglycemic Group 1 and non-hypoglycemic Group 2, each of which consists of 10 people, are formed. The oral glucose tolerance test (OGTT) is carried out for each person in the groups by measuring plasma glucose and insulin concentrations at every 30 minutes for a period of 5 hours. To distinguish the actual cause of hypoglycemia, the glucose minimal dynamic model is used. The model is executed in MATLAB platform using patient data and the results showed that insulin secretion is assumed to be the potential root cause for the hypoglycemia.
机译：这项研究是试图验证葡萄糖-胰岛素动态数学模型如何促进识别低血糖的根本原因。目的是通过将实验患者数据与动态数学模型相链接，来确定增加的胰岛素敏感性或增加的胰岛素分泌是否引起餐后降血糖（PPH）反应。为此目的，形成了两个小组，即低血糖组1和非低血糖组2，每组由10人组成。通过测量每30分钟一次的血浆葡萄糖和胰岛素浓度（持续5小时），对组中的每个人进行口服葡萄糖耐量测试（OGTT）。为了区分低血糖的实际原因，使用了葡萄糖最小动态模型。该模型在MATLAB平台上使用患者数据执行，结果表明胰岛素分泌被认为是低血糖症的潜在根本原因。

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