Pacini G, Bergman R N
Comput Methods Programs Biomed. 1986 Oct;23(2):113-22. doi: 10.1016/0169-2607(86)90106-9.
Insulin sensitivity and pancreatic responsivity are the two main factors controlling glucose tolerance. We have proposed a method for measuring these two factors, using computer analysis of a frequently-sampled intravenous glucose tolerance test (FSIGT). This 'minimal modelling approach' fits two mathematical models with FSIGT glucose and insulin data: one of glucose disappearance and one of insulin kinetics. MINMOD is the computer program which identifies the model parameters for each individual. A nonlinear least squares estimation technique is used, employing a gradient-type of estimation algorithm, and the first derivatives (not known analytically) are computed according to the 'sensitivity approach'. The program yields the parameter estimates and the precision of their estimation. From the model parameters, it is possible to extract four indices: SG, the ability of glucose per se to enhance its own disappearance at basal insulin, SI, the tissue insulin sensitivity index, phi 1, first phase pancreatic responsivity, and phi 2, second phase pancreatic responsivity. These four characteristic parameters have been shown to represent an integrated metabolic portrait of a single individual.
胰岛素敏感性和胰腺反应性是控制糖耐量的两个主要因素。我们提出了一种测量这两个因素的方法，即通过对频繁采样的静脉葡萄糖耐量试验（FSIGT）进行计算机分析。这种“最小模型法”将两个数学模型与FSIGT的葡萄糖和胰岛素数据相拟合：一个是葡萄糖消失模型，另一个是胰岛素动力学模型。MINMOD是用于识别每个个体模型参数的计算机程序。使用非线性最小二乘估计技术，采用梯度型估计算法，并根据“灵敏度法”计算一阶导数（无法通过解析得到）。该程序可得出参数估计值及其估计精度。根据模型参数，可以提取四个指标：SG，基础胰岛素水平下葡萄糖自身促进其消失的能力；SI，组织胰岛素敏感性指数；phi 1，第一阶段胰腺反应性；以及phi 2，第二阶段胰腺反应性。这四个特征参数已被证明代表了单个个体的综合代谢特征。
