Gooley Judith L, Walters Jacqueline M, Ward Glenn M
Department of Medicine, St. Vincent's Hospital, University of Melbourne, Victoria, Australia.
Diabetes Technol Ther. 2009 Jan;11(1):25-30. doi: 10.1089/dia.2008.0018.
Glucose effectiveness (S(g)) is an important component in glucose tolerance. Values of S(g) using "open loop" glucose kinetic computer programs are usually higher compared to closed loop method (CLM) programs that incorporate insulin secretion modeling. We aimed to test whether these differences are caused by (1) inclusion of insulin secretion modeling or (2) the method of representing plasma insulin values in the first few minutes of the frequently sampled intravenous glucose tolerance test (FSIGT).
FSIGTs without insulin supplementation were performed in six healthy volunteers, and the Bergman minimal model was fitted to the data using the simulation and modeling program SAAM.
The CLM, which represents the insulin data in the first few minutes by a best-fit curve extrapolated to the y-axis, yielded a significantly lower S(g) than the approach similar to the computer program MINMOD, where the first few minutes of insulin data are represented by a line joining the basal to the peak values (1.55 +/- 0.28 vs. 1.97 +/- 0.27 [SE] x 10(-2)/min, P < 0.05). This second analysis was then repeated while forcing the program to represent the insulin data after the insulin peak in the same way as in the CLM, obtaining an almost identical result for S(g) (1.99 +/- 0.29). Insulin sensitivity was not significantly affected.
The higher S(g) estimates are caused by the method of representing the first few minutes of insulin data rather than by the incorporation of insulin secretion modeling. It is, therefore, important to know how the early insulin data are represented when comparing results from different computer modeling programs.
葡萄糖效能（S(g)）是葡萄糖耐量的一个重要组成部分。与纳入胰岛素分泌模型的闭环方法（CLM）程序相比，使用“开环”葡萄糖动力学计算机程序得出的S(g)值通常更高。我们旨在测试这些差异是否由以下原因导致：（1）纳入胰岛素分泌模型；（2）在频繁采样静脉葡萄糖耐量试验（FSIGT）的最初几分钟内表示血浆胰岛素值的方法。
对6名健康志愿者进行了无胰岛素补充的FSIGT，并使用模拟和建模程序SAAM将伯格曼最小模型拟合到数据中。
CLM通过外推到y轴的最佳拟合曲线来表示最初几分钟的胰岛素数据，其得出的S(g)显著低于类似于计算机程序MINMOD的方法，即最初几分钟的胰岛素数据由连接基础值到峰值的一条线表示（1.55±0.28对1.97±0.27[SE]×10⁻²/min，P<0.05）。然后重复第二次分析，同时强制程序以与CLM相同的方式表示胰岛素峰值后的胰岛素数据，得出的S(g)结果几乎相同（1.99±0.29）。胰岛素敏感性未受到显著影响。
较高的S(g)估计值是由表示最初几分钟胰岛素数据的方法导致的，而非纳入胰岛素分泌模型。因此，在比较不同计算机建模程序的结果时，了解早期胰岛素数据的表示方式很重要。
