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首页> 外文期刊>Metabolism: Clinical and Experimental >Population and individual minimal modeling of the frequently sampled insulin-modified intravenous glucose tolerance test.
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Population and individual minimal modeling of the frequently sampled insulin-modified intravenous glucose tolerance test.

机译:经常采样的胰岛素修饰的静脉葡萄糖耐量试验的人群和个体最小模型。

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Population approaches are more robust estimators of insulin sensitivity (SI) and glucose effectiveness (SG) with the minimal model of glucose kinetics during an intravenous glucose tolerance test (IVGTT). We assessed the performance of 3 population methods, iterative two-stage (ITS), Bayesian hierarchical Markov chain Monte Carlo (MCMC), and NONMEM first-order conditional estimation (FOCE) with interaction (NM), and made a comparison with the standard two-stage method (STS) employing the weighted nonlinear regression analysis. To evaluate accuracy of individual and population estimates, 40 simulated insulin-modified frequently sampled IVGTTs (IM-FSIVGTT) were derived from real IM-FSIVGTTs (0.3 g glucose per kg body weight with 0.02 U/kg insulin at 20 minutes; 30 samples over 180 minutes) performed in 40 healthy Caucasian subjects (male/female, 22/18; age, 46 +/- 9 years; body mass index [BMI], 26.7 +/- 5.7 kg. m(-2); mean +/- SD). The population methods assumed a log-normal population distribution of parameters. All methods gave a similar but overestimated population SG by 9% to 13%. Population SI was underestimated to a different degree by the methods (STS 6%, ITS 10%, MCMC 13%, and NM 7%). The between-subject variability of SG was overestimated by STS and underestimated by the population methods (true 33%, STS 40%, ITS 19%, MCMC 24%, NM 24%; coefficient of variation). For SI, this quantity was well estimated by all methods (true 79%, STS 80%, ITS 82%, MCMC 83%, NM 82%). The results for individual estimates indicate that STS performs better than the population methods when estimating SI (STS 12%, ITS 16%, MCMC 16%, NM 16%; 1 outlying subject excluded; root mean squared error expressed as percent of mean) but worse for SG (STS 28%, ITS 21%, MCMC 20%, NM 19%). We conclude that the robust performance of population approaches, preventing parameter estimation failures associated with the nonlinear regression analysis, is not required with IM-FSIVGTT in subjects with normal glucose tolerance. The standard two-stage technique is the preferred method under such circumstances.
机译:人群方法是对胰岛素敏感性(SI)和葡萄糖有效性(SG)的更可靠的估计,在静脉葡萄糖耐量试验(IVGTT)期间具有最小的葡萄糖动力学模型。我们评估了三种总体方法的性能:迭代两阶段(ITS),贝叶斯层次马尔可夫链蒙特卡洛(MCMC)和带有交互(NM)的NONMEM一阶条件估计(FOCE),并与标准进行了比较采用加权非线性回归分析的两阶段方法(STS)。为了评估个人和人群估计的准确性,从真实的IM-FSIVGTTs中提取了40个模拟胰岛素修饰的频繁采样的IVGTT(IM-FSIVGTT)(每分钟体重0.3 g葡萄糖,在20分钟时为0.02 U / kg胰岛素;超过30个样品180分钟)在40位健康的白种人受试者(男性/女性,22/18;年龄,46 +/- 9岁;体重指数[BMI],26.7 +/- 5.7 kg。m(-2);平均值+ / -SD)。总体方法假设参数的对数正态分布。所有方法都使人口SG相似但被高估了9%至13%。通过方法(STS 6%,ITS 10%,MCMC 13%和NM 7%)在不同程度上低估了人口SI。 SG的受试者间变异性被STS高估,而被总体方法低估了(真实33%,STS​​ 40%,ITS 19%,MCMC 24%,NM 24%;变异系数)。对于SI,可以通过所有方法(真实79%,STS​​ 80%,ITS 82%,MCMC 83%,NM 82%)很好地估算此数量。单个估计的结果表明,在估计SI时,STS的性能优于总体方法(STS 12%,ITS 16%,MCMC 16%,NM 16%;排除了一名外围受试者;均方根误差表示为均值百分比),但SG的情况更糟(STS为28%,ITS为21%,MCMC为20%,NM为19%)。我们得出结论,对于糖耐量正常的受试者,IM-FSIVGTT不需要总体方法的强大性能,可以防止与非线性回归分析相关的参数估计失败。在这种情况下,标准的两阶段技术是首选方法。

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