Transient and steady-state euglycemic clamp validation of a model for glycemic control and insulin sensitivity testing
Transient and steady-state euglycemic clamp validation of a model for glycemic control and insulin sensitivity testing
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DOI：
10.1089/dia.2006.8.338
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发表时间：
2006-06-01
影响因子：
5.4
通讯作者：
Mann, Jim I.
中科院分区：
文献类型：
--
作者：
Lotz, Thomas F.;Chase, J. Geoffrey;Mann, Jim I.
背景资料：迫切需要一种简单而准确的胰岛素敏感性测量方法来诊断一般人群的胰岛素抵抗并量化临床干预引起的变化。一个新的生理控制模型的葡萄糖和胰岛素代谢的正常血糖-高胰岛素钳夹试验在稳态和瞬态states.Methods：数据包括n = 60（15瘦，15超重，15肥胖，和15病态肥胖）正常血糖的胰岛素抵抗个体进行正常血糖-高胰岛素钳夹试验。使用基于积分的方法拟合葡萄糖和胰岛素模型。在稳态和瞬态下，得到了钳夹衍生的胰岛素敏感性指数（ISI）和模型的胰岛素敏感性参数（SI）之间的相关性。结果与对数稳态模型评估（HOMA），一个广泛使用的空腹胰岛素sensitivity.Results替代：基于模型的胰岛素敏感性，S-I，和ISIG（ISI标准化的稳态葡萄糖）之间的相关性是r = 0.99（n = 60）在稳态和r = 0.97在瞬态，分别。各亚组之间的相关性没有显着变化，95%置信区间较窄。Log-HOMA相关性为r = -0.72到S-I和r = -0.71到ISIG的总人口，但在亚组中显着降低，具有宽95%的置信区间。结论：基于模型的胰岛素敏感性参数，SI，在所有亚组中与ISIG高度相关，即使只考虑短暂状态。SI的高度相关性提供了一种目前尚不可用的基于模型的胰岛素敏感性评估的可能性，该评估简短、简单但高度相关。
Background: There is an urgent need for a simple and accurate measure of insulin sensitivity to diagnose insulin resistance in the general population and quantify changes due to clinical intervention. A new physiological control model of glucose and insulin metabolism is validated with the euglycemic-hyperinsulinemic clamp during steady and transient states.Methods: The data consist of n = 60 (15 lean, 15 overweight, 15 obese, and 15 morbidly obese) euglycemic-hyperinsulinemic clamp trials performed on normoglycemic insulin-resistant individuals. The glucose and insulin model is fitted using an integral-based method. Correlations between clamp-derived insulin sensitivity index (ISI) and the model's insulin sensitivity parameter (SI) are obtained during steady and transient states. Results are compared with log-homeostasis model assessment (HOMA), a widely used fasting surrogate for insulin sensitivity.Results: Correlation between model-based insulin sensitivity, S-I, and ISIG (ISI normalized by steady-state glucose) is r = 0.99 (n = 60) at steady state and r = 0.97 at transient state, respectively. Correlations did not significantly change across subgroups, with narrow 95% confidence intervals. Log-HOMA correlations are r = -0.72 to S-I and r = -0.71 to ISIG for the overall population but are significantly lower in the subgroups, with wide 95% confidence intervals.Conclusions: The model-based insulin sensitivity parameter, SI, highly correlates to ISIG in all subgroups, even when only considering a transient state. The high correlation of SI offers the potential for a short, simple yet highly correlated, model-based assessment of insulin sensitivity that is not currently available.