B. Kovatchev, L. Farhy, D. Cox, M. Straume, V. Yankov, L. Gonder-Frederick, W. Clarke
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引用次数: 18
摘要
1型糖尿病患者胰岛素-葡萄糖相互作用的动态网络模型被开发并应用于40个受试者的数据集。每个数据集包含葡萄糖+胰岛素输注量和血糖(BG)测定,在1小时标准化的正糖高胰岛素钳夹和随后的1小时BG降至中度低血糖水平期间每5分钟采样一次。该模型近似于BG的时间模式,并在此基础上预测每个受试者的反调节反应。非线性拟合解释了受试者BG波动95%以上的方差,中位决定系数为97.7%。对于所有受试者,模型预测的反调节反应与测量的血浆肾上腺素浓度相关。测试期间观察到的BG最低点与模型预测的胰岛素利用系数(r = -0.51, p < 0.001)和反调节率(r = -0.63, p < 0.001)呈负相关。有多次严重低血糖发作史的受试者比无此类病史的受试者表现出较慢的反调节起效(p < 0.03)。
Modeling Insulin-Glucose Dynamics during Insulin Induced Hypoglycemia. Evaluation of Glucose Counterregulation
A dynamical network model of insulin-glucose interactions in subjects with Type I Diabetes was developed and applied to data sets for 40 subjects. Each data set contained the amount of dextrose + insulin infused and blood glucose (BG) determinations, sampled every 5 minutes during a one-hour standardized euglycemic hyperinsulinemic clamp and a subsequent one-hour BG reduction to moderate hypoglycemic levels. The model approximated the temporal pattern of BG and on that basis predicted the counterregulatory response of each subject. The nonlinear fits explained more than 95% of the variance of subjects' BG fluctuations, with a median coefficient of determination 97.7%. For all subjects the model-predicted counterregulatory responses correlated with measured plasma epinephrine concentrations. The observed nadirs of BG during the tests correlated negatively with the model-predicted insulin utilization coefficient (r = -0.51, p < 0.001) and counterregulation rates (r = -0.63, p < 0.001). Subjects with a history of multiple severe hypoglycemic episodes demonstrated slower onset of counterregulation compared to subjects with no such history (p < 0.03).