Department of Mechanical Engineering, Centre for Bioengineering, University of Canterbury, Christchurch, New Zealand.
Discipline of Nutrition, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.
J Diabetes Sci Technol. 2022 May;16(3):732-741. doi: 10.1177/1932296821991120. Epub 2021 Feb 15.
The ability to measure insulin secretion from pancreatic beta cells and monitor glucose-insulin physiology is vital to current health needs. C-peptide has been used successfully as a surrogate for plasma insulin concentration. Quantifying the expected variability of modelled insulin secretion will improve confidence in model estimates.
Forty-three healthy adult males of Māori or Pacific peoples ancestry living in New Zealand participated in an frequently sampled, intravenous glucose tolerance test (FS-IVGTT) with an average age of 29 years and a BMI of 33 kg/m. A 2-compartment model framework and standardized kinetic parameters were used to estimate endogenous pancreatic insulin secretion from plasma C-peptide measurements. Monte Carlo analysis (N = 10 000) was then used to independently vary parameters within ±2 standard deviations of the mean of each variable and the 5th and 95th percentiles determined the bounds of the expected range of insulin secretion. Cumulative distribution functions (CDFs) were calculated for each subject for area under the curve (AUC) total, AUC Phase 1, and AUC Phase 2. Normalizing each AUC by the participant's median value over all N = 10 000 iterations quantifies the expected model-based variability in AUC.
Larger variation is found in subjects with a BMI > 30 kg/m, where the interquartile range is 34.3% compared to subjects with a BMI ≤ 30 kg/m where the interquartile range is 24.7%.
Use of C-peptide measurements using a 2-compartment model and standardized kinetic parameters, one can expect ~±15% variation in modelled insulin secretion estimates. The variation should be considered when applying this insulin secretion estimation method to clinical diagnostic thresholds and interpretation of model-based analyses such as insulin sensitivity.
衡量胰岛β细胞胰岛素分泌能力并监测血糖-胰岛素生理功能对于当前的健康需求至关重要。C 肽已成功用作血浆胰岛素浓度的替代物。量化模拟胰岛素分泌的预期变异性将提高对模型估计的信心。
43 名居住在新西兰的毛利或太平洋岛民血统的健康成年男性参与了频繁采样的静脉葡萄糖耐量试验（FS-IVGTT），平均年龄 29 岁，BMI 为 33kg/m。使用两室模型框架和标准化动力学参数，根据血浆 C 肽测量值估算内源性胰腺胰岛素分泌。然后，使用蒙特卡罗分析（N=10000）独立地在每个变量的平均值的±2 个标准差范围内变化参数，并确定第 5 和 95 百分位数确定胰岛素分泌的预期范围的界限。为每个受试者计算曲线下面积（AUC）总、AUC 第 1 相和 AUC 第 2 相的累积分布函数（CDF）。将每个 AUC 除以参与者在所有 N=10000 次迭代中的中位数，可量化 AUC 的预期基于模型的变异性。
BMI>30kg/m 的受试者中发现的变异较大，其中四分位距为 34.3%，而 BMI≤30kg/m 的受试者中四分位距为 24.7%。
使用两室模型和标准化动力学参数测量 C 肽，可以预期模拟胰岛素分泌估计值的变化约为±15%。在将这种胰岛素分泌估计方法应用于临床诊断阈值和基于模型的分析（如胰岛素敏感性）的解释时，应考虑这种变异性。
