A physical activity-intensity driven glycemic model for type 1 diabetes.
A physical activity-intensity driven glycemic model for type 1 diabetes.
复制标题
体力活动强度驱动的 1 型糖尿病血糖模型。
DOI：
10.1016/j.cmpb.2022.107153
复制
发表时间：
2022
影响因子：
6.1
通讯作者：
Cinar,Ali
中科院分区：
文献类型：
--
作者：
Hobbs,Nicole;Samadi,Sediqeh;Rashid,Mudassir;Shahidehpour,Andrew;Askari,MohammadReza;Park,Minsun;Quinn,Laurie;Cinar,Ali
1型糖尿病（T1D）患者对体力活动的葡萄糖反应取决于体力活动的强度和持续时间、血浆胰岛素浓度和个体体能水平。为了准确地模拟血糖对体力活动的反应，这些因素必须被考虑到。MethodsSeveral生理模型描述的血糖对体力活动的反应提出了纳入模型条款成比例的体力活动强度和持续时间描述内源性葡萄糖的生产（EGP），葡萄糖的利用，和葡萄糖从血浆转移到组织。利用T1D在体力活动期间的临床数据，每个模型拟合assessed.ResultsThe建议的模型与条款容纳EGP，葡萄糖转移，和胰岛素非依赖性葡萄糖利用允许改善模拟的体力活动血糖反应，最大限度地减少模型误差（平均绝对百分比误差：16.11 ± 4.82 vs. 19.49 ± 5.87，p= 0.002）的平均值结论建立一个生理上合理的模型，模型项代表了体力活动期间葡萄糖代谢的每个主要贡献者，该模型的性能优于传统的通过葡萄糖描述体力活动的模型。单独使用。该模型准确地描述了血浆胰岛素和体力活动强度对葡萄糖产生和葡萄糖利用的关系，以产生针对每种体力活动条件的适当增加、减少或稳定的葡萄糖响应。所提出的模型将能够对自动胰岛素给药算法进行计算机模拟评估，该算法旨在通过基础胰岛素减少与相应血糖波动之间的适当关系来减轻体力活动的影响。
Background and ObjectiveThe glucose response to physical activity for a person with type 1 diabetes (T1D) depends upon the intensity and duration of the physical activity, plasma insulin concentrations, and the individual physical fitness level. To accurately model the glycemic response to physical activity, these factors must be considered.MethodsSeveral physiological models describing the glycemic response to physical activity are proposed by incorporating model terms proportional to the physical activity intensity and duration describing endogenous glucose production (EGP), glucose utilization, and glucose transfer from the plasma to tissues. Leveraging clinical data of T1D during physical activity, each model fit is assessed.ResultsThe proposed model with terms accommodating EGP, glucose transfer, and insulin-independent glucose utilization allow for an improved simulation of physical activity glycemic responses with the greatest reduction in model error (mean absolute percentage error: 16.11 ± 4.82 vs. 19.49 ± 5.87,p= 0.002).ConclusionsThe development of a physiologically plausible model with model terms representing each major contributor to glucose metabolism during physical activity can outperform traditional models with physical activity described through glucose utilization alone. This model accurately describes the relation of plasma insulin and physical activity intensity on glucose production and glucose utilization to generate the appropriately increasing, decreasing or stable glucose response for each physical activity condition. The proposed model will enable thein silicoevaluation of automated insulin dosing algorithms designed to mitigate the effects of physical activity with the appropriate relationship between the reduction in basal insulin and the corresponding glycemic excursion.