A physical activity-intensity driven glycemic model for type 1 diabetes

• Published in: Computer methods and programs in biomedicine 2022-11, Vol.226, p.107153-107153, Article 107153
• Main Authors: Hobbs, Nicole, Samadi, Sediqeh, Rashid, Mudassir, Shahidehpour, Andrew, Askari, Mohammad Reza, Park, Minsun, Quinn, Laurie, Cinar, Ali
• Format: Article
• Language: English
• Subjects: Blood Glucose - metabolism; Diabetes Mellitus, Type 1; Exercise; Glucose - metabolism; Humans; Hypoglycemic Agents; Insulin; Physical activity; Physiological modeling; Type 1 diabetes
• ISSN: 0169-2607; 1872-7565
• DOI: 10.1016/j.cmpb.2022.107153

•Factors that affect the glycemic response include the intensity and duration of physical activity, plasma insulin concentrations, and the individual physical fitness level.•To model the glycemic response for a person with type 1 diabetes to physical activity, these factors must be considered.•Several physiological models describing the glycemic response to physical activity are proposed by incorporating various model terms.•A model with terms accommodating endogenous glucose production, glucose transfer, and insulin-independent glucose utilization enable an improved estimation of glycemic responses to physical activity. The 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. Several 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. The 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). The 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 the in silico evaluation 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.