Analysis on the contribution of glucagon receptors to glucose dynamics in type 1 diabetes

Abstract

The glucagon effect is understudied in type 1 diabetes (T1D) simulators, without a clear consensus on the pharmacodynamics of glucagon over glucose. Glucagon receptors dynamics could present a significant contribution to T1D simulators, making them more physiologically accurate without an excessive increase in complexity. This work analyzes the receptors model contributions to glucose dynamics using a model proposed in previous work. Then, the model is assessed from two different perspectives: (1) A clinical dataset of the influence of diet (high or low carbohydrate content) on two consecutive glucagon doses (100 and 500 $\mu$g) is used to identify the model parameters and (2) three other glucagon action models from the literature are also identified to serve as comparators. Different identification methods are used to adapt to the distinctive features of the dataset. The root mean square error (RMSE) and the Akaike Information Criterion (AIC) were the discerning metrics used to compare the models fittings. Results show that the receptors model offers the lowest RMSE and AIC in contrast to the comparators. This model will hence be helpful in the development of accurate T1D simulators.