Novel methodological and computational techniques for uncertainty quantification in diabetes short-term management models using real data

Abstract

An open problem in diabetes clinical practice is determining where and how much insulin should be administered to a person with diabetes (PwD) and how many carbohydrates they should eat to maintain blood glucose levels at healthy safe levels. Here, we propose the use of a minimal model describing the glucose dynamics of PwD. Using glucose Pwd's data, we calibrate the minimal model considering the uncertainty due to errors in glucose measurement, finding the model parameter values that best reproduce the current glucose levels. Then, all the possible combinations of insulin administration and carbohydrate intake are analysed with the aim of maintaining the glucose at safe levels during the following hours. The resulting procedure is tested with data from two real persons with scenarios of the most typical situations. We expect to apply this procedure in more complex models to help the physicians to give suitable recommendations to PwD.