Abstract

Regular moderate-intensity exercise is strongly recommended for its beneficial effects in all people. In patients with type 1 diabetes, however, the exercise-associated glycemic imbalances remain an unresolved clinical challenge. Current guidelines require an in-depth understanding of the glycemic responses to exercise and each patient has to discover, by trial-and-error, his/her own strategy, several attempts being usually required to gain sufficient experience. Consequently, fear of hypoglycemia remains the strongest barrier to physical activity. This paper explores the potential strategies that may be employed to minimize the risk of exercise related glycemic imbalances. Moreover, a newly developed algorithm (ECRES, Exercise Carbohydrate Requirement Estimating Software) is described, which estimates on a patientand situation-specific basis the glucose supplement required by the patient to maintain safe blood glucose levels. The algorithm was tested on 27 patients who performed three 1-hr constant intensity walks (each starting at a different time interval following insulin injection). Results showed that in 70.4% of the trials, independent of the time of day, the algorithm provided a satisfactory estimate of the carbohydrates needed by patients to complete the exercise with a glucose level within safe thresholds (i.e. 3.9 - 10 mmol·L-1). Despite the algorithm requires further experimental testing to be applied by the majority of patients, these results indicate its potential usefulness as a tool for preventing immediate exerciseinduced glycemic imbalances (i.e. during exercise) in type 1 diabetic patients, in particular for spontaneous activities not planned in advance, thus allowing all insulin-dependent patients to safely enjoy the benefits of exercise.

Keywords: Carbohydrates, Decision support system, Hypoglycemia, Insulin, Metabolism, Model, Type 1 Diabetes, ECRES algorithm, Glucose oxidation, Exercise induced glycemic imbalances