Comparison of ECRES Algorithm with Classical Method in Management of Diabetes Type 1 Exercise-Related Imbalances

Nutrition and physical activity are important parts of a healthy lifestyle and management of diabetes. Regular moderate-intensity physical activity in type 1 diabetes patients can enhance insulin sensitivity, reduce the risk of cardiovascular disease and improve psychological well-being. Nevertheless, the risk of exercise-induced hypoglycemia is a great challenge for patients with type 1 diabetes and represents an important barrier to physical activity in these patients. Recently, an algorithm called ECRES has been developed with the aim of estimating, depending on patient’s own therapy and specific physical activity, the glucose supplement required by the patient to maintain safe blood glucose levels. The aim of this study is to compare the ECRES algorithm to classical quantitative approach. Therefore, we measured and compared glycaemia in 23 patients (mean age: 43 ± 12 years) during 1-h treadmill walk/run maintaining heart rate at 65% of his/her theoretical maximum value for age. For each subject two separate tests were performed: with carbohydrates supplement estimated by ECRES algorithm and by classical approach, respectively. The average heart rate observed during exercise (average progression speed: 5.8 ± 0.8 km/h at 4.2 ± 2.3% inclination) was 111.5 ± 9.4 bpm. Glycaemia measured by portable glucometer showed no significant differences between tests managed with ECRES algorithm and with classical approach, both before (149 ± 47 vs. 128 ± 41 mg/dL) and at the end of the performed exercise (134 ± 66 vs. 138 ± 54 mg/dL). The ECRES algorithm, however, estimated a significantly lower amount of carbohydrate needed for physical activity as compared to that suggested by the classical approach (14.8 ± 12.0 g vs. 23.4 ± 4.7 g; p < 0.05), while maintaining patients’ blood glucose within optimal clinical limits. The study results confirmed the validity of the estimates made by the ECRES algorithm.