Poor glycaemic control is associated with reduced exercise performance and oxygen economy during cardio-pulmonary exercise testing in people with type 1 diabetes

BackgroundTo explore the impact of glycaemic control (HbA1c) on functional capacity during cardio-pulmonary exercise testing in people with type 1 diabetes.MethodsSixty-four individuals with type 1 diabetes (age: 34 ± 8 years; 13 females, HbA1c: 7.8 ± 1% (62 ± 13 mmol/mol), duration of diabetes: 17 ± 9 years) performed a cardio-pulmonary cycle ergometer exercise test until volitional exhaustion. Stepwise linear regression was used to explore relationships between HbA1c and cardio-respiratory data with p ≤ 0.05. Furthermore, participants were divided into quartiles based on HbA1c levels and cardio-respiratory data were analysed by one-way ANOVA. Multiple regression analysis was performed to explore the relationships between changes in time to exhaustion and cardio-respiratory data. Data were adjusted for confounder.ResultsHbA1c was related to time to exhaustion and oxygen consumption at the power output elicited at the sub-maximal threshold of the heart rate turn point (r = 0.47, R2 = 0.22, p = 0.03). Significant differences were found at time to exhaustion between QI vs. QIV and at oxygen consumption at the power output elicited at the heart rate turn point between QI vs. QII and QI vs. QIV (p < 0.05). Changes in oxygen uptake, power output and in oxygen consumption at the power output elicited at the heart rate turn point and at maximum power output explained 55% of the variance in time to exhaustion (r = 0.74, R2 = 0.55, p < 0.01).ConclusionsPoor glycaemic control is related to less economical use of oxygen at sub-maximal work rates and an earlier time to exhaustion during cardio-pulmonary exercise testing. However, exercise training could have the same potential to counteract the influence of poor glycaemic control on functional capacity

Modeling of Carbohydrates Oxidation Rate During Exercise in Type 1 Highly-Trained Diabetic Patients

Management of Type 1 Diabetes (T1D) in the context of exercise or sports competition still represents a great challenge for athletes living with this disease, due to the wide excursions in blood glucose level with increased risk of life threatening hypoglycemia. Recently, an algorithm called ECRES has been developed to estimate patient-exercise tailored carbohydrates (CHO) supplement required to maintain safe blood glucose levels during physical activity. This method estimates a CHO supplement based on the patient\u2019s habitual therapy, the specific patient\u2019s insulin sensitivity and the overall amount of CHO oxidized during the specific exercise. The last is based on the glucose pulse relation, i.e. the relation between heart rate (HR) and CHO oxidation rate, already studied in sedentary and moderately-trained subjects, but not in well-trained athletes. This study aimed to model the glucose pulse relation during exercise in type 1 highly trained diabetic patients and in healthy subjects. HR, oxygen consumption and carbon dioxide production were acquired breath-by-breath in seven T1D and seven well-matched healthy highly-trained subjects at four different exercise intensity levels, as well as at rest. Results showed a linear CHOox-HR relation (CHOox\u2009=\u20090.76 \ub7 %HRmax - 19.6; n\u2009=\u200970, R2\u2009=\u20090.78) with no significant difference between the T1D and healthy athletes (p-value\u2009=\u20090.11). In conclusion, results of this study can be implemented in an updated version of the ECRES algorithm allowing an easy estimate of CHO supplement also in highly trained subjects. This useful support system can enhance the self-management of glycaemia during the training sessions of athletic patients throughout mHealth technologies