Optimisation du contrôle glycémique des patients atteints de diabète de type 1 : traitement efficace des hypoglycémies, calcul des glucides et pancréas artificiel
Optimal glucose control is essential to reduce the risk of diabetes-related complications. Yet, a large proportion of patients with type 1 diabetes (T1D) struggles to achieve glycated hemoglobin (A1c) targets and a high frequency of hypoglycemia events is still observed. We believe simplification of meal glucose control as well as efficient treatment of hypoglycemia have the potential to improve glucose control in T1D.  We showed that a large proportion of patients report being confident in applying carbohydrate counting for meal bolus calculation; yet, many specific difficulties were encountered by patients. The use of available technologies for carbohydrate counting by participants appears to be uncommon despite a favorable perception and interest towards such technology. Closed-loop automated insulin delivery systems, also called “artificial pancreas (AP)”, is a technology by which insulin infusion rates from the continuous subcutaneous insulin infusion (CSII; insulin pump) are regulated based on algorithm-generated recommendations relying on continuous glucose monitoring systems readings. The AP improves glucose control considerably in patients with T1D, but prandial glucose control remains a significant challenge. We have developed a simplified meal bolus strategy combined with the AP. In this strategy, patients choose a meal category based on a semi-quantitative carbohydrate assessment (e.g. a regular meal = 30 to 60 g of carbohydrates). In controlled conditions using a dual-hormone AP (insulin and glucagon), this strategy yielded adequate postprandial glucose control, except for very large carbohydrate content meals (> 90 g). After adding a meal category, this strategy was tested in uncontrolled conditions. Glucose control with the simplified strategy was comparable to what was seen with precise carbohydrate counting. However, a higher frequency of hypoglycemia events was observed which led to modifications to the algorithm. We finally showed the safety of this simplified strategy in the context of misclassification of the meals.  We also found a low adherence to guidelines for self-treatment of mild to moderate hypoglycemia. The average treatment observed for hypoglycemia was twice the recommended quantity of carbohydrates. On the other hand, we showed that 16 to 21 grams of carbohydrates is insufficient to treat, in a 15-min delay, a significant proportion of hypoglycemia episodes in T1D patients treated with insulin pump.  In conclusion, patients encounter several difficulties associated with carbohydrate counting and the AP represents a promising therapy to alleviate some of the carbohydrate counting burden. A simplified prandial bolus based on meal categorization could simplify carbohydrate counting while preserving adequate glycemic control. In addition, a large proportion of patients with T1D do not follow recommendations for treatment of hypoglycemia episodes, which could be partly explained by the lack of efficacy of this treatment in a large subgroup of patients.
Type 1 diabetes Insulin therapy Glycemic control Carbohydrates Artificial pancreas Treatment Hypoglycemia