Carbohydrate Counting Accuracy and Hybrid Closed-Loop Performance in Adolescents with Type 1 Diabetes

Abstract

Hybrid closed-loop systems rely on user-entered meal carbohydrate estimates to optimize insulin delivery. In adolescents with type 1 diabetes, higher accuracy of carb counting was associated with improved time-in-range and fewer postprandial excursions despite algorithm safeguards. Brief skills-based education improved estimation accuracy and device satisfaction. Incorporating recurring micro-trainings into routine visits may enhance long-term outcomes.