Efficacy and Safety of a Non-Carbohydrate Counting Meal Bolus Strategy in Adults with Type 1 Diabetes Using Open-Source Automated Insulin Delivery
Year: 2025
Type: article
Study design: Clinical Trial
Abstract: Aims: This study addressed the challenge of postprandial glycemic variability in type 1 diabetes (T1D), even with AID (automated insulin delivery). We evaluated the effectiveness of a non-carbohydrate counting (non-CC) meal bolus strategy in adults with T1D utilizing open-source AID. Methods: A total of 32 adults with T1D, aged 18 to 50 years, participated in a randomized crossover trial utilizing open-source AID. Following a 7-day run-in period, participants were randomly assigned to one of two groups: automatic mode (closed loop) or manual mode (open loop). After 2 weeks, the participants underwent a crossover to the alternate treatment mode. Prandial boluses were administered according to a sliding scale based on preprandial glucose levels, without utilizing either the exact carbohydrate content of meals or meal announcement buttons. The study compared the differences in time in range (TIR) and insulin dosage across the different phases. Results: Compared with the open-loop phase, the TIR for patients during the closed-loop phase increased significantly during the night (75.45% ± 12.08% vs. 83.05% ± 7.20%, P < 0.001) and 24 h (73.40% ± 9.98% vs. 79.21% ± 4.84%, P = 0.019), with a more pronounced effect observed at night. During the closed-loop phase, the frequency of 24-h hypoglycemic events (＜3.9 mmol/L) was reduced compared with the open-loop phase, with no difference in nocturnal hypoglycemic events. In addition, compared with the open-loop phase, there were no significant differences in average postprandial blood glucose and peak blood glucose levels during the closed-loop phase; however, the time to reach peak postprandial blood glucose was delayed (86.06 ± 20.80 min vs. 99.08 ± 15.05 min, P < 0.001). Conclusions: A non-CC meal bolus strategy based on preprandial glucose in adults with T1D utilizing open-source AID effectively prevents glycemic excursions and maintains a mean TIR over 70%.
Authors: Yunying Cai, Le Ma, Lun Zhang, Qiongli Neng, Heng Su
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4410615219