Impact of DBLG1 Hybrid Closed‐Loop Software Optimization and Meal Declaration Pattern on Glucose Metrics in Type 1 Diabetes: A 12‐Month Prospective Evaluation in 2014 Users

Background The meal period is critical for the outcome of automated insulin delivery. Our aim was to explore the long‐term impact on glucose metrics of algorithmic modifications of the DBLG1 hybrid closed‐loop system, with special emphasis on the meal declaration pattern. Methods We prospectively analysed CGM data from consenting adult patients with Type 1 diabetes across Europe who initiated the new version of DBLG1 paired with the Kaleido patch pump upon its release. Inclusion occurred over 7 months, with follow‐up extended up to 12 months. Time in range 70–180 mg/dL (TIR) was the primary endpoint. Utility endpoints included the number of declared meals. Results This study included 2014 users, age 42.5 ± 13.8 years, baseline HbA1c 7.6% ± 1.2%. Median TIR was 72.0%, 72.3%, 72.0% and 71.7% at M3, M6, M9 and M12, respectively. At M3, time < 54 mg/dL (0.2%), < 70 mg/dL (1.2%) and > 250 mg/dL (5.4%) were controlled and remained stable throughout M12, as well as GMI (7.0%–7.1%). The incidence rates of severe hypo‐ or hyperglycaemia remained very low. TIR in patients declaring ≥ 3 meals/day exceeded TIR in those declaring < 1 meal/day (73.3 [67.3, 78.7]% vs. 65.7 [60.7, 72.2]%, p < 0.0001). Conclusion This study demonstrates the sustained safety and effectiveness of the latest version of the DBLG1 software, with TIR exceeding 70% throughout the 12‐month follow‐up period in a large group of 2014 users. Furthermore, while glycaemic control was negatively affected when meal declaration was reduced, the software maintained its safety and acceptable effectiveness in this latter situation.