App-based automated meal analysis in adults with type 1 diabetes using automated insulin delivery: a randomized...

Image-based automated meal analysis using smartphones has the potential to facilitate meal management in type 1 diabetes. We evaluated the glycaemic efficacy of SNAQ-an image-based automated meal analysis app-in adults using hybrid automated insulin delivery (AID) systems requiring carbohydrate entry for prandial insulin dosing.

In this single-centre trial (NCT05671679) adults with type 1 diabetes on AID therapy were randomly assigned to using SNAQ-a commercial mobile app recognizing and quantifying food from images for meal management support-or continuing their usual meal management (control group) for 3 weeks. The primary endpoint was the change in the %time in range (TIR, 3.9-10.0 mmol/L). Following the first three weeks, SNAQ was also provided to the control group for evaluating the sustainability of benefits and usage across all participants.

Twenty-two participants were randomized between March 14 and November 23 2023 to using SNAQ and 22 to control. At baseline, TIR was 75.4 ± 13.7% and 74.3 ± 12.7% in the intervention and control group, respectively. After three weeks, the baseline-adjusted difference in TIR between SNAQ (used 1.6 ± 0.8 per day) and control was 6.6 percentage points in favour of SNAQ (95% CI 2.9 to 10.3, P < 0.001). SNAQ further improved mean glucose (-0.54 mmol/L, CI -0.9 to -0.2, P = 0.004) and time above range (-6.3%, CI -10 to -2.7, P = 0.001). Time below range, total daily insulin dose, bolus frequency, nor carbohydrate entered into the pump did not significantly differ between groups. Post-discontinuation, the glycaemic benefits of SNAQ were not sustained. No study-related serious adverse events occurred.

Short-term use of the automated meal analysis app SNAQ improved glucose control in adults with type 1 diabetes treated with AID.

The study was supported by the EFSD/EUDF Digitalisation on Diabetes Care Research Grant and by the Diabetes Center Berne.