Abstract
Accurate carbohydrate (CHO) counting to achieve satisfactory glucose control in type 1 diabetes (T1D) remains challenging in practice, and thus novel approaches are still needed (1,2). GoCARB is a computer vision-based application installed in a smartphone device that provides users with CHO content estimations from photos taken of plated meals (3). We present the results of a pilot prospective randomized controlled crossover study (NCT02546063) evaluating the effects of GoCARB on postprandial and overall glucose control in individuals with T1D using sensor-augmented insulin pump (SAP) therapy. One week of GoCARB use was compared with conventional methods to estimate meal CHO content in 20 adults with T1D using SAP therapy (mean age 35 ± 14 years, BMI 25.5 ± 3.8 kg/m2, HbA1c 7.5 ± 0.6% [58.7 ± 5.9 mmol/mol], duration of diabetes 17 ± 10 years, …
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