Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications

对两款智能手机应用程序碳水化合物计数准确性的前瞻性独立评估

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Abstract

INTRODUCTION: Smartphone applications (apps) have been designed that help patients to accurately count their carbohydrate intake in order to optimize prandial insulin dose matching. Our aim was to evaluate the accuracy of two carbohydrate (carb) counting apps. METHODS: Medical students, in the role of mock patients, evaluated meals using two smartphone apps: Foodvisor(®) (which uses automatic food photo recognition technology) and Glucicheck(®) (which requires the manual entry of carbohydrates with the help of a photo gallery). The macronutrient quantifications obtained with these two apps were compared to a reference quantification. RESULTS: The carbohydrate content of the entire meal was underestimated with Foodvisor(®) (Foodvisor(®) quantification minus gold standard quantification = - 7.2 ± 17.3 g; p < 0.05) but reasonably accurately estimated with Glucicheck(®) (Glucicheck(®) quantification minus gold standard quantification = 1.4 ± 13.4 g; ns). The percentage of meals with an absolute error in carbohydrate quantification above 20 g was greater for Foodvisor(®) compared to Glucicheck(®) (30% vs 14%; p < 0.01). CONCLUSION: The carb counting accuracy was slightly better when using Glucicheck(®) compared to Foodvisor(®). However, both apps provided a lower mean absolute carb counting error than that usually made by T1D patients in everyday life, suggesting that such apps may be a useful adjunct for estimating carbohydrate content.

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