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

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...

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Autores principales: Joubert, Michael, Meyer, Laurent, Doriot, Aline, Dreves, Bleuenn, Jeandidier, Nathalie, Reznik, Yves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Healthcare 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8266981/
https://www.ncbi.nlm.nih.gov/pubmed/34028700
http://dx.doi.org/10.1007/s13300-021-01082-2
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author Joubert, Michael
Meyer, Laurent
Doriot, Aline
Dreves, Bleuenn
Jeandidier, Nathalie
Reznik, Yves
author_facet Joubert, Michael
Meyer, Laurent
Doriot, Aline
Dreves, Bleuenn
Jeandidier, Nathalie
Reznik, Yves
author_sort Joubert, Michael
collection PubMed
description 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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spelling pubmed-82669812021-07-20 Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications Joubert, Michael Meyer, Laurent Doriot, Aline Dreves, Bleuenn Jeandidier, Nathalie Reznik, Yves Diabetes Ther Original Research 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. Springer Healthcare 2021-05-24 2021-07 /pmc/articles/PMC8266981/ /pubmed/34028700 http://dx.doi.org/10.1007/s13300-021-01082-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Joubert, Michael
Meyer, Laurent
Doriot, Aline
Dreves, Bleuenn
Jeandidier, Nathalie
Reznik, Yves
Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications
title Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications
title_full Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications
title_fullStr Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications
title_full_unstemmed Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications
title_short Prospective Independent Evaluation of the Carbohydrate Counting Accuracy of Two Smartphone Applications
title_sort prospective independent evaluation of the carbohydrate counting accuracy of two smartphone applications
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8266981/
https://www.ncbi.nlm.nih.gov/pubmed/34028700
http://dx.doi.org/10.1007/s13300-021-01082-2
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