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      Gestational Diabetes Management Using Smart Mobile Telemedicine

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          Abstract

          Gestational diabetes (GDM) burden has been increasing progressively over the past years. Knowing that intrauterine exposure to maternal diabetes confers high risk for macrosomia as well as for future type 2 diabetes and obesity of the offspring, health care organizations try to provide effective control in spite of the limited resources. Artificial-intelligence-augmented telemedicine has been proposed as a helpful tool to facilitate an efficient widespread medical assistance to GDM. The aim of the study we present was to test the feasibility and acceptance of a mobile decision-support system for GDM, developed in the seventh framework program MobiGuide Project, which includes computer-interpretable clinical practice guidelines, access to data from the electronic health record as well as from glucose, blood pressure, and activity sensors. The results of this pilot study with 20 patients showed that the system is feasible. Compliance of patients with blood glucose monitoring was higher than that observed in a historical group of 247 patients, similar in clinical characteristics, who had been followed up for the 3 years prior to the pilot study. A questionnaire on the use of the telemedicine system showed a high degree of acceptance.

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          Author and article information

          Journal
          J Diabetes Sci Technol
          J Diabetes Sci Technol
          DST
          spdst
          Journal of Diabetes Science and Technology
          SAGE Publications (Sage CA: Los Angeles, CA )
          1932-2968
          18 April 2017
          March 2018
          : 12
          : 2
          : 260-264
          Affiliations
          [1 ]Endocrinology and Nutrition Department, Parc Taulí University Hospital, Sabadell, Spain
          [2 ]Bioengineering and Telemedicine Centre, Universidad Politécnica de Madrid, Madrid, Spain
          [3 ]CIBER-BBN, Networking Research Centre for Bioengineering, Biomaterials and Nanomedicine, Madrid, Spain
          Author notes
          [*]Mercedes Rigla, MD, PhD, Endocrinology and Nutrition Department, Parc Taulí University Hospital, I3PT, Autonomous University of Barcelona, Parc Taulí, 1, 08208 Sabadell, Spain. Email: mrigla@ 123456tauli.cat
          Article
          PMC5851209 PMC5851209 5851209 10.1177_1932296817704442
          10.1177/1932296817704442
          5851209
          28420257
          fb102cf0-4ece-4400-976f-9d5ab9ebe7dc
          © 2017 Diabetes Technology Society
          History
          Funding
          Funded by: Seventh Framework Programme, FundRef http://doi.org/10.13039/501100004963;
          Award ID: 287811
          Categories
          Special Section: AI and Diabetes
          Guest Editors: Claudio Cobelli, Nick Oliver, Mercedes Rigla, and Stephen Patek

          artificial intelligence,decision support,gestational diabetes,telemedicine

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