Intelligent and Educational System for Gestational Diabetes Management

Gestational diabetes, diabetes diagnosed during pregnancy, affects 8.8% of pregnancies in Spain that means more than 40,000 women per year. This prevalence is based on the National Diabetes Data Group criteria, previous to the 4th workshop on Gestational Diabetes (1998), but, if the new diagnosis criteria proposed by the International Associations of Diabetes and Pregnancy Study Groups, based on the most important study never made before on this topic, prevalence would increase to the double. When a women is diagnosed, the risk of complications for her and the child increases and, therefore, she has to start an specific diet and frequent visits to the diabetes center in order to check that glucose values do not exceed 95 mg/dl before or 140 mg/dl 1-hour after meals. In other case, she should start insulin treatment. Our project is aimed to develop intelligent tools based on neuro-diffuse techniques and integrated in a telemedicine system that allows control of gestational diabetes automatically, guaranteeing glucose control objectives consecution and avoiding face-to-face visits to the health care center. Furthermore, educational and motivation tools for a healthy behaviour will be included. At the end of the study efficacy and security about insulin management will be compare with the recommendations proposed by the diabetes team and data about direct and indirect costs will be calculated. The investigators anticipate that the smart telemedicine system can allow us to detect high blood glucose values earlier than in-person scheduled visits.

This study aims to evaluate the safety and usability of a telemedicine system which includes intelligent tools for blood glucose analysis and supporting routine clinical monitoring carried out by nurses and endocrinologists. Type of study: Prospective, controlled, randomized (2:1) Participants: pregnant women diagnosed with gestational diabetes according to the National Diabetes Data Group criteria between 14 and 34 weeks of gestation. Patients with suspected clinical diagnosis of type 1 or type 2 diabetes will be excluded. In addition to the signed acceptance to participate in the study, requirements are: Availability of a desktop computer or laptop with an internet connection and USB port. Sufficient knowledge of Catalan and/or Spanish A mobile phone Objective: To technically evaluate the SineDie telemedicine system and also the users' degree of satisfaction. Methodology of the study: Once signed consent for participation the patient will be randomized either to continue regularly scheduled visits (33% chance) or to use the Telemedicine system (66% chance). The randomization will be done using a system of allocation based on random numbers. The SINEDiE system includes: Educational Program Automatical Evaluation of glucose data -immediately after each download (frequency not exceeding 72 hours) Alerts in case of failure of receiving information at the scheduled time or in case of incompleteness. Alerts for glucose values higher than desirable but which could be corrected by diet changes and / or exercise Alerts for high glucose values which cannot be corrected with the previous mentioned changes. In this case an appointment for face-to-face visit would be made. All warnings are also reported as an email to the endocrinologist and nurse Variables: Statistical analysis of data: blood glucose, standard deviation, number of preprandial values> 90, the number of postprandial values of> 140 messages and warnings Analytical variables: HbA1c at the start and every 4 weeks Complications of pregnancy and childbirth if any. Neonatal Complications if any Survey of satisfaction with telemedicine tool Expected duration of the study: 6 months Number of patients included 20 patients

After receiving an structured education on the matter, patients will be followed remotely by analysing glucose and diet/physical activity/other events data with a periodicity no longer than 48 hours

Intervention consists of a telemedicine platform which includes artificial intelligence tools to analyse glucose values and guarantee an optimal glucose control from the diagnosis of gestational diabetes to delivery.

Inclusion Criteria: Pregnancy; Gestational diabetes diagnosed according the National Diabetes data Group Criteria. Exclusion Criteria: Pregestational diabetes (diagnosed or suspected); Illiteracy; no computer connected to internet availability; unwillingness to participate in the study