Intelligent and Educational System for Gestational Diabetes Management

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT01850199
Recruitment Status : Completed
First Posted : May 9, 2013
Last Update Posted : July 28, 2016
CIBER-BBN: Networking Research Center for Bioengineering.
Technical University of Madrid
Information provided by (Responsible Party):
Mercedes Rigla, Corporacion Parc Tauli

Brief Summary:
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.

Condition or disease Intervention/treatment Phase
Gestational Diabetes Other: Smart telemedicine remote monitoring for gestational diabetes Other: Usual management Not Applicable

Detailed Description:

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


  • 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

Study Type : Interventional  (Clinical Trial)
Actual Enrollment : 120 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)
Primary Purpose: Supportive Care
Study Start Date : January 2014
Actual Primary Completion Date : September 2015
Actual Study Completion Date : September 2015

Resource links provided by the National Library of Medicine

U.S. FDA Resources

Arm Intervention/treatment
Active Comparator: Usual management (presential visits)
Patient will follow the usual care program, which includes in-person appointment (weekly/biweekly)
Other: Usual management
Usual care will be provided, including face-to-face visits
Experimental: Smart telemedicine remote monitoring for gestational diabetes
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
Other: Smart telemedicine remote monitoring for gestational diabetes
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.

Primary Outcome Measures :
  1. Median blood glucose (Interquartile range) [ Time Frame: From inclusion to delivery (estimate average period 10±2 weeks) ]
    Blood glucose data downloaded from the glucometer will allow to obtain the main outcome.

Secondary Outcome Measures :
  1. Time from glucose criteria for insulin prescription to actual insulin starting [ Time Frame: From inclusion to delivery From inclusion to delivery (estimate average period 10±2 weeks) ]

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years to 46 Years   (Adult)
Sexes Eligible for Study:   Female
Accepts Healthy Volunteers:   No

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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT01850199

Parc Tauli Sabadell University Hospital
Sabadell, Barcelona, Spain, 08208
Sponsors and Collaborators
Corporacion Parc Tauli
CIBER-BBN: Networking Research Center for Bioengineering.
Technical University of Madrid

Responsible Party: Mercedes Rigla, Director, Endocrinology and Nutrition Dpt., Corporacion Parc Tauli Identifier: NCT01850199     History of Changes
Other Study ID Numbers: SINEDiE
First Posted: May 9, 2013    Key Record Dates
Last Update Posted: July 28, 2016
Last Verified: July 2016

Keywords provided by Mercedes Rigla, Corporacion Parc Tauli:
Gestational diabetes
Artificial Intelligence

Additional relevant MeSH terms:
Diabetes, Gestational
Pregnancy Complications
Diabetes Mellitus
Glucose Metabolism Disorders
Metabolic Diseases
Endocrine System Diseases