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Enrolling by Invitation

NCT Number: NCT07345143

Artificial Intelligence and Gestacional Diabetes

Artificial intelligence (AI) technology can assist medical teams in remote monitoring and continuing education of women with gestational diabetes (GDM), potentially improving adherence to interventions and impacting outcomes. An AI remote monitoring model called "monitoring model for women with GDM using pharmacological therapy," created by the ChamouDr technical team, will be analyzed focusing on disease education, glycemic control monitoring, and therapeutic interventions. Women diagnosed with GDM are invited to participate in the study and sign a free and informed consent form. The AI tool is installed on the pregnant woman's cell phone, who receives instructions to collect capillary blood glucose 6 times a day according to the protocol, at home, and report the results via WhatsApp to the study tool. Algorithm generated by the AI model based on self monitoring of blood glucose (SMBG) informs about diabetes control in the last week. The dashboard is accessible via a web browser, and signals: in green and red for patients with satisfactory and unsatisfactory control, respectively. Thus, the AI model optimizes the team's time in analyzing and treating patients appropriately in a simple, cost-effective, and accessible way.

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Key information

Conditions

Gestational Diabetes Birth Weight Body Weight Congenital, Hereditary, and Neonatal Diseases and Abnormalities Diabetes Complications Diabetes Mellitus Diabetes, Gestational Endocrine System Diseases Female Urogenital Diseases and Pregnancy Complications Fetal Diseases Fetal Macrosomia Glucose Metabolism Disorders Macrosomia, Fetal Metabolic Diseases Nutritional and Metabolic Diseases Pathological Conditions, Signs and Symptoms Pregnancy Complications Pregnancy in Diabetics Signs and Symptoms Urogenital Diseases

Age range

18 year–40 year

Sex eligibility

Female

Study type

Interventional

Phase

Not applicable

Primary location

Fundação Faculdade Regional de Medicina de São José do Rio Preto

São José do Rio Preto, São Paulo, 15090-000, Brazil

About this study

AI technology can assist medical teams in remote monitoring and continuing education of women with GDM. Objective: To analyze the results of using an AI model in remote monitoring and continuing education of women with GDM and pharmacological treatment, correlating them with clinical outcomes for the mother-fetus binomial. Methods: prospective, longitudinal, interventional clinical study approved by the local ethics committee. Patients signed a consent form to participate. An AI remote monitoring model called "monitoring model for women with GDM using pharmacological therapy," created by the ChamouDr technical team, will be analyzed focusing on disease education, glycemic control monitoring, and therapeutic interventions. The modell uses WhatsApp®, through a structured chatbot and AI resources, to communicate with the participant. Comparative analyses will be conducted between two groups of 100 pregnant women with GDM on insulin therapy, followed in the high-risk prenatal clinic of the Obstetrics Department of a tertiary hospital: case group using the AI model versus control group, composed of patients previously monitored under conventional in-person supervision, without the use of this technology. Algorithm generated by the AI model based on SMBG informs about diabetes control in the last week. The dashboard is accessible via a web browser, and signals: in green and red for patients with satisfactory and unsatisfactory control, respectively. Thus, the AI model optimizes the team's time in analyzing and treating patients appropriately in a simple, cost-effective, and accessible way.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Gestacional diabetes women with gestational age of up to 28 weeks and 6 days
  • Gestacional diabetes women who sign the free and informed consent form

Exclusion criteria

  • Gestational age greater than 28 completed weeks at the first consultation
  • Participants with overt DM (fasting glucose > 126 mg/dl or postprandial > 200 mg/dl)
  • Unknown outcome.

Treatment and study plan

monitoring model for women with gestacional diabetes using pharmacological therapy

Other

Artificial Intelligence modell through WhatsApp® to remote monitoring gestacional diabetes in insulin treatment, focusing on disease education, glycemic control monitoring, and therapeutic interventions.

Other names: artificial intelligence for women with gestacional diabetes

Primary outcomes

  1. fetal death

    Time frame: From the moment of randomization to delivery (until 40 weeks of pregnancy)

    Fetal death resulting from metabolic changes caused by gestational diabetes

  2. Fetal birth weight

    Time frame: From the moment of randomization to delivery (until 40 weeks of pregnancy)

    Fetal weight at birth assessed using a precision scale.

  3. neonatal hypoglycemia

    Time frame: From the moment of randomization to delivery (until 40 weeks of pregnancy), and Assessment of neonatal blood glucose levels from birth up to 48 hours post-birth.

    Neonatal hypoglycemia is the abnormal reduction of glucose in the newborn's blood to levels considered insufficient to meet the metabolic needs of the brain and other tissues. Plasma glucose parameters:

    < 40 mg/dL in the first 4 hours of life, < 45 mg/dL between 4 and 24 hours of life, After 24 hours, values < 50-60 mg/dL

  4. glycemic control

    Time frame: From the moment of randomization to delivery (until 40 weeks of pregnancy)

    Glycemic control will be evaluated according to capillary glucose measurements that are taken 6 times a day: fasting, before and 1 hour after meals, following the target ranges of 70 to 95 mg/dL fasting; 70 ton 100 mg/dL pre-prandial; and 100 to 140 mg/dL post-prandial.

Secondary outcomes

  1. admission of the newborn to the intensive care unit

    Time frame: From the moment of randomization to delivery (until 40 weeks of pregnancy), and from birth to 48 hours postpartum

    The need for the newborn to be admitted to an intensive care unit due to metabolic disorders associated with poor maternal glycemic control.

  2. mother weight gain

    Time frame: From the moment of randomization to delivery (until 40 weeks of pregnancy).

    Maternal weight gain assessed during the gestational follow-up period up to delivery.

  3. gestational age at delivery

    Time frame: From the moment of randomization to delivery (until 40 weeks of pregnancy).

    Gestational age at the time of natural childbirth or cesarean section in weeks

  4. route of delivery

    Time frame: From the moment of randomization to delivery (until 40 weeks of pregnancy).

    Description of whether it was a natural birth or a cesarean section.

  5. Blood pressure

    Time frame: From the moment of randomization to delivery (until 40 weeks of pregnancy).

    Evaluate if hypertension is present and assess blood pressure levels during pregnancy and up to delivery.

Sponsors and collaborators

Lead sponsor

JOSE FERNANDO VILELA-MARTIN

Other

Registry information

Official study title

Artificial Intelligence in Education and Monitoring Women With Gestational Diabetes

Important dates

Study start
2024
Primary completion
2026
Study completion
2027
First posted
Jan 15, 2026
Registry last updated
Jan 15, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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