Gestational Diabetes, Macrosomia, Fetal
Conditions
Keywords
artificial intelligence, gestacional diabetes, machine learning, glucose monitoria, glucose sensor
Brief summary
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.
Detailed description
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.
Interventions
OTHERmonitoring model for women with gestacional diabetes using pharmacological therapy
Artificial Intelligence modell through WhatsApp® to remote monitoring gestacional diabetes in insulin treatment, focusing on disease education, glycemic control monitoring, and therapeutic interventions.
Sponsors
JOSE FERNANDO VILELA-MARTIN
Study design
Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
FEMALE
Age
18 Years to 40 Years
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| fetal death | From the moment of randomization to delivery (until 40 weeks of pregnancy) | Fetal death resulting from metabolic changes caused by gestational diabetes |
| Fetal birth weight | From the moment of randomization to delivery (until 40 weeks of pregnancy) | Fetal weight at birth assessed using a precision scale. |
| neonatal hypoglycemia | 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 |
| glycemic control | 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
| Measure | Time frame | Description |
|---|---|---|
| admission of the newborn to the intensive care unit | 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. |
| Blood pressure | 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. |
| mother weight gain | 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. |
| gestational age at delivery | 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 |
| route of delivery | From the moment of randomization to delivery (until 40 weeks of pregnancy). | Description of whether it was a natural birth or a cesarean section. |
Countries
Brazil
Outcome results
None listed