Artificial Intelligence and Gestacional Diabetes

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.

Conditions

• Gestational Diabetes
• Macrosomia, Fetal

Interventions

OTHER

monitoring 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 & Collaborators

• JOSE FERNANDO VILELA-MARTIN

  lead OTHER

Principal Investigators

• José F Vilela-Martin, MD, PhD · Hospital de Base

• Vanessa V Goulart, MD, MSc · Hospital de Base, Sao Jose do Rio Preto, Sao Paulo, Brazil

• Ligia C Junqueira, MD · Hospital de Base, Sao Jose do Rio Preto, Sao Paulo, Brazil

• Amanda T Lotierzo, MD · Hospital de Base, Sao Jose do Rio Preto, Sao Paulo, Brazil

• Carolina C Amorim, MD · Hospital de Base, Sao Jose do Rio Preto, Sao Paulo, Brazil

• Maria Amalia BC Cançado, MD · Hospital de Base, Sao Jose do Rio Preto, Sao Paulo, Brazil

• Leticia A Mantoani, student · Hospital de Base, Sao Jose do Rio Preto, Sao Paulo, Brazil

• Rodrigo F Zancaner · Chamoudr company

• Rafael Beolchi · Chamoudr company

• Lucas F Queiroz · Chamoudr company

• Luciana N Cosenso-Martin, MD, PhD · Hospital de Base, Sao Jose do Rio Preto, Sao Paulo, Brazil

Study Design

Allocation

NON_RANDOMIZED

Purpose

TREATMENT

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Max Age

40 Years

Sex

FEMALE

Healthy Volunteers

No

Timeline & Regulatory

Start

2024-06-01

Primary Completion

2026-12-20

Completion

2027-12-20

Countries

• Brazil

Study Locations