Evaluating the Efficacy of GPT-based Nutrition and Diabetic Counseling in Gestational Diabetes Management: A Randomized Controlled Trial (AIM-GDM)

NCT ID: NCT06582719

Last Updated: 2025-06-13

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 80 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2025-05-29
• Study Completion Date: 2027-01-31

Brief Summary

The purpose of this study is to assess whether an AI based counseling service can be beneficial for patients to assist in management of gestational diabetes.

Detailed Description

Gestational diabetes mellitus (GDM) affects approximately 6-9% of pregnancies globally, posing significant risks to both maternal and neonatal health. Standard management includes dietary counseling, glucose monitoring, and insulin therapy when necessary. However, the rising prevalence of GDM and limited healthcare resources necessitate innovative solutions to supplement traditional care. Generative Pre-trained Transformers (GPTs), a type of large language model (LLM), offer personalized, real-time counseling and support. Recent advancements in AI have shown promise in various healthcare applications, but the efficacy of GPT-based counseling in GDM management remains underexplored. This study builds on preliminary evidence suggesting that AI can enhance patient engagement and outcomes, aiming to validate these findings in a controlled trial.

The integration of AI, specifically GPTs, into healthcare can revolutionize patient management by providing continuous, tailored support. This study aims to evaluate whether GPT-based counseling can improve glycemic control and patient satisfaction in GDM management, compared to traditional counseling alone. By placing AI within the context of prenatal care, this research seeks to address gaps in current GDM management practices and offer scalable, personalized solutions.

Conditions

Gestational Diabetes

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: SINGLE

Study Groups

Nutritional Counseling plus AI Intervention

Group Type: EXPERIMENTAL

GPT-based counseling

Intervention Type: DEVICE

AI-based counseling provided to the patient, accessible on their smartphone device at the time of Gestational Diabetes diagnosis

Nutritional Counseling

Intervention Type: OTHER

Standard Nutritional Counselling provided by a registered dietician at the time of Gestational Diabetes diagnosis

Nutritional Counseling

Group Type: ACTIVE_COMPARATOR

Nutritional Counseling

Intervention Type: OTHER

Standard Nutritional Counselling provided by a registered dietician at the time of Gestational Diabetes diagnosis

Interventions

GPT-based counseling

AI-based counseling provided to the patient, accessible on their smartphone device at the time of Gestational Diabetes diagnosis

Intervention Type: DEVICE

Nutritional Counseling

Standard Nutritional Counselling provided by a registered dietician at the time of Gestational Diabetes diagnosis

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Women aged 18-45
• Diagnosed with GDM in pregnancy
• Able to use a smartphone
• Fluent in English or Spanish

Exclusion Criteria

• Pre-existing diabetes
• High-risk pregnancies due to other medical conditions
• Inability to consent
• Non-English and/or Non-Spanish speakers
• No smartphone access

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 45 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: Yes

Sponsors

Montefiore Medical Center

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Dimitrios Mastrogiannis, MD

Role: PRINCIPAL_INVESTIGATOR

Albert Einstein College of Medicine

Locations

Montefiore Medical Center

The Bronx, New York, United States

Site Status: RECRUITING

Countries

United States

Central Contacts

Avish Arora, MD/PhD

Role: CONTACT

avarora@montefiore.org

7184058200

References

Alexander GR, Himes JH, Kaufman RB, Mor J, Kogan M. A United States national reference for fetal growth. Obstet Gynecol. 1996 Feb;87(2):163-8. doi: 10.1016/0029-7844(95)00386-X.

Reference Type: BACKGROUND

PMID: 8559516 (View on PubMed)

Centers for Disease Control and Prevention (CDC). (2022). National Diabetes Statistics Report

Reference Type: BACKGROUND

Other Identifiers

2024-16035

Identifier Type: -

Identifier Source: org_study_id