Clinical trial NCT06582719: Evaluating the Efficacy of GPT-based Nutrition and Diabetic Counseling in Gestational Diabetes Management: A Randomized Controlled Trial (AIM-GDM)
Official title: Evaluating the Efficacy of GPT-based Nutrition and Diabetic Counseling in Gestational Diabetes Management: A Randomized Controlled Trial (AIM-GDM)
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Gestational Diabetes
Lead sponsor: Montefiore Medical Center
Sponsor class: OTHER
First posted: 2024-09-03
Enrollment: 80
Sex: FEMALE
Minimum age (years): 18
Maximum age (years): 45
Standard ages: ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: TREATMENT

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.

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

Primary outcomes:
measure: Birth weight at time of Delivery
timeFrame: Within 12 hours of delivery
Secondary outcomes:
measure: Rate of Neonatal Intensive Care Unit (NICU) admissions
timeFrame: Within 12 hours of delivery
measure: Rate of Cesarean Section
timeFrame: Within 12 hours of delivery
measure: Rate of Progression to medication requirements
timeFrame: At the time of delivery
measure: Rate of Shoulder Dystocia
timeFrame: Within 12 hours of delivery
Other outcomes:
Locations:
city: Bronx
country: United States
facility: Montefiore Medical Center
state: New York
Study officials:
affiliation: Albert Einstein College of Medicine
name: Dimitrios Mastrogiannis, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
citation: Centers for Disease Control and Prevention (CDC). (2022). National Diabetes Statistics Report