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.
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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Enrollment
80
AI-based counseling provided to the patient, accessible on their smartphone device at the time of Gestational Diabetes diagnosis
Standard Nutritional Counselling provided by a registered dietician at the time of Gestational Diabetes diagnosis
Montefiore Medical Center
The Bronx, New York, United States
Birth weight at time of Delivery
Newborns will be weighed within 12 hours of the time of delivery. Birth weights will be summarized and reported by study group using basic descriptive statistics. Higher birth weights have been associated with Gestational Diabetes Mellitus (GDM) and increased risk of perinatal complications.
Time frame: Within 12 hours of delivery
Rate of Neonatal Intensive Care Unit (NICU) admissions
Rate of NICU admission will be expressed as the percentage of newborns who were admitted to the NICU within 12 hours of delivery. Rates will be summarized and reported by study group using basic descriptive statistics. Increased admissions to the NICU are associated with less favorable perinatal outcomes.
Time frame: Within 12 hours of delivery
Rate of Cesarean Section
Rate of Cesarean Section will be expressed as the percentage of patients who delivered via Cesarean section. Rates will be summarized and reported by study group using basic descriptive statistics. Patients with GDM are more likely to need Cesarean sections leading to less favorable perinatal outcomes for the newborn.
Time frame: Within 12 hours of delivery
Rate of Progression to medication requirements
The rate of progression to medication requirements for GDM will be assessed as the percentage of patients who are administered either insulin or oral hypoglycemic at the time of delivery. Rates will be summarized and reported by study group using basic descriptive statistics. Higher rates of progression to medications are associated with increased hyperglycemia and less favorable perinatal outcomes in general.
Time frame: At the time of delivery
Rate of Shoulder Dystocia
Rate of Shoulder Dystocia will be expressed as the percentage of patients who have been diagnosed with should dystocia within 12 hours of delivery. Rates will be summarized and reported by study group using basic descriptive statistics. GDM is a risk factor for shoulder dystocia and higher rates of shoulder dystocia are associated with increased perinatal complications.
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
Time frame: Within 12 hours of delivery