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Active, Not Recruiting

NCT Number: NCT06963528

Gestational Diabetes Monitoring and Management

The primary goal is to predict the clinical outcomes of mother and baby using blood glucose and other routinely collected clinical data in pregnancy to predict adverse outcomes at birth in women with GDM. The secondary goal is to develop models to predict optimal blood glucose testing schedules for pregnant women. Exploratory Objectives are (1) to understand patterns of dosage and / or medication choice and (2) to describe different phenotypes of gestational diabetes based on multiple data input.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Conditions

Gestational Diabetes Birth Hypoxia Birth Outcome, Adverse Birth Weight Birth, Preterm Body Weight Body Weight Changes Cardiovascular Diseases Diabetes Complications Diabetes Mellitus Diabetes, Gestational Endocrine System Diseases Female Urogenital Diseases and Pregnancy Complications Gestational Complication Gestational Diabetes Mellitus in Pregnancy Gestational Hypertension Gestational Mother Gestational Weight Gain Glucose Metabolism Disorders Hypertension Hypertension, Pregnancy-Induced Metabolic Diseases Nutritional and Metabolic Diseases Obstetric Labor Complications Obstetric Labor, Premature Pathological Conditions, Signs and Symptoms Pregnancy Bleeding Pregnancy Complications Pregnancy Induced Hypertension Pregnancy Loss Pregnancy Preterm Pregnancy Weight Gain Pregnancy in Diabetic Pregnancy in Diabetics Pregnancy, High Risk Premature Birth Signs and Symptoms Urogenital Diseases Vascular Diseases Weight Gain

Age range

18 year–99 year

Sex eligibility

Female

Study type

Observational

Primary location

University of Oxford

Oxford, OX1 3PJ, United Kingdom

About this study

Gestational diabetes is a sub-type of diabetes that causes a person's blood sugar level to become too high during pregnancy. This health condition affects approximately 10% of pregnant women in the UK and up to 20% worldwide. Women who have gestational diabetes need to take daily blood tests to monitor their blood sugar. While much work exists on telehealth using blood glucose monitoring, little exists in modern AI-based methods for performing the prediction of patient health status in such settings. This study builds on world-leading research in this field within the Institute of Biomedical Engineering and the Nuffield Department of Women's & Reproductive Health at the University of Oxford. The focus of this project is to clearly identify patients in different risk groups, predict the clinical outcome of mothers and babies, and reduce the overall number of blood tests. During this study, CI and investigators will develop novel state-of-the-art AI models to improve blood glucose control. This study will use existing retrospective data in pursuit of objectives. The hypothesis in this study is that better blood glucose control will improve clinical outcomes. The predictive models developed in this research study will provide an estimate of patient-specific health risk through time, and notify patients of the clinically appropriate number of blood glucose tests required to monitor their condition. As a result, innovations arising from this study can support future studies to facilitate rapid clinical treatment, transform a hospital-only treatment pathway into a cost-effective home-based alternative, and improve the overall quality of maternal healthcare.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Pregnant women with GDM during pregnancy
  • Record of blood glucose monitoring registered on the GDm-Health system

Exclusion criteria

The participant may not enter the study if ANY of the following apply:

  • Women who have not consented for their data to be shared through GDm-Health
  • Women who opted out of the use of their data in health research

Treatment and study plan

Primary outcomes

  1. Clinical outcome of mothers at birth

    Time frame: From enrollment to the delivery date, assesed upto 52 weeks.

    Gestational age at delivery in years, Mode of delivery (vaginal, caesarean, assisted) as categocial measurements, Maternal weight gain in kg, Maternal pregnancy-induced hypertension in binary Yes or No, Maternal pregnancy-induced pre-eclampsia in binary Yes or No.

  2. Clinical outcome of mothers after birth

    Time frame: From the delivery date to the date that mother was discharged from the hospital, assessed up to 52 weeks, whichever come first.

    Perineal trauma (3rd- or 4th-degree perineal tear or tear requiring suturing in the operating room) in text notes, Admission to higher level of care for mother in ICD codes, Length of hospital stay for mother in days, Method of feeding at discharge from hospital in texts.

  3. Clinical outcome of neonates at birth

    Time frame: From enrollment to the delivery date to the date to giving birth, assesed upto 52 weeks.

    Newborn status at birth in categocial (alive, stillbirth), Birth weight in kg, Gender of neonate in categocial of male or female, APGAR score at 5 mins in numerical numbers from 0 to 10.

  4. Clinical outcome of neonates after birth

    Time frame: From the delivery date to the date that neonate was discharged from the hospital, assessed up to 52 weeks, whichever come first.

    Incidence of shoulder dystocia/birth injury in ICD codes to indicate yes or no, Incidence of neonatal hypoglycaemia in ICD codes to indicate Yes or No, Incidence of neonatal significant hyperbilirubinemia in ICD codes to indicate Yes or No, Length of hospital stay for neonate in days.

Sponsors and collaborators

Lead sponsor

University of Oxford

Other

Collaborators

  • Oxford University Hospitals NHS Trust
  • Royal Academy of Engineering

Registry information

Official study title

Predictive Monitoring and Management of Pregnant Women With Gestational Diabetes Mellitus

Important dates

Study start
2021
Primary completion
2023
Study completion
2025
First posted
May 9, 2025
Registry last updated
May 18, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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