Gestational DiabetesNCT06963528
Gestational Diabetes Monitoring and Management
An observational study of Gestational Diabetes and Pregnancy Complications, run by University of Oxford at 1 site in United Kingdom.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 to 99 years, women only
- Conditions the study is for
- Gestational Diabetes, Pregnancy Complications, Pregnancy in Diabetic
- How many people
- 1,800 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Dec 2021to 31 Aug 2025
- Phase
- Observational
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 99 years
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: Routinely collected from the NHS and submerged into four groups, including Caucasian, Asian, Black, and other
Who may be able to join
- Pregnant women with GDM during pregnancy
- Record of blood glucose monitoring registered on the GDm-Health system
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Predictive Monitoring and Management of Pregnant Women With Gestational Diabetes Mellitus
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.
Read the detailed description
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.
- Conditions
- Gestational Diabetes, Pregnancy Complications, Pregnancy in Diabetic, Pregnancy, High Risk, Diabetes Complications, Pregnancy Induced Hypertension
- Keywords
- gestational diabetes, machine learning, predictive monitoring, clustering, patient subtype, deep learning, transfomer model, foundation model, diabetes, blood glucose, c section, high risk pregnancy, diabetes complications
- Medical subject headings
- Diabetes, Gestational, Pregnancy Complications, Pregnancy in Diabetics, Diabetes Complications, Hypertension, Pregnancy-Induced, Gestational Weight Gain, Birth Weight, Premature Birth
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Mothers with diabetes in pregnancy | Mothers with first appearance of diabetes in pregnancy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Clinical outcome of mothers at birth
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.
Measured: From enrollment to the delivery date, assesed upto 52 weeks.
Clinical outcome of mothers after birth
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.
Measured: From the delivery date to the date that mother was discharged from the hospital, assessed up to 52 weeks, whichever come first.
Clinical outcome of neonates at birth
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.
Measured: From enrollment to the delivery date to the date to giving birth, assesed upto 52 weeks.
Clinical outcome of neonates after birth
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.
Measured: From the delivery date to the date that neonate was discharged from the hospital, assessed up to 52 weeks, whichever come first.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 May 2025
- Study start1 Dec 2021
- Primary completion1 Sep 2023
- Study completion31 Aug 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Gestational DiabetesStudies of the same condition, open and under way.
- More trials run by University of OxfordThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 1,800 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Oxford
- Sponsor type
- University, hospital or other
- Collaborators
- Royal Academy of Engineering, Oxford University Hospitals NHS Trust
- Responsible party
- Sponsor
- Investigators
- Huiiq Yvonne Lu, Principal investigator, University of Oxford
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06963528
- Sponsor's protocol ID
- 301255_Minor Amendment 5
- Other IDs
- IRAS 301255
- Status last verified
- Dec 2024
- First submitted
- 26 Mar 2025
- Last updated
- 18 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Ethical approval restrictions.