Early Prediction of Gestational Diabetes in High-risk Women Based on Breath Metabolomics
- Conditions
- Gestational Diabetes
- Registration Number
- NCT06753734
- Brief Summary
This study aim to develope novel breath markers of gestational diabetes through a prospective high-risk population cohort study and achieve early prediction of gestational diabetes based on an interpretable machine learning model.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ENROLLING_BY_INVITATION
- Sex
- Female
- Target Recruitment
- 600
Inclusion Criteria
Not provided
Exclusion Criteria
- Diabetes mellitus or abnormal glucose metabolism before pregnancy
- Hyperemesis gravidarum (urine ketone positive))
- Thyroid dysfunction
- Asthmatic patients
- Hypertensive diseases that are difficult to control
- Severe hepatic and renal insufficiency or severe electrolyte disturbance
- Malignant tumor
- Acute inflammation
- lung disease
- Patients with gastritis, duodenum and other digestive system diseases
- Those with upper respiratory or oral problems who cannot cooperate with expiratory collection
- smoker
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Incidence of gestational diabetes mellitus 24-28 weeks gestation
- Secondary Outcome Measures
Name Time Method
Related Research Topics
Explore scientific publications, clinical data analysis, treatment approaches, and expert-compiled information related to the mechanisms and outcomes of this trial. Click any topic for comprehensive research insights.
What volatile organic compounds (VOCs) in breath metabolomics correlate with gestational diabetes risk in high-risk cohorts?
How does breath-based machine learning prediction compare to standard oral glucose tolerance testing for gestational diabetes?
Which metabolic pathways are dysregulated in breath profiles of women with gestational diabetes mellitus (GDM) versus controls?
What are the sensitivity/specificity thresholds of breath metabolomic biomarkers for early GDM detection in Tianjin Central Hospital studies?
How do breath metabolomic signatures in high-risk pregnancies compare to urine metabolomics or imaging-based GDM prediction models?
Trial Locations
- Locations (1)
Tianjin Central Hospital of Gynecology Obstetrics
🇨🇳Tianjin, China
Tianjin Central Hospital of Gynecology Obstetrics🇨🇳Tianjin, China