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AI enabled early risk prediction for Gestational Diabetes and it s progress to Postpartum Type 2 Diabetes.

Multi-Modal AI System for Gestational Diabetes and Postpartum Type 2 Diabetes Risk Prediction.

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2026/06/112987
Enrollment
3000
Registered
2026-06-18
Start date
Unknown
Completion date
Unknown
Last updated
2026-09-14

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: O244- Gestational diabetes mellitus

Interventions

Intervention1: Nil: Nil Intervention2: Nil: Nil Intervention3: Nil: Nil Intervention4: NIL: NIL Control Intervention1: NIL: NIL

Sponsors

TANUH, AI Centre of Excellence
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Confirmed singleton pregnancy. Maternal age 20 to 45 years at enrolment, verified against hospital registration records . Gestational age (1st Trimester or early 2nd Trimester ) . Undergoing routine prenatal care. Voluntary consent for participation. Availability to participate for the duration of study (routine antenatal care and postpartum follow-up visits) .

Exclusion criteria

Exclusion criteria: Individuals with overt Diabetes (Type I or Type II) Autoimmune diseases, Chronic illnesses. Known Medicines that influence the glucose metabolism/ hormone treatments. Any other known complications that will affect the ultrasound imaging.

Design outcomes

Primary

MeasureTime frame
Gestational Diabetes Mellitus(GDM) is usually diagnosed during the second trimester of pregnancy (between 24 and 28 weeks) using the oral glucose tolerance test (OGTT). This approach misses the opportunity for early identification and early preventive care. In addition, follow-up testing after delivery to assess the risk of diabetes is often inadequate. Early identification and intervention are important to reduce pregnancy-related complications and to lower the future risk of developing type 2 diabetes. This project aims to develop and validate an artificial intelligence (AI)-based multimodal risk prediction system using information collected as part of routine medical care and, where separately consented, additional comprehensive investigations.Improved early risk prediction for GDM may also help in better management of gestational diabetes during pregnancy. Timepoint: 1st Timester 2nd Trimester 3rd Trimester Every Quarter for upto 1 year Post Partum

Secondary

MeasureTime frame
This is an observational study. The study as a secondary outcome might help in identifying early markers of Gestational DiabetesTimepoint: 1st Trimester

Countries

India

Contacts

Public ContactArihant Kochhar

Indian Institute of Science

jayap@iisc.ac.in7892071469

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Sep 19, 2026