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Early Risk Prediction of Preeclampsia Using Multimodal Biomarkers and Generative AI: Applications in Low and Middle Income Countries

Early Risk Prediction of Preeclampsia Using Multimodal Biomarkers and Generative AI: Applications in Low and Middle Income Countries

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600126061
Enrollment
Unknown
Registered
2026-06-03
Start date
2026-06-03
Completion date
Unknown
Last updated
2026-06-08

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

Conditions

Preeclampsia

Interventions

Preeclampsia/normal observation group:None

Sponsors

Women's Hospital School Of Medicine Zhejiang University
Lead Sponsor

Eligibility

Sex/Gender
Female

Inclusion criteria

Inclusion criteria: The first group included pregnancies with a gestational age of <= 14+0 weeks, single pregnancies, who agreed and signed the informed consent form, and could be followed up until delivery.

Exclusion criteria

Exclusion criteria: 1. Hypertension was diagnosed before enrollment. 2. The patient met the criteria for PE at the time of enrollment. 3. Severe systemic diseases (such as active tumors, organ transplants, severe infections/sepsis, etc.). 4. Pre-pregnancy diabetes/pregnancy-related diabetes. 5. Chronic kidney disease/primary proteinuria, autoimmune diseases. 6. Assisted reproduction, obesity (BMI >= 30), smoking/alcohol consumption, etc.

Design outcomes

Primary

MeasureTime frame
Circulating cell-free DNA;Imaging parameters of the placenta in early pregnancy;Urinary metabolites;Serum protein;—

Countries

China

Contacts

Public ContactQiong Luo

Women's Hospital School Of Medicine Zhejiang University

luoq@zju.edu.cn+86 571 8706 1501

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jun 11, 2026