PH-DyPred: Multimodal dynamic risk prediction in pulmonary hypertension
Official title: Research on Dynamic Risk Prediction for Patients With Pulmonary Hypertension Based on Multimodal Data Fusion: A Prospective Observational Study
Run by First Affiliated Hospital of Fujian Medical University · NCT07131241 · Data updated 2026-11-12
This project will try to build a prediction model using scans, ECGs, blood tests, and clinical data to see which adults with pulmonary hypertension are at higher risk of hospitalization, worsening symptoms, or death.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 1000 (estimated) |
| Sponsor | First Affiliated Hospital of Fujian Medical University Academic / other |
| Locations | 1 site (Fuzhou, Fujian) |
| Status | Recruiting |
| Started | June 27, 2025 |
| Main results expected | June 30, 2028 |
| Study ends | June 30, 2029 |
| Registry record updated | October 6, 2026 |
| Trial ID | NCT07131241 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults aged 18 or older with pulmonary artery systolic pressure ≥35 mmHg on echocardiography who can provide informed consent and attend baseline and follow-up visits are ideal candidates.
✕Probably not a fit
Patients with active cancer treatment, severe hepatic or renal failure, uncontrolled infection or autoimmune disease, recent major surgery, pregnancy, or those unable to complete follow-up may not receive benefit from the study findings.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This prospective observational cohort will enroll adults with pulmonary hypertension and collect serial multimodal data including echocardiography, cardiac MRI, PET-MR, ECG, blood biomarkers, and clinical information. Biospecimens (whole blood, serum, plasma, urine, stool) will be banked for multi-omics analyses and linked with imaging and outcomes using de-identified codes. Machine learning and data-fusion methods will be used to derive and internally and externally validate a dynamic prognostic model predicting hospitalization, functional decline, and mortality. The aim is to identify key predictive markers and enable individualized early-warning and management strategies.
Why it matters
Potential benefit: If successful, the model could provide earlier warnings and help clinicians tailor monitoring and treatment to reduce hospitalizations and slow disease progression.
How similar studies have gone: Previous work combining imaging, biomarkers, and machine learning has shown promising signals for risk stratification in pulmonary hypertension, but fully integrated multimodal models including PET-MR and multi-omics remain largely novel and unproven.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adults aged 18 years or older * Pulmonary artery systolic pressure (PASP) ≥35 mmHg as estimated by echocardiography * Provided written informed consent Exclusion Criteria: * Severe hepatic or renal insufficiency * Malignancy under active treatment * Severe infection * Active autoimmune disease * Major surgery within the past 3 months * Pregnant or breastfeeding women * Severe psychiatric disorder impairing ability to comply with the study protocol
Where it's running
-
The First Affiliated Hospital of Fujian Medical University
Fuzhou, Fujian, China Recruiting
Study contacts
- Principal investigator: Dajun Chai, MD — First Affiliated Hospital of Fujian Medical University
- Study coordinator: Dajun Chai, MD
- Email: dajunchai-fy@fjmu.edu.cn
- Phone: 0086059187981637
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.