PH-DyPred: A Multimodal Dynamic Risk Prediction Study in Pulmonary Hypertension

NCT07131241 | Recruiting DMC

• 1 other identifier: MRCTA,ECFAH of FMU[2025]716
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

Pulmonary hypertension (PH) is a progressive cardiopulmonary disease characterized by elevated pulmonary artery pressure and vascular remodeling, which leads to right heart failure and increased mortality. Despite advances in diagnostics, risk stratification remains limited due to the disease's heterogeneity. This study aims to develop and validate a dynamic risk prediction model for PH by integrating multimodal data-including echocardiography, Cardiac MRI, PET-MR, ECG, biomarkers, and clinical features-using advanced machine learning algorithms. The study will establish a prospective cohort of PH patients to explore predictive markers, stratify prognosis, and provide a scientific basis for early warning and individualized management.

Conditions

Pulmonary Hypertension

Keywords

Pulmonary Hypertension; Dynamic Risk Prediction; Multimodal Data Fusion; Echocardiography; Right Heart Function; Cardiac Magnetic Resonance

Outcome Measures

Primary Outcomes (2)

• Time to clinical worsening

  Defined as any of the following: hospitalization for PH, escalation of therapy, 6MWD decrease \>15%, WHO-FC worsening, or death. Measured from baseline.

  Up to 36 months

• All-cause mortality

  Death from any cause during follow-up, as confirmed by medical records or death registry.

  Up to 36 months

Secondary Outcomes (12)

• Composite risk score performance (AUC)

  At baseline and follow-up every 6 months

• Changes in NT-proBNP levels

  Baseline, 6, 12, 24, 36 months

• Hospitalization rate for PH-related causes

  Up to 36 months

• Change in Tricuspid Annular Plane Systolic Excursion (TAPSE) Measured by Transthoracic Echocardiography

  Baseline, 6, 12, 24, 36 months

• Change in Right Ventricular Diameter Measured by Transthoracic Echocardiography

  Baseline, 6, 12, 24, 36 months

Other Outcomes (12)

• Longitudinal changes in health-related quality of life (HRQoL) among patients with suspected or confirmed pulmonary hypertension

  Baseline, 6, 12, 24, and 36 months

• Area Under the ROC Curve (AUC) of the Multimodal Risk Prediction Model

  Baseline, 12, 24, 36 months

• Harrell's Concordance Index (C-index) of the Multimodal Risk Prediction Model

  Baseline, 12, 24, 36 months

Study Arms (1)

Suspected PH by Echocardiography

This study includes a prospective observational cohort of patients with suspected pulmonary hypertension (PH), identified by transthoracic echocardiography (TTE) showing a pulmonary artery systolic pressure (PASP) ≥35 mmHg. No experimental intervention will be applied. Participants will undergo comprehensive data collection, including echocardiography, cardiac magnetic resonance imaging (CMR), electrocardiography (ECG), laboratory testing, and biospecimen sampling (blood, urine, and stool). Follow-up will occur every 6 months for up to 3 years to record clinical outcomes and support the development of a dynamic, multimodal risk prediction model based on artificial intelligence.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population includes adult patients (≥18 years) undergoing transthoracic echocardiography. Participants with a pulmonary artery systolic pressure (PASP) ≥35 mmHg on echocardiography will be included as suspected pulmonary hypertension cases. This cohort represents a real-world population at risk for or with early-stage pulmonary hypertension, suitable for developing dynamic risk prediction models based on multimodal data integration.

You may qualify if:

• Adults aged 18 years or older
• Pulmonary artery systolic pressure (PASP) ≥35 mmHg as estimated by echocardiography
• Provided written informed consent

You may not qualify if:

• 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

Sponsors & Collaborators

• First Affiliated Hospital of Fujian Medical University: lead

Study Sites (1)

The First Affiliated Hospital of Fujian Medical University

Fuzhou, Fujian, 350011, China

RECRUITING

Related Publications (12)

• Fauvel C, Gomberg-Maitland M, Benza RL. Risk Stratification in Pulmonary Hypertension: We Need to "GoDeeper"! Chest. 2024 Sep;166(3):420-422. doi: 10.1016/j.chest.2024.05.020. No abstract available.

  PMID: 39260943 BACKGROUND

• Lorenzatti D, Motwani M. Cardiovascular magnetic resonance in pulmonary hypertension: Keeping it simple. Prog Cardiovasc Dis. 2025 May-Jun;90:116-118. doi: 10.1016/j.pcad.2025.04.010. Epub 2025 Apr 26. No abstract available.

  PMID: 40294712 BACKGROUND

• Kjellstrom B, Lindholm A, Ostenfeld E. Cardiac Magnetic Resonance Imaging in Pulmonary Arterial Hypertension: Ready for Clinical Practice and Guidelines? Curr Heart Fail Rep. 2020 Oct;17(5):181-191. doi: 10.1007/s11897-020-00479-7.

  PMID: 32870447 BACKGROUND

• Meyer GMB, Spilimbergo FB, Altmayer S, Pacini GS, Zanon M, Watte G, Marchiori E, Hochhegger B. Multiparametric Magnetic Resonance Imaging in the Assessment of Pulmonary Hypertension: Initial Experience of a One-Stop Study. Lung. 2018 Apr;196(2):165-171. doi: 10.1007/s00408-018-0097-7. Epub 2018 Feb 12.

  PMID: 29435739 BACKGROUND

• van de Veerdonk MC, Kind T, Marcus JT, Mauritz GJ, Heymans MW, Bogaard HJ, Boonstra A, Marques KM, Westerhof N, Vonk-Noordegraaf A. Progressive right ventricular dysfunction in patients with pulmonary arterial hypertension responding to therapy. J Am Coll Cardiol. 2011 Dec 6;58(24):2511-9. doi: 10.1016/j.jacc.2011.06.068.

  PMID: 22133851 BACKGROUND

• Small M, Perchenet L, Bennett A, Linder J. The diagnostic journey of pulmonary arterial hypertension patients: results from a multinational real-world survey. Ther Adv Respir Dis. 2024 Jan-Dec;18:17534666231218886. doi: 10.1177/17534666231218886.

  PMID: 38357903 BACKGROUND

• Hameed A, Condliffe R, Swift AJ, Alabed S, Kiely DG, Charalampopoulos A. Assessment of Right Ventricular Function-a State of the Art. Curr Heart Fail Rep. 2023 Jun;20(3):194-207. doi: 10.1007/s11897-023-00600-6. Epub 2023 Jun 5.

  PMID: 37271771 BACKGROUND

• Rachedi NS, Tang Y, Tai YY, Zhao J, Chauvet C, Grynblat J, Akoumia KKF, Estephan L, Torrino S, Sbai C, Ait-Mouffok A, Latoche JD, Al Aaraj Y, Brau F, Abelanet S, Clavel S, Zhang Y, Guillermier C, Kumar NVG, Tavakoli S, Mercier O, Risbano MG, Yao ZK, Yang G, Ouerfelli O, Lewis JS, Montani D, Humbert M, Steinhauser ML, Anderson CJ, Oldham WM, Perros F, Bertero T, Chan SY. Dietary intake and glutamine-serine metabolism control pathologic vascular stiffness. Cell Metab. 2024 Jun 4;36(6):1335-1350.e8. doi: 10.1016/j.cmet.2024.04.010. Epub 2024 May 2.

  PMID: 38701775 BACKGROUND

• Yorke J, Corris P, Gaine S, Gibbs JS, Kiely DG, Harries C, Pollock V, Armstrong I. emPHasis-10: development of a health-related quality of life measure in pulmonary hypertension. Eur Respir J. 2014 Apr;43(4):1106-13. doi: 10.1183/09031936.00127113. Epub 2013 Nov 14.

  PMID: 24232702 BACKGROUND

• Zhao W, Huang Z, Diao X, Yang Z, Zhao Z, Xia Y, Zhao Q, Sun Z, Xi Q, Huo Y, Xu O, Geng J, Li X, Duan A, Zhang S, Gao L, Wang Y, Li S, Luo Q, Liu Z. Development and validation of multimodal deep learning algorithms for detecting pulmonary hypertension. NPJ Digit Med. 2025 Apr 10;8(1):198. doi: 10.1038/s41746-025-01593-3.

  PMID: 40205021 BACKGROUND

• Rich S, Haworth SG, Hassoun PM, Yacoub MH. Pulmonary hypertension: the unaddressed global health burden. Lancet Respir Med. 2018 Aug;6(8):577-579. doi: 10.1016/S2213-2600(18)30268-6. Epub 2018 Jun 29. No abstract available.

  PMID: 30072105 BACKGROUND

• Humbert M, Kovacs G, Hoeper MM, Badagliacca R, Berger RMF, Brida M, Carlsen J, Coats AJS, Escribano-Subias P, Ferrari P, Ferreira DS, Ghofrani HA, Giannakoulas G, Kiely DG, Mayer E, Meszaros G, Nagavci B, Olsson KM, Pepke-Zaba J, Quint JK, Radegran G, Simonneau G, Sitbon O, Tonia T, Toshner M, Vachiery JL, Vonk Noordegraaf A, Delcroix M, Rosenkranz S; ESC/ERS Scientific Document Group. 2022 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension. Eur Heart J. 2022 Oct 11;43(38):3618-3731. doi: 10.1093/eurheartj/ehac237. No abstract available.

  PMID: 36017548 BACKGROUND

Related Links

• Description: Official website of the First Affiliated Hospital of Fujian Medical University, the lead institution responsible for this study. The site includes institutional information, clinical departments, research governance, and contact information.

Biospecimen

Retention: SAMPLES WITH DNA

Whole blood, serum, plasma, urine, and stool samples will be collected and stored for future analysis. Blood-derived samples will be used for genomic, proteomic, metabolomic, and microRNA profiling. Urine samples will be analyzed for renal biomarkers and metabolomic profiling. Stool samples will be used for microbiome analysis. All specimens will be processed and stored according to standardized protocols in a secure biobank. Biospecimens are linked to clinical, imaging, and follow-up data via de-identified subject codes for integrated analysis.

MeSH Terms

Conditions

Hypertension, Pulmonary

Condition Hierarchy (Ancestors)

Lung Diseases; Respiratory Tract Diseases; Hypertension; Vascular Diseases; Cardiovascular Diseases

Study Officials

• Dajun Chai, MD

  First Affiliated Hospital of Fujian Medical University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Dajun Chai, MD

CONTACT

0086059187981637; dajunchai-fy@fjmu.edu.cn

Biyun Chen, MSc

CONTACT

008613876168899; heraty@sina.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 2 Years
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor and Chief Physician, Department of Cardiology

Study Record Dates

• First Submitted: August 6, 2025
• First Posted: August 20, 2025
• Study Start: June 27, 2025
• Primary Completion (Estimated): June 30, 2028
• Study Completion (Estimated): June 30, 2029
• Last Updated: August 28, 2025

Record last verified: 2025-06

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
• Time Frame: IPD will be made available beginning 24 months after the primary study completion date and remain accessible for up to 24 months.
• Access Criteria: Qualified researchers with a scientifically sound proposal may request access to the data. Requests will be evaluated by the study steering committee. Approved users must sign a data use agreement ensuring compliance with privacy, ethical, and scientific standards.

Locations

CN (1)