Pulmonary HypertensionPH-DyPredNCT07131241
PH-DyPred: A Multimodal Dynamic Risk Prediction Study in Pulmonary Hypertension
An observational study of Pulmonary Hypertension, run by First Affiliated Hospital of Fujian Medical University at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Pulmonary Hypertension
- How many people
- 1,000 participants
- Where
- 1 siteChina
- Study dates
- 27 Jun 2025to 30 Jun 2029
- How long will I take part?
- 2 Years
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
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.
Who may be able to join
- Adults aged 18 years or older
- Pulmonary artery systolic pressure (PASP) ≥35 mmHg as estimated by echocardiography
- Provided written informed consent
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
The First Affiliated Hospital of Fujian Medical University
Fuzhou, Fujian, 350011
Biyun Chen, MSc, 008613876168899, heraty@sina.com
About this study
Official title: Research on Dynamic Risk Prediction for Patients With Pulmonary Hypertension Based on Multimodal Data Fusion: A Prospective Observational Study
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.
Read the detailed description
This is a prospective, observational cohort study designed to investigate dynamic risk prediction in patients diagnosed with pulmonary hypertension (PH). The study will collect multimodal clinical data-comprising imaging (echocardiography, cardiac MRI, PET-MR), electrocardiographic parameters, blood-based biomarkers, and demographic and clinical information-at baseline and follow-up intervals. The core objective is to develop a data fusion-based prognostic model capable of predicting adverse outcomes such as hospitalization, functional deterioration, or mortality. Machine learning methods will be employed to identify key predictive features. The model will be validated internally and externally across different subgroups. The study seeks to inform individualized risk-based decision-making and advance precision screening in PH care.
In addition, biospecimens will be collected to support comprehensive multi-omics profiling. Whole blood, serum, plasma, urine, and stool samples will be obtained and processed using standardized protocols. Blood-derived samples will be used for genomic, proteomic, metabolomic, and microRNA analyses; urine specimens will support metabolomic and renal biomarker assays; and stool samples will be used for gut microbiome sequencing. All biospecimens will be stored in a secure biobank and linked with clinical, imaging, and longitudinal follow-up data using de-identified subject codes to enable integrated multimodal analyses and facilitate future exploratory investigations of disease mechanisms and biomarker discovery.
Health economic evaluation, including cost-effectiveness and budget impact analyses, will be conducted using collected data on healthcare resource utilization, direct medical costs, and clinical outcomes to inform future policy and reimbursement decision-making.
- Conditions
- Pulmonary Hypertension
- Keywords
- Pulmonary Hypertension, Dynamic Risk Prediction, Multimodal Data Fusion, Echocardiography, Right Heart Function, Cardiac Magnetic Resonance
- Medical subject headings
- Hypertension, Pulmonary
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Up to 36 months
All-cause mortality
Death from any cause during follow-up, as confirmed by medical records or death registry.
Measured: Up to 36 months
Secondary outcomes (12)
Composite risk score performance (AUC)
Area under the ROC curve for the multimodal model predicting adverse outcomes.
Measured: At baseline and follow-up every 6 months
Changes in NT-proBNP levels
Evaluate biomarker dynamics and predictive value.
Measured: Baseline, 6, 12, 24, 36 months
Hospitalization rate for PH-related causes
Frequency of hospital admissions due to PH complications.
Measured: Up to 36 months
Change in Tricuspid Annular Plane Systolic Excursion (TAPSE) Measured by Transthoracic Echocardiography
TAPSE (mm) will be measured via transthoracic echocardiography to evaluate longitudinal right ventricular systolic function over time.
Measured: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular Diameter Measured by Transthoracic Echocardiography
Right ventricular internal diameter (mm) will be assessed by echocardiography as an indicator of RV structural remodeling.
Measured: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular Fractional Area Change (RVFAC) Measured by Transthoracic Echocardiography
RVFAC (%) will be calculated as the percentage change in RV area between end-diastole and end-systole to assess systolic function.
Measured: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular Ejection Fraction (RVEF) Measured by Cardiac Magnetic Resonance Imaging
RVEF (%) will be quantified using cardiac magnetic resonance imaging to evaluate global systolic function.
Measured: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular End-Diastolic Volume Measured by Cardiac Magnetic Resonance Imaging
Right ventricular end-diastolic volume (mL) will be measured by CMR to assess structural remodeling over time.
Measured: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular Mass Measured by Cardiac Magnetic Resonance Imaging
Right ventricular mass (grams) will be measured by CMR as an index of ventricular hypertrophy and remodeling.
Measured: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular FAPI Uptake (SUVmean) Measured by FAPI PET-MR
tandardized uptake value mean (SUVmean) of FAPI in the right ventricular free wall will be quantified using PET-MR imaging to assess fibroblast activation and myocardial fibrotic activity over time in patients with pulmonary hypertension.
Measured: Baseline, 12, 24, and 36 months
Change in Right Ventricular FAPI Uptake (SUVmax) Measured by FAPI PET-MR
Maximum standardized uptake value (SUVmax) of FAPI in the right ventricle will be measured via PET-MR as an indicator of peak regional fibroblast activation.
Measured: Baseline, 12, 24, and 36 months
Change in Right Ventricular FAPI Uptake Ratio Relative to Left Ventricle (SUVratio) Measured by FAPI PET-MR
The ratio of right ventricular to left ventricular myocardial FAPI uptake (SUVmean RV/SUVmean LV) will be calculated as a normalized index of right ventricular fibrotic remodeling.
Measured: Baseline, 12, 24, and 36 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 Aug 2025
- Study start27 Jun 2025
- Primary completion30 Jun 2028 (estimated)
- Study completion30 Jun 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (12)Papers the sponsor has linked to this study.
- Other trials for Pulmonary HypertensionStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,000 participants (estimated)
- Target duration
- 2 Years
Sponsor and investigators
- Lead sponsor
- First Affiliated Hospital of Fujian Medical University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Dajun Chai, First Affiliated Hospital of Fujian Medical University
- Investigators
- Dajun Chai, MD, Principal investigator, First Affiliated Hospital of Fujian Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07131241
- Sponsor's protocol ID
- MRCTA,ECFAH of FMU[2025]716
- Acronym
- PH-DyPred
- Status last verified
- Oct 2026
- First submitted
- 6 Aug 2025
- Last updated
- 6 Oct 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified individual participant data, including demographic information, clinical characteristics, imaging parameters (echocardiography and CMR), ECG data, laboratory test results, biospecimen profiles (e.g., biomarkers, multi-omics), and follow-up outcomes, will be shared.
Publications
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.
PubMed 39260943Lorenzatti 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.
PubMed 40294712Kjellstrom 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.
PubMed 32870447Meyer 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.
PubMed 29435739van 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.
PubMed 22133851Small 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.
PubMed 38357903Hameed 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.
PubMed 37271771Rachedi 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.
PubMed 38701775Yorke 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.
PubMed 24232702Zhao 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.
PubMed 40205021Rich 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.
PubMed 30072105Humbert 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.
PubMed 36017548
Study at a glance
From the registry record, last updated by the sponsor on 6 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Research on Dynamic Risk Prediction for Patients With Pulmonary Hypertension Based on Multimodal Data Fusion: A Prospective Observational Study
- ClinicalTrials.gov ID
- NCT07131241
- Acronym / sponsor ID
- PH-DyPred / MRCTA,ECFAH of FMU[2025]716
- Conditions
- Pulmonary Hypertension
- Keywords
- Pulmonary Hypertension, Dynamic Risk Prediction, Multimodal Data Fusion, Echocardiography, Right Heart Function, Cardiac Magnetic Resonance
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- First Affiliated Hospital of Fujian Medical UniversityUniversity, hospital or other
- Study start
- 27 Jun 2025 (actual)
- Primary completion
- 30 Jun 2028 (estimated)
- Study completion
- 30 Jun 2029 (estimated)
- First posted
- 20 Aug 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
This is a prospective, observational cohort study designed to investigate dynamic risk prediction in patients diagnosed with pulmonary hypertension (PH). The study will collect multimodal clinical data-comprising imaging (echocardiography, cardiac MRI, PET-MR), electrocardiographic parameters, blood-based biomarkers, and demographic and clinical information-at baseline and follow-up intervals. The core objective is to develop a data fusion-based prognostic model capable of predicting adverse outcomes such as hospitalization, functional deterioration, or mortality. Machine learning methods will be employed to identify key predictive features. The model will be validated internally and externally across different subgroups. The study seeks to inform individualized risk-based decision-making and advance precision screening in PH care.
In addition, biospecimens will be collected to support comprehensive multi-omics profiling. Whole blood, serum, plasma, urine, and stool samples will be obtained and processed using standardized protocols. Blood-derived samples will be used for genomic, proteomic, metabolomic, and microRNA analyses; urine specimens will support metabolomic and renal biomarker assays; and stool samples will be used for gut microbiome sequencing. All biospecimens will be stored in a secure biobank and linked with clinical, imaging, and longitudinal follow-up data using de-identified subject codes to enable integrated multimodal analyses and facilitate future exploratory investigations of disease mechanisms and biomarker discovery.
Health economic evaluation, including cost-effectiveness and budget impact analyses, will be conducted using collected data on healthcare resource utilization, direct medical costs, and clinical outcomes to inform future policy and reimbursement decision-making.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 2 Years
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (3 listed)
- Adults aged 18 years or older
- Pulmonary artery systolic pressure (PASP) ≥35 mmHg as estimated by echocardiography
- Provided written informed consent
Key exclusion criteria (7 listed)
- Severe hepatic or renal insufficiency
- Malignancy under active treatment
- Severe infection
- Active autoimmune disease
- Major surgery within the past 3 months
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Time to clinical worsening
Time frame: Up to 36 months
Defined as any of the following: hospitalization for PH, escalation of therapy, 6MWD decrease >15%, WHO-FC worsening, or death. Measured from baseline.
All-cause mortality
Time frame: Up to 36 months
Death from any cause during follow-up, as confirmed by medical records or death registry.
12 secondary outcomes
Composite risk score performance (AUC)
Time frame: At baseline and follow-up every 6 months
Changes in NT-proBNP levels
Time frame: Baseline, 6, 12, 24, 36 months
Hospitalization rate for PH-related causes
Time frame: Up to 36 months
Change in Tricuspid Annular Plane Systolic Excursion (TAPSE) Measured by Transthoracic Echocardiography
Time frame: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular Diameter Measured by Transthoracic Echocardiography
Time frame: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular Fractional Area Change (RVFAC) Measured by Transthoracic Echocardiography
Time frame: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular Ejection Fraction (RVEF) Measured by Cardiac Magnetic Resonance Imaging
Time frame: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular End-Diastolic Volume Measured by Cardiac Magnetic Resonance Imaging
Time frame: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular Mass Measured by Cardiac Magnetic Resonance Imaging
Time frame: Baseline, 6, 12, 24, 36 months
Change in Right Ventricular FAPI Uptake (SUVmean) Measured by FAPI PET-MR
Time frame: Baseline, 12, 24, and 36 months
Change in Right Ventricular FAPI Uptake (SUVmax) Measured by FAPI PET-MR
Time frame: Baseline, 12, 24, and 36 months
Change in Right Ventricular FAPI Uptake Ratio Relative to Left Ventricle (SUVratio) Measured by FAPI PET-MR
Time frame: Baseline, 12, 24, and 36 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Oct 2026.
- Background: PubMed 39260943Fauvel 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.
- Background: PubMed 40294712Lorenzatti 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.
- Background: PubMed 32870447Kjellstrom 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.
- Background: PubMed 29435739Meyer 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.
- Background: PubMed 22133851van 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.
- Background: PubMed 38357903Small 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.
- Background: PubMed 37271771Hameed 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.
- Background: PubMed 38701775Rachedi 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.
- Background: PubMed 24232702Yorke 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.
- Background: PubMed 40205021Zhao 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.
- Background: PubMed 30072105Rich 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.
- Background: PubMed 36017548Humbert 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.
- 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.Link provided by the sponsor.
- Individual participant dataSharing planned: Yes. De-identified individual participant data, including demographic information, clinical characteristics, imaging parameters (echocardiography and CMR), ECG data, laboratory test results, biospecimen profiles (e.g., biomarkers, multi-omics), and follow-up outcomes, will be shared.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Dajun Chai, MD principal investigator
First Affiliated Hospital of Fujian Medical University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pulmonary Hypertension, run by First Affiliated Hospital of Fujian Medical University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 6 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Dajun Chai, MD (0086059187981637, dajunchai-fy@fjmu.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Time to clinical worsening (time frame: Up to 36 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07131241, which also lists 12 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Oct 2026.