Cardiac MRI-based prediction tool for outcomes in dilated cardiomyopathy
Official title: Study on Risk Early Warning of Clinical Prediction Model Based on Multi-Parameter Stress Perfusion Cardiac Magnetic Resonance in Adverse Prognosis of Dilated Cardiomyopathy
Run by Shandong Provincial Hospital · NCT07527715 · Data updated 2026-11-12
This project will test whether adding multi-parameter stress perfusion cardiac MRI to routine clinical data can better predict which people with dilated cardiomyopathy will go on to develop heart failure, arrhythmias, hospitalizations, or death.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 2000 (estimated) |
| Sponsor | Shandong Provincial Hospital Government |
| Locations | 1 site (Jinan, Shandong) |
| Status | Recruiting |
| Started | December 1, 2021 |
| Main results expected | December 1, 2028 |
| Study ends | December 1, 2038 |
| Registry record updated | April 14, 2026 |
| Trial ID | NCT07527715 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are adults with dilated cardiomyopathy characterized by increased indexed LV end-diastolic volume and reduced left ventricular ejection fraction, who can undergo CMR and do not have significant coronary, infiltrative, valvular, arrhythmogenic, or congenital heart disease.
✕Probably not a fit
Patients with significant coronary artery disease (>50% stenosis), infiltrative disease, valvular or arrhythmogenic cardiomyopathy, congenital heart disease, or those unable to have MRI are excluded and are unlikely to benefit from this model.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This is an observational, non-invasive study that will combine multi-parameter stress perfusion cardiac magnetic resonance (MP stress perfusion CMR) imaging with standard clinical data to build a risk prediction model for adverse outcomes in dilated cardiomyopathy (DCM). Participants with enlarged left ventricles and reduced ejection fraction, and without significant coronary, infiltrative, valvular, arrhythmogenic, or congenital heart disease, will undergo CMR and be followed over time. Investigators will train and validate the model using follow-up clinical outcomes including heart failure events, arrhythmias, hospitalizations, and mortality. The project is conducted at Jinan Central Hospital and uses routinely collected clinical tests alongside high-resolution CMR measures of structure, function, perfusion, and tissue damage.
Why it matters
Potential benefit: If successful, the model could help clinicians identify high-risk DCM patients earlier so they receive closer monitoring and targeted treatments to reduce hospitalizations and premature death.
How similar studies have gone: Prior research shows individual CMR measures like reduced LVEF and myocardial fibrosis predict outcomes in DCM, but combining multi-parameter stress perfusion CMR with clinical data into a validated prediction model is relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria 1.An elevated left ventricular end-diastolic volume indexed to body surface area and reduced LVEF, compared with published age- and gender-specific reference values Exclusion Criteria 1. significant coronary artery disease (CAD), defined as a stenosis of ˃50% in a major coronary artery 2. infiltrative disease 3. valvular cardiomyopathy 4. arrhythmogenic cardiomyopathy 5. congenital heart disease
Where it's running
-
Jinan central hospital
Jinan, Shandong, China Recruiting
Study contacts
- Study coordinator: Wenxian Wang, Dr
- Email: wwx990511@163.com
- Phone: 8617705414294
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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.