Improving prediction of coronary artery disease using arterial stiffness measurements
Official title: Pulse Wave Velocity and Machine Learning for Prediction of Coronary Artery Disease by Coronary CT Angiography - the Heart Waves Study
Run by Danderyd Hospital · NCT06734247 · Data updated 2026-05-14
This study is no longer in our active list. It may have stopped recruiting or finished. The details below are as of 2026-05-14 and are kept for reference. Check ClinicalTrials.gov for its current status, or see similar studies below.
This study is testing if using a new method that measures how stiff your arteries are can help doctors better predict coronary artery disease in patients who might have it.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 30 Years to 70 Years |
| Sex | All |
| Enrollment | 200 (estimated) |
| Sponsor | Danderyd Hospital Academic / other |
| Drugs / interventions | radiation |
| Locations | 1 site (Stockholm) |
| Trial ID | NCT06734247 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are stable patients aged 30 to 70 years with suspected symptomatic coronary artery disease who are undergoing CCTA.
✕Probably not a fit
Patients with known coronary artery disease or significant cardiac or pulmonary conditions that could explain their symptoms may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study aims to evaluate how device-estimated pulse wave velocity and machine learning techniques can enhance the prediction of symptomatic coronary artery disease in stable patients. It focuses on patients with suspected coronary artery disease who are undergoing coronary computer tomography angiography (CCTA). The study will compare traditional pre-test probability assessments with a new risk factor-weighted clinical likelihood method to improve risk estimation. By integrating non-invasive measurements of arterial stiffness, the study seeks to refine the decision-making process for further investigations.
Why it matters
Potential benefit: If successful, this study could lead to more accurate predictions of coronary artery disease, potentially reducing unnecessary invasive procedures for patients.
How similar studies have gone: Other studies have shown promise in using machine learning and non-invasive measures for cardiovascular risk assessment, indicating a potential for success in this approach.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patients undergoing coronary computer tomography angiography to investigate stable suspected symptomatic coronary artery disease. * Age 30 to \<70 years of age. Exclusion Criteria: * Known coronary artery disease (prior myocardial infarction, percutaneous coronary intervention, coronary artery bypass graft or any angiographic evidence of coronary artery disease ≥50% lesion in a major epicardial vessel). * Known significant cardiac (\> moderate valvular disease, heart failure with reduced ejection fraction, hypertrophic cardiomyopathy, or congenital heart disease), or pulmonary condition which could explain symptoms. * Known ongoing atrial fibrillation/flutter. * No Swedish social security number. * Unable to provide written informed consent.
Where it's running
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Danderyd University Hospital
Stockholm, Sweden Recruiting
Study contacts
- Principal investigator: Jonas Spaak, MD, PhD — Karolinska Institutet, Department of Clinical Sciences, Danderyd Hospital, Division of Cardiovascular Medicine, Stockholm, Sweden
- Study coordinator: Henrik Hellqvist, MD
- Email: henrik.hellqvist@ki.se
- Phone: +46812355000
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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.