Deep Learning Detection of Pulmonary Hypertension and Low Ejection Fraction
This study is looking at whether a digital stethoscope, the Eko CORE 500, can help detect two heart conditions: pulmonary hypertension (PH), which is high blood pressure in the lungs, and low left ventricular ejection fraction (EF ≤ 40%), which means your heart isn't pumping blood as effectively as it should. Both conditions can be serious if not found early. Researchers will use the Eko CORE 500 to record your heart sounds (phonocardiograms) and heart's electrical activity (three-lead ECG). These recordings will then be used to develop and test artificial intelligence programs that can identify PH and low EF. You can join if you are an adult aged 18 or older and have recently had or will soon have a heart ultrasound (echocardiogram) or a right heart catheterization. The main goal is to see how well these AI programs can detect PH.
- Study design
- This is an observational study aiming to enroll 3850 participants. It is not a randomized trial and does not involve a specific phase of drug development.
- What's involved
- You would have one study visit, lasting about 20 minutes, where heart sounds and a three-lead ECG will be recorded while you are seated.
- Compensation
- Not stated in the trial record.
- Follow-up
- The study will assess the detection of pulmonary hypertension for up to 24 months.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
Deep Learning Detection of Pulmonary Hypertension and Low Ejection Fraction Via Digital Stethoscope and 3-Lead ECG
At a glance
Conditions
Where it's being run
4 sites across 2 statesStudy leadership
- Rose McDonough, MD · STUDY_DIRECTOR · Senior Manager, Medical Affairs
Who to contact
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Do you actually qualify for this trial?
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Inclusion
Exclusion
What this trial measures
- Sensitivity and specificity of the deep-learning algorithm for detecting pulmonary hypertension (PH)Up to 24 months
The primary outcome is the diagnostic performance of the algorithm developed from Eko CORE 500 recordings to detect pulmonary hypertension, as confirmed by clinical echocardiography or right heart catheterization. Sensitivity and specificity will be calculated by comparing algorithm predictions to the echocardiogram or right heart catheterization gold standard.