A Multi-Site Observational Clinical Investigation to Collect Non-invasive Sensor Data During a Right Heart Catheterization and Train Machine Learning Models to Estimate Intracardiac Hemodynamic Parameters Evaluation of a Novel maChine leArning Model's Performance for Non-invasive inTracardiac pressURE Monitoring in Heart Failure - The CAPTURE-HF Trial
Acorai is developing a non-invasive monitoring system for the estimation of intracardiac hemodynamic parameters in patients with suspected or confirmed heart failure, and/or pulmonary hypertension, who require hemodynamic assessment. The device will be intended as a companion test or clinical decision support tool to be used and interpreted by qualified healthcare professionals to aid standard-of-care clinical assessment in identifying hemodynamic congestion and supporting personalized treatment of heart failure and pulmonary congestion. This study is part of the development of a non-invasive monitoring system for the estimation of intracardiac hemodynamic parameters. It will be conducted to collect the data needed to train the machine learning models retrospectively.
• Subject is, at least, 18 years of age at the time of screening visit.
• Subject is willing and physically able to comply with the specified evaluations as per the clinical investigation plan, as assessed by the investigator.
• Subject is referred for invasive hemodynamic assessment with right heart cardiac catheterization.
• Patient has provided written informed consent using the Ethics Committee/ Institutional Review Board approved consent form.