Non-invasive Pulmonary Artery Prediction (ADOPTS)

A proprietary machine-learning algorithm has been developed to model continuous pulmonary artery pressure (PAP), a physiologic marker of cardiopulmonary function. The algorithm was developed from PAP recordings obtained during invasive right heart catheterization. The study will evaluate whether this algorithm can perform as well when embedded into a non-invasive wearable device that records EKG, heart sounds, and thoracic impedance has yet to be established.

Inclusion Criteria:Written informed consent and authorization to use and disclose health information.20 years of age or older.Diagnosis of HF for >3 months, with preserved or reduced left ventricular ejection fraction (LVEF).Female subjects of childbearing age with a negative urine or serum pregnancy test at the time of the right heart cauterization procedure and trial.Exclusion Criteria:Active infection.Unable to tolerate a right heart catheterization (RHC), in the investigator's opinion.Implantation of cardiac resynchronization therapy (CRT)<3 months before enrollment.Enrolled in concurrent studies that may confound the results of this study.Clinical condition that would not allow them to complete the study, in the investigator's opinion.