A prototype device will be supplied by Silverleaf Medical Science (Redlands, CA) to record these signals. This study will take place at Loma Linda VA, in the cardiac catheterization lab as an add-on to clinically-indicated right heart catheterizations, and under the supervision of heart failure and interventional cardiologists. The investigators will screen and enroll 20 Veterans who consent to participate in the study. Veterans who decline to consent and vulnerable populations will be excluded from the study. The investigators will obtain simultaneous recordings from the prototype device (EKG, heart sounds, and thoracic impedance) and from the PAP catheter , both at rest (5 minutes), and in response to physiological maneuvers: hand grip, passive leg raise, and Valsalva (1 minute recordings with 1-minute breaks). De-identified recordings from the prototype device will be shared with the team at Silverleaf Medical Science to derive a computed PAP. The investigators will test the hypothesis that computed PAP is no different than measured PAP. If the algorithm can produce a computed PAP with high accuracy,'[it would be the first wearable system to non-invasively report PAP.
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.