Clinical Trials Directory

Trials / Unknown

UnknownNCT05622695

Non-invasive Pulmonary Artery Prediction

Study to Determine if Novel Wearable Monitoring System and Machine-Learning Algorithm Can Model Continuous Pulmonary Artery Pressure Recordings in Human Subjects

Status
Unknown
Phase
Study type
Observational
Enrollment
25 (estimated)
Sponsor
Silverleaf Medical Sciences INC · Industry
Sex
All
Age
20 Years
Healthy volunteers
Not accepted

Summary

Cardiac remote monitoring devices have expanded our ability to track physiological changes used in the diagnosis and management of patients with cardiac disease. Implantable remote monitoring technologies have been shown to predict heart failure events, and guide therapy to reduce heart failure hospitalizations. The CardioMEMs System, the most studied and established remote monitoring system, relies on a pulmonary artery implant for continuous PAP measurement. However, there are no commercially available wearable systems that can reproduce continuous PAP tracings. This study aims to determine if a machine-learning algorithm with data from a wearable cardiac remote-monitoring system incorporating EKG, heart sounds, and thoracic impedance can reproduce a continuous PAP tracing obtained during right heart catheterization.

Conditions

Interventions

TypeNameDescription
DEVICEcatheterizationSwan-Ganz catheterization (also called right heart catheterization or pulmonary artery catheterization) is the passing of a thin tube (catheter) into the right side of the heart and the arteries leading to the lungs. It is done to monitor the heart's function and blood flow and pressures in and around the heart.

Timeline

Start date
2022-10-30
Primary completion
2023-04-30
Completion
2023-08-31
First posted
2022-11-21
Last updated
2022-11-21

Locations

1 site across 1 country: United States

Source: ClinicalTrials.gov record NCT05622695. Inclusion in this directory is not an endorsement.