Heart Failure Clinical Trial
— ADOPTSOfficial title:
Study to Determine if Novel Wearable Monitoring System and Machine-Learning Algorithm Can Model Continuous Pulmonary Artery Pressure Recordings in Human Subjects
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.
| Status | Recruiting |
| Enrollment | 25 |
| Est. completion date | August 31, 2023 |
| Est. primary completion date | April 30, 2023 |
| Accepts healthy volunteers | No |
| Gender | All |
| Age group | 20 Years and older |
| Eligibility | Inclusion Criteria: 1. Subjects age 18+ years 2. Undergoing a right heart cardiac catheterization or in the cardiac care unit with active monitoring using an arterial line or Swan-Ganz catheter. Exclusion Criteria: 1. Vulnerable population 2. Unable to consent for any reason 3. Unstable patient 4. Known skin reaction to latex or adhesives |
| Country | Name | City | State |
|---|---|---|---|
| United States | PIH Good Samaritan Hospital | Los Angeles | California |
| Lead Sponsor | Collaborator |
|---|---|
| Silverleaf Medical Sciences INC | PIH Health Good Samaritan Hospital |
United States,
Zheng J, Abudayyeh I, Mladenov G, Struppa D, Fu G, Chu H, Rakovski C. An artificial intelligence-based noninvasive solution to estimate pulmonary artery pressure. Front Cardiovasc Med. 2022 Aug 24;9:855356. doi: 10.3389/fcvm.2022.855356. eCollection 2022. — View Citation
| Type | Measure | Description | Time frame | Safety issue |
|---|---|---|---|---|
| Primary | The correlation of pulmonary artery pressure values measured by Sawn Gan catheter and that derived by a machine learning algorithm | The primary objective of this study is to determine if a machine-learning algorithm with data from a wearable device can reproduce simultaneous pulmonary artery pressure obtained during right heart catheterization or data obtained from a Sawn Ganz catheter already in place in the setting of cardiac care unit admission. | the Swan-Ganz catheter obtains the pulmonary artery pressures for a minimum of 5 minutes. | |
| Primary | The correlation of pulmonary artery wedge pressure values measured by Sawn Gan catheter and that derived by a machine learning algorithm | The second objective of this study is to determine if a machine-learning algorithm with data from a wearable device can reproduce simultaneous pulmonary artery wedge pressure obtained during right heart catheterization or data obtained from a Sawn Ganz catheter already in place in the setting of cardiac care unit admission. | the Swan-Ganz catheter obtains wedge pressures first for a minimum of 20 seconds (20-30 seconds). |
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