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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
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05622695
Acronym
ADOPTS
Enrollment
25
Registered
2022-11-21
Start date
2022-10-30
Completion date
2023-08-31
Last updated
2022-11-21

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Heart Failure, Pulmonary Arterial Hypertension

Brief 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.

Interventions

DEVICEcatheterization

Swan-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.

Sponsors

PIH Health Good Samaritan Hospital
CollaboratorUNKNOWN
Silverleaf Medical Sciences INC
Lead SponsorINDUSTRY

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
20 Years to No maximum
Healthy volunteers
No

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

Design outcomes

Primary

MeasureTime frameDescription
The correlation of pulmonary artery pressure values measured by Sawn Gan catheter and that derived by a machine learning algorithmthe Swan-Ganz catheter obtains the pulmonary artery pressures for a minimum of 5 minutes.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 correlation of pulmonary artery wedge pressure values measured by Sawn Gan catheter and that derived by a machine learning algorithmthe Swan-Ganz catheter obtains wedge pressures first for a minimum of 20 seconds (20-30 seconds).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.

Countries

United States

Contacts

Primary ContactJianwei Zheng, Ph.D.
zheng@slmedsci.com9493298388

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026