Non-invasive Pulmonary Artery Prediction
ADOPTS
Study to Determine if Novel Wearable Monitoring System and Machine-Learning Algorithm Can Model Continuous Pulmonary Artery Pressure Recordings in Human Subjects
1 other identifier
observational
25
1 country
1
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for all trials
Started Oct 2022
Shorter than P25 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
October 30, 2022
CompletedFirst Submitted
Initial submission to the registry
November 3, 2022
CompletedFirst Posted
Study publicly available on registry
November 21, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
April 30, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
August 31, 2023
CompletedNovember 21, 2022
November 1, 2022
6 months
November 3, 2022
November 9, 2022
Conditions
Outcome Measures
Primary Outcomes (2)
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.
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).
Study Arms (1)
Catheterization Arm
Participants will be limited to adults older than 18 years of age, able to consent, planned for the cardiac catheterization lab for a right heart catheterization or in the cardiac care unit with an existing arterial line or Swan-Ganz catheter actively measuring the pulmonary artery pressure on a continuous basis.
Interventions
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.
Eligibility Criteria
Adults with heart failure conditions.
You may qualify if:
- Subjects age 18+ years
- Undergoing a right heart cardiac catheterization or in the cardiac care unit with active monitoring using an arterial line or Swan-Ganz catheter.
You may not qualify if:
- Vulnerable population
- Unable to consent for any reason
- Unstable patient
- Known skin reaction to latex or adhesives
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
PIH Good Samaritan Hospital
Los Angeles, California, 90017, United States
Related Publications (1)
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.
PMID: 36093166RESULT
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Study Officials
- STUDY CHAIR
Jianwei Zheng, Ph.D.
Silverleaf Medical Sciences
- PRINCIPAL INVESTIGATOR
Ihab Alomari, Dr.
PIH Good Samaritan Hospital
- STUDY DIRECTOR
Islam Abudayyeh, Dr.
Loma Linda University Health
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- INDUSTRY
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
November 3, 2022
First Posted
November 21, 2022
Study Start
October 30, 2022
Primary Completion
April 30, 2023
Study Completion
August 31, 2023
Last Updated
November 21, 2022
Record last verified: 2022-11
Data Sharing
- IPD Sharing
- Will not share