CClinicalTrials.gg
Status unknownNCT05622695ADOPTSUpdated Nov 21, 2022

Non-invasive Pulmonary Artery Prediction

An observational study in Heart Failure and Pulmonary Arterial Hypertension, sponsored by Silverleaf Medical Sciences INC. Status unknown at 1 site in United States. Open to participants aged 20 Years and older. Per ClinicalTrials.gov, last updated 2022-11-21.

Sponsored by Silverleaf Medical Sciences INC · Observational

The sponsor has not verified this record recently (last verified Nov 2022), so the status shown — last known as Recruiting — may be out of date.
Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
25
Ages
20 Years and older
Sex
All
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Study 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.

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Conditions studied

  • Heart Failure
  • Pulmonary Arterial Hypertension
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In context

Pulmonary Arterial Hypertension

761 studies on the registry are indexed under Pulmonary Arterial Hypertension; 142 are open to participants now.

This study's planned enrollment of 25 is below the median of 100 across 197 observational studies indexed under Pulmonary Arterial Hypertension.

Browse Pulmonary Arterial Hypertension studies →

Lead sponsor

Silverleaf Medical Sciences INC is the lead sponsor of 2 studies on the registry; none are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
20 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

Adults with heart failure conditions.

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

Exclusion Criteria:

  1. Vulnerable population
  2. Unable to consent for any reason
  3. Unstable patient
  4. Known skin reaction to latex or adhesives
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Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
25 participants (estimated)
Patient registry
No

Groups and cohorts

  • 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.

    Device: 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.

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What researchers measure

Primary outcomes

  1. 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.

    Time frame: the Swan-Ganz catheter obtains the pulmonary artery pressures for a minimum of 5 minutes.

  2. 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.

    Time frame: the Swan-Ganz catheter obtains wedge pressures first for a minimum of 20 seconds (20-30 seconds).

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Study locations

1 of 1 sites recruiting
  • PIH Good Samaritan Hospital
    Los Angeles, California 90017, United States
    • Ihab Alomari, Dr. · Contact · 505-573-1457
    Recruiting
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References and documents

Publications

  • 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. PubMed 36093166 ↗

Individual participant data

Plan to share: No

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Nov 21, 2022, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT05622695
Lead sponsor
Silverleaf Medical Sciences INC
Collaborators
PIH Health Good Samaritan Hospital
Responsible party
Sponsor
First posted
Nov 21, 2022
Start date
Oct 30, 2022
Primary completion
Apr 30, 2023 (estimated)
Completion
Aug 31, 2023 (estimated)
Last update
Nov 21, 2022

Study contacts

Jianwei Zheng, Ph.D.
Contact
zheng@slmedsci.com
9493298388
Jianwei Zheng, Ph.D.
study chair · Silverleaf Medical Sciences
Ihab Alomari, Dr.
principal investigator · PIH Good Samaritan Hospital
Islam Abudayyeh, Dr.
study director · Loma Linda University Health

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is status unknown, as verified in Nov 2022. You cannot join it, but the record below documents what was studied.

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