MedTrace Logo

Non-invasive Pulmonary Artery Prediction (ADOPTS)

NCT05641675 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 25

Last updated 2022-12-20

No results posted yet for this study

Summary

A proprietary machine-learning algorithm has been developed to model continuous pulmonary artery pressure (PAP), a physiologic marker of cardiopulmonary function. The algorithm was developed from PAP recordings obtained during invasive right heart catheterization. The study will evaluate whether this algorithm can perform as well when embedded into a non-invasive wearable device that records EKG, heart sounds, and thoracic impedance has yet to be established.

Conditions

Interventions

DIAGNOSTIC_TEST

right heart catheterization

Connect to a heart monitor to record heart rate, blood pressure and blood oxygen levels Place sterile sheets on chest and neck (or groin area) Clean the skin over the neck or groin Give local anaesthetic to numb the area (this may sting a little when it is given) Gently pass a catheter into a vein to the heart Record pressure readings from the heart chambers and lungs Give medication, depending on heart's pressure readings Remove the catheter and apply pressure where it was inserted

Sponsors & Collaborators

  • VA Loma Linda Health Care System

    collaborator FED

  • Silverleaf Medical Sciences INC

    lead INDUSTRY

Principal Investigators

  • Jay Patel · Loma Linda Veterans Administration Healthcare System

  • Islam Abudayyeh · Silverleaf Medical Sciences INC

  • Jianwei Zheng, Ph.D. · Silverleaf Medical Sciences INC

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-02-01
Primary Completion
2023-07-01
Completion
2023-10-01

Countries

  • United States

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05641675 on ClinicalTrials.gov