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Non-invasive Pulmonary Artery Prediction (ADOPTS)

NCT ID: NCT05641675

Last Updated: 2022-12-20

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

25 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-02-01

Study Completion Date

2023-10-01

Brief Summary

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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.

Detailed Description

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A prototype device will be supplied by Silverleaf Medical Science (Redlands, CA) to record these signals. This study will take place at Loma Linda VA, in the cardiac catheterization lab as an add-on to clinically-indicated right heart catheterizations, and under the supervision of heart failure and interventional cardiologists. The investigators will screen and enroll 20 Veterans who consent to participate in the study. Veterans who decline to consent and vulnerable populations will be excluded from the study. The investigators will obtain simultaneous recordings from the prototype device (EKG, heart sounds, and thoracic impedance) and from the PAP catheter , both at rest (5 minutes), and in response to physiological maneuvers: hand grip, passive leg raise, and Valsalva (1 minute recordings with 1-minute breaks). De-identified recordings from the prototype device will be shared with the team at Silverleaf Medical Science to derive a computed PAP. The investigators will test the hypothesis that computed PAP is no different than measured PAP. If the algorithm can produce a computed PAP with high accuracy,'\[it would be the first wearable system to non-invasively report PAP.

Conditions

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Heart Failure Pulmonary Arterial Hypertension

Keywords

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Pulmonary artery pressure Electrocardiogram Heart failure Machine Learning

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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right heart catheterization cohort

The study investigators will screen up to 50 Veterans undergoing right heart catheterization for clinical indications with the intention to consent up to 20 Veterans. Veterans will be screened by study investigators. Veterans who decline to consent and vulnerable populations (pregnant, incapacitated, incarcerated) will be excluded from the study.

right heart catheterization

Intervention Type DIAGNOSTIC_TEST

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

Interventions

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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

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* Written informed consent and authorization to use and disclose health information.
* 20 years of age or older.
* Diagnosis of HF for \>3 months, with preserved or reduced left ventricular ejection fraction (LVEF).
* Female subjects of childbearing age with a negative urine or serum pregnancy test at the time of the right heart cauterization procedure and trial.

Exclusion Criteria

* Active infection.
* Unable to tolerate a right heart catheterization (RHC), in the investigator's opinion.
* Implantation of cardiac resynchronization therapy (CRT)\<3 months before enrollment.
* Enrolled in concurrent studies that may confound the results of this study.
* Clinical condition that would not allow them to complete the study, in the investigator's opinion.
Minimum Eligible Age

20 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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VA Loma Linda Health Care System

FED

Sponsor Role collaborator

Silverleaf Medical Sciences INC

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Jay Patel

Role: PRINCIPAL_INVESTIGATOR

Loma Linda Veterans Administration Healthcare System

Islam Abudayyeh

Role: STUDY_DIRECTOR

Silverleaf Medical Sciences INC

Jianwei Zheng, Ph.D.

Role: STUDY_CHAIR

Silverleaf Medical Sciences INC

Locations

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Loma Linda Veterans Administration Healthcare System

Loma Linda, California, United States

Site Status

Countries

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United States

Central Contacts

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Jianwei Zheng, Ph.D.

Role: CONTACT

Phone: 9492398388

Email: [email protected]

Facility Contacts

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Jay Patel

Role: primary

References

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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.

Reference Type RESULT
PMID: 36093166 (View on PubMed)

Other Identifiers

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ADOPTS_VALL

Identifier Type: -

Identifier Source: org_study_id