Clinical trial NCT05641675: Non-invasive Pulmonary Artery Prediction (ADOPTS)
Official title: Feasibility Study to Determine if Novel Wearable Monitoring System and Machine-Learning Algorithm Can Model Continuous Pulmonary Artery Pressure Recordings in Human Subjects
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Heart Failure
Pulmonary Arterial Hypertension
Keywords: Pulmonary artery pressure
Electrocardiogram
Heart failure
Machine Learning
Lead sponsor: Silverleaf Medical Sciences INC
Sponsor class: INDUSTRY
Collaborators: name: VA Loma Linda Health Care System
First posted: 2022-12-08
Enrollment: 25
Sex: ALL
Minimum age (years): 20
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: 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.

Brief 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.

Detailed description: 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.

Eligibility criteria: 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.

Primary outcomes:
measure: Major Outcome
timeFrame: the Swan-Ganz catheter obtains the pulmonary artery pressures for a minimum of 5 minutes
Secondary outcomes:
Other outcomes:
Locations:
city: Loma Linda
country: United States
facility: Loma Linda Veterans Administration Healthcare System
state: California
Study officials:
affiliation: Loma Linda Veterans Administration Healthcare System
name: Jay Patel
role: PRINCIPAL_INVESTIGATOR
affiliation: Silverleaf Medical Sciences INC
name: Islam Abudayyeh
role: STUDY_DIRECTOR
affiliation: Silverleaf Medical Sciences INC
name: Jianwei Zheng, Ph.D.
role: STUDY_CHAIR
References:
citation: 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.