Acorai MLG Study (Machine Learning Generalisation)

Heart Failure Clinical Trial

Official title:

A Multi-Site Observational Clinical Investigation to Collect Non-invasive Sensor Data During a Right Heart Catheterization and Train Machine Learning Models to Estimate Intracardiac Hemodynamic Parameters

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05835024
• Other study ID #: ASDC-1
• Status: Recruiting
• Start date: August 15, 2023
• Est. completion date: December 30, 2023

Study information

• Verified date: August 2023
• Source: Acorai AB
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Acorai is developing a non-invasive monitoring system for the estimation of intracardiac hemodynamic parameters in patients with suspected or confirmed heart failure, and/or pulmonary hypertension, who require hemodynamic assessment. The device will be intended as a companion test or clinical decision support tool to be used and interpreted by qualified healthcare professionals to aid standard-of-care clinical assessment in identifying hemodynamic congestion and supporting personalized treatment of heart failure and pulmonary congestion.

This study is part of the development of a non-invasive monitoring system for the estimation of intracardiac hemodynamic parameters. It will be conducted to collect the data needed to train the machine learning models retrospectively.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1214
• Est. completion date: December 30, 2023
• Est. primary completion date: December 30, 2023
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Subject is, at least, 18 years of age at the time of screening visit.

• Subject is willing and physically able to comply with the specified evaluations as per the clinical investigation plan, as assessed by the investigator.

• Subject is referred for invasive hemodynamic assessment with right heart cardiac catheterization.

• Patient has provided written informed consent using the Ethics Committee/ Institutional Review Board approved consent form.

Exclusion Criteria:

• Discretionary exclusion when, in the opinion of the investigator, the inclusion of a potential subject is not in their best interest or not in the interest of compliant performance of the clinical investigation.

Related Conditions & MeSH terms

• Heart Failure

Intervention

Device:
• Acorai Sensor Data Collection (ASDC) system 1.0
A supervised session that includes 10 minutes of patient information entry, 5 minutes of sensor recording time and 10 minutes of margin for setting up the system and patient, thus a total evaluation duration of approximately 25 minutes prior to the Right Heart Catheterization. No follow-up period for the subjects will be required for this clinical investigation. Patients will be followed as per standard of care, at the hospital. A single follow-up observational data collection will be conducted at 90 days, to collect the number of unplanned hospitalizations since the procedure visit. This does not involve active patient participation.

Locations

Country	Name	City	State
United Kingdom	Harefield Hospital	London

Sponsors (1)

Lead Sponsor	Collaborator
Acorai AB

Country where clinical trial is conducted

United Kingdom, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy of ML	Accuracy of the machine learning models trained on data collected from the ASDC system to estimate measurements obtained during a right heart catheterization.	Day 0 to Day 90
Secondary	Abnormal RHC measurements	The diagnostic accuracy of the machine learning models trained on data collected from the ASDC system to detect clinically significant abnormal right heart catheterization measurements.	Day 0 to Day 90
Secondary	NT-proBNP	Accuracy of the combination of NT-proBNP with the optimal machine learning model to estimate measurements obtained during a right heart catheterization.	Day 0 to Day 90