Detection of Aortic Stenosis With Smartphone Auscultation Using Machine Learning (HEARTBEAT-Pilot)

NCT06404437 | Active Not Recruiting

• 1 other identifier: 23-39-B
• Study Type: observational
• Target: 100
• Locations: 1 country
• Sites: 1

Brief Summary

Severe aortic stenosis, a common heart valve issue, is usually treated surgically or through intervention. Diagnosis typically occurs after symptoms appear, but research suggests already treating asymptomatic cases may help patients live longer. Current diagnostics using echocardiography are detailed but time-consuming, prompting the exploration of a smartphone application using built-in microphones and machine learning for quicker and more accessible screening.

Conditions

Aortic Valve Stenosis

Keywords

Machine Learning; Digital Health; Heart Valve Disease; Cardiology

Outcome Measures

Primary Outcomes (1)

• Algorithm Performance

  Performance of algorithmic diagnosis measured by accuracy, sensitivity, specificity, and positive predictive value

  Baseline

Secondary Outcomes (2)

• Comparison with Digital Stethoscope

  Baseline

• Comparison of Auscultation Points

  Baseline

Study Arms (2)

Severe Aortic Stenosis

Diagnostic Test: Auscultation

No Relevant Heart Valve Disease

Diagnostic Test: Auscultation

Interventions

Auscultation DIAGNOSTIC_TEST

Auscultation at five auscultation points using a digital stethoscope and a smartphone

No Relevant Heart Valve Disease; Severe Aortic Stenosis

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

No relevant heart valve disease or severe aortic stenosis with no other relevant heart valve disease

You may qualify if:

• Age ≥ 18 years
• No relevant heart valve disease or severe aortic stenosis with no other relevant heart valve disease in echocardiography no older than 3 months

You may not qualify if:

• Previous surgerical or interventional therapy of a heart valve

Sponsors & Collaborators

• Friedrich-Alexander-Universität Erlangen-Nürnberg: lead
• University of Erlangen-Nürnberg Medical School: collaborator
• University Hospital Erlangen: collaborator

Study Sites (1)

Deparment of Medicine 2 - Cardiology and Angiology, Friedrich-Alexander-Universität Erlangen-Nürnberg

Erlangen, 91054, Germany

Location

MeSH Terms

Conditions

Aortic Valve Stenosis; Heart Valve Diseases

Interventions

Auscultation

Condition Hierarchy (Ancestors)

Aortic Valve Disease; Heart Diseases; Cardiovascular Diseases; Ventricular Outflow Obstruction

Intervention Hierarchy (Ancestors)

Physical Examination; Diagnostic Techniques and Procedures; Diagnosis

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Physician

Study Record Dates

• First Submitted: May 5, 2024
• First Posted: May 8, 2024
• Study Start: March 9, 2023
• Primary Completion: May 22, 2024
• Study Completion: March 1, 2026
• Last Updated: December 24, 2025

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF, ANALYTIC CODE

Locations

DE (1)