NCT06404437

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

Name: Clinical Trial NCT06404437
Creator: Friedrich-Alexander-Universität Erlangen-Nürnberg
Keywords: Aortic Valve Stenosis, Auscultation, diagnostic test, clinical trial, Germany

Friedrich-Alexander-Universität Erlangen-Nürnberg·ClinicalTrials.gov·diagnostic testRecruiting

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Study focus

Disease/Condition: Aortic Valve Stenosis
Drug/Device/Intervention: Auscultation
Study type: Observational
Intervention type: diagnostic test

Sponsor & location

Primary sponsor: Friedrich-Alexander-Universität Erlangen-Nürnberg
Location: Erlangen, Germany

Timeline & enrollment

Phase: N/A
Start date: Mar 09, 2023
End date: Oct 01, 2024
Enrollment: 100 participants

Primary outcome

Algorithm Performance

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.

ICD-10 classifications

Aortic (valve) stenosisAortic (valve) stenosis with insufficiencyCongenital stenosis of aortic valveStenosis of aortaRheumatic aortic stenosis

Data source

Registry: ClinicalTrials.gov
Trial ID: NCT06404437
Type: Non-Device Trial

About this record

Access comprehensive clinical trial information for NCT06404437 through Pure Global AI's free database. This phase not specified trial is sponsored by Friedrich-Alexander-Universität Erlangen-Nürnberg and is currently Recruiting. The study focuses on Aortic Valve Stenosis. Target enrollment is 100 participants.

This page provides complete trial specifications, intervention details, outcomes, and location information. Pure Global AI offers free access to ClinicalTrials.gov data, helping medical device and pharmaceutical companies navigate clinical research efficiently.