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Voice Analysis to Detect Pulmonary Arterial Pressure Changes in Heart Failure
Sponsor: Noah Labs
Summary
VAPP-HF is a prospective, multi-center, observational study assessing whether daily voice recordings analyzed by a machine learning algorithm can detect changes in pulmonary arterial (PA) pressure in heart failure patients with implanted PA pressure sensors (e.g., CardioMEMS, Cordella). Patients across three sites in Germany and the United States provide daily voice recordings via a mobile app for 12 weeks while continuing standard PA pressure monitoring and heart failure care. Voice data is analyzed retrospectively after study completion; no clinical decisions are based on voice analysis during the study. The primary endpoint is the sensitivity and specificity of the AI-based voice analysis in detecting PA pressure changes at defined thresholds.
Official title: Voice Analysis Using Artificial Intelligence to Detect Changes in Pulmonary Arterial Pressure in Patients With Heart Failure and an Implanted Pressure Sensor
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
60
Start Date
2024-12-12
Completion Date
2026-09
Last Updated
2026-03-02
Healthy Volunteers
No
Conditions
Interventions
Daily Voice Recording
Patients record daily voice samples (sustained vowels and a standardized reading passage) using the Noah Labs mobile app. PA pressure readings are collected daily per standard care using the implanted sensor. Voice recordings are analyzed retrospectively using machine learning algorithms after study completion.
Locations (3)
University of California, San Francisco (UCSF)
San Francisco, California, United States
BG Klinikum Unfallkrankenhaus Berlin, Dept. of Cardiology
Berlin, State of Berlin, Germany
University Hospital Frankfurt, Dept. of Cardiology and Angiology
Frankfurt, Germany