Voice Analysis to Detect Pulmonary Arterial Pressure Changes in Heart Failure

Condition(s) studied

Investigational drug(s) / intervention(s)

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.

Study 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.

Eligibility

Primary outcome measure(s)

• Sensitivity of AI Voice Analysis in Detecting PA Pressure Changes — 12 weeks
  Sensitivity and specificity of the AI-based voice analysis algorithm in detecting pulmonary arterial pressure changes at pre-specified thresholds.

Trial sites (3)

Other trials for the same condition