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NCT Number: NCT07443670

Voice Analysis to Detect Pulmonary Arterial Pressure Changes in Heart Failure

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.

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

BG Klinikum Unfallkrankenhaus Berlin, Dept. of Cardiology, Berlin, State of Berlin, Germany

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About this study

Implanted PA pressure sensors enable early detection of heart failure decompensation but are costly and invasive. Fluid retention in heart failure may affect the vocal apparatus, producing measurable voice changes that could serve as a non-invasive alternative for monitoring pulmonary congestion.

Participants record daily voice samples consisting of sustained vowel sounds and a standardized reading passage via the Noah Labs mobile app. PA pressure readings are collected daily per standard care. Voice recordings and clinical data are analyzed retrospectively using classical machine learning and deep learning approaches. No additional clinical visits are required.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 18 years or older
  • Successful implantation of a PA pressure sensor and monitored by a participating study center
  • Willingness to record a short predefined text daily for 3 months using a smartphone or tablet
  • Ability to comfortably read aloud the study passage in English or German
  • Written informed consent obtained

Exclusion criteria

  • Pregnant, breastfeeding, or unwilling to practice birth control during participation
  • Condition that in the opinion of the investigator would compromise patient safety or data quality
  • Pathological voice changes due to surgery or injury
  • Planned invasive cardiac procedures during the study period
  • COPD requiring home oxygen therapy
  • Chronic kidney disease requiring dialysis
  • Cognitive dysfunction limiting ability to perform daily voice recording
  • Inability to read English or German
  • Physical inability to use the recording device

Treatment and study plan

Daily Voice Recording

Other

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.

Primary outcomes

  1. Sensitivity of AI Voice Analysis in Detecting PA Pressure Changes

    Time frame: 12 weeks

    Sensitivity and specificity of the AI-based voice analysis algorithm in detecting pulmonary arterial pressure changes at pre-specified thresholds.

Secondary outcomes

  1. orrelation Between Voice Predictions and Clinical Events

    Time frame: 12 weeks

    Correlation between voice biomarker predictions and clinical outcomes including hospitalizations and diuretic adjustments.

  2. Predictive Accuracy of Machine Learning Models

    Time frame: 12 weeks

    Predictive accuracy of machine learning models for early detection of signs of heart failure decompensation, reported as area under the ROC curve.

  3. Adherence to Daily Voice Recording

    Time frame: 12 weeks

    Percentage of days with at least one transmitted voice recording over the 12-week study period.

Study contacts

Contact information is provided by the study sponsor or research team.

Leonhard Riehle, MD

CONTACT

[email protected]

+491715547970

Sponsors and collaborators

Lead sponsor

Noah Labs

Industry

Registry information

Official study title

Voice Analysis Using Artificial Intelligence to Detect Changes in Pulmonary Arterial Pressure in Patients With Heart Failure and an Implanted Pressure Sensor

Acronym: VAPP-HF

Important dates

Study start
2024
Primary completion
2026
Study completion
2026
First posted
Mar 2, 2026
Registry last updated
Mar 2, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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