Skip to main content
OpenTrials
Active, Not Recruiting

NCT Number: NCT07443969

Pre-Symptomatic Detection of Impending Decompensation in Heart Failure Through Voice Data

PRE-DETECT-HF is a prospective, single-arm observational study evaluating a voice-based machine learning algorithm for early detection of heart failure decompensation. 123 patients hospitalized for acute decompensated or de-novo heart failure will be enrolled across three sites in the Netherlands and Spain.

Patients make daily voice recordings via a smartphone app and answer symptom questions for 6 months. The algorithm analyzes voice patterns compared to a baseline recording at discharge. Treatment decisions are based on symptom data only; voice-based predictions are analyzed retrospectively after study completion.

The primary endpoint is sensitivity of the voice-based software in detecting heart failure deterioration, defined as heart failure hospitalization, or intensification of heart failure therapy. Secondary endpoints include app adherence, usability, and associations between voice data and blood biomarkers.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Zuyderland Medical Centre, Heerlen, Netherlands

Loading trial locations.

About this study

Heart failure decompensation is often detected too late by conventional symptom and weight monitoring, leaving insufficient time to intervene. Invasive alternatives such as implantable pulmonary artery pressure monitors are effective but require surgical implantation. Voice-based digital biomarkers offer a promising non-invasive approach, as fluid overload may produce detectable changes in vocal features.

Patients begin voice recordings during hospitalization while still volume overloaded. At home, patients record daily using standardized and variable text content. The voice-based algorithm extracts biomechanical vocal features and calculates a risk score.

Healthcare providers access a dashboard showing symptom-based notifications and may adjust therapy at their discretion. Voice-derived risk scores are withheld during the study and analyzed retrospectively.

Study visits occur at months 3 and 6 (in-clinic) and month 1 (telephone). Blood samples are collected at baseline, month 3, and month 6 for analysis of traditional (NT-proBNP, creatinine) and novel biomarkers. Usability and quality of life are assessed via questionnaires distributed throughout the study period.

Who can participate

Healthy volunteers accepted: No

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

Inclusion criteria

  • Informed consent provided
  • Currently hospitalized for acutely decompensated HF or de-novo HF
  • Age: 18 years and above

Exclusion criteria

  • Inability to provide consent
  • Pregnancy
  • Life-expectancy lower than 1 year due to a condition other than HF
  • Planned cardiac intervention within the next 6 months (e.g. valve replacement, bypass surgery)
  • Disabling mental diseases (e.g., Alzheimer's disease)
  • Symptoms mainly caused by chronic disease other than HF such as chronic obstructive pulmonary disease
  • Inability to use a smartphone or a tablet computer despite support by informal caregiver if required
  • Insufficient knowledge of the local language
  • Previous operations on organs involved in generation of voice (vocal tract, vocal folds, etc.)
  • Participation in another interventional study within 30 days of inclusion

Treatment and study plan

Daily Voice Recording and Symptom Monitoring

Other

Patients use the mobile app daily to record voice samples and answer symptom-related questions. Voice recordings are analyzed by a algorithm, which extracts vocal biomechanical features. Healthcare providers receive notifications based on symptom data only and may adjust therapy at their discretion. Voice-derived risk scores are not shared with clinicians during the study and are analyzed retrospectively after study completion.

Primary outcomes

  1. Sensitivity of Voice-Based Software in Detecting Heart Failure Deterioration

    Time frame: 6 month

    Sensitivity of the voice-based prediction in detecting heart failure deterioration, defined as heart failure-related hospitalization, or intensification of heart failure therapy due to worsening heart failure.

Secondary outcomes

  1. Alert Lead Time in Days

    Time frame: 6 month

    Median number of days prior to a heart failure deterioration event that the voice-based algorithm generates an alert, reported in days.

  2. Unexplained Alert Rate per Patient-Year

    Time frame: 6 month

    Number of voice-based alerts not associated with clinical deterioration, reported as a single rate per patient-year of follow-up.

  3. Adherence to voice-based monitoring

    Time frame: 6 month

    Adherence to voice-based monitoring in number and percentage of days with at least one transmitted voice recording.

  4. App Usability via In-App Questionnaires

    Time frame: 6 month

    User experiences, expectations, and acceptance assessed via standardized in-app questionnaires on a 7-point Likert scale.

  5. Quality of Life using the Kansas City Cardiomyopathy Questionnaire

    Time frame: 6 months

    Kansas City Cardiomyopathy Questionnaire (KCCQ) overall summary score (range 0-100, higher scores indicate better health status) at baseline, month 3, and month 6.

Other outcomes

  1. Laboratory results: creatinine, potassium, sodium, urea, NT-proBNP

    Time frame: 6 month

    Laboratory results: creatinine, potassium, sodium, urea, NT-proBNP

Sponsors and collaborators

Lead sponsor

Noah Labs

Industry

Collaborators

  • Hospital Clinic of Barcelona
  • Maastricht University
  • Zuyderland Medical Centre

Registry information

Official study title

Pre-Symptomatic Detection of Impending Decompensation in Heart Failure Through

Acronym: PRE-DETECT-HF

Important dates

Study start
2025
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.

Published trials that share one or more normalized conditions with this study.