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

NCT07443969 | Active Not Recruiting

• 1 other identifier: 2
• Study Type: observational
• Target: 123
• Locations: 2 countries
• Sites: 3

Brief Summary

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.

Conditions

Heart Failure; Chronic Heart Disease; Chronic Heart Failure

Outcome Measures

Primary Outcomes (1)

• Sensitivity of Voice-Based Software in Detecting Heart Failure Deterioration

  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.

  6 month

Secondary Outcomes (5)

• Alert Lead Time in Days

  6 month

• Unexplained Alert Rate per Patient-Year

  6 month

• Adherence to voice-based monitoring

  6 month

• App Usability via In-App Questionnaires

  6 month

• Quality of Life using the Kansas City Cardiomyopathy Questionnaire

  6 months

Other Outcomes (1)

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

  6 month

Study Arms (1)

Voice-Based Monitoring

All participants receive standard heart failure care as per local standard of care plus daily voice monitoring via a mobile application. Patients record voice samples daily and answer symptom questions. Healthcare providers receive symptom-based notifications and may adjust therapy at their discretion. Voice-based risk scores are not used for clinical decisions during the study and are analyzed retrospectively.

Other: Daily Voice Recording and Symptom Monitoring

Interventions

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.

Voice-Based Monitoring

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adults aged 18 years or older hospitalized for acute decompensated heart failure or de-novo heart failure, irrespective of left ventricular ejection fraction, recruited from the wards of three participating hospitals in the Netherlands and Spain.

You may qualify if:

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

You may not qualify if:

• 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.)

Sponsors & Collaborators

• Noah Labs: lead
• Hospital Clinic of Barcelona: collaborator
• Maastricht University: collaborator
• Zuyderland Medical Centre: collaborator

Study Sites (3)

Zuyderland Medical Centre

Heerlen, 6419, Netherlands

Location

Maastricht University Medical Centre

Maastricht, 6202AZ, Netherlands

Location

Hospital Clínic de Barcelona

Barcelona, 08036, Spain

Location

Biospecimen

Retention: SAMPLES WITHOUT DNA

Blood samples collected at baseline, month 3, and month 6. One additional blood vial per draw stored at -70°C to -80°C for batch analysis of traditional and novel heart failure biomarkers.

MeSH Terms

Conditions

Heart Failure

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 25, 2024
• First Posted: March 2, 2026
• Study Start: January 9, 2025
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): June 1, 2026
• Last Updated: March 2, 2026

Record last verified: 2026-02

Data Sharing

• IPD Sharing: Will not share

Locations

ES (1); NL (2)