Pre-Symptomatic Detection of Impending Decompensation in Heart Failure Through Voice Data (PRE-DETECT-HF)

Pre-Symptomatic Detection of Impending Decompensation in Heart Failure Through

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.

Study Overview

• Status: Active, not recruiting
• Conditions: Heart Failure; Chronic Heart Failure; Chronic Heart Disease
• Intervention / Treatment: Other: Daily Voice Recording and Symptom Monitoring

Detailed Description

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.

• Study Type: Observational
• Enrollment (Estimated): 123

Contacts and Locations

Study Locations

• Netherlands
  • Heerlen, Netherlands, 6419
    • Zuyderland Medical Centre
  • Maastricht, Netherlands, 6202AZ
    • Maastricht University Medical Centre
• Spain
  • Barcelona, Spain, 08036
    • Hospital Clinic De Barcelona

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• 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.

Description

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

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

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; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
Alert Lead Time in Days	Median number of days prior to a heart failure deterioration event that the voice-based algorithm generates an alert, reported in days.	6 month
Unexplained Alert Rate per Patient-Year	Number of voice-based alerts not associated with clinical deterioration, reported as a single rate per patient-year of follow-up.	6 month
Adherence to voice-based monitoring	Adherence to voice-based monitoring in number and percentage of days with at least one transmitted voice recording.	6 month
App Usability via In-App Questionnaires	User experiences, expectations, and acceptance assessed via standardized in-app questionnaires on a 7-point Likert scale.	6 month
Quality of Life using the Kansas City Cardiomyopathy Questionnaire	Kansas City Cardiomyopathy Questionnaire (KCCQ) overall summary score (range 0-100, higher scores indicate better health status) at baseline, month 3, and month 6.	6 months

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Laboratory results: creatinine, potassium, sodium, urea, NT-proBNP	Laboratory results: creatinine, potassium, sodium, urea, NT-proBNP	6 month

Collaborators and Investigators

• Sponsor: Noah Labs
• Collaborators: Hospital Clinic of Barcelona; Maastricht University; Zuyderland Medical Centre

Study record dates

Study Major Dates

• Study Start (Actual): January 9, 2025
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): June 1, 2026

Study Registration Dates

• First Submitted: January 25, 2024
• First Submitted That Met QC Criteria: February 24, 2026
• First Posted (Actual): March 2, 2026

Study Record Updates

• Last Update Posted (Actual): March 2, 2026
• Last Update Submitted That Met QC Criteria: February 24, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Cardiovascular Diseases; Heart Diseases; Heart Failure
• Other Study ID Numbers: 2 (Other Identifier: Instituto Cardiovascular de Buenos Aires)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No