Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms (DECISION)
NCT07113223 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1968
Last updated 2026-03-31
Summary
The DECISION trial aims to evaluate the efficacy of an artificial intelligence (AI)-powered system, Willem™, for improving the detection of heart failure (HF) in primary care settings by interpreting electrocardiograms (ECGs). The study seeks to answer whether AI-assisted ECG interpretation enhances diagnostic accuracy and clinical outcomes compared to standard ECG evaluation in patients with suspected HF or those at high risk.
This multicenter, pragmatic, randomized clinical trial involves two groups: patients receiving AI-assisted ECG analysis and those undergoing standard ECG evaluation. The study's primary analysis will compare the diagnostic performance of AI-assisted ECG versus standard ECG using sensitivity, specificity, and predictive value metrics. Secondary analyses will evaluate healthcare resource utilization, clinical outcomes, and usability feedback from healthcare providers. Results will inform the potential integration of AI-assisted ECG in routine primary care workflows for earlier HF detection and better resource allocation.
Conditions
- Heart Failure
- Cardiovascular Risk Factors
Interventions
- DEVICE
-
Willem™ platform ECG assessment
AI-assisted ECG analysis via the Willem™ platform
Sponsors & Collaborators
-
Fundación para la Investigación Biomédica del Hospital 12 de Octubre
collaborator UNKNOWN -
Fundación para la Investigación Biomédica del Hospital Gregorio Maranon
collaborator OTHER -
Fundación para la Investigación e Innovación Biosanitaria de Atención Primaria de la Comunidad de Madrid (FIIBAP)
collaborator UNKNOWN -
Instituto de Investigación Marqués de Valdecilla
collaborator OTHER - collaborator OTHER
-
Region Stockholm
collaborator OTHER_GOV - collaborator INDUSTRY
-
Servicio Madrileno De Salud (SERMAS)
collaborator UNKNOWN -
Idoven 1903 S.L.
lead INDUSTRY
Study Design
- Allocation
- RANDOMIZED
- Purpose
- DIAGNOSTIC
- Masking
- SINGLE
- Model
- PARALLEL
Eligibility
- Min Age
- 65 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2025-07-23
- Primary Completion
- 2026-07-31
- Completion
- 2026-09-30
Countries
- Spain
- Sweden
Study Locations
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