Actively Recruiting
Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms (DECISION)
Led by Idoven 1903 S.L. · Updated on 2026-03-31
1968
Participants Needed
5
Research Sites
57 weeks
Total Duration
On this page
Sponsors
I
Idoven 1903 S.L.
Lead Sponsor
F
Fundación para la Investigación Biomédica del Hospital 12 de Octubre
Collaborating Sponsor
AI-Summary
What this Trial Is About
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
Official Title
Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms (DECISION)
Who Can Participate
Eligibility Criteria
You may qualify if you...
-
Patients with Suspected HF (Group S):
- Able to understand and accept the study constraints and to provide informed consent (either themselves or a legal representative).
- Age over 65 years (i.e., 65 included).
- Presence of symptoms and/or signs typical of Heart Failure (defined by the European Society of Cardiology, ESC), including breathlessness (during activity or at rest, lying down, waking up at night needing to catch their breath), fatigue, swollen ankles/legs, and/or palpitations.
-
Patients at Risk of Heart Failure due to the presence of cardiovascular (Group R):
- Able to understand and accept the study constraints and to provide informed consent (either themselves or a legal representative).
- Age over 65 years (i.e., 65 included).
- Absence of symptoms and/or signs typical of Heart Failure (defined by the ESC), including breathlessness (during activity or at rest, lying down, waking up at night needing to catch their breath), fatigue, swollen ankles/legs, and/or palpitations.
- Presence of at least 1 ACC/AHA Heart Failure risk factor, including hypertension, cardiovascular disease (atrial fibrillation, coronary heart disease or stroke), diabetes, obesity, exposure to cardiotoxic agents, genetic variant for cardiomyopathy, or family history of cardiomyopathy that requires an ECG test for any reason in a primary care center or with an indication of a regular health examination where an ECG is included.
You will not qualify if you...
- Unwillingness or inability to sign the written informed consent.
- Previous Heart Failure diagnosis.
- Unavailability or suboptimal quality ECG.
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 5 locations
1
Hospital General Universitario Gregorio Marañón
Madrid, Spain
Actively Recruiting
2
Hospital Universitario 12 de Octubre
Madrid, Spain
Actively Recruiting
3
Primary Care: Gerencia Asistencial Atención Primaria Madrid
Madrid, Spain
Actively Recruiting
4
Hospital Universitario Marqués de Valdecilla
Santander, Spain
Actively Recruiting
5
Region Stockholm
Stockholm, Sweden
Actively Recruiting
Research Team
J
Juan Francisco Delgado Jiménez, MD, PhD
CONTACT
How is the study designed?
Study Type
INTERVENTIONAL
Masking
SINGLE
Allocation
RANDOMIZED
Model
PARALLEL
Primary Purpose
DIAGNOSTIC
Number of Arms
2
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