RecruitingNot ApplicableNCT07113223

Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms (DECISION)

Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms: a Pragmatic Randomized Clinical Trial (DECISION)


Sponsor

Idoven 1903 S.L.

Enrollment

1,968 participants

Start Date

Jul 23, 2025

Study Type

INTERVENTIONAL

Conditions

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.


Eligibility

Min Age: 65 Years

Inclusion Criteria9

  • 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.

Exclusion Criteria3

  • Unwillingness or inability to sign the written informed consent.
  • Previous Heart Failure diagnosis.
  • Unavailability or suboptimal quality ECG.

Interventions

DEVICEWillem™ platform ECG assessment

AI-assisted ECG analysis via the Willem™ platform


Locations(5)

Hospital General Universitario Gregorio Marañón

Madrid, Spain

Hospital Universitario 12 de Octubre

Madrid, Spain

Primary Care: Gerencia Asistencial Atención Primaria Madrid

Madrid, Spain

Hospital Universitario Marqués de Valdecilla

Santander, Spain

Region Stockholm

Stockholm, Sweden

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NCT07113223


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