Tests an AI heart tool reading ECGs to find heart failure early
Tests an AI system reading heart tracings to detect heart failure in older adults.
Plain-language title generated from the registry record
Registry title: Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms (DECISION)
Key facts
- Where
- Stockholm, SwedenSee the site
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for people aged 65 or older who have signs of heart failure, or who have no signs but have at least 1 heart failure risk factor, and who need an ECG at a primary care center.
- Age
- 65 years or older (65 included).
- Sex
- All sexes can join.
- Disease stage
- Two groups: people with typical heart failure symptoms or signs (such as breathlessness, tiredness, swollen ankles or legs, palpitations), or people without these symptoms who have at least 1 heart failure risk factor (such as high blood pressure, heart or blood vessel disease, diabetes, obesity).
- Earlier treatment
- People with a previous heart failure diagnosis cannot join.
Main reasons for not taking part
- Previous heart failure diagnosis
- Unwilling or unable to sign the written informed consent
- No ECG available, or ECG of poor quality
Read by machine on 9 November 2026.
Where in Sweden
- Region StockholmStockholm, SwedenTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Idoven 1903 S.L.
- Trial code
- NCT07113223
- Record updated
- 4 November 2026
- Original description
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.Read full original descriptionShow less
Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms: a Pragmatic Randomized Clinical Trial (DECISION)
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.
Inclusion: 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: Previous Heart Failure diagnosis; Unwillingness or inability to sign the written informed consent; Unavailability or suboptimal quality ECG.