Heart FailureDECISIONNCT07113223
Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms (DECISION)
A study testing Willem™ platform ECG assessment in people with Heart Failure and Cardiovascular Risk Factors, run by Idoven 1903 S.L. at 5 sites in 2 countries.
Trial 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). Read more about this study
- Who is it for?
- Ages 65 years and older
- Conditions the study is for
- Heart Failure, Cardiovascular Risk Factors
- What is being tested?
- Willem™ platform ECG assessment
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 1,968 participants
- Where
- 5 sitesin 2 countries
- Study dates
- 23 Jul 2025to Mar 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 65 years and older
- All sexes
- No healthy volunteers
- Older adult
Who may be able to join
- 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).
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- 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.
Who cannot join
- Unwillingness or inability to sign the written informed consent.
- Previous Heart Failure diagnosis.
- Unavailability or suboptimal quality ECG.
Trial locations and contacts
5 sites in 2 countries. Contact the study team or a site near you to ask about taking part.
5 sites in 2 countries
Spain4 sites, 4 recruiting
- Recruiting
Hospital General Universitario Gregorio Marañón
Madrid
Javier Bermejo Thomas, MD, PhD, javier.bermejo@salud.madrid.org
- Recruiting
Hospital Universitario 12 de Octubre
Madrid
Javier de Juan Bagudá, MD, PhD, javier.juan@salud.madrid.org
- Recruiting
Primary Care: Gerencia Asistencial Atención Primaria Madrid
Madrid
Sara Ares Blanco, MD, PhD, sara.ares@salud.madrid.org
- Recruiting
Hospital Universitario Marqués de Valdecilla
Santander
José María de la Torre, MD, PhD, josemariadela.torre@scsalud.es
Sweden1 site, 1 recruiting
- Recruiting
Region Stockholm
Stockholm
Jacob Andersson Emad, MD, PhD, jacob.andersson-emad@regionstockholm.se
About this study
Official title: 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.
Read the detailed description
Heart failure (HF) is a prevalent and underdiagnosed condition with high morbidity and mortality. Up to 50% of HF cases remain undetected, often due to subtle or absent symptoms in early stages. Early diagnosis is critical to improving outcomes, reducing hospitalizations, and alleviating healthcare costs. While ECGs are a cornerstone in HF diagnosis, their interpretation in primary care can be challenging, leading to diagnostic delays.
Artificial intelligence (AI) has emerged as a promising tool to support clinicians by enhancing ECG interpretation. In this regard, the DECISION trial evaluates the Willem™ platform, an AI-powered decision-support system, to improve HF detection. Willem™ uses a proprietary database to analyze ECGs, identifying over 80 cardiac patterns with high accuracy.
This study hypothesizes that AI-assisted ECG improves HF detection compared to standard ECG interpretation. Therefore, the main goal of the DECISION trial is to assess the diagnostic performance of AI-assisted ECG in detecting structural and functional cardiac abnormalities indicative of HF.
This multicenter, randomized trial includes primary care centers (PCCs) in Spain and Sweden, randomized into two groups: an intervention group using AI-assisted ECG and a control group using standard ECG. AI outputs will be available for physicians in the intervention group as supplementary information during decision making.
Primary outcomes focus on the accuracy of HF detection confirmed by transthoracic echocardiograms (TTE). Secondary outcomes include healthcare resource utilization, clinical outcomes, and physician satisfaction. The results will inform whether AI can be integrated into primary care workflows to optimize HF diagnosis and management.
- Conditions
- Heart Failure, Cardiovascular Risk Factors
- Being tested
- Willem™ platform ECG assessment
- Keywords
- Heart Failure, Artificial Intelligence, Electrocardiogram (ECG), Primary Care, Diagnostic Tools, Cardiology, Electrocardiography, Risk Stratification
- Medical subject headings
- Heart Failure
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Willem™ platform ECG assessmentDevice
AI-assisted ECG analysis via the Willem™ platform
| Study group | Role | What they receive |
|---|---|---|
| Experimental | Experimental | AI-assisted ECG analysis via the Willem™ platform Receives: Device: Willem™ platform ECG assessment |
| Comparator | No intervention | Standard ECG assessment |
What is being measured
The primary outcome is the main question the study is designed to answer.
Device performance in patients with suspected Heart Failure
To compare the diagnostic performance of clinicians using a decision-aid system based on AI-assisted ECG vs. standard ECG in patients with suspected Heart Failure (symptoms and/or signs of Heart Failure) in the primary care setting analyzing the frequency of patients without cardiac pattern alterations in the ECG, ending up with diagnosis of absence of HF (using the NT-proBNP for stratification and eventually echocardiography when needed) 7 days after screening with the cardiology service.
Measured: After performing the transthoracic echocardiography (TTE) in Visit 3 (7 days after screening)
Secondary outcomes (2)
Device performance in patients at cardiovascular risk but without Heart Failure symptoms
To compare the diagnostic performance of clinicians using a decision-aid system based on AI-assisted ECG vs. standard ECG in patients at risk but without Heart Failure symptoms in the primary care setting analyzing the frequency of patients with cardiac pattern alterations in the ECG, ending up with a diagnosis of HF (using the NT-proBNP for stratification and eventually echocardiography when needed) 7 days after screening with the cardiology service.
Measured: After performing the transthoracic echocardiography (TTE) in Visit 3 (7 days after screening)
Device performance at 6 months after ECG
To compare the clinical performance of a decision-aid system based on AI-assisted ECG vs standard ECG, in patients with symptoms and patients at risk of Heart Failure in the primary care setting analyzing the frequency of patients with cardiac pattern alterations in the ECG, ending up with diagnosis of HF (using the NT-proBNP for stratification and eventually echocardiography when needed) 6 months after screening with the cardiology service.
Measured: Six months after the ECG was performed
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Aug 2025
- Study start23 Jul 2025
- Primary completionSep 2026 (estimated)
- Study completionMar 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Heart FailureStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- Multicenter, randomized, two-arm parallel-group, controlled trial
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 1,968 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Idoven 1903 S.L.
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Hospital Universitario 12 de Octubre, Fundación para la Investigación Biomédica del Hospital Gregorio Maranon, Fundación para la Investigación e Innovación Biosanitaria de Atención Primaria de la Comunidad de Madrid (FIIBAP), Instituto de Investigación Marqués de Valdecilla, Karolinska Institutet, Region Stockholm, AstraZeneca, Servicio Madrileno De Salud (SERMAS)
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07113223
- Sponsor's protocol ID
- 24/062
- Other IDs
- 230225
- Acronym
- DECISION
- Status last verified
- Dec 2025
- First submitted
- 28 Jul 2025
- Last updated
- 20 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified Individual Participant Data (IPD) that underlies the results reported in the publication will be shared after publications of primary results upon request of investigators whose proposed research has received EC/IRB approval and after data use agreement.
Study at a glance
From the registry record, last updated by the sponsor on 20 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Determining Efficacy of an Artificial Intelligence-based System for Heart Failure Detection Through Interpretation of Electrocardiograms: a Pragmatic Randomized Clinical Trial (DECISION)
- ClinicalTrials.gov ID
- NCT07113223
- Acronym / sponsor ID
- DECISION / 24/062
- Conditions
- Heart Failure, Cardiovascular Risk Factors
- Keywords
- Heart Failure, Artificial Intelligence, Electrocardiogram (ECG), Primary Care, Diagnostic Tools, Cardiology, Electrocardiography, Risk Stratification
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 1,968 participants (estimated)
- Lead sponsor
- Idoven 1903 S.L.Industry (pharma, biotech, devices)
- Collaborators
- Hospital Universitario 12 de Octubre, Fundación para la Investigación Biomédica del Hospital Gregorio Maranon, Fundación para la Investigación e Innovación Biosanitaria de Atención Primaria de la Comunidad de Madrid (FIIBAP), Instituto de Investigación Marqués de Valdecilla, Karolinska Institutet, Region Stockholm, AstraZeneca, Servicio Madrileno De Salud (SERMAS)
- Study start
- 23 Jul 2025 (actual)
- Primary completion
- Sep 2026 (estimated)
- Study completion
- Mar 2027 (estimated)
- First posted
- 8 Aug 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Heart failure (HF) is a prevalent and underdiagnosed condition with high morbidity and mortality. Up to 50% of HF cases remain undetected, often due to subtle or absent symptoms in early stages. Early diagnosis is critical to improving outcomes, reducing hospitalizations, and alleviating healthcare costs. While ECGs are a cornerstone in HF diagnosis, their interpretation in primary care can be challenging, leading to diagnostic delays.
Artificial intelligence (AI) has emerged as a promising tool to support clinicians by enhancing ECG interpretation. In this regard, the DECISION trial evaluates the Willem™ platform, an AI-powered decision-support system, to improve HF detection. Willem™ uses a proprietary database to analyze ECGs, identifying over 80 cardiac patterns with high accuracy.
This study hypothesizes that AI-assisted ECG improves HF detection compared to standard ECG interpretation. Therefore, the main goal of the DECISION trial is to assess the diagnostic performance of AI-assisted ECG in detecting structural and functional cardiac abnormalities indicative of HF.
This multicenter, randomized trial includes primary care centers (PCCs) in Spain and Sweden, randomized into two groups: an intervention group using AI-assisted ECG and a control group using standard ECG. AI outputs will be available for physicians in the intervention group as supplementary information during decision making.
Primary outcomes focus on the accuracy of HF detection confirmed by transthoracic echocardiograms (TTE). Secondary outcomes include healthcare resource utilization, clinical outcomes, and physician satisfaction. The results will inform whether AI can be integrated into primary care workflows to optimize HF diagnosis and management.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (participant)
- Number of arms
- 2
- Model description
- Multicenter, randomized, two-arm parallel-group, controlled trial
| Arm | Type | Receives |
|---|---|---|
| Experimental | Experimental | Device: Willem™ platform ECG assessmentAI-assisted ECG analysis via the Willem™ platform |
| Comparator | No intervention | –Standard ECG assessment |
Who may qualify
- Ages
- 65 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Older adult
Key inclusion criteria (9 listed)
- Patients with Suspected HF (Group S):
- Patients at Risk of Heart Failure due to the presence of cardiovascular (Group R):
Key exclusion criteria (3 listed)
- Unwillingness or inability to sign the written informed consent.
- Previous Heart Failure diagnosis.
- Unavailability or suboptimal quality ECG.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Willem™ platform ECG assessmentAI-assisted ECG analysis via the Willem™ platform | Device | Experimental |
Primary outcome
Device performance in patients with suspected Heart Failure
Time frame: After performing the transthoracic echocardiography (TTE) in Visit 3 (7 days after screening)
To compare the diagnostic performance of clinicians using a decision-aid system based on AI-assisted ECG vs. standard ECG in patients with suspected Heart Failure (symptoms and/or signs of Heart Failure) in the primary care setting analyzing the frequency of patients without cardiac pattern alterations in the ECG, ending up with diagnosis of absence of HF (using the NT-proBNP for stratification and eventually echocardiography when needed) 7 days after screening with the cardiology service.
2 secondary outcomes
Device performance in patients at cardiovascular risk but without Heart Failure symptoms
Time frame: After performing the transthoracic echocardiography (TTE) in Visit 3 (7 days after screening)
Device performance at 6 months after ECG
Time frame: Six months after the ECG was performed
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Jul 2026.
- Individual participant dataSharing planned: Yes. De-identified Individual Participant Data (IPD) that underlies the results reported in the publication will be shared after publications of primary results upon request of investigators whose proposed research has received EC/IRB approval and after data use agreement.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
5 sites in 2 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Willem™ platform ECG assessment in people with Heart Failure and Cardiovascular Risk Factors, run by Idoven 1903 S.L. at 5 sites in 2 countries.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 9 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 20 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 5 sites in Spain, Sweden. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Juan Francisco Delgado Jiménez, MD, PhD (+34917792640, juan.delgado@salud.madrid.org), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Device performance in patients with suspected Heart Failure (time frame: After performing the transthoracic echocardiography (TTE) in Visit 3 (7 days after screening)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Jul 2026.