Acute Myocardial Infarction (AMI)ASSISTNCT06939738
Artificial Intelligence Scalable Solution for ST Myocardial Infarction
An observational study of Acute Myocardial Infarction (AMI), run by Idoven 1903 S.L. at 5 sites in 2 countries.
Trial summary
The ASSIST clinical study is an observational, multicenter study to assess the performance of a cloud-based and AI-powered electrocardiogram (ECG) analysis platform, named Willem™, developed to detect Acute Myocardial Infarction (AMI). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Acute Myocardial Infarction (AMI)
- How many people
- 489 participants
- Where
- 5 sitesin 2 countries
- Study dates
- 1 Apr 2025to 30 Jun 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adult patients with suspected Acute Coronary Syndrome (ACS) presenting to the emergency department and subsequently referred for angiography at the Catheterization Laboratory of the participating sites.
Who may be able to join
- Age ≥ 18 years;
- Available digitally stored 12-lead ECG traces prior to invasive coronary angiography;
- Available angiographic and clinical data.
Who cannot join
- ECGs with poor signal quality;
- Lack of digitally stored 12-lead ECG traces prior to coronary angiography;
- Previous coronary events (AMI, coronary revascularizations);
- Non-available clinical or angiographic data.
Trial locations and contacts
5 sites in 2 countries.
5 sites in 2 countries
Spain3 sites
Germans Trias i Pujol University Hospital
Barcelona, 08916
Hospital General Universitario Gregorio Marañón
Madrid, 28007
La Paz University Hospital
Madrid, 28046
Portugal2 sites
Unidade Local de Saúde de São José
Lisbon, 1169-056
Unidade Local de Saúde de Lisboa Ocidental
Lisbon, 1449-005
About this study
Official title: Artificial Intelligence Scalable Solution for ST Myocardial Infarction (ASSIST): Cross-sectional Study
The ASSIST clinical study is an observational, multicenter study to assess the performance of a cloud-based and AI-powered electrocardiogram (ECG) analysis platform, named Willem™, developed to detect Acute Myocardial Infarction (AMI).
The main objectives are to compare Willem™ performance to detect and triage ECG patterns associated with AMI compared with human ECG interpretation, and to assess the time periods for both approaches.
Read the detailed description
Delays in triage and diagnosis of patients presented with chest pain or other symptoms suggestive of Acute coronary syndrome (ACS) can be fatal. This study aims to improve those two aspects in acute ischemic disease care: reducing the delays to intervention and improving the accuracy of initial diagnosis, which are of paramount importance in cases of ACS, especially in ST-elevation myocardial infarction (STEMI). The former plays a critical role in minimizing in-hospital mortality rates, which have been shown to decrease proportionally with reduction of times to intervention. The latter relies on a correct interpretation of the ECG, first-line diagnostic tool in the assessment of patients with suspected ACS.
The current standard of care for ACS includes a 12-lead ECG that should be performed within the first 10 minutes from the first medical contact. The ECG must be interpreted by a qualified physician, who will alert the on-call cardiologist to confirm or not the activation of the "infarction code", based on the ECG and clinical presentation. Such activation will mainly entail immediate transfer of the patient to the nearest hospital with the possibility of emergency coronary angiography (if not present in the initial institution), and eventual percutaneous coronary intervention (PCI). Regarding the diagnosis of Acute Myocardial Infarction (AMI), an accurate and rapid interpretation of the first ECG is critical for the differential diagnosis between STEMI, NSTEMI or unstable angina; and follow the proper standard of care guidelines. The largest delays occurs between the first ECG and the transportation for the cardiac catheterization laboratory, which has prognostic implications.
In recent years, automatic digital tools based on artificial intelligence (AI) have been proposed as a solution to support physicians in the ECG interpretation, reducing their workload and time-to-diagnosis, suggesting the beneficial impact of AI-platforms for accurate diagnosis of AMI. In this setting, the AI-platforms should be able to automatically detect ECG patterns linked to unfavorable coronary anatomy and poor outcomes. It is also essential to have the capacity to identify more subtle ECG patterns, not obvious during physicians' interpretation, but indicating high-risk coronary anatomy. Additionally, the platform should assist the prediction of most severe coronary lesions, especially obstructive stenosis. This ability to detect coronary lesions could be useful in preventing unnecessary or premature activation of the catheterization laboratory, mainly in NSTEMI setting.
The ASSIST clinical study is a cross-sectional, multicenter study aiming to collect data to develop the Willem™ platform, an AI-based tool for ECG analysis. This plataform could improve the accuracy for AMI diagnosis, particularly the differentiation between STEMI and NSTEMI, and early identification of patients with Occlusion Myocardial Infarction (OMI).
- Conditions
- Acute Myocardial Infarction (AMI)
- Keywords
- Acute Myocardial Infarction (AMI), STEMI, NSTEMI, Occlusion Myocardial Infarction (OMI), AI-based ECG analysis
- Medical subject headings
- ST Elevation Myocardial Infarction, Non-ST Elevated Myocardial Infarction
What is being measured
The primary outcome is the main question the study is designed to answer.
Device performance
Assessment of Willem™ diagnostic performance to detect Acute Myocardial Infarction (AMI) based on ECG analysis. The diagnostic performance metrics and their measurement units will be:
- Accuracy, Sensitivity, and Specificity (%)
- Positive Predictive Value (PPV) and Negative Predictive Value (NPV) (%)
- F1-score (score from 0.0 to 1.0)
Measured: At the time of enrolment and throughout the baseline visit (single study visit)
Secondary outcomes (1)
Time assessment
Assessment of the time needed for AMI diagnosis and for intervention (e.g. door-to-balloon time)
Measured: At the time of enrolment and throughout the baseline visit (single study visit)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Apr 2025
- Study start1 Apr 2025
- Primary completion15 Jun 2026
- Study completion30 Jun 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute Myocardial Infarction (AMI)Studies 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
- Observational
- Observational model
- Case only
- Time perspective
- Cross-sectional
- Enrolment
- 489 participants (actual)
Sponsor and investigators
- Lead sponsor
- Idoven 1903 S.L.
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- Alfonso Jurado, MD, PhD, Principal investigator, La Paz University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06939738
- Sponsor's protocol ID
- ASSIST_01
- Acronym
- ASSIST
- Status last verified
- Jul 2026
- First submitted
- 15 Apr 2025
- Last updated
- 20 Jul 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided: Grouped data corresponding to the clinical study objectives may be published at the end of the study. All data collected throughout the study would be included, since all clinical variables are collected per the standard of care and all relate to the two study objectives.
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
- Artificial Intelligence Scalable Solution for ST Myocardial Infarction (ASSIST): Cross-sectional Study
- ClinicalTrials.gov ID
- NCT06939738
- Acronym / sponsor ID
- ASSIST / ASSIST_01
- Conditions
- Acute Myocardial Infarction (AMI)
- Keywords
- Acute Myocardial Infarction (AMI), STEMI, NSTEMI, Occlusion Myocardial Infarction (OMI), AI-based ECG analysis
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 489 participants (actual)
- Lead sponsor
- Idoven 1903 S.L.Industry (pharma, biotech, devices)
- Study start
- 1 Apr 2025 (actual)
- Primary completion
- 15 Jun 2026 (actual)
- Study completion
- 30 Jun 2026 (actual)
- First posted
- 23 Apr 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 ASSIST clinical study is an observational, multicenter study to assess the performance of a cloud-based and AI-powered electrocardiogram (ECG) analysis platform, named Willem™, developed to detect Acute Myocardial Infarction (AMI).
The main objectives are to compare Willem™ performance to detect and triage ECG patterns associated with AMI compared with human ECG interpretation, and to assess the time periods for both approaches.
Detailed description
Delays in triage and diagnosis of patients presented with chest pain or other symptoms suggestive of Acute coronary syndrome (ACS) can be fatal. This study aims to improve those two aspects in acute ischemic disease care: reducing the delays to intervention and improving the accuracy of initial diagnosis, which are of paramount importance in cases of ACS, especially in ST-elevation myocardial infarction (STEMI). The former plays a critical role in minimizing in-hospital mortality rates, which have been shown to decrease proportionally with reduction of times to intervention. The latter relies on a correct interpretation of the ECG, first-line diagnostic tool in the assessment of patients with suspected ACS.
The current standard of care for ACS includes a 12-lead ECG that should be performed within the first 10 minutes from the first medical contact. The ECG must be interpreted by a qualified physician, who will alert the on-call cardiologist to confirm or not the activation of the "infarction code", based on the ECG and clinical presentation. Such activation will mainly entail immediate transfer of the patient to the nearest hospital with the possibility of emergency coronary angiography (if not present in the initial institution), and eventual percutaneous coronary intervention (PCI). Regarding the diagnosis of Acute Myocardial Infarction (AMI), an accurate and rapid interpretation of the first ECG is critical for the differential diagnosis between STEMI, NSTEMI or unstable angina; and follow the proper standard of care guidelines. The largest delays occurs between the first ECG and the transportation for the cardiac catheterization laboratory, which has prognostic implications.
In recent years, automatic digital tools based on artificial intelligence (AI) have been proposed as a solution to support physicians in the ECG interpretation, reducing their workload and time-to-diagnosis, suggesting the beneficial impact of AI-platforms for accurate diagnosis of AMI. In this setting, the AI-platforms should be able to automatically detect ECG patterns linked to unfavorable coronary anatomy and poor outcomes. It is also essential to have the capacity to identify more subtle ECG patterns, not obvious during physicians' interpretation, but indicating high-risk coronary anatomy. Additionally, the platform should assist the prediction of most severe coronary lesions, especially obstructive stenosis. This ability to detect coronary lesions could be useful in preventing unnecessary or premature activation of the catheterization laboratory, mainly in NSTEMI setting.
The ASSIST clinical study is a cross-sectional, multicenter study aiming to collect data to develop the Willem™ platform, an AI-based tool for ECG analysis. This plataform could improve the accuracy for AMI diagnosis, particularly the differentiation between STEMI and NSTEMI, and early identification of patients with Occlusion Myocardial Infarction (OMI).
Study design
- Observational model
- Case only
- Time perspective
- Cross-sectional
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients with suspected Acute Coronary Syndrome (ACS) presenting to the emergency department and subsequently referred for angiography at the Catheterization Laboratory of the participating sites.
Key inclusion criteria (3 listed)
- Age ≥ 18 years;
- Available digitally stored 12-lead ECG traces prior to invasive coronary angiography;
- Available angiographic and clinical data.
Key exclusion criteria (4 listed)
- ECGs with poor signal quality;
- Lack of digitally stored 12-lead ECG traces prior to coronary angiography;
- Previous coronary events (AMI, coronary revascularizations);
- Non-available clinical or angiographic data.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Device performance
Time frame: At the time of enrolment and throughout the baseline visit (single study visit)
Assessment of Willem™ diagnostic performance to detect Acute Myocardial Infarction (AMI) based on ECG analysis. The diagnostic performance metrics and their measurement units will be: * Accuracy, Sensitivity, and Specificity (%) * Positive Predictive Value (PPV) and Negative Predictive Value (NPV) (%) * F1-score (score from 0.0 to 1.0)
1 secondary outcome
Time assessment
Time frame: At the time of enrolment and throughout the baseline visit (single study visit)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Jul 2026.
- Individual participant dataSharing planned: Undecided. Grouped data corresponding to the clinical study objectives may be published at the end of the study. All data collected throughout the study would be included, since all clinical variables are collected per the standard of care and all relate to the two study objectives.
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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. This study is not recruiting at the moment.
Alfonso Jurado, MD, PhD principal investigator
La Paz University Hospital
5 sites in 2 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Acute Myocardial Infarction (AMI), 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 3 inclusion and 4 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: finished, 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, Portugal. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Device performance (time frame: At the time of enrolment and throughout the baseline visit (single study visit)). 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.