Acute Coronary SyndromesECG-IANCT07810686
Smartphone AI Assistance for Prehospital ECG Interpretation
A study testing Smartphone large language model assistance (GPT-4o, version-locked) in people with Acute Coronary Syndromes and ST Elevation Myocardial Infarction, run by École Supérieure de Soins Ambulanciers - College of Higher Education in Prehospital Care at 1 site in Switzerland.
Trial summary
Prehospital providers interpret 12-lead electrocardiograms (ECGs) under time pressure and without immediate expert support. Missed acute coronary occlusion - occlusion myocardial infarction (OMI) - delays reperfusion, while false positive interpretations trigger unnecessary catheterization laboratory activations. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Acute Coronary Syndromes, ST Elevation Myocardial Infarction, Non-ST Elevated Myocardial Infarction
- What is being tested?
- Smartphone large language model assistance (GPT-4o, version-locked)
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 144 participants
- Where
- 1 siteSwitzerland
- Study dates
- 2 Sep 2026to 30 Nov 2026
- 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 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Prehospital care provider practising in French-speaking Switzerland
- Any level of training: emergency medical technician, paramedic (ES), nurse (ES/HES) in prehospital emergency care, or prehospital emergency physician
- Electronic informed consent signed before randomization
Who cannot join
- Cardiologist
- Any person not practising in prehospital care
- Insufficient command of written French to answer the vignettes reliably
- Refusal to participate or withdrawal of consent
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Switzerland1 site, 1 recruiting
- Recruiting
Caserne des pompiers de Morat (Swiss French-speaking prehospital clinical research conference)
Murten/Morat, Canton of Fribourg, 3280
Laurent Bourgeois, +41 22 388 34 04, laurent.bourgeois@edu.ge.ch
About this study
Official title: AI & Prehospital ECG Analysis: A Randomized Controlled Trial of a Smartphone Large Language Model for Occlusion Myocardial Infarction Detection by Prehospital Providers
Prehospital providers interpret 12-lead electrocardiograms (ECGs) under time pressure and without immediate expert support. Missed acute coronary occlusion - occlusion myocardial infarction (OMI) - delays reperfusion, while false positive interpretations trigger unnecessary catheterization laboratory activations. Multimodal large language models (LLMs) available on any smartphone can now analyze a photographed ECG, and prehospital providers have begun using them spontaneously. No randomized trial has evaluated whether this practice improves diagnostic performance.
This randomized controlled trial compares the diagnostic performance of prehospital providers interpreting ECG clinical vignettes with and without mandatory assistance from a single, version-locked smartphone large language model. Participants - paramedics, emergency medical technicians, nurses and physicians practicing in prehospital care in French-speaking Switzerland - are randomized 1:1 on a dedicated digital platform and answer 14 clinical vignettes presented in individually randomized order. Each vignette is built around a real, anonymized 12-lead ECG obtained during routine clinical care.
The primary outcome is the proportion of vignettes for which the participant correctly identifies the presence or absence of an OMI. Secondary outcomes are sensitivity, specificity, and the accuracy of the prehospital priority decision level.
Read the detailed description
Design and setting. Two-arm parallel-group randomized controlled trial conducted on a dedicated digital platform. Phase 1 takes place during a single in-person session at the Swiss French-speaking prehospital clinical research conference (Morat, Switzerland, 2 September 2026). Phase 2 extends recruitment to prehospital emergency services across French-speaking Switzerland (September to November 2026) using an identical standardized protocol.
Randomization. Individual 1:1 allocation performed automatically by the platform using permuted blocks of variable size (4 to 6), without stratification, after the demographic questionnaire and before the first vignette. Allocation cannot be changed once assigned. The presentation order of the 14 vignettes is independently randomized for each participant, which neutralizes position effects and prevents copying between neighbouring participants.
Intervention. Participants allocated to the intervention arm must consult the study-imposed large language model for every vignette before submitting their answer; the platform locks the submit button until use of the tool is confirmed. A single model (OpenAI GPT-4o) in an API version locked for the entire study is used by all participants, with a standardized, non-modifiable prompt identical for every participant and every vignette. Participants cannot add text, ask follow-up questions, or provide additional clinical context. Exposure to the tool is mandatory, but adherence to its interpretation is not: participants remain free to base their final answer on their own clinical reasoning. Control participants interpret the same ECGs unaided, with smartphones turned face down and out of reach.
Reference standard. For each vignette, the expected answers were defined a priori by the study cardiologist and locked, with any subsequent modification time-stamped in the platform audit log. The reference standard is the answer expected of a prehospital provider at the point of care, anchored on coronary angiography wherever angiography is discriminant. For non-ischaemic mimics, the expected answer depends on whether the acute presentation allows the condition to be distinguished from a coronary occlusion: it does not for the Takotsubo case included in the study, whose expected answer is therefore "yes", whereas acute pericarditis, being usually recognizable, has an expected answer of "no". This pre-specified departure from a purely angiographic standard is reported as such, and the primary analysis is repeated in a sensitivity analysis in which all mimics are classified as non-OMI.
Blinding. Participants and investigators cannot be masked. The statistician conducting the primary analysis receives coded group labels only, and the allocation key is released after database lock and approval of the statistical analysis plan.
Statistical analysis. Mixed-effects logistic regression with correct OMI identification at vignette level as the dependent variable, arm as the main fixed effect, grouped ECG category as a fixed covariate, and random intercepts for participant and for vignette. Intention-to-treat, alpha 0.05 two-sided. The target is 130 evaluable participants (65 per arm), giving 80% power to detect an absolute increase from 0.65 to 0.80 with an intraclass correlation up to approximately 0.43. Allowing for approximately 10% of sessions to be abandoned before completion, planned enrollment is 144 (72 per arm).
ECG material. All tracings originate from routine clinical care at the Geneva University Hospitals, were selected by a cardiologist to cover predefined electrocardiographic categories, and were anonymized at source before transmission to the research team. No patient is enrolled, followed or contacted, and the research team holds no key allowing re-identification.
Pilot. A technical pilot involving a small number of prehospital providers was conducted before the study start date to test the platform. Pilot sessions took place outside the standardized study conditions and are identified in the database by a dedicated centre code; their data are excluded from all analyses, as pre-specified in the protocol.
- Conditions
- Acute Coronary Syndromes, ST Elevation Myocardial Infarction, Non-ST Elevated Myocardial Infarction, Myocardial Infarction (MI), Diagnostic Errors
- Being tested
- Smartphone large language model assistance (GPT-4o, version-locked)
- Keywords
- artificial intelligence, large language model, GPT-4o, electrocardiography, occlusion myocardial infarction, OMI, prehospital care, paramedics, emergency medical services, clinical decision support, diagnostic accuracy, clinical vignettes, Switzerland, French-speaking Switzerland, prehospital providers
- Medical subject headings
- Acute Coronary Syndrome, ST Elevation Myocardial Infarction, Non-ST Elevated Myocardial Infarction, Myocardial Infarction
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Smartphone large language model assistance (GPT-4o, version-locked)Diagnostic test
Also called ChatGPT, gpt-4o-2024-08-06
The platform transmits the ECG image to a single large language model (OpenAI GPT-4o, API snapshot gpt-4o-2024-08-06), locked for the entire study, together with a standardised prompt identical for all participants and all vignettes: "I am on an urgent prehospital call with a patient who presents this ECG. Analyse it and tell me what you think." Participants cannot modify the prompt, ask follow-up questions or provide additional clinical context. The model version and system fingerprint returned by the API are recorded for every call. The model's interpretation is displayed within the vignette. Use of the tool is mandatory; adherence to its interpretation is not.
| Study group | Role | What they receive |
|---|---|---|
| Control: unaided ECG interpretation | No intervention | Participants interpret each of the 14 ECG vignettes without any assistance. Smartphones are turned face down and out of reach for the duration of the session. No intervention is administered. |
| AI-assisted ECG interpretation | Experimental | Participants must consult the study-imposed large language model for every vignette before submitting their answer. The platform locks the submit button until use of the tool is confirmed. Participants remain free not to follow the interpretation produced by the model and may base their final answer on their own clinical reasoning. Receives: Diagnostic Test: Smartphone large language model assistance (GPT-4o, version-locked) |
What is being measured
The primary outcome is the main question the study is designed to answer.
Proportion of vignettes with correct identification of occlusion myocardial infarction (OMI) status
For each of the 14 vignettes, the participant answers a binary question: "At this stage of care, is an OMI (acute coronary occlusion) likely? Yes / No". Responses are scored against a reference standard defined a priori, vignette by vignette, by the study cardiologist and locked before data collection. This reference standard is the answer expected of a prehospital provider at the point of care, anchored on coronary angiography wherever angiography is discriminant. For non-ischaemic mimics the expected answer depends on whether the acute presentation allows the condition to be distinguished from a coronary occlusion: it does not for the Takotsubo case (expected answer "yes"), whereas acute pericarditis is usually recognisable (expected answer "no"). This pre-specified departure from a purely angiographic standard is reported as such, and the analysis is repeated in a sensitivity analysis classifying all mimics as non-OMI. The outcome is the proportion of correctly classified vignettes
Measured: Single study session, approximately 90 minutes; 14 vignettes per participant
Secondary outcomes (3)
Sensitivity of OMI detection
Proportion of correctly identified OMI among vignettes whose expected answer is "yes", compared between arms. Analysed by mixed-effects logistic regression restricted to these vignettes, with arm as fixed effect and a random intercept per participant.
Measured: Single study session, approximately 90 minutes
Specificity of OMI detection
Proportion of correctly identified non-OMI among vignettes whose expected answer is "no" (non-occlusive ischaemia, indeterminate ischaemia, recognisable non-ischaemic mimics, normal or non-specific ECGs), compared between arms. Same modelling approach as for sensitivity.
Measured: Single study session, approximately 90 minutes
Accuracy of the prehospital priority decision level
Proportion of vignettes for which the participant selects the correct prehospital priority decision level, on a pre-specified five-level scale ranging from high-risk acute coronary syndrome with activation of the STEMI pathway to clearly non-cardiac symptoms. The expected level is defined a priori for each vignette and locked before data collection.
Measured: Single study session, approximately 90 minutes
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Sep 2026
- Study start2 Sep 2026
- Primary completion30 Nov 2026 (estimated)
- Study completion30 Nov 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute Coronary SyndromesStudies 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
- Two parallel groups of prehospital providers, randomized 1:1 at the individual level. Each participant completes a single session comprising 14 ECG clinical vignettes presented in an individually randomized order. The control group interprets the ECGs unaided; the intervention group must consult a study-imposed smartphone large language model for every vignette before submitting an answer.
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 144 participants (estimated)
Sponsor and investigators
- Lead sponsor
- École Supérieure de Soins Ambulanciers - College of Higher Education in Prehospital Care
- Sponsor type
- University, hospital or other
- Collaborators
- University Hospital, Geneva, Swissrescue.ch, Website for Prehospital Healthcare Providers, Les Pontins, Switzerland
- Responsible party
- Principal investigator, Laurent Bourgeois, École Supérieure de Soins Ambulanciers - College of Higher Education in Prehospital Care
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07810686
- Sponsor's protocol ID
- ECG-IA-2026
- Other IDs
- 2026-01430
- Acronym
- ECG-IA
- Status last verified
- Sep 2026
- First submitted
- 27 Aug 2026
- Last updated
- 9 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Fully anonymised individual participant data - responses to all vignettes, demographic variables and platform-generated technical variables - will be deposited in an open repository (Zenodo or OSF) at the time of publication, in accordance with FAIR principles. The ECG tracings themselves are excluded from this deposit: they originate from routine clinical care at the Geneva University Hospitals, which authorise their use for this study only and do not permit transmission to third parties. Requests concerning the tracings must be addressed to the Geneva University Hospitals.
Study at a glance
From the registry record, last updated by the sponsor on 9 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI & Prehospital ECG Analysis: A Randomized Controlled Trial of a Smartphone Large Language Model for Occlusion Myocardial Infarction Detection by Prehospital Providers
- ClinicalTrials.gov ID
- NCT07810686
- Acronym / sponsor ID
- ECG-IA / ECG-IA-2026
- Conditions
- Acute Coronary Syndromes, ST Elevation Myocardial Infarction, Non-ST Elevated Myocardial Infarction, Myocardial Infarction (MI), Diagnostic Errors
- Keywords
- artificial intelligence, large language model, GPT-4o, electrocardiography, occlusion myocardial infarction, OMI, prehospital care, paramedics
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 144 participants (estimated)
- Lead sponsor
- École Supérieure de Soins Ambulanciers - College of Higher Education in Prehospital CareUniversity, hospital or other
- Collaborators
- University Hospital, Geneva, Swissrescue.ch, Website for Prehospital Healthcare Providers, Les Pontins, Switzerland
- Study start
- 2 Sep 2026 (actual)
- Primary completion
- 30 Nov 2026 (estimated)
- Study completion
- 30 Nov 2026 (estimated)
- First posted
- 9 Sep 2026 (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.
Prehospital providers interpret 12-lead electrocardiograms (ECGs) under time pressure and without immediate expert support. Missed acute coronary occlusion - occlusion myocardial infarction (OMI) - delays reperfusion, while false positive interpretations trigger unnecessary catheterization laboratory activations. Multimodal large language models (LLMs) available on any smartphone can now analyze a photographed ECG, and prehospital providers have begun using them spontaneously. No randomized trial has evaluated whether this practice improves diagnostic performance.
This randomized controlled trial compares the diagnostic performance of prehospital providers interpreting ECG clinical vignettes with and without mandatory assistance from a single, version-locked smartphone large language model. Participants - paramedics, emergency medical technicians, nurses and physicians practicing in prehospital care in French-speaking Switzerland - are randomized 1:1 on a dedicated digital platform and answer 14 clinical vignettes presented in individually randomized order. Each vignette is built around a real, anonymized 12-lead ECG obtained during routine clinical care.
The primary outcome is the proportion of vignettes for which the participant correctly identifies the presence or absence of an OMI. Secondary outcomes are sensitivity, specificity, and the accuracy of the prehospital priority decision level.
Detailed description
Design and setting. Two-arm parallel-group randomized controlled trial conducted on a dedicated digital platform. Phase 1 takes place during a single in-person session at the Swiss French-speaking prehospital clinical research conference (Morat, Switzerland, 2 September 2026). Phase 2 extends recruitment to prehospital emergency services across French-speaking Switzerland (September to November 2026) using an identical standardized protocol.
Randomization. Individual 1:1 allocation performed automatically by the platform using permuted blocks of variable size (4 to 6), without stratification, after the demographic questionnaire and before the first vignette. Allocation cannot be changed once assigned. The presentation order of the 14 vignettes is independently randomized for each participant, which neutralizes position effects and prevents copying between neighbouring participants.
Intervention. Participants allocated to the intervention arm must consult the study-imposed large language model for every vignette before submitting their answer; the platform locks the submit button until use of the tool is confirmed. A single model (OpenAI GPT-4o) in an API version locked for the entire study is used by all participants, with a standardized, non-modifiable prompt identical for every participant and every vignette. Participants cannot add text, ask follow-up questions, or provide additional clinical context. Exposure to the tool is mandatory, but adherence to its interpretation is not: participants remain free to base their final answer on their own clinical reasoning. Control participants interpret the same ECGs unaided, with smartphones turned face down and out of reach.
Reference standard. For each vignette, the expected answers were defined a priori by the study cardiologist and locked, with any subsequent modification time-stamped in the platform audit log. The reference standard is the answer expected of a prehospital provider at the point of care, anchored on coronary angiography wherever angiography is discriminant. For non-ischaemic mimics, the expected answer depends on whether the acute presentation allows the condition to be distinguished from a coronary occlusion: it does not for the Takotsubo case included in the study, whose expected answer is therefore "yes", whereas acute pericarditis, being usually recognizable, has an expected answer of "no". This pre-specified departure from a purely angiographic standard is reported as such, and the primary analysis is repeated in a sensitivity analysis in which all mimics are classified as non-OMI.
Blinding. Participants and investigators cannot be masked. The statistician conducting the primary analysis receives coded group labels only, and the allocation key is released after database lock and approval of the statistical analysis plan.
Statistical analysis. Mixed-effects logistic regression with correct OMI identification at vignette level as the dependent variable, arm as the main fixed effect, grouped ECG category as a fixed covariate, and random intercepts for participant and for vignette. Intention-to-treat, alpha 0.05 two-sided. The target is 130 evaluable participants (65 per arm), giving 80% power to detect an absolute increase from 0.65 to 0.80 with an intraclass correlation up to approximately 0.43. Allowing for approximately 10% of sessions to be abandoned before completion, planned enrollment is 144 (72 per arm).
ECG material. All tracings originate from routine clinical care at the Geneva University Hospitals, were selected by a cardiologist to cover predefined electrocardiographic categories, and were anonymized at source before transmission to the research team. No patient is enrolled, followed or contacted, and the research team holds no key allowing re-identification.
Pilot. A technical pilot involving a small number of prehospital providers was conducted before the study start date to test the platform. Pilot sessions took place outside the standardized study conditions and are identified in the database by a dedicated centre code; their data are excluded from all analyses, as pre-specified in the protocol.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- Two parallel groups of prehospital providers, randomized 1:1 at the individual level. Each participant completes a single session comprising 14 ECG clinical vignettes presented in an individually randomized order. The control group interprets the ECGs unaided; the intervention group must consult a study-imposed smartphone large language model for every vignette before submitting an answer.
| Arm | Type | Receives |
|---|---|---|
| Control: unaided ECG interpretation | No intervention | –Participants interpret each of the 14 ECG vignettes without any assistance. Smartphones are turned face down and out of reach for the duration of the session. No intervention is administered. |
| AI-assisted ECG interpretation | Experimental | Diagnostic Test: Smartphone large language model assistance (GPT-4o, version-locked)Participants must consult the study-imposed large language model for every vignette before submitting their answer. The platform locks the submit button until use of the tool is confirmed. Participants remain free not to follow the interpretation produced by the model and may base their final answer on their own clinical reasoning. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Prehospital care provider practising in French-speaking Switzerland
- Any level of training: emergency medical technician, paramedic (ES), nurse (ES/HES) in prehospital emergency care, or prehospital emergency physician
- Electronic informed consent signed before randomization
Key exclusion criteria (4 listed)
- Cardiologist
- Any person not practising in prehospital care
- Insufficient command of written French to answer the vignettes reliably
- Refusal to participate or withdrawal of consent
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 |
|---|---|---|
| Smartphone large language model assistance (GPT-4o, version-locked)Also: ChatGPT, gpt-4o-2024-08-06The platform transmits the ECG image to a single large language model (OpenAI GPT-4o, API snapshot gpt-4o-2024-08-06), locked for the entire study, together with a standardised prompt identical for all participants and all vignettes: "I am on an urgent prehospital call with a patient who presents this ECG. Analyse it and tell me what you think." Participants cannot modify the prompt, ask follow-up questions or provide additional clinical context. The model version and system fingerprint returned by the API are recorded for every call. The model's interpretation is displayed within the vignette. Use of the tool is mandatory; adherence to its interpretation is not. | Diagnostic test | AI-assisted ECG interpretation |
Primary outcome
Proportion of vignettes with correct identification of occlusion myocardial infarction (OMI) status
Time frame: Single study session, approximately 90 minutes; 14 vignettes per participant
For each of the 14 vignettes, the participant answers a binary question: "At this stage of care, is an OMI (acute coronary occlusion) likely? Yes / No". Responses are scored against a reference standard defined a priori, vignette by vignette, by the study cardiologist and locked before data collection. This reference standard is the answer expected of a prehospital provider at the point of care, anchored on coronary angiography wherever angiography is discriminant. For non-ischaemic mimics the expected answer depends on whether the acute presentation allows the condition to be distinguished from a coronary occlusion: it does not for the Takotsubo case (expected answer "yes"), whereas acute pericarditis is usually recognisable (expected answer "no"). This pre-specified departure from a purely angiographic standard is reported as such, and the analysis is repeated in a sensitivity analysis classifying all mimics as non-OMI. The outcome is the proportion of correctly classified vignettes
3 secondary outcomes
Sensitivity of OMI detection
Time frame: Single study session, approximately 90 minutes
Specificity of OMI detection
Time frame: Single study session, approximately 90 minutes
Accuracy of the prehospital priority decision level
Time frame: Single study session, approximately 90 minutes
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 9 Sep 2026.
- Individual participant dataSharing planned: Yes. Fully anonymised individual participant data - responses to all vignettes, demographic variables and platform-generated technical variables - will be deposited in an open repository (Zenodo or OSF) at the time of publication, in accordance with FAIR principles. The ECG tracings themselves are excluded from this deposit: they originate from routine clinical care at the Geneva University Hospitals, which authorise their use for this study only and do not permit transmission to third parties. Requests concerning the tracings must be addressed to the Geneva University Hospitals.
Related trials for Acute Coronary Syndromes
Active, not recruiting
Safety and Clinical Performance of the Freesolve Resorbable Magnesium Scaffold System in the Treatment of Subjects With Long de Novo Lesions
Coronary Artery Disease, Atherosclerosis of Coronary Artery
Active, not recruiting
Interventional Strategy for Non-culprit Lesions With Major Vulnerability Criteria at OCT in Patients With ACS
Coronary Artery Disease, Coronary Disease
Active, not recruiting
Point-of-Care Troponin Testing in the Emergency Department
Acute Coronary Syndromes
Enrolling by invitationObservational study
Prevalence of CYP2C19 Genetic Polymorphisms Among Egyptian Patients Receiving Clopidogrel Following PCI
Acute Coronary Syndrome
RecruitingObservational study
CytOSorb TreatMent Of Critically Ill PatientS Registry
Septic Shock, Acute Respiratory Distress Syndrome
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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Smartphone large language model assistance (GPT-4o, version-locked) in people with Acute Coronary Syndromes and ST Elevation Myocardial Infarction, run by École Supérieure de Soins Ambulanciers - College of Higher Education in Prehospital Care at 1 site in Switzerland.
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: looking for participants now, as of the sponsor's last update on 9 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Switzerland. 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 Laurent Bourgeois (+41 22 388 34 04, laurent.bourgeois@edu.ge.ch), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Proportion of vignettes with correct identification of occlusion myocardial infarction (OMI) status (time frame: Single study session, approximately 90 minutes; 14 vignettes per participant). 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 9 Sep 2026.