AI-based EEG for better stroke and post-cardiac arrest outcomes
Official title: AI-based Algorithm Development for Improved Diagnostics in the Intensive Care and Acute Stroke Setting Using Electroencephalography (SMART-EEG)
Run by Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA) · NCT07886957 · Data updated 2026-11-12
Researchers are testing whether a simple subhairline EEG patch plus AI can help predict outcomes after cardiac arrest and detect brain bleeds in stroke patients.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 825 (estimated) |
| Sponsor | Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA) Academic / other |
| Locations | 1 site (Amsterdam, North Holland) |
| Status | Recruiting |
| Started | March 26, 2026 |
| Main results expected | March 26, 2028 |
| Study ends | March 26, 2028 |
| Registry record updated | October 21, 2026 |
| Trial ID | NCT07886957 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults 18 years or older with postanoxic coma after cardiac arrest admitted to ICU, or adults with suspected stroke/SAH presenting to the emergency department within defined time windows.
✕Probably not a fit
Patients without access to or suitable for EEG monitoring, or those outside the specified time windows, may not benefit from this approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study develops AI algorithms that analyze subhairline EEG data to predict neurological outcomes in adults with postanoxic coma after cardiac arrest and to detect intracranial hemorrhage in adults with suspected stroke or SAH. Participants will receive a continuous subhairline EEG patch in addition to standard care EEG where applicable. The study aims to validate AI models for outcome prediction at around 24 hours after cardiac arrest and for hemorrhage detection using EEG and clinical information. The approach seeks to enable faster, noninvasive assessment in critical care and emergency settings.
Why it matters
Potential benefit: If successful, the AI-driven subhairline EEG approach could provide rapid, noninvasive insights to guide early treatment decisions in ICU and ED patients.
How similar studies have gone: Pilot data suggest subhairline EEG is a feasible alternative to scalp EEG and that AI interpretation may offer rapid decision support, but broader validation is needed.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: All participants: \- Age 18 years or older Postanoxic coma (ICU): * Postanoxic coma after cardiac arrest, admitted to the intensive care unit * No objection to participation within 4 weeks of receiving an opt-out information letter Suspected stroke (emergency department): * Suspected stroke as assessed by the ambulance personnel presenting the patient to the emergency department, or confirmed stroke. * Symptom onset, or last seen well if onset was not witnessed, less than 24 hours ago. * Written (deferred) informed consent by the patient or legal representative Suspected subarachnoid hemorrhage (emergency department): * Suspected subarachnoid hemorrhage as judged by the attending ambulance paramedic, or confirmed subarachnoid hemorrhage. * Symptom onset, or last seen well if onset was not witnessed, less than 48 hours ago. * Written (deferred) informed consent by the patient or legal representative. Exclusion Criteria: All participants: \- (Suspected) skin damage or infection at the placement area of the subhairline EEG patch Postanoxic coma (ICU): \- Other types of severe brain injury, either pre-existing or coinciding with cardiac arrest. These include stroke, traumatic brain injury and progressive neurodegenerative disease.
Where it's running
-
Amsterdam University Medical Center
Amsterdam, North Holland, Netherlands Recruiting
Study contacts
- Study coordinator: Kars Tjepkema
- Email: k.r.tjepkema@amsterdamumc.nl
- Phone: 0031644761222
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.