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Brain vs. machine: who predicts stroke outcomes better?

NCT ID NCT06534645

Knowledge-focused Sponsor: University of Zurich Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now This study
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study compares how well stroke neurologists and a deep learning AI model predict recovery in 250 stroke patients. Researchers will track actual disability at 24 hours and 3 months, then compare those results to predictions made by doctors and the AI. The goal is to understand what factors matter most and build a better prediction tool for clinical use.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this could lead to a reliable AI tool that helps doctors predict stroke recovery more accurately, improving patient care.
What could go wrong
This is an early observational study, not testing a treatment. The AI model may not perform better than doctors, and results may not apply to all stroke patients.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 250 people

The number the study aims to enrol. It can still change while the study runs.

Started

Oct 2024

Expected to finish

Jul 2027

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Patients with suspicion of acute ischemic stroke independent of stroke etiology, who received medical imaging (CT or MRI scan of the brain depending on the clinical indication) after admission to hospital at USZ or before at an external hospital sending the patient to the USZ for treatment.

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Patients from up to 18 years years of age without any upper age limit. * Patients with clinical suspicion of acute ischemic stroke (acute onset focal neurological deficit) at the discretion of the paramedic or treating physician within 24 hours of symptom onset including wake-up situation and unclear symptom onset planned for clinically indicated neuroimaging. * Patients with externally performed neuroimaging before admission or referral to the USZ will be included from the time point N2 on if no refusal of use of data is documented. Exclusion Criteria: • Patients with documented objection of subsequent use of personal health data or patients who reject the use of personal health data during follow-up after initial informed consent by an independent physician in the acute setting. We will not include patients in the study if there is no written informed consent either from the patient her-/himself, the next of kin or the independent physician.

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Conditions

The condition(s) this trial relates to.

ischemic stroke stroke disorder

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Stroke outcome prediction supported by deep learning algorithm

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • University Hospital Zurich, Department of Neurology

    RECRUITING

    Zurich, 8091, Switzerland

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