AI aims to uncover hidden barriers to stroke care

NCT ID NCT07257146

ENROLLING_BY_INVITATION Knowledge-focused Sponsor: Middle East North Africa Stroke and Interventional Neurotherapies Organization Source: ClinicalTrials.gov ↗

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

Summary

This study looks at 250 stroke patients to understand why some arrive late at the hospital. Researchers use a questionnaire, mapping tools, and brain scans to find social, transport, and knowledge barriers. A machine learning model will try to predict who is at risk for delay, with the goal of improving emergency stroke care.

What this could mean

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

Active substance: Targeted Stroke Systems of Care Training (SABI-Guided)
What this could lead to: If successful, this could help hospitals identify and reduce barriers that delay stroke patients from getting timely treatment, potentially saving lives.
What could go wrong: This is an observational study with historical controls, so results may not prove cause and effect. The machine learning model may not work well in other regions or populations.

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

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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.

HEALTHCARE ACCESS HEALTHCARE DISPARITIES PRACTICE STROKE THROMBECTOMY

Contacts and locations

Locations

Alexandria Stroke and Neurointervention Center

Alexandria, Egypt

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