Smart-SABI: Digital Phenotyping of Stroke Access Barriers
Smart-SABI
Machine Learning Identification of Modifiable Access Barriers in Acute Ischemic Stroke: A Multimodal "Digital Phenotyping" Approach
2 other identifiers
observational
250
1 country
1
Brief Summary
This study aims to identify and quantify the non-clinical barriers (social, transport, and knowledge-based) that delay patient arrival at the hospital during an Acute Ischemic Stroke. By utilizing a multimodal approach that combines a validated patient questionnaire (SABI Tool), Geographic Information Systems (GIS) analysis, and biological markers (infarct volume), the investigators seek to develop a Machine Learning model capable of predicting high-risk phenotypes for pre-hospital delay. The ultimate goal is to validate "Social Determinants of Health" against objective biological outcomes.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Oct 2025
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
October 11, 2025
CompletedFirst Submitted
Initial submission to the registry
November 20, 2025
CompletedFirst Posted
Study publicly available on registry
December 2, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
February 11, 2027
ExpectedStudy Completion
Last participant's last visit for all outcomes
April 11, 2027
December 2, 2025
November 1, 2025
1.3 years
November 20, 2025
November 20, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Correlation of SABI Score with Infarct Core Volume (The Biological Anchor)
To validate if subjective barriers correlate with objective physiological damage. The total score on the SABI questionnaire (Scale 0-100, higher scores indicate higher barriers) will be correlated with the admission Infarct Core Volume (measured in milliliters via automated CT-Perfusion software).
Baseline (Admission Imaging)
Secondary Outcomes (3)
Predictive Accuracy of ML Model for "High-Risk" Delay
Baseline through Study Completion (12 months)
Agreement between Subjective Transport Barriers and GIS Metrics
Baseline
Functional Outcome (mRS) at 90 Days
90 Days post-discharge
Study Arms (1)
Acute Ischemic Stroke (AIS) Patients
Acute Ischemic Stroke (AIS) Patients This cohort consists of adult patients presenting to the Emergency Department with a confirmed clinical and radiological diagnosis of Acute Ischemic Stroke. The group encompasses a continuous spectrum of arrival times, subsequently stratified during analysis into "Early Arrivers" (presenting within the therapeutic window, typically \< 4.5 hours) and "Late Arrivers" (presenting after the therapeutic window).
Interventions
Implementation of targeted barrier-reduction strategies at selected stroke centers based on baseline SABI profiles. The primary intervention consists of EMS Training Programs focused on stroke recognition, triage protocols, and rapid transport to Mechanical Thrombectomy (MT) capable centers. Comparator/Control: Pre-intervention period (historical control) where standard of care was utilized without the targeted SABI-guided training. Post-Intervention: Assessment of MT utilization rates and SABI scores following the implementation of the training modules.
Eligibility Criteria
The source population comprises patients recruited from 12 tertiary centers across the MENA region: Alexandria University, Ain Shams University, and Cairo University (Egypt); Eskisehir Osmangazi University and Dr. Lutfi Kirdar City Hospital (Turkey); Amman Specialized IR Center (Jordan); King Khalid University, King Abdullah Medical City, and Imam Abdulrahman Al Faisal University (Saudi Arabia); Institute National de Neurology (Tunisia); Cleveland Clinic Abu Dhabi (UAE); and Weill Cornell Medicine (Qatar). This multinational design ensures significant geographic heterogeneity-ranging from the dense urban traffic of Istanbul and Cairo to the mountainous terrain of Abha-which is critical for GIS transport analysis. Additionally, the inclusion of diverse economic and cultural backgrounds supports robust SABI analysis regarding stroke awareness and health-seeking behaviors across the region.
You may qualify if:
- Diagnosis of Acute Ischemic Stroke (AIS) confirmed by neuroimaging (CT or MRI). Age $\\geq$ 18 years. Presentation to the Emergency Department within 7 days of symptom onset (to ensure recall accuracy).
- Patient or Legally Authorized Representative (LAR) able to provide informed consent.
- Verifiable residential address (required for GIS analysis).
You may not qualify if:
- In-hospital stroke onset. Stroke mimics (e.g., seizure, complex migraine, hypoglycemia). Hemorrhagic stroke. Homelessness or lack of fixed address (precludes geospatial analysis). Severe aphasia or cognitive deficit without an available surrogate/caregiver to complete the questionnaire.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Alexandria Stroke and Neurointervention Center
Alexandria, Egypt
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Prof of Neurology and Neuroradiology Alexandria university
Study Record Dates
First Submitted
November 20, 2025
First Posted
December 2, 2025
Study Start
October 11, 2025
Primary Completion (Estimated)
February 11, 2027
Study Completion (Estimated)
April 11, 2027
Last Updated
December 2, 2025
Record last verified: 2025-11