Clinical Validation of an Artificial Intelligence-Based G-FAST Score in Patients With Stroke
Overview
- Phase
- Not Applicable
- Status
- Not yet recruiting
- Sponsor
- Xuanwu Hospital, Beijing
- Enrollment
- 297
- Primary Endpoint
- Agreement between AI-generated and physician-scored G-FAST scale assessments
Overview
Brief Summary
This study aims to validate the clinical performance of an artificial intelligence (AI)-based automatic assessment system for the G-FAST score. The core comparison is the consistency and accuracy between AI-generated G-FAST results and standardized manual G-FAST assessments performed by trained professionals. The goal is to provide a convenient, efficient, and objective tool for acute stroke screening and early identification, reduce the subjective variability of manual scoring, and optimize the pre-hospital and in-hospital stroke assessment workflow.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Prospective
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •Aged ≥ 18 years, of either sex.
- •Clinically diagnosed with stroke, and confirmed by cranial CT/MRI to have ischemic or hemorrhagic stroke.
- •Onset within 7 days.
- •Alert and oriented, able to cooperate with standardized video and audio data collection.
- •The patient or their legally authorized representative understands the study and voluntarily provides written informed consent (including consent for audio-visual data collection).
Exclusion Criteria
- •Neurological deficits caused by non-stroke etiologies (e.g., brain tumor, traumatic brain injury, encephalitis).
- •Patients with impaired consciousness, severe cognitive dysfunction, or psychiatric disorders that prevent cooperation with video collection and scale assessment.
- •Patients with severe visual or hearing impairment, or global aphasia, who are unable to follow instructions.
- •Critically ill patients requiring immediate cardiopulmonary resuscitation or endotracheal intubation, making video and audio data collection impossible.
- •Patients with severe facial or limb deformities, or large-area dressings that severely interfere with camera data collection.
- •Patients with unilateral or bilateral upper limb amputation, severe deformity, unhealed fracture, joint fixation, or severe contracture.
Arms & Interventions
AI-first interview group
Participants first undergo G-FAST assessment by AI, followed by G-FAST assessment by human assessors.
Human-first group
Participants first undergo G-FAST assessment by human assessors, followed by G-FAST assessment by AI.
Outcomes
Primary Outcomes
Agreement between AI-generated and physician-scored G-FAST scale assessments
Time Frame: within 7 days of acute stroke onset
The agreement between the scores generated by the artificial intelligence (AI) system and the scores assigned by neurologists on G-FAST scale will be evaluated using weighted Kappa coefficients.
Secondary Outcomes
- Agreement of AI System vs. Neurologists in Binary G-FAST Classification (Score ≥3 vs. <3)(within 7 days of acute stroke onset)
- Bland-Altman Agreement Limit Analysis(within 7 days of acute stroke onset)
- Diagnostic performance analysis(within 7 days of acute stroke onset)
Investigators
qingfeng ma
MD
Xuanwu Hospital, Beijing