Clinical Validation of an Artificial Intelligence-Based G-FAST Score in Patients With Stroke

Capital Medical University

Status: Not yet enrolling

Conditions: Stroke

Study type: Observational

Funder types: Other

Identifiers

NCT07538492

qingfeng ma G-FAST Scale

Details and patient eligibility

About

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.

Enrollment: 297 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. Aged ≥ 18 years, of either sex.
2. Clinically diagnosed with stroke, and confirmed by cranial CT/MRI to have ischemic or hemorrhagic stroke.
3. Onset within 7 days.
4. Alert and oriented, able to cooperate with standardized video and audio data collection.
5. 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

1. Neurological deficits caused by non-stroke etiologies (e.g., brain tumor, traumatic brain injury, encephalitis).
2. Patients with impaired consciousness, severe cognitive dysfunction, or psychiatric disorders that prevent cooperation with video collection and scale assessment.
3. Patients with severe visual or hearing impairment, or global aphasia, who are unable to follow instructions.
4. Critically ill patients requiring immediate cardiopulmonary resuscitation or endotracheal intubation, making video and audio data collection impossible.
5. Patients with severe facial or limb deformities, or large-area dressings that severely interfere with camera data collection.
6. Patients with unilateral or bilateral upper limb amputation, severe deformity, unhealed fracture, joint fixation, or severe contracture.

Trial design

297 participants in 2 patient groups

AI-first interview group

Description:

Participants first undergo G-FAST assessment by AI, followed by G-FAST assessment by human assessors.

Human-first group

Description:

Participants first undergo G-FAST assessment by human assessors, followed by G-FAST assessment by AI.