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

NCT07538492 | Not Yet Recruiting

• 1 other identifier: qingfeng ma G-FAST Scale
• Study Type: observational
• Target: 297
• Locations: 0 countries
• Sites: N/A

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.

Conditions

Stroke

Keywords

Artificial Intelligence; G-FAST

Outcome Measures

Primary Outcomes (1)

• Agreement between AI-generated and physician-scored G-FAST scale assessments

  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.

  within 7 days of acute stroke onset

Secondary Outcomes (3)

• 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

Study Arms (2)

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.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with acute ischemic stroke who undergo G-FAST scale assessments using both AI and manual methods.

You may qualify if:

• 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).

You may not qualify if:

• 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.

Sponsors & Collaborators

• Xuanwu Hospital, Beijing: lead
• Capital Medical University: collaborator
• People's Hospital of Beijing Daxing District: collaborator
• Beijing Tiantan Hospital: collaborator
• The First Hospital of Fangshan District,Beijing: collaborator

MeSH Terms

Conditions

Stroke

Condition Hierarchy (Ancestors)

Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases; Cardiovascular Diseases

Study Officials

• Qingfeng Ma, MD

  Xuanwu Hospital, Beijing

  STUDY CHAIR

Central Study Contacts

Qingfeng Ma, MD

CONTACT

+8613601069493; m.qingfeng@163.com

Zixin Wang, MD Candidate

CONTACT

+8615031041048; wzx15031041048@163.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: MD

Study Record Dates

• First Submitted: April 7, 2026
• First Posted: April 20, 2026
• Study Start: April 10, 2026
• Primary Completion (Estimated): December 31, 2028
• Study Completion (Estimated): December 31, 2028
• Last Updated: April 20, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share