StrokeNCT07538492
Clinical Validation of an Artificial Intelligence-Based G-FAST Score in Patients With Stroke
An observational study of Stroke, run by Xuanwu Hospital, Beijing.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Stroke
- How many people
- 297 participants
- Where
- No sites listed yet
- Study dates
- 10 Apr 2026to 31 Dec 2028
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients with acute ischemic stroke who undergo G-FAST scale assessments using both AI and manual methods.
Who may be able to join
- 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).
Who cannot join
- 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.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
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
- Medical subject headings
- Stroke
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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)
Kappa coefficient will be calculated to evaluate the agreement between the artificial intelligence (AI) system and neurologist experts in the binary classification of G-FAST scale scores, defined as high risk (total score ≥3) vs. low risk (total score <3) for large vessel occlusion stroke.
Measured: within 7 days of acute stroke onset
Bland-Altman Agreement Limit Analysis
A Bland-Altman plot will be constructed, with the difference between manual scores and AI scores on the vertical axis and the mean of the two scores on the horizontal axis. The limits of agreement (mean difference ± 1.96 × standard deviation) will be calculated.
Measured: within 7 days of acute stroke onset
Diagnostic performance analysis
Taking the manual score as the gold standard, a 2×2 contingency table was constructed to calculate the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and Youden index of the AI scoring system for stratifying the G-FAST score (LVO ≥3 vs. non-LVO <3). The ROC curve was plotted and the AUC was calculated.
Measured: within 7 days of acute stroke onset
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 Apr 2026
- Study start10 Apr 2026 (estimated)
- Primary completion31 Dec 2028 (estimated)
- Study completion31 Dec 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for StrokeStudies of the same condition, open and under way.
- More trials run by Xuanwu Hospital, BeijingThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 297 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Xuanwu Hospital, Beijing
- Sponsor type
- University, hospital or other
- Collaborators
- Capital Medical University, People's Hospital of Beijing Daxing District, Beijing Tiantan Hospital, The First Hospital of Fangshan District,Beijing
- Responsible party
- Principal investigator, qingfeng ma, Xuanwu Hospital, Beijing
- Investigators
- Qingfeng Ma, MD, Study chair, Xuanwu Hospital, Beijing
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07538492
- Sponsor's protocol ID
- qingfeng ma G-FAST Scale
- Status last verified
- Apr 2026
- First submitted
- 7 Apr 2026
- Last updated
- 20 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Due to the protection of participant privacy and institutional review board requirements, individual participant data (IPD) will not be shared publicly.
Study at a glance
From the registry record, last updated by the sponsor on 20 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Clinical Validation of an Artificial Intelligence-Based G-FAST Score in Patients With Stroke
- ClinicalTrials.gov ID
- NCT07538492
- Acronym / sponsor ID
- qingfeng ma G-FAST Scale
- Conditions
- Stroke
- Keywords
- Artificial Intelligence, G-FAST
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 297 participants (estimated)
- Lead sponsor
- Xuanwu Hospital, BeijingUniversity, hospital or other
- Collaborators
- Capital Medical University, People's Hospital of Beijing Daxing District, Beijing Tiantan Hospital, The First Hospital of Fangshan District,Beijing
- Study start
- 10 Apr 2026 (estimated)
- Primary completion
- 31 Dec 2028 (estimated)
- Study completion
- 31 Dec 2028 (estimated)
- First posted
- 20 Apr 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with acute ischemic stroke who undergo G-FAST scale assessments using both AI and manual methods.
Key inclusion criteria (5 listed)
- 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).
Key exclusion criteria (6 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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.
3 secondary outcomes
Agreement of AI System vs. Neurologists in Binary G-FAST Classification (Score ≥3 vs. <3)
Time frame: within 7 days of acute stroke onset
Bland-Altman Agreement Limit Analysis
Time frame: within 7 days of acute stroke onset
Diagnostic performance analysis
Time frame: within 7 days of acute stroke onset
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Apr 2026.
- Individual participant dataSharing planned: No. Due to the protection of participant privacy and institutional review board requirements, individual participant data (IPD) will not be shared publicly.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Qingfeng Ma, MD study chair
Xuanwu Hospital, Beijing
Questions about this trial
What is this clinical trial studying?
An observational study of Stroke, run by Xuanwu Hospital, Beijing.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 20 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Qingfeng Ma, MD (+8613601069493, m.qingfeng@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Agreement between AI-generated and physician-scored G-FAST scale assessments (time frame: within 7 days of acute stroke onset). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Apr 2026; AzTrials last refreshed its copy on 1 Nov 2026.