Ischemic Cerebrovascular DiseaseNCT06978348
Research on Early Prediction Model of Ischemic Cerebrovascular Disease Based on Artificial Intelligence Technology.
An observational study of Ischemic Cerebrovascular Disease and Artificial Intelligence, run by Shanghai Jiao Tong University School of Medicine at 1 site in China.
Trial summary
Establish an artificial intelligence clinical decision support system for patients with carotid/vertebral artery cerebrovascular stenosis, early identification of patients who may have cerebral infarction. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Ischemic Cerebrovascular Disease, Artificial Intelligence, Prediction Model
- How many people
- 244,296 participants
- Where
- 1 siteChina
- Study dates
- 10 May 2025to 10 Jun 2025
- 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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: 1. Patients who visited our hospital from January, 2012 to January, 2022; 2. Patients undergoing cervical/vertebral artery cerebrovascular ultrasonography those.
Who may be able to join
- Patients undergoing vascular (carotid/vertebral artery) B-ultrasound
Who cannot join
- Patients with missing clinical data such as medical history, cerebrovascular ultrasound results and biochemical data
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Model
Shanghai, Shanghai Municipality
Yijun Cheng
About this study
Official title: Establish an Artificial Intelligence Clinical Decision Support System for Patients With Carotid/Vertebral Artery Stenosis.
Establish an artificial intelligence clinical decision support system for patients with carotid/vertebral artery cerebrovascular stenosis, early identification of patients who may have cerebral infarction. With the support of this project, it is expected that a secondary prevention clinical decision support system for chronic stroke will be established, which is likely to become an important auxiliary tool for the management of cerebrovascular diseases in the future.
Read the detailed description
Stroke is a disease with a high mortality rate and incidence rate, and it is one of the main reasons for high medical expenses. Ischemic stroke accounts for approximately 85% of all subtypes of stroke. Carotid artery and vertebral artery stenosis are definite and intervenable risk factors for ischemic stroke. However, the selection of clinical intervention timing and methods for patients with cerebrovascular stenosis is limited to the rate of carotid/vertebral artery stenosis and the symptoms of the patients. Cerebral infarction caused by carotid/vertebral artery stenosis often leads to irreparable neurological deficits. Currently, there is a lack of comprehensive evaluation methods for the severity of ischemic cerebrovascular diseases such as carotid/vertebral artery stenosis, and even less a clinical decision-making system that can predict the progression of the disease. This project intends to take the demographic data and clinical information of patients with cerebrovascular stenosis from multiple centers and ethnic groups as the entry point, combine the multidisciplinary advantages of imaging, ultrasound, clinical medicine and computer science, and use artificial intelligence technology to construct a model for predicting the disease progression and the probability of adverse cardiovascular events such as stroke in patients with cerebrovascular stenosis. Based on this, the investigators' hospital intends to develop a set of secondary prevention management tools and clinical decision support systems for ischemic cerebrovascular diseases.
What is being measured
The primary outcome is the main question the study is designed to answer.
Establish an artificial intelligence clinical decision support system for patients with carotid/vertebral artery cerebrovascular stenosis，Early identification of patients who may have cerebral infarction.
1.The clinical history, imaging data, blood test indicators and other data of patients who completed carotid/vertebral artery cerebrovascular ultrasound examinations from January 2012 to December 2022 were collected to establish a data set；2. This dataset was statistically analyzed in combination with the general risk factors of cerebrovascular diseases and the specific risk factors of carotid artery stenosis；3. The above-mentioned model was trained using the existing clinical database of patients with carotid and cerebrovascular stenosis in the hospital；4. Through machine learning, an artificial intelligence clinical decision support system for patients with carotid/vertebral artery stenosis is established to identify patients with early cerebrovascular stenosis who require surgical intervention, and even asymptomatic patients.
Measured: December 2025
Secondary outcomes (1)
Analyze the risk factors leading to stroke
By collecting the baseline demographic data, clinical history, imaging, laboratory tests and other data of all patients who underwent carotid/vertebral artery vascular ultrasound during the period from 2012.01 to 2022.12, the risk factors causing stroke were analyzed.
Measured: December 2025
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 May 2025
- Study start10 May 2025
- Primary completion10 Jun 2025 (estimated)
- Study completion10 Jun 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Ischemic Cerebrovascular DiseaseStudies of the same condition, open and under way.
- More trials run by Shanghai Jiao Tong University School of MedicineThe 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
- Case only
- Time perspective
- Retrospective
- Enrolment
- 244,296 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Shanghai Jiao Tong University School of Medicine
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yijun Cheng, Shanghai Jiao Tong University School of Medicine
- Investigators
- Yijun Cheng, Doc, Principal investigator, Ruijin HospitalHanbing Shang, Doc, Principal investigator, Ruijin Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06978348
- Sponsor's protocol ID
- AI-iSTROKE
- Status last verified
- May 2025
- First submitted
- 18 Apr 2025
- Last updated
- 18 May 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 18 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Establish an Artificial Intelligence Clinical Decision Support System for Patients With Carotid/Vertebral Artery Stenosis.
- ClinicalTrials.gov ID
- NCT06978348
- Acronym / sponsor ID
- AI-iSTROKE
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 244,296 participants (estimated)
- Lead sponsor
- Shanghai Jiao Tong University School of MedicineUniversity, hospital or other
- Study start
- 10 May 2025 (actual)
- Primary completion
- 10 Jun 2025 (estimated)
- Study completion
- 10 Jun 2025 (estimated)
- First posted
- 18 May 2025 (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.
Establish an artificial intelligence clinical decision support system for patients with carotid/vertebral artery cerebrovascular stenosis, early identification of patients who may have cerebral infarction. With the support of this project, it is expected that a secondary prevention clinical decision support system for chronic stroke will be established, which is likely to become an important auxiliary tool for the management of cerebrovascular diseases in the future.
Detailed description
Stroke is a disease with a high mortality rate and incidence rate, and it is one of the main reasons for high medical expenses. Ischemic stroke accounts for approximately 85% of all subtypes of stroke. Carotid artery and vertebral artery stenosis are definite and intervenable risk factors for ischemic stroke. However, the selection of clinical intervention timing and methods for patients with cerebrovascular stenosis is limited to the rate of carotid/vertebral artery stenosis and the symptoms of the patients. Cerebral infarction caused by carotid/vertebral artery stenosis often leads to irreparable neurological deficits. Currently, there is a lack of comprehensive evaluation methods for the severity of ischemic cerebrovascular diseases such as carotid/vertebral artery stenosis, and even less a clinical decision-making system that can predict the progression of the disease. This project intends to take the demographic data and clinical information of patients with cerebrovascular stenosis from multiple centers and ethnic groups as the entry point, combine the multidisciplinary advantages of imaging, ultrasound, clinical medicine and computer science, and use artificial intelligence technology to construct a model for predicting the disease progression and the probability of adverse cardiovascular events such as stroke in patients with cerebrovascular stenosis. Based on this, the investigators' hospital intends to develop a set of secondary prevention management tools and clinical decision support systems for ischemic cerebrovascular diseases.
Study design
- Observational model
- Case only
- Time perspective
- Retrospective
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- 1. Patients who visited our hospital from January, 2012 to January, 2022; 2. Patients undergoing cervical/vertebral artery cerebrovascular ultrasonography those.
Key inclusion criteria (1 listed)
- Patients undergoing vascular (carotid/vertebral artery) B-ultrasound
Key exclusion criteria (1 listed)
- Patients with missing clinical data such as medical history, cerebrovascular ultrasound results and biochemical data
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
Establish an artificial intelligence clinical decision support system for patients with carotid/vertebral artery cerebrovascular stenosis，Early identification of patients who may have cerebral infarction.
Time frame: December 2025
1.The clinical history, imaging data, blood test indicators and other data of patients who completed carotid/vertebral artery cerebrovascular ultrasound examinations from January 2012 to December 2022 were collected to establish a data set；2. This dataset was statistically analyzed in combination with the general risk factors of cerebrovascular diseases and the specific risk factors of carotid artery stenosis；3. The above-mentioned model was trained using the existing clinical database of patients with carotid and cerebrovascular stenosis in the hospital；4. Through machine learning, an artificial intelligence clinical decision support system for patients with carotid/vertebral artery stenosis is established to identify patients with early cerebrovascular stenosis who require surgical intervention, and even asymptomatic patients.
1 secondary outcome
Analyze the risk factors leading to stroke
Time frame: December 2025
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 18 May 2025.
- Individual participant dataSharing planned: No
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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.
Yijun Cheng, Doc principal investigator
Ruijin Hospital
Hanbing Shang, Doc principal investigator
Ruijin Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Ischemic Cerebrovascular Disease and Artificial Intelligence, run by Shanghai Jiao Tong University School of Medicine at 1 site in China.
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 1 inclusion and 1 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: looking for participants now, as of the sponsor's last update on 18 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
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 Yijun Cheng, Doc (86+15021058538, cyj12574@rjh.com.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Establish an artificial intelligence clinical decision support system for patients with carotid/vertebral artery cerebrovascular stenosis，Early identification of patients who may have cerebral infarction. (time frame: December 2025). 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 18 May 2025.