Research on Early Prediction Model of Ischemic Cerebrovascular Disease Based on Artificial Intelligence Technology.
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Ischemic Cerebrovascular Disease, Artificial Intelligence, Prediction Model. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Establish an Artificial Intelligence Clinical Decision Support System for Patients With Carotid/Vertebral Artery Stenosis.
Overview
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.
Primary outcome measures
- 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]
Secondary outcome measures (1)
- Analyze the risk factors leading to stroke [Time frame: December 2025]
Eligibility criteria
Inclusion criteria
Patients undergoing vascular (carotid/vertebral artery) B-ultrasound
Exclusion criteria
Patients with missing clinical data such as medical history, cerebrovascular ultrasound results and biochemical data
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Case-only
Study locations
China · 1 center
- Model — Shanghai
Identifiers
NCT: NCT06978348 · AI-iSTROKE