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Through a multicenter prospective AIS cohort study, we analyze the potential association of human proteome, microbiome and metabolome alterations with AIS prognosis, searching for key proteins, differential organisms and metabolites, combining experimental data at multiple molecular levels with computational models, and establishing early prediction models through machine learning-based prediction algorithms. While closely tracking the recurrence of stroke in AIS patients, we evaluate the predictive value of human proteome, microbiome and metabolites for stroke recurrence through a nested case-control study, which provides key reference information for exploring the unknown residual risk of AIS recurrence.
Currently, the burden of brain vascular disease in China is the highest in the world, and among them, the incidence rate of acute ischemic stroke (AIS) is high, the recurrence rate is high, the disability rate is high, the mortality rate is high, and the social burden is heavy. With the increasing number of AIS patients, how to effectively prevent and treat them is a huge challenge facing us. The occurrence and development of AIS are caused by the joint action of multiple risk factors and mutual influence, and single technical means are difficult to deeply explore its complex mechanism. Therefore, building a risk prediction model for poor prognosis and recurrence based on multi-omics technology and layering risk factors for patients are the important research directions for the future. This study aims to establish a multi-center cohort by collecting fecal and blood samples from AIS patients and conducting proteomic, microbial and metabolomic detection. It records the prognosis and recurrence events and uses cross-omics analysis technology to explore the multi-omics network molecular mechanism and screen for new intervention targets. It establishes an early prediction model and explores the stroke secondary prevention strategy based on multi-omics data.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| modeling queue | The modeling queue is used to manage and prioritize tasks related to the development and training of models. |
| |
| validation queue | The validation queue is designed to handle tasks related to the evaluation and validation of models. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| microbiome; metabolomics; proteomics | Other | post-stroke change of microbiome; metabolomics; proteomics |
|
| Measure | Description | Time Frame |
|---|---|---|
| Incidence of new cardiovascular events and death | any stroke /TIA/ myocardial infarction/Vascular death | within 12 months after onset |
| Measure | Description | Time Frame |
|---|---|---|
| Brain Injury Conditions | Clinical investigators evaluate brain injury conditions according to head CT or MR, which including the signs of infarct lesions, hemorrhagic transformation post-infarction or cerebral edema. | 3, 12 months after ischemic stroke |
| Small Vessel Disease Burden |
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Inclusion Criteria:
Exclusion Criteria:
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The study population mainly includes patients who meet the diagnostic criteria for acute ischemic stroke (AIS), are aged between 18 and 75 years, have a stroke onset within the past 7 days, and have clear consciousness. Patients with severe systemic diseases, a recent history of stroke, severe liver or kidney disease, a history of long-term alcohol consumption, those unable to provide a sample, or those assessed by the investigator as unsuitable for participation in the study are excluded.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Jia Yin, M.D | Contact | 13802964883 | jiajiayin@139.com | |
| Weike Hu, M.D | Contact | 18326349212 | weike946@gmail.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Nanfang Hospital,Southern Medical University | Recruiting | Guangzhou | Guangdong | 510515 | China |
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| ID | Term |
|---|---|
| D000083242 | Ischemic Stroke |
| ID | Term |
|---|---|
| D020521 | Stroke |
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
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| ID | Term |
|---|---|
| D064307 | Microbiota |
| ID | Term |
|---|---|
| D008827 | Microbiological Phenomena |
| D058448 | Biota |
| D044822 | Biodiversity |
| D017753 | Ecosystem |
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Blood, stool
Clinical investigators evaluate small vessel disease burden according to head CT or MR, which including the signs of white matter degeneration, lacunar infarctions, cerebral microbleeds or enlarged perivascular spaces. |
| 3, 12 months after ischemic stroke |
| Cerebrovascular Pathology | Clinical investigators evaluate cerebrovascular pathology according to head CT or MR, which including the signs of vascular stenosis, vascular dissection or collateral circulation compensation. | 3, 12 months after ischemic stroke |
| Modified Rankin Scale ( mRS ) score | The MRS score is primarily used to measure the degree of disability and daily living ability of patients. The MRS score ranges from 0 to 6, with a total of 7 levels. The higher the score, the more severe the disability and the worse the prognosis. | 7 day and 3, 12 months after ischemic stroke |
| National Institutes of Health Stroke Scale ( NIHSS ) score | The NIHSS score is commonly used to assess the degree of neurological impairment in patients with acute stroke. The NIHSS consists of 11 items, with a total score ranging from 0 to 42. Each item has different scoring criteria, typically ranging from 0 (normal) to 4 (most severe). | 7 day and 3, 12 months after ischemic stroke |
| Activity of Daily Living Scale ( ADL ) score | The ADL score is primarily used to measure a person's ability to perform basic daily activities. This study uses the Barthel Index scoring method, which ranges from 0 to 100 points, with scoring items including eating, bathing, grooming, dressing, bowel control, bladder control, toileting, transferring, mobility and stairs. A higher score indicates greater independence, while a lower score indicates greater dependence. | 7 day and 3, 12 months after ischemic stroke |
| Mini-mental State Examination ( MMSE ) score | The MMSE (Mini-Mental State Examination) is a tool used to assess cognitive function, including orientation, memory, attention, language skills, calculation ability, and visuospatial skills. It is commonly used to screen for dementia in older adults. The MMSE has a total score of 30 points: a score of 24-30 suggests normal cognitive function, 18-23 indicates mild cognitive impairment, and 0-17 indicates moderate to severe cognitive impairment. | 3, 12 months after ischemic stroke |
| Montreal Cognitive Assessment ( MOCA ) score | The MoCA is a tool used to assess cognitive impairment. Compared to the MMSE, the MoCA is more sensitive, particularly for detecting mild cognitive impairment (MCI). The MoCA has a total score of 30 points: a score of 26-30 suggests normal cognitive function, 18-25 indicates mild cognitive impairment (MCI), and 0-17 indicates moderate to severe cognitive impairment. Typically, individuals with lower educational levels (less than 12 years of education) receive an additional point as an adjustment to their total score. | 3, 12 months after ischemic stroke |
| Hamilton Depression Scale ( HAMD ) score | The HAMD is a clinical scale used to assess the severity of depression. This study uses the 17-item version (HAMD-17), which covers a range of symptoms, including mood, sleep, appetite, and somatic symptoms. The total score ranges from 0 to 52, with each item rated based on the severity of symptoms, typically from 0 (no symptoms) to 4 (severe symptoms). | 3, 12 months after ischemic stroke |
| Hamilton Anxiety Scale ( HAMA ) score | The HAMA is a clinical scale used to assess the severity of anxiety symptoms. It consists of 14 items, each evaluating different symptoms related to anxiety. These symptoms cover both psychological and somatic manifestations of anxiety. Each item is rated based on the severity of symptoms, with scores ranging from 0 (no symptoms) to 4 (very severe symptoms). | 3, 12 months after ischemic stroke |
| D009422 |
| Nervous System Diseases |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D004777 |
| Environment |
| D055669 | Ecological and Environmental Phenomena |
| D001686 | Biological Phenomena |
| D004778 | Environment and Public Health |