Clinical trial NCT05148182: Metabolomics Characterization of Biomarkers of ASCVD and Prediction Model
Official title: Metabolomics Characterization of Biomarkers of ASCVD and Prediction Model
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Atherosclerosis
Prediction Model
Keywords: metabolomics
Atherosclerosis
Biomarkers
prediction model
Lead sponsor: Shanghai 10th People's Hospital
Sponsor class: OTHER
First posted: 2021-12-08
Enrollment: 1869
Sex: ALL
Minimum age (years): 18
Maximum age (years): 90
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: According to China PAR equations and Chinese guidelines and consensus on cardiovascular risk assessment and management, the patients were defined as low, medium, high risk groups.

Brief summary: 1. Describe the risk factors and metabonomics characteristics of atherosclerotic cardiovascular disease in Chinese patients.
2. Establish accurate prediction model of atherosclerotic heart disease.

Detailed description: According to the Chinese cardiovascular disease report released in 2017, cardiovascular disease death is the leading cause of death of urban and rural residents, so cardiovascular disease risk assessment is particularly important. The development of cardiovascular risk assessment model was dated from Framingham Heart Study which first proposed the concept of risk factors, and then adjusted the model several times. In 2016, the China-PAR evaluated the cardiovascular disease risk of Chinese population. However, the application of metabolomics in coronary heart disease is a rapidly developing field and also a new field .

Therefore, the aim of this study was to

1.Describe the risk factors of atherosclerotic cardiovascular disease and the characteristics of metabolomics in Chinese population.

2. Establish an accurate prediction model of atherosclerotic heart disease. Research plan：

1. 1869 risk-stratified people were recruited.
2. Plasma samples were collected incluing disease status and other potential influencing factors.
3. Through the high-throughput detection of body metabolites, combined with multivariate statistical analysis, the metabolic markers with significant difference in different risk levels were screened for risk prediction.
4. All recruited people underwent coronary angiography.
5. The distribution of age and gender in each group should be matched and balanced as far as possible.

Eligibility criteria: Inclusion Criteria:

1. The age of the population is 18 or more than 18 years old.
2. According to China PAR equations, Chinese guidelines and consensus on cardiovascular risk assessment and management，it is considered as healthy, low, medium, high and extremely high risk group.
3. The subjects read and fully understood the patient's instructions and signed the informed consent

Exclusion Criteria:

1. Refused to sign informed consent.
2. ACS is caused by surgery, trauma, or other diseases.
3. Age less than 18 years old.
4. Pregnant women.
5. In the past 3 months, the patients were treated with trauma surgery.
6. There are aortic dissection, pulmonary embolism, pneumonia, pericarditis, myocarditis, stress cardiomyopathy.
7. Severe heart failure.
8. Liver and kidney failure.
9. Blood borne infectious diseases: including HIV / AIDS, hepatitis B, hepatitis C, etc.
10. Patients with a history of malignancies, autoimmune diseases, severe infectious diseases and trauma.
11. Any condition (such as travel, speech disorder, mental disorder) that the researcher believes can significantly limit the completion of the patient's follow-up.

Primary outcomes:
measure: Metabolomics Characterization of Biomarkers
timeFrame: 3 years
measure: Coronary vascularization.
timeFrame: 3 years
measure: All cause mortality
timeFrame: 3 years
measure: Cardiac mortality
timeFrame: 3 years
Secondary outcomes:
Other outcomes:
Locations:
city: Shanghai
country: China
facility: Department of Cardiology,Shanghai Tenth People's Hospital
city: Shanghai
country: China
facility: Shanghai Tenth People's Hospital
Study officials:
References: