Sleep Disordered Breathing (SDB)
Conditions
Brief summary
Obstructive sleep apnea (OSA) significantly increases the risk of cardiovascular events in patients with acute coronary syndrome (ACS), yet the underlying metabolic mechanisms remain unclear. This study aims to analyze the metabolic characteristics of ACS patients with OSA using metabolomics based on a prospective cohort. The study intends to construct an artificial intelligence-based risk stratification model to improve prognosis prediction and facilitate precision medicine for this population.
Interventions
OTHERBiological Sample Collection
Collection of blood, urine, and stool samples for metabolomics analysis.
Sponsors
Beijing Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
No
Inclusion criteria
* Age 18-85 years. * Diagnosed with ACS, including ST-segment elevation myocardial infarction, non-ST-segment elevation myocardial infarction, and unstable angina. * Willing to participate and sign the informed consent form.
Exclusion criteria
* Cardiogenic shock or cardiac arrest. * Central sleep apnea or other types of sleep disordered breathing. * Previous or current treatment with continuous positive airway pressure. * Inability to complete polysomnography or invalid data. * Malignancy or life expectancy \< 1 year.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Incidence of Major Adverse Cardiovascular and Cerebrovascular Events (MACCE) | 12 Months |
Contacts
CONTACTWei Gong
Outcome results
None listed