Clinical Outcomes of Patients With Coronary Artery Disease

Coronary heart disease (CHD) stands as a foremost contributor to global mortality, characterized by complex pathogenesis that renders conventional "one-size-fits-all" preventive strategies inefficient. Therefore, the investigators designed a prospective, multi-center cohort study among patients hospitalized due to either confirmed or suspected CHD, which aimed to establish a holographic data set for the diagnosis and treatment of CHD and explore the impact of critical therapeutic strategies in the real world on the clinical outcomes of CHD patients, providing evidence to optimize the management pathway.

Coronary heart disease (CHD) stands as a foremost contributor to global mortality. Despite the increasing investment in the prevention of risk factors and the popularization of percutaneous coronary intervention (PCI), the age-standardized incidence and mortality of CHD continue to increase. CHD is characterized by complex pathogenesis, rendering conventional "one-size-fits-all" preventive strategies inefficient. Currently, there is a need to address two critical challenges. The first centers on early detection, precise risk stratification, and personalized intervention strategies for high-risk CHD patients, with a focus on the exploration of inflammation-driven risks, lesion-based risk stratification, and tailored anti-thrombotic therapies. The second challenge lies in the transformation of clinical risk assessment and decision-making processes into a precise level through the utilization of big data mining techniques. Therefore, the investigators designed a prospective, multi-center cohort study among patients hospitalized due to either confirmed or suspected CHD, which aimed to establish a holographic data set for the diagnosis and treatment of CHD and explore the impact of critical therapeutic strategies in the real world on the clinical outcomes of CHD patients, providing evidence to optimize the management pathway.