Association Between Cardiovascular Diseases and Mental Illness

Overview

Cardiovascular diseases (CVD) are important public health concerns around the world and closely associated with the development and progression of mental illness, which in turn increases the risk of developing cardiovascular diseases. This study aimed (1) to explore the known or unknown protective and risk factors underlying this comorbidity using questionnaires; (2) to study the biomarkers (body fluid, imaging) of the participants, and to find the influence on the relationship between CVD and mental health; (3) to identify high-risk populations for mental disorders in CVD patients and to establish prediction models. (4) to establish a specialized medical database.

Patients with depression and cardiovascular comorbidities have a worse prognosis, a sharply reduced quality of life, and a much higher incidence of fatal CVD events, such as acute infarction, than patients with a single disease. However, due to the variety of potential causative factors and clinical manifestations, population variability, long duration of the disease, as well as neurological disorders of the exact causative mechanism still unclear, the psychological assessment among patients with cardiovascular diseases is remarkably inadequate studied. In this study, two cohorts are established that include 2000 hospitalized patients and 5000 of the entire population. All individuals are screened for depression and anxiety. Those who score positive will be advised to enroll in this study. Patients are then randomized to receive collaborative care involving the patient, the patient's primary care physician, cardiologist and nurse case manager, or usual care is defined for each patient. Whole blood and serum samples are obtained from all patients, which will be measured for a panel of metabolic and inflammatory indicators. Patients in both cohorts will be monitored for depression severity and duration at 6 and 12 months after enrollment. A statistical technique is applied to determine the effect size of potential risk factors.

Conditions