Developing a Model to Predict Depression After Coronary Artery Bypass Graft Surgery Using Patient Data

What this Trial Is About

Researchers are working to develop a predictive model for clinically significant depressive symptoms CSDS in patients undergoing coronary artery bypass graft CABG surgery. CSDS affect about 30% of these patients, which is much higher than in the general population, and are linked to poorer quality of life and higher risks of illness and death. This project aims to use pre- and perioperative data to identify patients at risk for depression after surgery, helping clinicians make better prevention and management decisions. The study involves recruiting 350 patients from two hospitals undergoing elective off-pump CABG or CABG with or without valve intervention. Participants will be divided into a training group of 200 and a test group of 100 to develop and validate the prediction model. Data will include demographic, psychometric, medical, inflammation, and cardiac interoception information, analyzed using machine learning. The model will predict depression symptoms 6 weeks after surgery. Participants will be assessed before surgery and again 6 weeks post-surgery using questionnaires including the Patient Health Questionnaire PHQ-9, General Anxiety Disorder GAD-7 scale, PTSD Checklist PCL-5, and Short-Form Health Survey SF-12. The study will monitor mental and physical health changes and identify factors linked to postoperative depression. Participation involves following the study protocol and completing questionnaires at specified times, lasting through the 6-week post-surgery period.

Depressive Symptoms After Cardiac Surgery