AI Model for Assessing Cardiac Surgeons' Techniques (CAMERA)

National Center for Cardiovascular Diseases

Status: Enrolling

Conditions: CABG-patients; CABG; Cardiovascular Surgery; Surgeons; Artificial Intelligence (AI)

Study type: Observational

Funder types: Other

Identifiers

NCT06739005

2024-ZX070

Details and patient eligibility

About

The goal of this study aims to investigate the use of artificial intelligence to analyze and evaluate the characteristics and proficiency of surgeons during vascular anastomosis in coronary artery bypass grafting (CABG) procedures. The main question it aims to answer is:

Consistency assessment between AI evaluation scores and human expert evaluation scores for surgeons during left anterior descending (LAD) artery anastomosis.

Enrollment: 284 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age ≥ 18 years
• Undergoing internal mammary artery-to-left anterior descending artery bypass grafting
• First-time recipient of isolated CABG surgery
• Signed written informed consent

Exclusion criteria

• Patients with acute coronary syndrome
• Patients with contraindications to coronary CT angiography or coronary angiography
• Patients with renal insufficiency or active liver disease, including those with persistently elevated serum transaminases of unknown cause or any serum transaminase levels exceeding three times the upper limit of normal.