AI-ECG Supported Decision-Making for Coronary Angiography in Acute Chest Pain: The QCG-AID Study.

ABSTRACT: This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analysis system, QCG, to enhance urgent coronary angiography (CAG) decision-making for acute chest pain in the emergency department (ED). We retrospectively analyzed 300 ED cases, categorized as non-coronary chest pain (Group 1), acute coronary syndrome (ACS) without occlusive coronary artery disease (CAD) (Group 2), and ACS with occlusive CAD (Group 3). Six clinicians made urgent CAG decision using a conventional approach (clinical data and ECG) and a QCG-assisted approach (including QCG scores). The QCG-assisted approach improved correct CAG decisions in Group 2 (36.0% vs. 45.3%, P = 0.003) and Group 3 (85.3% vs. 90.0%, P = 0.017), with minimal impact in Group 1 (92.7% vs. 95.0%, <

SUBMITTER: Park J 

PROVIDER: S-EPMC11964906 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature