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AI-ECG for Preoperative Cardiovascular Risk Stratification Before General Surgery
Sponsor: Seoul National University Bundang Hospital
Summary
This randomized controlled trial evaluates whether an artificial intelligence-enhanced electrocardiography (AI-ECG)-based strategy for preoperative cardiovascular risk stratification is noninferior to usual care in patients undergoing elective general surgery. Eligible patients are randomly assigned to either an AI-ECG-guided preoperative assessment strategy or usual preoperative care. The primary outcome is the incidence of major adverse cardiovascular events (MACE) within 30 days after surgery, defined as a composite of all-cause death, ventricular fibrillation/tachycardia or cardiac arrest, non-fatal myocardial infarction, unplanned revascularization (PCI or CABG), mechanical ventilation for ≥3 days, and acute heart failure requiring intravenous diuretics. Secondary outcomes include the rate of preoperative cardiac imaging and functional testing (echocardiography, coronary CT, SPECT, stress test), the rate of preoperative cardiology consultation, length of hospital stay, direct medical costs, and the time required for preoperative evaluation. The study aims to determine whether AI-ECG can safely guide preoperative cardiovascular evaluation while reducing unnecessary testing, resource use, and cost.
Official title: Utilization of AI-ECG for Preoperative Cardiovascular Risk Stratification in General Surgery: A Randomized Controlled Trial
Key Details
Gender
All
Age Range
20 Years - Any
Study Type
INTERVENTIONAL
Enrollment
3200
Start Date
2026-09-01
Completion Date
2029-05-31
Last Updated
2026-08-19
Healthy Volunteers
No
Conditions
Interventions
AI-ECG-based preoperative risk stratification (ECG Buddy)
A standard 12-lead ECG is analyzed by an AI-enhanced ECG algorithm (ECG Buddy) to stratify preoperative cardiovascular risk. Designated AI-ECG biomarkers are used as decision thresholds to guide subsequent preoperative cardiovascular evaluation and cardiology consultation.
Locations (1)
Seoul National University Bundang Hospital
Seongnam-si, Gyeonggido, South Korea