AI-ECG for Preoperative Cardiovascular Risk Stratification Before General Surgery

NCT07774689 — Not applicable, Not yet recruiting, 3200 participants, Seoul National University Bundang Hospital

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Utilization of AI-ECG for Preoperative Cardiovascular Risk Stratification in General Surgery: A Randomized Controlled Trial

Registry	NCT07774689
Status	Not yet recruiting
Phase	Not applicable
Study type	Interventional; randomized, parallel, masking: none, health services research
Enrollment	3200 (Estimated)
Sponsor	Seoul National University Bundang Hospital (Other)
Conditions	Perioperative Cardiovascular Risk, Postoperative Complications (Cardiopulmonary), Preoperative Care
Interventions	AI-ECG-based preoperative risk stratification (ECG Buddy) (Diagnostic test)
Dates	start 2026-09-01 (estimated), primary completion 2029-05-31 (estimated), completion 2029-05-31 (estimated), first posted 2026-08-19, last updated 2026-08-19
Locations	1 site in South Korea

-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.

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+Arms and interventions

Arm	Type	Interventions	Description
AI-ECG-guided preoperative strategy	Experimental	Diagnostic Test: AI-ECG-based preoperative risk stratification (ECG Buddy)	Patients undergo preoperative cardiovascular risk stratification guided by the output of the AI-ECG device (ECG Buddy). Further preoperative cardiovascular evaluation and cardiology consultation are directed according to the AI-ECG-based assessment.
Usual care	No intervention		Patients receive usual preoperative care for cardiovascular evaluation according to standard institutional practice, without use of the AI-ECG-based strategy.

AI-ECG-based preoperative risk stratification (ECG Buddy) (Diagnostic test): 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.

+Outcome measures

Primary outcomes

Incidence of major adverse cardiovascular events (MACE) within 30 days after surgery [Within 30 days after surgery]: 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

Rate of preoperative cardiac imaging and functional testing [From randomization to surgery, up to 24 weeks]: Proportion of patients undergoing preoperative echocardiography, coronary CT, SPECT, or stress testing.
Rate of preoperative cardiology consultation [From randomization to surgery, up to 24 weeks]
Length of hospital stay [Through hospital discharge (up to 30 days)]
Direct medical costs [Within 30 days after surgery]
Time required for preoperative evaluation [From randomization to surgery, up to 24 weeks]

+Eligibility

Sex: All, ages: 20 Years to any

Inclusion Criteria:

* Adults aged 20 years or older
* Patients scheduled for elective (non-emergent) general surgery
* Willing and able to provide voluntary written informed consent

Exclusion Criteria:

* Emergency surgery
* Surgery under local anesthesia

+Locations (1)

Facility	City	Country	Status
Seoul National University Bundang Hospital	Seongnam-si, Gyeonggido	South Korea

+Publications

Cho Y, Yoon M, Kim J, Lee JH, Oh IY, Lee CJ, Kang SM, Choi DJ. Artificial Intelligence-Based Electrocardiographic Biomarker for Outcome Prediction in Patients With Acute Heart Failure: Prospective Cohort Study. J Med Internet Res. 2024 Jul 3;26:e52139. doi: 10.2196/52139. PMID 38959500
Siontis KC, Noseworthy PA, Attia ZI, Friedman PA. Artificial intelligence-enhanced electrocardiography in cardiovascular disease management. Nat Rev Cardiol. 2021 Jul;18(7):465-478. doi: 10.1038/s41569-020-00503-2. Epub 2021 Feb 1. PMID 33526938
Thompson A, Fleischmann KE, Smilowitz NR, de Las Fuentes L, Mukherjee D, Aggarwal NR, Ahmad FS, Allen RB, Altin SE, Auerbach A, Berger JS, Chow B, Dakik HA, Eisenstein EL, Gerhard-Herman M, Ghadimi K, Kachulis B, Leclerc J, Lee CS, Macaulay TE, Mates G, Merli GJ, Parwani P, Poole JE, Rich MW, Ruetzler K, Stain SC, Sweitzer B, Talbot AW, Vallabhajosyula S, Whittle J, Williams KA Sr; Peer Review Committee Members. 2024 AHA/ACC/ACS/ASNC/HRS/SCA/SCCT/SCMR/SVM Guideline for Perioperative Cardiovascular Management for Noncardiac Surgery: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2024 Nov 5;150(19):e351-e442. doi: 10.1161/CIR.0000000000001285. Epub 2024 Sep 24. PMID 39316661

+Investigators

Ji Hyun Lee, MD, Principal investigator, Seul National University Bundang Hospital