AI-ECG for Preoperative Cardiovascular Risk Stratification Before General Surgery

NCT07774689 | Not Yet Recruiting

• 1 other identifier: B-2603-1033-001
• Study Type: interventional
• Target: 3,200
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Perioperative Cardiovascular Risk; Postoperative Complications (Cardiopulmonary); Preoperative Care

Keywords

Artificial intelligence; Electrocardiography; Perioperative cardiovascular risk; Preoperative evaluation; Major adverse cardiovascular events

Outcome Measures

Primary Outcomes (1)

• Incidence of major adverse cardiovascular events (MACE) 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.

  Within 30 days after surgery

Secondary Outcomes (5)

• Rate of preoperative cardiac imaging and functional testing

  From randomization to surgery, up to 24 weeks

• 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

Study Arms (2)

AI-ECG-guided preoperative strategy

EXPERIMENTAL

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.

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

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.

Interventions

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.

AI-ECG-guided preoperative strategy

Eligibility Criteria

• Age: 20 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

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

You may not qualify if:

• Emergency surgery
• Surgery under local anesthesia

Sponsors & Collaborators

• Seoul National University Bundang Hospital: lead

Study Sites (1)

Seoul National University Bundang Hospital

Seongnam-si, Gyeonggido, 13620, South Korea

Location

Related Publications (3)

• 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 BACKGROUND

• 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 BACKGROUND

• 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 BACKGROUND

MeSH Terms

Conditions

Postoperative Complications

Condition Hierarchy (Ancestors)

Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Ji Hyun Lee, MD

  Seul National University Bundang Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Ji Hyun Lee, MD

CONTACT

82-31-787-7045; jihyunlee310@snubh.org

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Masking Details: Open-label treatment assignment with blinded endpoint adjudication (PROBE design). Outcomes are adjudicated by an independent committee blinded to treatment allocation.
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 5, 2026
• First Posted: August 19, 2026
• Study Start: September 1, 2026
• Primary Completion (Estimated): May 31, 2029
• Study Completion (Estimated): May 31, 2029
• Last Updated: August 19, 2026

Record last verified: 2026-08

Locations

KR (1)