NCT06231797

AI-ECG Screening for Left Ventricular Systolic Dysfunction

AI-ECG Screening for Left Ventricular Systolic Dysfunction: A Prospective, Observational, Multicenter Study

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 1,530 (estimated)
• Sponsor: Seoul National University Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: —

Summary

The purpose of the current study is to verify the effectiveness of the artificial intelligence algorithm applied to the electrocardiogram as a potential screening tool for left ventricular systolic dysfunction.

Detailed description

The current investigators have developed an artificial intelligence (AI) algorithm based on 12-lead electrocardiogram (ECG) detecting left ventricular systolic dysfunction, through 364,845 ECGs from 148,547 patients. Then, when the model was tested retrospectively on 59,805 ECGs of 24,376 patients, the model performance expressed as an area under the receiver operating characteristic curve was 0.889 (95% CI 0.887-0.891). The investigators are planning to prospectively validate the model's effectiveness as a potential screening tool for left ventricular systolic dysfunction.

Conditions

• Left Ventricular Systolic Dysfunction

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	AI algorithm conducted on 12-lead ECG and transthoracic echocardiography	12-lead ECG is performed for each patient. For 12-lead ECG, AITIALVSD (AI algorithm) analysis will be performed through a separate server.

Timeline

• Start date: 2024-02-01
• Primary completion: 2024-07-10
• Completion: 2025-07-10
• First posted: 2024-01-30
• Last updated: 2024-02-05