External Validation of Artificial Intelligence-enabled Electrocardiography (AI-ECG) for the Detection of Left Ventricular Dysfunction (LVD)

Not yet recruiting

• Conditions: Cardiac Disease

• Registration Number: NCT07038018
• Lead Sponsor: Tri-Service General Hospital

Brief Summary

This is a multi-center, retrospective study evaluating the performance of an artificial intelligence-enabled electrocardiography (AI-ECG) algorithm in detecting reduced left ventricular ejection fraction (LVEF ≤ 40%). All included patients from participating hospitals must have undergone a digital 12-lead electrocardiogram (ECG) and an echocardiogram with assessment of LVEF within seven days. The AI-ECG algorithm will be applied to evaluate its diagnostic performance, which will be further assessed across subgroups stratified by demographic characteristics and clinical factors.

Detailed Description

Data were collected from 13 hospitals, excluding the medical center that developed the artificial intelligence-enabled electrocardiography (AI-ECG) algorithm. The primary objective of the study was to evaluate the sensitivity and specificity of the AI-ECG model in detecting left ventricular dysfunction, defined as left ventricular ejection fraction (LVEF) ≤ 40%. To ensure clinical applicability, predefined thresholds required both sensitivity and specificity to exceed 0.80 in external validation cohorts. Sample size calculations were based on testing the null hypothesis that sensitivity equals 0.80. In the development hospital cohort, the model demonstrated a sensitivity of 0.869 and a specificity of 0.896. With a two-sided significance level (α) of 0.05 and a power of 90%, an estimated 310 cases of LVEF ≤ 40% were required.

Given that the prevalence of left ventricular dysfunction was 4% in the development hospital cohort but expected to be lower-between 2.5% and 3%-in external validation settings (i.e., regional and local hospitals), the total sample size needed to accrue the target number of cases was estimated to range between 10,333 and 12,400 patients. To achieve this, six regional hospitals and seven local hospitals were selected as external validation sites. Because both electrocardiography and echocardiography were required within a seven-day interval-leading to anticipated exclusions-approximately 1,500 patients were targeted from each regional hospital and 500 from each local hospital, resulting in a final target sample size of approximately 12,500 patients.

Study Timeline

• Status Verified: 2025-06
• Study First Submitted: 2025-06-16
• Study First Submitted QC: 2025-06-25
• Last Update Submitted: 2025-06-25
• Study First Posted: 2025-06-26
• Last Update Posted: 2025-06-26
• Study Start: 2025-08-01
• Primary Completion: 2025-08-31
• Study Completion: 2025-09-30

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 12500

Inclusion Criteria

• patients with ECGs and an echocardiogram within 7 days

Exclusion Criteria

• Missing ECG signals
• Missing LVEF assessment in echocardiograms

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
The Sensitivity and specificity of AI-ECG model for left ventricular ejection fraction ≤ 40%	within 7 days	The primary objective of the study was to evaluate the sensitivity and specificity of the artificial intelligence-enabled electrocardiography (AI-ECG) model in detecting left ventricular dysfunction, defined as left ventricular ejection fraction (LVEF) ≤ 40% as confirmed by transthoracic echocardiography.

Trial Locations

Locations (13)

Hualien Armed Forces General Hospital; 🇨🇳 Hualien City, Taiwan

Kaohsiung Armed Forces General Hospital Gangshan Branch; 🇨🇳 Kaohsiung, Taiwan

Kaohsiung Armed Forces General Hospital; 🇨🇳 Kaohsiung, Taiwan

Zuoying Armed Forces General Hospital; 🇨🇳 Kaohsiung, Taiwan

Tri-Service General Hospital Keelung Branch; 🇨🇳 Keelung, Taiwan

Tri-Service General Hospital Penghu Branch; 🇨🇳 Pengfu, Taiwan

Kaohsiung Armed Forces General Hospital Pingtung Branch; 🇨🇳 Pingtung, Taiwan

Taichung Armed Forces General Hospital Zhongqing Branch; 🇨🇳 Taichung, Taiwan

Taichung Armed Forces General Hospital; 🇨🇳 Taichung, Taiwan

Tri-Service General Hospital Beitou Branch; 🇨🇳 Taipei, Taiwan

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