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.
patients with ECGs and an echocardiogram within 7 days
Missing ECG signals
Missing LVEF assessment in echocardiograms
All patients with ECGs and an echocardiogram within 7 days
Cohort
Retrospective
AI-ECG Algorithm
Diagnostic testAI-ECG Algorithm to detect LVEF\<=40%
The Sensitivity and specificity of AI-ECG model for left ventricular ejection fraction ≤ 40%
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.
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