About this trial
This pilot study is designed to evaluate the clinical performance and utility of the SmartECG-EF software in patients undergoing evaluations at Inha University Hospital. The primary objective is to assess how effectively the device assists clinicians in evaluating cardiac function and related clinical parameters. The study will prospectively enroll eligible participants to gather real-world clinical data, contributing to enhanced diagnostic accuracy and patient management.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Written informed consent provided voluntarily by the subject
Age ≥ 19 years
Patients who undergo standard 12-lead ECG measurement during the study period
Subjects with sinus rhythm on ECG at the time of examination
Disqualifiers
Subjects deemed inappropriate or unlikely to comply with the study requirements by the investigator
Patients with atrial fibrillation or atrial flutter on ECG at the time of examination
Patients with pacing rhythm due to a pacemaker
Subjects with severe tremor, uncooperativity, or skin conditions that make 1-lead ECG measurement difficult
Trial population
Patients visiting Inha University Hospital who undergo standard 12-lead and additional 1-lead ECG evaluations for cardiac assessment.
Trial design
Cohort
Prospective
Treatments tested in this trial
SmartECG-EF
DeviceThe SmartECG-EF software is used to analyze 12-lead and 1-lead electrocardiogram (ECG) data to evaluate cardiac function, including left ventricular systolic dysfunction (LVSD), heart failure indicators, and related arrhythmic parameters.
Treatment groups
Trial outcomes
Primary outcomes
Correlation and Agreement between 12-Lead and 1-Lead AI Scores
To evaluate the correlation (using Pearson or Spearman correlation coefficients), agreement (ICC using absolute agreement, two-way random model), and Bland-Altman analysis (mean difference and 95% limits of agreement) between 12-lead and 1-lead based AI scores.
Secondary outcomes
Area Under the ROC Curve (AUC-ROC) of AI scores
To assess the AUC-ROC of 1-lead and 12-lead based AI results against disease-specific reference standards, including heart failure, left ventricular systolic dysfunction (LVSD), and arrhythmic parameters.
Sensitivity and Specificity of AI scores
To assess sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 1-lead and 12-lead based AI results against disease-specific reference standards, including heart failure, left ventricular systolic dysfunction (LVSD), and arrhythmic parameters.
Sponsors and contacts
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