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AI-ECG for One-Year Mortality Risk Prediction

NCT07659262 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 461982

Last updated 2026-06-24

No results posted yet for this study

Summary

Cardiovascular disease (CVD) remains one of the leading causes of death worldwide. While the electrocardiogram (ECG) is a standard, widely accessible tool for cardiovascular screening, traditional risk assessment models often rely heavily on blood test results, which may be unavailable in electronic health records (EHRs). To address this limitation, the Chang Gung ECG Mortality Risk Prediction Software, an artificial intelligence (AI)-based Software as a Medical Device (SaMD), was developed. The software analyzes standard 10-second, 12-lead resting ECG signals to predict the probability of cardiac-related mortality within one year.

This study is a multicenter retrospective cohort study designed to validate the clinical performance of the AI software. Researchers will analyze retrospectively collected ECG data from patients aged 20 years or older with suspected cardiovascular disease across three hospitals in Taiwan. The AI model's predictions will be compared with the actual one-year mortality outcomes documented in the patients' medical records. The primary objective is to determine whether the AI model can accurately and consistently stratify patients according to their risk of cardiac-related mortality (e.g., heart failure, arrhythmia, and myocardial infarction), with an area under the receiver operating characteristic curve (AUC) greater than 0.80. The software is intended to serve as a clinical decision-support tool for long-term risk stratification in non-acute clinical settings, thereby assisting physicians in clinical decision-making and long-term patient management.

Conditions

  • Electrocardiogram
  • Mortality Risk Prediction

Interventions

DEVICE

Chang Gung ECG Mortality Risk Prediction Software (Model: CGMH-DRP-001)

A stand-alone 1D-ResNet-18 deep learning software that analyzes 10-second, 12-lead resting ECG signals to predict the one-year mortality risk associated with cardiac diseases.

Sponsors & Collaborators

  • Kaohsiung Armed Forces General Hospital

    collaborator OTHER

  • Taipei Medical University WanFang Hospital

    collaborator OTHER

  • National Defense Medical Center, Taiwan

    lead OTHER

Principal Investigators

  • Chin Lin, PhD · National Defense Medical Center

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-04-01
Primary Completion
2025-07-21
Completion
2025-07-21

Countries

  • Taiwan

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07659262 on ClinicalTrials.gov