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Use of Determine Learning-based Cardiodynamicsgram (CDG) for Rapid and Precise Stratification of Chest Pain in Emergency Department

NCT06669884 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 8000

Last updated 2024-11-12

No results posted yet for this study

Summary

Chest pain accounts for 10-20 percent of all emergency department visits. The stratification of chest pain is always a challenge. Electrocardiograms (ECG) have been used in clinical practice for 100 years, which is too important to be replaced due to its advantages of non-invasive, simple, rapid and inexpensive. ECG contains numerous signals derived from depolarization and repolarization of cardiomyocytes. However, the interpretation of ECG hasn't improved much in a hundred years. Based on determine-learning, Cong W's team developed an technique called "cardiodynamicsgram (CDG)", which is an outstanding method to identify myocardial ischemia. This study will further investigate the accuracy of CDG in stratification of patients with chest pain in Emergency department.

Conditions

Interventions

OTHER

Cardiodynamicsgram (CDG)

Cardiodynamicsgram (CDG) technique

Sponsors & Collaborators

  • Qilu Hospital of Shandong University

    lead OTHER

Principal Investigators

  • Yuguo Chen, Professor · Qliu Hospital of Shandong University

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-10-28
Primary Completion
2024-09-30
Completion
2024-10-31

Countries

  • China

Study Locations

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Entities

Diseases

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 NCT06669884 on ClinicalTrials.gov