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

Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Observational
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.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Healthy Volunteers: f
View:

• aged 18 years or older

• Those with suspected ACS who have symptoms of acute chest pain, visiting in the emergency department

Locations
Other Locations
China
Qilu Hospital of Shandong University
RECRUITING
Jinan
Contact Information
Primary
Jiaojiao Pang, Doctor
jiaojiaopang@126.com
0086-0531-82165674
Time Frame
Start Date: 2021-10-28
Estimated Completion Date: 2024-10-31
Participants
Target number of participants: 8000
Treatments
machine learning algorithm
machine learning algorithm based on ECG features
Related Therapeutic Areas
Sponsors
Leads: Qilu Hospital of Shandong University

This content was sourced from clinicaltrials.gov