An observational study in Chest Pain and Acute Coronary Syndrome, sponsored by Qilu Hospital of Shandong University. Recruiting at 1 site in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2024-11-12.
Sponsored by Qilu Hospital of Shandong University · Observational
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.
1,461 studies on the registry are indexed under Acute Coronary Syndrome; 267 are open to participants now.
This study's planned enrollment of 8,000 is above the median of 500 across 561 observational studies indexed under Acute Coronary Syndrome.
Browse Acute Coronary Syndrome studies →Qilu Hospital of Shandong University is the lead sponsor of 299 studies on the registry; 181 are open to participants now.
Counted across the registry records on this site, refreshed daily.
patients who suffers from acute chest pain suspected with acute coronary syndrome (ACS)
Exclusion Criteria:
machine learning algorithm based on ECG features
Other: Cardiodynamicsgram (CDG)
Cardiodynamicsgram (CDG) technique
The efficacy of CDG in the risk stratification of patients who have symptoms of acute chest pain suspected with acute coronary syndrome （ACS)
Establishing an algorithm model of CDG in risk stratification in chest pain patients, the efficacy of the model was assessed by sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and AUC, etc.
Time frame: from the date of enrollment until the date of discharge, up to 30 days
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Qilu Hospital of Shandong University