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

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.

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Key information

Conditions

Chest Pain Acute Coronary Syndrome Cardiovascular Diseases Heart Diseases Myocardial Ischemia Neurologic Manifestations Pain Pathological Conditions, Signs and Symptoms Signs and Symptoms Vascular Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Qilu Hospital of Shandong University

Jinan, Shandong, 250012, China

Location status: Recruiting

Location contact

Jiaojiao Pang, Doctor

CONTACT

[email protected]

0086-0531-82165674

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

aged 18 years or older
Those with suspected ACS who have symptoms of acute chest pain, visiting in the emergency department

Exclusion criteria

Those who diagnosed with ST-segment elevation myocardial infarction (STEMI)
Those with hemodynamic instability (cardiogenic shock, cardiac arrest)
Those with malignant arrhythmias(ventricular tachycardia, ventricular fibrillation, third-degree atrioventricular block)
Those with aortic coarctation, or acute pulmonary embolism
Those who has an unanalysable ECG report due to loosened leads, unstable baseline, or signal interference, etc.

Treatment and study plan

Cardiodynamicsgram (CDG)

Other

Cardiodynamicsgram (CDG) technique

Primary outcomes

The efficacy of CDG in the risk stratification of patients who have symptoms of acute chest pain suspected with acute coronary syndrome （ACS)

Time frame: from the date of enrollment until the date of discharge, up to 30 days

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.

Study contacts

Contact information is provided by the study sponsor or research team.

Jiaojiao Pang, Doctor

CONTACT

[email protected]

0086-0531-82165674

Sponsors and collaborators

Lead sponsor

Qilu Hospital of Shandong University

Other

Registry information

Important dates

Study start: 2021
Primary completion: 2024
Study completion: 2024
First posted: Nov 1, 2024
Registry last updated: Nov 12, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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