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Clinical Trial Details — Status: Active, not recruiting

Administrative data

NCT number NCT05018715
Other study ID # XMa0001
Secondary ID
Status Active, not recruiting
Phase
First received
Last updated
Start date August 22, 2021
Est. completion date December 31, 2023

Study information

Verified date September 2021
Source First Affiliated Hospital of Xinjiang Medical University
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Based on the clinical data of patients, a machine learning model for coronary heart disease diagnosis was established to evaluate whether the model could improve the accuracy of coronary heart disease diagnosis, and to evaluate its authenticity, reliability and benefits.


Description:

A total of 300 patients with CHD WHO were hospitalized in the First Affiliated Hospital of Xinjiang Medical University from August 2021 to February 2022 were selected, all of whom met the DIAGNOSTIC criteria of CHD formulated by the World Health Organization (WHO) and excluded diseases such as highly severe valvular disease and congenital heart disease.A total of 300 healthy subjects from the First Affiliated Hospital of Xinjiang Medical University during the same period were selected as controls.Observation indicators included: Clinical indicators collected included: General conditions: gender, age, medical history;Blood biochemical indexes, such as blood routine, liver function, kidney function, blood lipid, blood glucose, myocardial markers, electrolyte, serum creatinine concentration, body mass index, BNP and other indicators;Related tests such as ELECTROcardiogram, holter electrocardiogram, cardiac ultrasound (left atrial diameter, ascending aorta, ventricular septal thickness, left posterior wall thickness, right ventricular diameter, ejection fraction, abnormal ventricular wall motion, evidence of infarction or ischemia, valve abnormality, congenital heart disease, etc.);Signs include: audio data of heart sounds in nine parts of precardiac area;Medication status.All blood biochemical indexes and examinations were completed in the laboratory department and ultrasound department of our hospital, and the physical signs were completed in the ward.The results of coronary angiography, pre-hospital and post-hospital echocardiography and other related data were recorded.Machine learning model was constructed based on clinical data to assist diagnosis of patients with coronary heart disease


Recruitment information / eligibility

Status Active, not recruiting
Enrollment 600
Est. completion date December 31, 2023
Est. primary completion date December 31, 2023
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years to 100 Years
Eligibility Inclusion Criteria: - Patients who meet the diagnostic criteria for CHD set by the World Health Organization Exclusion Criteria: - Exclude serious valvular disease, congenital heart disease, respiratory system and other diseases.

Study Design


Intervention

Diagnostic Test:
Machine learning model diagnosis
Machine learning model diagnosis

Locations

Country Name City State
China The first affiliated Hospital of Xinjiang Medical University Ürümqi Xinjiang

Sponsors (2)

Lead Sponsor Collaborator
Xiang Ma Shihezi University

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary make a definite diagnosis of CHD Based on the patient's typical angina pectoris symptoms, combined with the patient's age and coronary heart disease risk factors, and excluding other causes of angina pectoris, a preliminary diagnosis can be established. Coronary CTA, coronary angiography and other examinations find direct evidence of coronary artery stenosis, which can confirm the diagnosis 2021-2023
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