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Application of machine learning in assessing coronary stenosis and risk stratification before coronary angiography

Application of machine learning in assessing coronary stenosis and risk stratification before coronary angiography

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300076284
Enrollment
Unknown
Registered
2023-09-28
Start date
2023-10-01
Completion date
Unknown
Last updated
2023-10-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Coronary Heart Disease

Interventions

Gold Standard:Grouping based on coronary angiography results: Firstly,Severe coronary artery stenosis (coronary artery stenosis needs PCI or CABG treatment). secondly,moderate coronary artery or mild

Sponsors

The Second Affiliated Hospital of Zhengzhou University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
30 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1.Patients underwent coronary angiography or coronary intervention (PCI) for the first time. 2.the clinical data of patients must have the following 11 clinical data: gender, age, fasting blood glucose (FPG), low density lipoprotein (LDL), hypertension history, diabetes history, smoking history, cold sweating at the onset of disease, electrocardiogram, color Doppler ultrasound showed whether there were plaque in the neck vessels, and whether the color Doppler ultrasound showed abnormal wall motion.

Exclusion criteria

Exclusion criteria: 1. Recheck coronary angiography after interventional therapy. 2. The same patient underwent multiple PCI operations, and the clinical data after the first PCI were not selected. 3. There are no complete 11 clinical data.

Design outcomes

Primary

MeasureTime frame
fasting blood glucose;gender;Age;low density lipoprotein;hypertension history;diabetes history;smoking history;cold sweating at the onset of disease; electrocardiogram; color Doppler ultrasound showed whether there were plaque in the neck vessels;whether the color Doppler ultrasound showed abnormal wall motion;

Countries

China

Contacts

Public ContactEn Li

The Second Affiliated Hospital of Zhengzhou University

lidongfs@zzu.edu.cn+86 136 3386 2945

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026