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Deep learning-based CT radiomics method for discriminating the risk stratification of severe coronary artery calcification:A multicenter, prospective study

Intelligent imaging assessment and risk warning of cardiovascular and cerebrovascular diseases

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300069164
Enrollment
Unknown
Registered
2023-03-08
Start date
2023-04-01
Completion date
Unknown
Last updated
2023-05-22

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

Conditions

Coronary heart disease

Interventions

Group of severe coronary artery calcification :None

Sponsors

Qilu Hospital of Shandong University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
30 Years to 90 Years

Inclusion criteria

Inclusion criteria: (1) age >18,male and female; (2) Patients with known or suspected CAD; (3) Agaston calcium score >400; (4) Patients provided signed informed consent.

Exclusion criteria

Exclusion criteria: (1) Coronary artery calcification score 3 times the upper limit of normal), severe renal insufficiency (creatinine > 134µmol/L or estimated glomerular filtration rate < 60ml/min/1.73m2); (9) severe chronic obstructive pulmonary disease or asthma; (10) serious non-cardiovascular diseases (malignancies, thyroid diseases, infections, connective tissue diseases); (11) Those who are allergic to the related drug ingredients of this study; (12) Pregnant or lactating women; (13) mental retardation or mental disorders; (14) refuse to sign informed consent; (15) Loss of follow-up.

Design outcomes

Primary

MeasureTime frame
all-cause death;cardiac death;acute myocardial infarction;Unplanned revascularization;Heart failure readmission;—

Countries

China

Contacts

Public ContactMei Zhang

Qilu Hospital of Shandong University

daixh@sina.vip.com+86 18560086629

Outcome results

None listed

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