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Construction and evaluation of prediction model of mace after PCI based on CCTA image characteristics and deep learning technology

Construction and evaluation of prediction model of mace after PCI based on CCTA image characteristics and deep learning technology

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600117215
Enrollment
Unknown
Registered
2026-01-21
Start date
2026-02-01
Completion date
Unknown
Last updated
2026-01-27

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

Conditions

Coronary atherosclerotic heart disease

Interventions

Observation group:N/A

Sponsors

Jiangdu People’s Hospital Affiliated to Yangzhou University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age: 18 years old and above, with no upper age limit. 2. Disease type: CCTA examination must be performed before surgery to confirm the presence of coronary artery disease (such as stable angina, acute coronary syndrome, acute myocardial infarction, etc.). 3. Treatment criteria: Patients must have undergone PCI treatment and have at least 12 months of follow-up data after the surgery is completed. 4. Image quality requirements: CCTA images must have good quality and be free of severe artifacts, motion artifacts, or image blurring, and be able to extract effective features for subsequent analysis. 5. Data integrity: The patient's imaging data, clinical information, and follow-up data are complete, ensuring the accuracy of data analysis.

Exclusion criteria

Exclusion criteria: 1.Poor image quality, missing follow-up data, patients with severe complications, and patients who cannot undergo postoperative follow-up.

Design outcomes

Primary

MeasureTime frame
Distinguishing ability (AUC);

Secondary

MeasureTime frame
clinical diagnostic efficacy (sensitivity and specificity);predictive accuracy (calibration);

Countries

China

Contacts

Public ContactMa Kaiyang

Jiangdu People’s Hospital Affiliated to Yangzhou University

362033934@qq.com+86 514 8653 2322

Outcome results

None listed

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