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Construction of a Postoperative Risk Prediction Model for Aortic Dissection Based on Multimodal Data Fusion and Its Application in Short- and Long-Term Prognostic Assessment

Construction of a Postoperative Risk Prediction Model for Aortic Dissection Based on Multimodal Data Fusion and Its Application in Short- and Long-Term Prognostic Assessment

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600117776
Enrollment
Unknown
Registered
2026-01-28
Start date
2025-09-01
Completion date
Unknown
Last updated
2026-02-02

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

Conditions

aortic dissection

Interventions

Observation group:None

Sponsors

West China Hospital of Sichuan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Patients diagnosed with aortic dissection (AD) undergoing surgical treatment; 2. Patients aged 18 years and older; 3. Complete and extractable multimodal data (clinical, imaging, laboratory dynamic monitoring, and follow-up data missing rate <= 20%); 4. Signed informed consent and willing to participate in the study.

Exclusion criteria

Exclusion criteria: 1. Death within 30 days after surgery due to non-AD-related causes (such as trauma or malignant tumors); 2. Loss to follow-up or missing critical data (such as damaged original imaging files or incomplete follow-up records) exceeding 20% of total variables.

Design outcomes

Primary

MeasureTime frame
Outcome Indicators;Surgical data;Postoperative imaging data;Cardiac ultrasound data;Postoperative ultrasound data;

Secondary

MeasureTime frame
Electrophysiological indicators;Laboratory test indicators;

Countries

China

Contacts

Public ContactChaoyi Qin

West China Hospital of Sichuan University

qinchaoyi@wchscu.edu.cn+86 185 8328 6895

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 7, 2026