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Study for Machine-Learning Based Prognosis Prediction Model for Acute Stanford Type A Aortic Dissection Patients After Surgery

Study for Machine-Learning Based Prognosis Prediction Model for Acute Stanford Type A Aortic Dissection Patients After Surgery

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000033489
Enrollment
Unknown
Registered
2020-06-02
Start date
2020-07-01
Completion date
Unknown
Last updated
2020-08-03

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

Conditions

Acute Stanford type A aortic dissection

Interventions

Gold Standard:Clinical outcome
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Prognosis&#32
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Stanford&#32
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Dissection&#32
Patients&#32
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surgery

Sponsors

Zhongshan Hospital affiliated to Shanghai Fudan University
Lead Sponsor

Eligibility

Sex/Gender
Male

Inclusion criteria

Inclusion criteria: All patients with acute type A aortic dissection who received cardiac surgery at Zhongshan Hospital.

Exclusion criteria

Exclusion criteria: Patients with inaccessible preoperative assessment data.

Design outcomes

Primary

MeasureTime frame
acute kidney injury;postoperative pulmonary complications;ICU LOS;death;stroke;heart failure;coagulation disorder;SEN, SPE, ACC, AUC of ROC;—

Countries

China

Contacts

Public ContactGuo Kefang

Zhongshan Hospital affiliated to Shanghai Fudan University

604494092@qq.com+8613817706936

Outcome results

None listed

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