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Prediction model and risk factor analysis of postoperative complications of end-stage liver disease surgery based on machine learning

Prediction model and risk factor analysis of postoperative complications of end-stage liver disease surgery based on machine learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300075369
Enrollment
Unknown
Registered
2023-09-02
Start date
2023-09-02
Completion date
Unknown
Last updated
2023-09-04

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

Conditions

Liver transplantation

Interventions

Case group:No

Sponsors

The Second Affiliated Hospital of Dalian Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: (1) Patients with terminal stage of viral hepatitis, alcoholic cirrhosis, non-alcoholic fatty liver disease, hepatocellular carcinoma, primary sclerosing cholangitis, primary biliary cirrhosis, autoimmune hepatitis and patients with acute liver failure (2) Patients undergoing end-stage liver disease surgery

Exclusion criteria

Exclusion criteria: (1) Age= 18 years old (2) Patients who have undergone two or more liver salvage surgeries (3) Patients who have undergone 2 or more end-stage organ surgeries (4) Preoperative patients with severe pneumonia (5) Preoperative patients with cardiovascular and cerebrovascular diseases

Design outcomes

Primary

MeasureTime frame
Blood gas analysis;Blood routine;Liver function;Kidney function;CT chest;electrocardiogram;—

Secondary

MeasureTime frame
Length of hospital stay;—

Countries

China

Contacts

Public ContactXiao Zhaoyang

The Second Affiliated Hospital of Dalian Medical University

xiaozhaoy2012@163.com+86 177 0987 3399

Outcome results

None listed

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