Explainable Machine Learning for the Assessment of Donor Grafts in Liver Transplantation

NCT ID: NCT06535217

Last Updated: 2024-08-02

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 5636 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2017-01-01
• Study Completion Date: 2024-06-30

Brief Summary

Clinically, organ evaluation generally performed by the senior surgeons based on their experience and the visual and tactual inspection of the graft during procurement. However, it is proved that transplant surgeons intuition in the evaluation of donor risk and the estimation of steatosis is inconsistent and usually inaccurate. Besides, graft assessment is a dynamic process refer to amount of complex factors, which is considered to be an incredibly complicated relationship that is nonlinear in nature. Unfortunately, the classical statistic techniques in vogue such as multiple regression require the statistical assumption of independent and linear relationships between explanatory and outcome variables, and fail to analyse a large number of variables. We attempted to develop liver graft assessment models by predicting postoperative DGF using several ML techniques. Secondly, the best prediction model was selected by comparing the performance of different AI algorithms and logistic regression. Finally, we sought to explain the decision made by AI algorithms using a visualization algorithm based on the best prediction model, helping clinicians evaluate specific organ and whether to receive that may develop DGF postoperatively.

Conditions

Liver Transplant; Complications

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: RETROSPECTIVE

Study Groups

DGF

patients occured delayed graft function after liver transplantation

Liver transplantation

Intervention Type: PROCEDURE

Liver transplantation

non-DGF

patients NOT occured delayed graft function after liver transplantation

Liver transplantation

Intervention Type: PROCEDURE

Liver transplantation

Interventions

Liver transplantation

Liver transplantation

Intervention Type: PROCEDURE

Eligibility Criteria

Inclusion Criteria

1. Age≥18 years-old

2. Underwent deceased donor liver transplantation

Exclusion Criteria

1. Underwent living-donor LT;

2. Missing rates of data were more than 80%

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

the China Liver Transplant Registry

UNKNOWN

Sponsor Role: collaborator

Third Affiliated Hospital, Sun Yat-Sen University

OTHER

Sponsor Role: lead

Responsible Party

Zhixing Liang

M.D.

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

The Third Affiliated Hospital of Sun Yat-Sen University

Guangzhou, Guangdong, China

Countries

China

Other Identifiers

ZSSY-2403

Identifier Type: -

Identifier Source: org_study_id