A Retrospective Cohort Study on Predicting Delayed Graft Function in Liver Transplant Patients with Hepatocellular Carcinoma: a Nomogram and Machine Learning Approaches.
NCT ID: NCT06626724
Last Updated: 2024-10-04
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
131 participants
OBSERVATIONAL
2020-01-01
2024-04-30
Brief Summary
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Methods: A retrospective cohort study was conducted, including 131 liver transplant patients from January 2020 to April 2022. Preoperative biochemical markers and hematological parameters were analyzed. Logistic regression and XGBoost models were constructed to predict DGF, and their performance was evaluated using the area under the ROC curve (AUC). Shapley Additive Explanations (SHAP) analysis was employed to interpret the feature contributions.
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Detailed Description
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Conditions
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Study Design
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COHORT
RETROSPECTIVE
Interventions
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Liver transplantation
Liver transplantation for patients with hepatocellular carcinoma.
Eligibility Criteria
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Inclusion Criteria
2. Patients who have received liver transplantation.
3. Complete preoperative and postoperative medical imaging data, clinical records and pathological test reports are available.
Exclusion Criteria
2. Recipients were younger than 18 years and older than 75 years
3. Due to incomplete or missing clinical data, this dataset did not meet the criteria for inclusion in the statistical analysis.
4. Serious complications associated with liver transplantation, such as acute transplant rejection or transplant liver failure, occur within 7 days after surgery.
5. Re-surgery within 7 days after surgery due to liver transplant-related complications or other surgical procedures, such as transplant site infection or other major surgery.
18 Days
75 Days
ALL
No
Sponsors
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Jian You
OTHER
Responsible Party
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Jian You
Research assistant
Locations
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Zhongnan Hospital of Wuhan University
Wuhan, Hubei, China
Countries
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Other Identifiers
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Zhongnan Hospital
Identifier Type: -
Identifier Source: org_study_id
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