Zhongnan Hospital of Wuhan University
Wuhan, Hubei, 430071, China
NCT Number: NCT06626724
Background: This study aimed to develop a predictive model for delayed graft function (DGF) in liver transplant patients with hepatocellular carcinoma (HCC) based on preoperative biochemical indicators, using both logistic regression and XGBoost machine learning algorithms.
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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Notify Me18 day–75 day
All sexes
Observational
Wuhan, Hubei, 430071, China
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Liver transplantation for patients with hepatocellular carcinoma.
Time frame: Results of biochemical examination on the 7th day after liver transplantation in patients with hepatocellular carcinoma.
Jian You
Other
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