ArticleAnnals of medicine2025
The evaluation of inflammatory and immune composite markers for complications after deceased donor liver transplantation - a retrospective cohort study.
Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Mechanistic insights into neutrophil involvement in liver transplant ischemia-reperfusion injury and rejection.Frontiers in immunology · 2026Review
- Interpretable machine learning model for early complication prediction after split liver transplantation.World journal of gastroenterology · 2025Article
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Authors and funding
7 authors.
Funding
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Abstract
backgroundInflammation-immune composite markers have been increasingly investigated in various diseases, but their value in the setting of deceased donor liver transplantation remains insufficiently investigate.
methodA retrospective cohort study was conducted on deceased donor liver transplant recipients at Zunyi Medical University. Univariate and multivariate logistic regression analyses identified independent risk factors for major complications. A nomogram was constructed based on these factors. Model performance was evaluated using ROC curve, calibration curve, decision curve analysis, and clinical impact curve.
resultsPreoperative factors such as donor age, MLR, Anhepatic, Total Cholesterol, CIT, CAR, Lactate, and SII were identified as independent risk factors for postoperative complications with CD ≥ III but < IV, as well as CD ≥ IV complications. The Nomogram based on these results demonstrated good predictive ability and stability in the Bootstrap validation.
conclusionPreoperative MLR and SII showed good predictive ability for postoperative complications graded as CD ≥ III but < IV, while CAR was predictive of CD ≥ IV complications and was associated with EAD and prolonged ICU stay. MLR was an independent risk factor for 90-day postoperative mortality. The nomogram of major outcomes requires further validation in multi-center studies.
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