ArticleEuropean journal of medical research2025
Predicting post-liver transplantation mortality: a retrospective cohort study on risk factor identification and prognostic nomogram construction.
Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundTo identify risk factors for post-transplant mortality and develop a machine learning-integrated prognostic tool to optimise clinical decision-making in liver transplantation (LT) recipients.
methodsThis retrospective cohort study analysed 173 allogeneic LT recipients at the Affiliated Hospital of Zunyi Medical University between August 2019 and December 2023. Clinical and biochemical variables were systematically collected, including recipient profiles [age, gender, prior abdominal surgery Performance Status (PS) scores], biochemical markers (serum creatinine, sodium, albumin, total bilirubin, neutrophil/lymphocyte counts), and prognostic scores [Model for End-Stage Liver Disease (MELD), MELD-sodium (MELD-Na), Child-Turcotte-Pugh (CTP), neutrophil-to-lymphocyte ratio (NLR), and albumin-bilirubin (ALBI)]. Intraoperative metrics, such as blood loss volume and anhepatic phase duration, were also recorded. Univariate and multivariate Cox regression identified mortality predictors. LASSO-regularised Cox regression facilitated variable selection and nomogram construction. Internal validation used decision curve analysis (quantifying clinical net benefit) and time-dependent receiver operating characteristic (ROC) curve analysis [12/18/24-month area under the curve (AUC)]. Kaplan-Meier survival analysis stratified patients into tertiles.
resultsUnivariate analysis identified MELD score > 25, blood loss > 5 L, PS score, neutrophil count, total bilirubin level, and MELD-Na score as significant predictors (p < 0.05). Multivariate Cox regression confirmed massive haemorrhage (> 5 L) as an independent mortality predictor (p < 0.001). LASSO-selected predictors (prior abdominal surgery, blood loss > 5 L, and ALBI score) formed a prognostic nomogram demonstrating strong discrimination (1-year AUC: 0.824; 2-year AUC: 0.788). Tertile-based stratification revealed significant intergroup differences in survival (p < 0.001).
conclusionsMassive intraoperative haemorrhage independently predicted post-LT mortality. The validated nomogram integrating surgical history, haemorrhage severity, and ALBI score enables clinically actionable risk stratification, potentially informing perioperative resource allocation and personalised management protocols.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.