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Updated: Sep 15, 2025
Porcine Liver Transplantation Without Veno-Venous Bypass As an Extended Criteria Donor Model
Published on: August 17, 2022
A Novel Nomogram Integrating Early Postoperative Hemodynamics with Perioperative Clinical Variables for Predicting
Yuan Gao1, Bingtian Dong1, Enfa Zhao1
1Department of Ultrasound, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui, China.
Rationale And Objectives:
Post-liver transplantation (LT) mortality remains significant despite surgical advances. Current prediction models show limited predictive performance for post-LT outcomes. We aimed to develop and validate a novel LT overall survival (LTOS)-nomogram integrating early postoperative hemodynamic parameters with perioperative clinical variables for predicting survival after LT.
Methods:
This single-center retrospective study included 204 recipients who underwent LT between April 2016 and December 2023. Patients were randomly divided into training (n=104) and testing (n=100) sets. The Boruta algorithm combined with least absolute shrinkage and selection operator regression identified key predictors for survival. A Cox regression-based nomogram was constructed and validated using time-dependent receiver operating characteristic curves and area under the curves (AUCs), calibration, and decision curve analysis curves.
Results:
Five key predictors were identified by both algorithms: portal vein flow and hepatic artery resistive index measured by Doppler ultrasound within 24 h post-LT, preoperative white blood cell count, portal vein thrombosis, and abdominal adhesion. Kaplan-Meier analyses demonstrated significant survival differences for patients categorized by these factors (P<0.001). The LTOS-nomogram demonstrated good predictive performance for 30-day, 90-day, and 1-year survival in both training (AUCs=0.907, 0.888, and 0.845, respectively) and testing sets (AUCs=0.847, 0.900, and 0.816, respectively), with good calibration and higher net benefit in decision curve analysis, outperforming the model for end-stage liver disease score and Child-Pugh classification. An online calculator was developed to facilitate clinical application (https://ltosproject.netlify.app).
Conclusion:
The LTOS-nomogram effectively predicts post-LT survival by integrating early postoperative hemodynamic parameters with perioperative clinical variables, providing a valuable tool for risk stratification and individualized management of LT recipients.
