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Updated: Jun 3, 2026
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Human Liver Microphysiological System for Assessing Drug-Induced Liver Toxicity In Vitro
Published on: January 31, 2022
Development and Internal Validation of a Web-Based Dynamic Nomogram for Dynamic Risk Stratification of Early
Trung Dinh Ngo1, Thu Thi Nguyen1, Khanh Nam Le1
1Surgical and Transplant Intensive Care Unit, Military Central Hospital 108, Hanoi, Vietnam.
Annals of Transplantation
|June 2, 2026
Summary
A new dynamic tool helps predict early bacterial infections after liver transplants. It uses routine clinical data to estimate individual patient risk, improving early detection and management of post-transplant infections.
Area of Science:
- Transplantation research
- Infectious disease epidemiology
- Medical informatics
Background:
- Early bacterial infections are a significant complication following living donor liver transplantation (LDLT).
- Current tools for individualized risk stratification of these infections are limited in clinical practice.
- Accurate early risk assessment is crucial for timely intervention and improved patient outcomes.
Purpose of the Study:
- To develop and validate a dynamic risk stratification tool for predicting early bacterial infections after LDLT.
- To identify independent predictors of early bacterial infection in LDLT recipients.
- To implement the tool as static and web-based dynamic nomograms for clinical use.
Main Methods:
- A retrospective cohort study of 205 adult LDLT recipients with 30-day follow-up.
- Univariable and multivariable logistic regression to identify infection predictors.
- Receiver operating characteristic (ROC) analysis, calibration, and decision curve analysis for model performance evaluation.
- Construction of static and web-based dynamic nomograms.
Main Results:
- Early bacterial infections occurred in 21.9% of patients.
- Independent predictors included higher pre-transplant MELD score, post-transplant blood transfusion, bile leakage, and longer ICU stay.
- The dynamic tool showed good discrimination (AUC=0.792) and calibration.
- The web-based nomogram allowed real-time, individualized risk estimation.
Conclusions:
- A validated dynamic risk stratification tool for early bacterial infections post-LDLT was developed.
- The tool provides evolving postoperative risk assessment, outperforming fixed-time predictions.
- External validation is necessary to confirm performance and generalizability before widespread clinical adoption.
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