Annals of medicine · 2025
Development of a predictive nomogram for post-liver transplantation complications using clinical parameters and liver stiffness measured by sound touch elastography.
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Gao Yuan, Dong Bingtian, Wang Ying, Zhao Enfa, Liu Yu, Zhang Chaoxue
Аннотация
BACKGROUND & AIMS: Monitoring and managing complications after liver transplantation (LT) are crucial for ensuring graft and patient survival. This study aimed to investigate the association between liver stiffness measurement (LSM) and spleen stiffness measurement (SSM) by sound touch elastography (STE) with post-LT complications, and to develop a predictive post-LT complications (PLTC)-nomogram.
METHODS: We conducted a retrospective study of patients who received LT between January 2019 and March 2024. After collecting clinical parameters and STE measurements, we constructed a prediction model using univariate and multivariate logistic regression, visualized as a nomogram. Its performance was evaluated with the area under the receiver operating characteristic curve (AUC), precision-recall (PR) curve, calibration curve, and decision curve analysis (DCA). The nomogram's performance was also compared with LSM, SSM, aspartate aminotransferase-to-platelet ratio index (APRI), and fibrosis-4 index (FIB-4).
RESULTS: A total of 113 recipients were included in the study. Post-LT complications occurred in 41 (36.3%) recipients, including rejection, vascular, biliary, renal, and malignant complications. Multivariate logistic regression analysis identified five factors independently associated with post-LT complications: LSM (odds ratio [OR], 2.64; 95% confidence interval [CI], 1.60-4.35), alkaline phosphatase (OR, 1.02; 95% CI, 1.01-1.04), total bilirubin (OR, 1.08; 95% CI, 1.01-1.15), creatinine (OR, 1.04; 95% CI, 1.02-1.07), and white blood cell count (OR, 0.42; 95% CI, 0.25-0.72). These five factors were used to develop the PLTC-nomogram. The nomogram demonstrated excellent performance with an AUC of 0.968 (95% CI, 0.940-0.996), outperforming LSM (AUC = 0.846), SSM (AUC = 0.676), APRI (AUC = 0.758) and FIB-4 (AUC = 0.800). Area under the PR curve (0.951), calibration curve, and DCA further confirmed that the PLTC-nomogram provided robust diagnostic performance. The PLTC nomogram is available via an online platform (https://AYGY-PLTC.shinyapps.io/dynnomapp/).
CONCLUSIONS: The PLTC-nomogram incorporating clinical parameters and LSM by STE offers a reliable and noninvasive method for predicting post-LT complications.
METHODS: We conducted a retrospective study of patients who received LT between January 2019 and March 2024. After collecting clinical parameters and STE measurements, we constructed a prediction model using univariate and multivariate logistic regression, visualized as a nomogram. Its performance was evaluated with the area under the receiver operating characteristic curve (AUC), precision-recall (PR) curve, calibration curve, and decision curve analysis (DCA). The nomogram's performance was also compared with LSM, SSM, aspartate aminotransferase-to-platelet ratio index (APRI), and fibrosis-4 index (FIB-4).
RESULTS: A total of 113 recipients were included in the study. Post-LT complications occurred in 41 (36.3%) recipients, including rejection, vascular, biliary, renal, and malignant complications. Multivariate logistic regression analysis identified five factors independently associated with post-LT complications: LSM (odds ratio [OR], 2.64; 95% confidence interval [CI], 1.60-4.35), alkaline phosphatase (OR, 1.02; 95% CI, 1.01-1.04), total bilirubin (OR, 1.08; 95% CI, 1.01-1.15), creatinine (OR, 1.04; 95% CI, 1.02-1.07), and white blood cell count (OR, 0.42; 95% CI, 0.25-0.72). These five factors were used to develop the PLTC-nomogram. The nomogram demonstrated excellent performance with an AUC of 0.968 (95% CI, 0.940-0.996), outperforming LSM (AUC = 0.846), SSM (AUC = 0.676), APRI (AUC = 0.758) and FIB-4 (AUC = 0.800). Area under the PR curve (0.951), calibration curve, and DCA further confirmed that the PLTC-nomogram provided robust diagnostic performance. The PLTC nomogram is available via an online platform (https://AYGY-PLTC.shinyapps.io/dynnomapp/).
CONCLUSIONS: The PLTC-nomogram incorporating clinical parameters and LSM by STE offers a reliable and noninvasive method for predicting post-LT complications.