Prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factor

Abstract This study was designed to build models predicting early graft failure after liver transplantation. Cox regression model for predicting early graft failure after liver transplantation using post-transplantation aspartate aminotransferase, total bilirubin, and international normalized ratio...

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Main Authors: Jinsoo Rhu, Jong Man Kim, Kyunga Kim, Heejin Yoo, Gyu-Seong Choi, Jae-Won Joh
Format: Article
Language:English
Published: Nature Publishing Group 2021-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-92298-6
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spelling doaj-ca33fcedf3684d00b0ffa4012b88638f2021-06-20T11:31:16ZengNature Publishing GroupScientific Reports2045-23222021-06-011111910.1038/s41598-021-92298-6Prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factorJinsoo Rhu0Jong Man Kim1Kyunga Kim2Heejin Yoo3Gyu-Seong Choi4Jae-Won Joh5Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of MedicineDepartment of Surgery, Samsung Medical Center, Sungkyunkwan University School of MedicineStatistics and Data Center, Research Institute for Future Medicine, Samsung Medical CenterStatistics and Data Center, Research Institute for Future Medicine, Samsung Medical CenterDepartment of Surgery, Samsung Medical Center, Sungkyunkwan University School of MedicineDepartment of Surgery, Samsung Medical Center, Sungkyunkwan University School of MedicineAbstract This study was designed to build models predicting early graft failure after liver transplantation. Cox regression model for predicting early graft failure after liver transplantation using post-transplantation aspartate aminotransferase, total bilirubin, and international normalized ratio of prothrombin time was constructed based on data from both living donor (n = 1153) and deceased donor (n = 359) liver transplantation performed during 2004 to 2018. The model was compared with Model for Early Allograft Function Scoring (MEAF) and early allograft dysfunction (EAD) with their C-index and time-dependent area-under-curve (AUC). The C-index of the model for living donor (0.73, CI = 0.67–0.79) was significantly higher compared to those of both MEAF (0.69, P = 0.03) and EAD (0.66, P = 0.001) while C-index for deceased donor (0.74, CI = 0.65–0.83) was only significantly higher compared to C-index of EAD. (0.66, P = 0.002) Time-dependent AUC at 2 weeks of living donor (0.96, CI = 0.91–1.00) and deceased donor (0.98, CI = 0.96–1.00) were significantly higher compared to those of EAD. (both 0.83, P < 0.001 for living donor and deceased donor) Time-dependent AUC at 4 weeks of living donor (0.93, CI = 0.86–0.99) was significantly higher compared to those of both MEAF (0.87, P = 0.02) and EAD. (0.84, P = 0.02) Time-dependent AUC at 4 weeks of deceased donor (0.94, CI = 0.89–1.00) was significantly higher compared to both MEAF (0.82, P = 0.02) and EAD. (0.81, P < 0.001). The prediction model for early graft failure after liver transplantation showed high predictability and validity with higher predictability compared to traditional models for both living donor and deceased donor liver transplantation.https://doi.org/10.1038/s41598-021-92298-6
collection DOAJ
language English
format Article
sources DOAJ
author Jinsoo Rhu
Jong Man Kim
Kyunga Kim
Heejin Yoo
Gyu-Seong Choi
Jae-Won Joh
spellingShingle Jinsoo Rhu
Jong Man Kim
Kyunga Kim
Heejin Yoo
Gyu-Seong Choi
Jae-Won Joh
Prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factor
Scientific Reports
author_facet Jinsoo Rhu
Jong Man Kim
Kyunga Kim
Heejin Yoo
Gyu-Seong Choi
Jae-Won Joh
author_sort Jinsoo Rhu
title Prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factor
title_short Prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factor
title_full Prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factor
title_fullStr Prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factor
title_full_unstemmed Prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factor
title_sort prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factor
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-06-01
description Abstract This study was designed to build models predicting early graft failure after liver transplantation. Cox regression model for predicting early graft failure after liver transplantation using post-transplantation aspartate aminotransferase, total bilirubin, and international normalized ratio of prothrombin time was constructed based on data from both living donor (n = 1153) and deceased donor (n = 359) liver transplantation performed during 2004 to 2018. The model was compared with Model for Early Allograft Function Scoring (MEAF) and early allograft dysfunction (EAD) with their C-index and time-dependent area-under-curve (AUC). The C-index of the model for living donor (0.73, CI = 0.67–0.79) was significantly higher compared to those of both MEAF (0.69, P = 0.03) and EAD (0.66, P = 0.001) while C-index for deceased donor (0.74, CI = 0.65–0.83) was only significantly higher compared to C-index of EAD. (0.66, P = 0.002) Time-dependent AUC at 2 weeks of living donor (0.96, CI = 0.91–1.00) and deceased donor (0.98, CI = 0.96–1.00) were significantly higher compared to those of EAD. (both 0.83, P < 0.001 for living donor and deceased donor) Time-dependent AUC at 4 weeks of living donor (0.93, CI = 0.86–0.99) was significantly higher compared to those of both MEAF (0.87, P = 0.02) and EAD. (0.84, P = 0.02) Time-dependent AUC at 4 weeks of deceased donor (0.94, CI = 0.89–1.00) was significantly higher compared to both MEAF (0.82, P = 0.02) and EAD. (0.81, P < 0.001). The prediction model for early graft failure after liver transplantation showed high predictability and validity with higher predictability compared to traditional models for both living donor and deceased donor liver transplantation.
url https://doi.org/10.1038/s41598-021-92298-6
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