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A nomogram for prediction of early allograft dysfunction in living donor liver transplantation
Liver transplantation is the treatment of choice for end-stage liver diseases. However, early allograft dysfunction (EAD) is frequently encountered and associated with graft loss or mortality after transplantation. This study aimed to establish a predictive model of EAD after living donor liver tran...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571974/ https://www.ncbi.nlm.nih.gov/pubmed/33080739 http://dx.doi.org/10.1097/MD.0000000000022749 |
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author | Ko, Yu-Chen Tsai, Hsin-I Lee, Chao-Wei Lin, Jr-Rung Lee, Wei-Chen Yu, Huang-Ping |
author_facet | Ko, Yu-Chen Tsai, Hsin-I Lee, Chao-Wei Lin, Jr-Rung Lee, Wei-Chen Yu, Huang-Ping |
author_sort | Ko, Yu-Chen |
collection | PubMed |
description | Liver transplantation is the treatment of choice for end-stage liver diseases. However, early allograft dysfunction (EAD) is frequently encountered and associated with graft loss or mortality after transplantation. This study aimed to establish a predictive model of EAD after living donor liver transplantation. A total of 77 liver transplants were recruited to the study. Multivariate analysis was utilized to identify significant risk factors for EAD. A nomogram was constructed according to the contributions of the risk factors. The predictive values were determined by discrimination and calibration methods. A cohort of 30 patients was recruited to validate this predictive model. Four independent risk factors, including donor age, intraoperative blood loss, preoperative alanine aminotransferase (ALT), and reperfusion total bilirubin, were identified and used to build the nomogram. The c-statistics of the primary cohort and the validation group were 0.846 and 0.767, respectively. The calibration curves for the probability of EAD presented an acceptable agreement between the prediction by the nomogram and the actual incidence. In conclusion, the study developed a new nomogram for predicting the risk of EAD following living donor liver transplantation. This model may help clinicians to determine individual risk of EAD following living donor liver transplantation. |
format | Online Article Text |
id | pubmed-7571974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-75719742020-10-29 A nomogram for prediction of early allograft dysfunction in living donor liver transplantation Ko, Yu-Chen Tsai, Hsin-I Lee, Chao-Wei Lin, Jr-Rung Lee, Wei-Chen Yu, Huang-Ping Medicine (Baltimore) 7100 Liver transplantation is the treatment of choice for end-stage liver diseases. However, early allograft dysfunction (EAD) is frequently encountered and associated with graft loss or mortality after transplantation. This study aimed to establish a predictive model of EAD after living donor liver transplantation. A total of 77 liver transplants were recruited to the study. Multivariate analysis was utilized to identify significant risk factors for EAD. A nomogram was constructed according to the contributions of the risk factors. The predictive values were determined by discrimination and calibration methods. A cohort of 30 patients was recruited to validate this predictive model. Four independent risk factors, including donor age, intraoperative blood loss, preoperative alanine aminotransferase (ALT), and reperfusion total bilirubin, were identified and used to build the nomogram. The c-statistics of the primary cohort and the validation group were 0.846 and 0.767, respectively. The calibration curves for the probability of EAD presented an acceptable agreement between the prediction by the nomogram and the actual incidence. In conclusion, the study developed a new nomogram for predicting the risk of EAD following living donor liver transplantation. This model may help clinicians to determine individual risk of EAD following living donor liver transplantation. Lippincott Williams & Wilkins 2020-10-16 /pmc/articles/PMC7571974/ /pubmed/33080739 http://dx.doi.org/10.1097/MD.0000000000022749 Text en Copyright © 2020 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 |
spellingShingle | 7100 Ko, Yu-Chen Tsai, Hsin-I Lee, Chao-Wei Lin, Jr-Rung Lee, Wei-Chen Yu, Huang-Ping A nomogram for prediction of early allograft dysfunction in living donor liver transplantation |
title | A nomogram for prediction of early allograft dysfunction in living donor liver transplantation |
title_full | A nomogram for prediction of early allograft dysfunction in living donor liver transplantation |
title_fullStr | A nomogram for prediction of early allograft dysfunction in living donor liver transplantation |
title_full_unstemmed | A nomogram for prediction of early allograft dysfunction in living donor liver transplantation |
title_short | A nomogram for prediction of early allograft dysfunction in living donor liver transplantation |
title_sort | nomogram for prediction of early allograft dysfunction in living donor liver transplantation |
topic | 7100 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571974/ https://www.ncbi.nlm.nih.gov/pubmed/33080739 http://dx.doi.org/10.1097/MD.0000000000022749 |
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