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A panel of biomarkers in the prediction for early allograft dysfunction and mortality after living donor liver transplantation.
Tsai, Hsin-I; Lo, Chi-Jen; Lee, Chao-Wei; Lin, Jr-Rung; Lee, Wei-Chen; Ho, Hung-Yao; Tsai, Chia-Yi; Cheng, Mei-Ling; Yu, Huang-Ping.
Afiliação
  • Tsai HI; Department of Anesthesiology, Chang Gung Memorial Hospital Taoyuan 333, Taiwan.
  • Lo CJ; College of Medicine, Chang Gung University Taoyuan 333, Taiwan.
  • Lee CW; Metabolomics Core Laboratory, Healthy Aging Research Center, Chang Gung University Taoyuan 333, Taiwan.
  • Lin JR; College of Medicine, Chang Gung University Taoyuan 333, Taiwan.
  • Lee WC; Department of General Surgery, Chang Gung Memorial Hospital Taoyuan 333, Taiwan.
  • Ho HY; Clinical Informatics and Medical Statistics Research Center and Graduate Institute of Clinical Medicine, Chang Gung University Taoyuan 333, Taiwan.
  • Tsai CY; Department of General Surgery, Chang Gung Memorial Hospital Taoyuan 333, Taiwan.
  • Cheng ML; Department of Liver and Transplantation Surgery, Chang-Gung Memorial Hospital, Chang-Gung University College of Medicine Taoyuan 333, Taiwan.
  • Yu HP; Metabolomics Core Laboratory, Healthy Aging Research Center, Chang Gung University Taoyuan 333, Taiwan.
Am J Transl Res ; 13(1): 372-382, 2021.
Article em En | MEDLINE | ID: mdl-33527031
ABSTRACT
Early allograft dysfunction (EAD) is associated with graft failure and mortality after living donor liver transplantation (LDLT). In this study, we report biomarkers superior to other conventional clinical markers in the prediction of EAD and all-cause in-hospital mortality in LDLT patient cohort. Blood samples of living donor liver transplant recipients were collected on postoperative day 1 and analyzed by liquid chromatography coupled with mass spectrometry (LC-MS). Significant metabolites associated with the prediction of EAD were identified using orthogonal projection to latent structures-discriminant analysis (OPLS-DA). A few lipids, more specifically, lysoPC (160), PC (180/205), betaine and palmitic acid (C160) were found to effectively differentiate EAD from non-EAD on postoperative day 1. A combination of these four metabolites showed an AUC of 0.821, which was further improved to 0.846 by the addition of a clinical parameter, total bilirubin. The panel exhibits a high prognostic accuracy in prediction of all-cause in-hospital mortality and mortality within 7 postoperative days with AUCs of 0.843 and 0.954. These results show the combination of metabolomics-derived biomarkers and clinical parameters demonstrates the power of panels in diagnostic and prognostic evaluation of LDLT.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Am J Transl Res Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Am J Transl Res Ano de publicação: 2021 Tipo de documento: Article