Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros










Base de dados
Intervalo de ano de publicação
1.
Hepatol Res ; 51(4): 490-502, 2021 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-33227168

RESUMO

AIM: The aim of this study was to use a metabonomics approach to identify potential biomarkers of exhaled breath condensate (EBC) for predicting the prognosis of acute-on-chronic liver failure (ACLF). METHODS: Using liquid chromatography mass spectrometry, EBC metabolites of ACLF patients surviving without liver transplantation (n = 57) and those with worse outcomes (n = 45), and controls (n = 15) were profiled from a specialized liver disease center in Beijing. The metabolites were used to identify candidate biomarkers, and the predicted performance of potential biomarkers was tested. RESULTS: Forty-one metabolites, involving glycerophospholipid metabolism, sphingolipid metabolism, arachidonic acid metabolism, and amino acid metabolism, as candidate biomarkers for discriminating the different outcomes of ACLF were selected. A prognostic model was constructed by a panel of four metabolites including phosphatidylinositol [20:4(5Z,8Z,11Z,14Z)/13:0], phosphatidyl ethanolamine (12:0/22:0), L-metanephrine and ethylbenzene, which could predict the worse prognosis in ACLF patients with sensitivity (84.4%) and specificity (89.5%) (area under the receiver operating characteristic curve [AUC] = 0.859, 95% confidence interval [CI] = 0.787-0.931). Compared with Model for End-Stage Liver Disease (MELD) score (AUC = 0.639, 95% CI = 0.526-0.753) and MELD-sodium (MELD-Na) score (AUC = 0.692, 95% CI = 0.582-0.803), EBC-associated metabolite signature model could better predict worse outcomes in patients with ACLF (p < 0.05). Using the MELD-Na score and EBC metabolite signatures, a decision tree model was built for predicting the prognosis of ACLF identified on logistic regression analyses (AUC = 0.906, 95% CI = 0.846-0.965). CONCLUSION: EBC metabolic signatures show promise as potential biomarkers for predicting worse prognosis of ACLF.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...