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Prognostic Nomogram for Patients with Hepatitis E Virus-related Acute Liver Failure: A Multicenter Study in China

BACKGROUND AND AIMS: Timely and effective assessment scoring systems for predicting the mortality of patients with hepatitis E virus-related acute liver failure (HEV-ALF) are urgently needed. The present study aimed to establish an effective nomogram for predicting the mortality of HEV-ALF patients....

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Detalles Bibliográficos
Autores principales: Wu, Jian, Shi, Cuifen, Sheng, Xinyu, Xu, Yanping, Zhang, Jinrong, Zhao, Xinguo, Yu, Jiong, Shi, Xinhui, Li, Gongqi, Cao, Hongcui, Li, Lanjuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: XIA & HE Publishing Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8666371/
https://www.ncbi.nlm.nih.gov/pubmed/34966646
http://dx.doi.org/10.14218/JCTH.2020.00117
Descripción
Sumario:BACKGROUND AND AIMS: Timely and effective assessment scoring systems for predicting the mortality of patients with hepatitis E virus-related acute liver failure (HEV-ALF) are urgently needed. The present study aimed to establish an effective nomogram for predicting the mortality of HEV-ALF patients. METHODS: The nomogram was based on a cross-sectional set of 404 HEV-ALF patients who were identified and enrolled from a cohort of 650 patients with liver failure. To compare the performance with that of the model for end-stage liver disease (MELD) scoring and CLIF-Consortium-acute-on-chronic liver failure score (CLIF-C-ACLFs) models, we assessed the predictive accuracy of the nomogram using the concordance index (C-index), and its discriminative ability using time-dependent receiver operating characteristics (td-ROC) analysis, respectively. RESULTS: Multivariate logistic regression analysis of the development set carried out to predict mortality revealed that γ-glutamyl transpeptidase, albumin, total bilirubin, urea nitrogen, creatinine, international normalized ratio, and neutrophil-to-lymphocyte ratio were independent factors, all of which were incorporated into the new nomogram to predict the mortality of HEV-ALF patients. The area under the curve of this nomogram for mortality prediction was 0.671 (95% confidence interval: 0.602–0.740), which was higher than that of the MELD and CLIF-C-ACLFs models. Moreover, the td-ROC and decision curves analysis showed that both discriminative ability and threshold probabilities of the nomogram were superior to those of the MELD and CLIF-C-ACLFs models. A similar trend was observed in the validation set. CONCLUSIONS: The novel nomogram is an accurate and efficient mortality prediction method for HEV-ALF patients.