Development of a prognostic model for pediatric acute liver failure in a Brazilian center

Objective: Pediatric acute liver failure (PALF) is a heterogeneous, rare, and severe condition, which outcome is survival due to liver spontaneous recovery or death. The patients who do not recover may be allocated to liver transplantation, which is the standard treatment. This study aimed to build...

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Main Authors: José Colleti Junior, Ana Cristina Aoun Tannuri, Uenis Tannuri, Artur Figueiredo Delgado, Werther Brunow de Carvalho
Format: Article
Language:English
Published: Elsevier 2022-11-01
Series:Jornal de Pediatria
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S002175572200033X
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author José Colleti Junior
Ana Cristina Aoun Tannuri
Uenis Tannuri
Artur Figueiredo Delgado
Werther Brunow de Carvalho
author_facet José Colleti Junior
Ana Cristina Aoun Tannuri
Uenis Tannuri
Artur Figueiredo Delgado
Werther Brunow de Carvalho
author_sort José Colleti Junior
collection DOAJ
description Objective: Pediatric acute liver failure (PALF) is a heterogeneous, rare, and severe condition, which outcome is survival due to liver spontaneous recovery or death. The patients who do not recover may be allocated to liver transplantation, which is the standard treatment. This study aimed to build a prognostic model to support the clinical decision to indicate liver transplantation for patients with PALF in a Brazilian center. Methods: The authors retrospectively analyzed the clinical variables of 120 patients in the liver transplantation program of the 'Children's Institute of the University of São Paulo, Brazil. The authors conducted a univariate analysis of variables associated with survival in PALF. Logistic multivariate analysis was performed to find a prognostic model for the outcome of patients with pediatric acute liver failure. Results: Risk factors were analyzed using univariate analysis. Two prognostic models were built using multiple logistic regression, which resulted in 2 models: model 1(INR/ALT) and model 2 (INR/Total bilirubin). Both models showed a high sensitivity (97.9%/96.9%), good positive predictive value (89.5%/90.4%), and accuracy (88.4%/88.5%), respectively. The receiver operating characteristic was calculated for both models, and the area under the curve was 0.87 for model 1 and 0.88 for model 2. The Hosmer-Lemeshow test showed that model 1 was good. Conclusion: The authors built a prognostic model for PALF using INR and ALT that can contribute to the clinical decision to allocate patients to liver transplantation.
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spelling doaj.art-cae4c29c14804bd8bbd18daf362a8b882022-12-22T03:26:33ZengElsevierJornal de Pediatria0021-75572022-11-01986607613Development of a prognostic model for pediatric acute liver failure in a Brazilian centerJosé Colleti Junior0Ana Cristina Aoun Tannuri1Uenis Tannuri2Artur Figueiredo Delgado3Werther Brunow de Carvalho4Corresponding author.; Universidade de São Paulo, Departamento de Pediatria, Instituto da Criança, São Paulo, SP, BrazilUniversidade de São Paulo, Departamento de Pediatria, Instituto da Criança, São Paulo, SP, BrazilUniversidade de São Paulo, Departamento de Pediatria, Instituto da Criança, São Paulo, SP, BrazilUniversidade de São Paulo, Departamento de Pediatria, Instituto da Criança, São Paulo, SP, BrazilUniversidade de São Paulo, Departamento de Pediatria, Instituto da Criança, São Paulo, SP, BrazilObjective: Pediatric acute liver failure (PALF) is a heterogeneous, rare, and severe condition, which outcome is survival due to liver spontaneous recovery or death. The patients who do not recover may be allocated to liver transplantation, which is the standard treatment. This study aimed to build a prognostic model to support the clinical decision to indicate liver transplantation for patients with PALF in a Brazilian center. Methods: The authors retrospectively analyzed the clinical variables of 120 patients in the liver transplantation program of the 'Children's Institute of the University of São Paulo, Brazil. The authors conducted a univariate analysis of variables associated with survival in PALF. Logistic multivariate analysis was performed to find a prognostic model for the outcome of patients with pediatric acute liver failure. Results: Risk factors were analyzed using univariate analysis. Two prognostic models were built using multiple logistic regression, which resulted in 2 models: model 1(INR/ALT) and model 2 (INR/Total bilirubin). Both models showed a high sensitivity (97.9%/96.9%), good positive predictive value (89.5%/90.4%), and accuracy (88.4%/88.5%), respectively. The receiver operating characteristic was calculated for both models, and the area under the curve was 0.87 for model 1 and 0.88 for model 2. The Hosmer-Lemeshow test showed that model 1 was good. Conclusion: The authors built a prognostic model for PALF using INR and ALT that can contribute to the clinical decision to allocate patients to liver transplantation.http://www.sciencedirect.com/science/article/pii/S002175572200033XAcute liver failureLiver transplantationRisk factorsPrognosisPediatrics
spellingShingle José Colleti Junior
Ana Cristina Aoun Tannuri
Uenis Tannuri
Artur Figueiredo Delgado
Werther Brunow de Carvalho
Development of a prognostic model for pediatric acute liver failure in a Brazilian center
Jornal de Pediatria
Acute liver failure
Liver transplantation
Risk factors
Prognosis
Pediatrics
title Development of a prognostic model for pediatric acute liver failure in a Brazilian center
title_full Development of a prognostic model for pediatric acute liver failure in a Brazilian center
title_fullStr Development of a prognostic model for pediatric acute liver failure in a Brazilian center
title_full_unstemmed Development of a prognostic model for pediatric acute liver failure in a Brazilian center
title_short Development of a prognostic model for pediatric acute liver failure in a Brazilian center
title_sort development of a prognostic model for pediatric acute liver failure in a brazilian center
topic Acute liver failure
Liver transplantation
Risk factors
Prognosis
Pediatrics
url http://www.sciencedirect.com/science/article/pii/S002175572200033X
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