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Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application

Patients with COVID-19 and metabolic-dysfunction associated fatty liver disease (MAFLD) appear to be at higher risk for severe manifestations, especially in the youngest decades. Our aim was to examine whether patients with MAFLD and/or with increased liver fibrosis scores (FIB-4) are at risk for se...

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Autores principales: Zoncapè, Mirko, Carlin, Michele, Bicego, Manuele, Simonetti, Andrea, Ceruti, Vittoria, Mantovani, Anna, Inglese, Francesco, Zamboni, Giulia, Sartorio, Andrea, Minuz, Pietro, Romano, Simone, Crisafulli, Ernesto, Sacerdoti, David, Fava, Cristiano, Dalbeni, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238243/
https://www.ncbi.nlm.nih.gov/pubmed/37268769
http://dx.doi.org/10.1007/s11739-023-03316-6
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author Zoncapè, Mirko
Carlin, Michele
Bicego, Manuele
Simonetti, Andrea
Ceruti, Vittoria
Mantovani, Anna
Inglese, Francesco
Zamboni, Giulia
Sartorio, Andrea
Minuz, Pietro
Romano, Simone
Crisafulli, Ernesto
Sacerdoti, David
Fava, Cristiano
Dalbeni, Andrea
author_facet Zoncapè, Mirko
Carlin, Michele
Bicego, Manuele
Simonetti, Andrea
Ceruti, Vittoria
Mantovani, Anna
Inglese, Francesco
Zamboni, Giulia
Sartorio, Andrea
Minuz, Pietro
Romano, Simone
Crisafulli, Ernesto
Sacerdoti, David
Fava, Cristiano
Dalbeni, Andrea
author_sort Zoncapè, Mirko
collection PubMed
description Patients with COVID-19 and metabolic-dysfunction associated fatty liver disease (MAFLD) appear to be at higher risk for severe manifestations, especially in the youngest decades. Our aim was to examine whether patients with MAFLD and/or with increased liver fibrosis scores (FIB-4) are at risk for severe COVID-19 illness, using a machine learning (ML) model. Six hundred and seventy two patients were enrolled for SARS-CoV-2 pneumonia between February 2020 and May 2021. Steatosis was detected by ultrasound or computed tomography (CT). ML model valuated the risks of both in-hospital death and prolonged hospitalizations (> 28 days), considering MAFLD, blood hepatic profile (HP), and FIB-4 score. 49.6% had MAFLD. The accuracy in predicting in-hospital death was 0.709 for the HP alone and 0.721 for HP + FIB-4; in the 55–75 age subgroup, 0.842/0.855; in the MAFLD subgroup, 0.739/ 0.772; in the MAFLD 55–75 years, 0.825/0.833. Similar results were obtained when considering the accuracy in predicting prolonged hospitalization. In our cohort of COVID-19 patients, the presence of a worse HP and a higher FIB-4 correlated with a higher risk of death and prolonged hospitalization, regardless of the presence of MAFLD. These findings could improve the clinical risk stratification of patients diagnosed with SARS-CoV-2 pneumonia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11739-023-03316-6.
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spelling pubmed-102382432023-06-06 Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application Zoncapè, Mirko Carlin, Michele Bicego, Manuele Simonetti, Andrea Ceruti, Vittoria Mantovani, Anna Inglese, Francesco Zamboni, Giulia Sartorio, Andrea Minuz, Pietro Romano, Simone Crisafulli, Ernesto Sacerdoti, David Fava, Cristiano Dalbeni, Andrea Intern Emerg Med EM - Original Patients with COVID-19 and metabolic-dysfunction associated fatty liver disease (MAFLD) appear to be at higher risk for severe manifestations, especially in the youngest decades. Our aim was to examine whether patients with MAFLD and/or with increased liver fibrosis scores (FIB-4) are at risk for severe COVID-19 illness, using a machine learning (ML) model. Six hundred and seventy two patients were enrolled for SARS-CoV-2 pneumonia between February 2020 and May 2021. Steatosis was detected by ultrasound or computed tomography (CT). ML model valuated the risks of both in-hospital death and prolonged hospitalizations (> 28 days), considering MAFLD, blood hepatic profile (HP), and FIB-4 score. 49.6% had MAFLD. The accuracy in predicting in-hospital death was 0.709 for the HP alone and 0.721 for HP + FIB-4; in the 55–75 age subgroup, 0.842/0.855; in the MAFLD subgroup, 0.739/ 0.772; in the MAFLD 55–75 years, 0.825/0.833. Similar results were obtained when considering the accuracy in predicting prolonged hospitalization. In our cohort of COVID-19 patients, the presence of a worse HP and a higher FIB-4 correlated with a higher risk of death and prolonged hospitalization, regardless of the presence of MAFLD. These findings could improve the clinical risk stratification of patients diagnosed with SARS-CoV-2 pneumonia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11739-023-03316-6. Springer International Publishing 2023-06-03 2023 /pmc/articles/PMC10238243/ /pubmed/37268769 http://dx.doi.org/10.1007/s11739-023-03316-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle EM - Original
Zoncapè, Mirko
Carlin, Michele
Bicego, Manuele
Simonetti, Andrea
Ceruti, Vittoria
Mantovani, Anna
Inglese, Francesco
Zamboni, Giulia
Sartorio, Andrea
Minuz, Pietro
Romano, Simone
Crisafulli, Ernesto
Sacerdoti, David
Fava, Cristiano
Dalbeni, Andrea
Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application
title Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application
title_full Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application
title_fullStr Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application
title_full_unstemmed Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application
title_short Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application
title_sort metabolic-associated fatty liver disease and liver fibrosis scores as covid-19 outcome predictors: a machine-learning application
topic EM - Original
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238243/
https://www.ncbi.nlm.nih.gov/pubmed/37268769
http://dx.doi.org/10.1007/s11739-023-03316-6
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