Identifying advanced MAFLD in a cohort of T2DM and clinical features

Background: MAFLD is the most common cause of chronic liver disease, affecting 25% of the global population. Patients with T2DM have an increased risk of developing MAFLD. In addition, patients with T2DM have a higher risk of advanced forms of steatohepatitis and fibrosis. Identifying those patients...

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Autores: Sánchez Bao, Ana María, Soto Gonzalez, Alfonso, Delgado Blanco, Manuel, Balboa Barreiro, Vanesa, Bellido Guerrero, Diego
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Servizo Galego de Saúde (SERGAS)
Repositorio:RUNA. Repositorio da Consellería de Sanidade e Sergas
OAI Identifier:oai:runa.sergas.gal:20.500.11940/21589
Acceso en línea:https://portalcientifico.sergas.gal//documentos/642b36b0a1c8a315fd231c3f
http://hdl.handle.net/20.500.11940/21589
Access Level:acceso abierto
Palabra clave:Humans
Non-alcoholic Fatty Liver Disease
Liver Cirrhosis
Fibrosis
Elasticity Imaging Techniques
Diabetes Mellitus, Type 2
AS Ferrol
CHUF
AS A Coruña
CHUAC
INIBIC
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oai_identifier_str oai:runa.sergas.gal:20.500.11940/21589
network_acronym_str ES
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repository_id_str
spelling Identifying advanced MAFLD in a cohort of T2DM and clinical featuresSánchez Bao, Ana MaríaSoto Gonzalez, AlfonsoDelgado Blanco, ManuelBalboa Barreiro, VanesaBellido Guerrero, DiegoHumansNon-alcoholic Fatty Liver DiseaseLiver CirrhosisFibrosisElasticity Imaging TechniquesDiabetes Mellitus, Type 2AS FerrolCHUFAS A CoruñaCHUACAS A CoruñaCHUACAS A CoruñaINIBICAS FerrolCHUFBackground: MAFLD is the most common cause of chronic liver disease, affecting 25% of the global population. Patients with T2DM have an increased risk of developing MAFLD. In addition, patients with T2DM have a higher risk of advanced forms of steatohepatitis and fibrosis. Identifying those patients is critical in order to refer them to specialist and appropriate management of their disease. Aims and Objectives: To estimate advanced fibrosis prevalence in a cohort of patients with T2DM and to identify possible predictors. Methods: subjects with T2DM during regular health check-up were enrolled. Demographic and general characteristics were measured, including metabolic parameters and homeostasis model assessment of insulin resistance (HOMA2-IR). Four non-invasive fibrosis scores (NAFLD fibrosis scores, FIB-4, APRI, Hepamet fibrosis score) were measure and compared with transient elastography (TE). Results: 96 patients (21%) presented risk of significant fibrosis (?F2) measured by TE and 45 patients (10%) presented with risk of advanced fibrosis F3-F4. Liver fibrosis was related to BMI, AC, HOMA2-IR. The results of the non-invasive fibrosis scores have been validated with the results obtained in the TE. It is observed that the index with the greatest area under the curve (AUC) is APRI (AUC=0.729), with a sensitivity of 62.2% and a specificity of 76.1%. However, the test with better positive likelihood ratio (LR+) in our study is NAFLD fibrosis score. Conclusions: Our results show that in a general T2DM follow up, 10% of patients were at risk of advanced fibrosis. We found a positive correlation between liver fibrosis and BMI, AC and HOMA2-IR. Non-invasive fibrosis markers can be useful for screening, showing NAFLD Fibrosis score a better LHR+ compared to TE. Further studies are needed to validate these results and elucidate the best screening approach to identify those patients at risk of advanced MAFLD.2023info:eu-repo/semantics/articlehttps://portalcientifico.sergas.gal//documentos/642b36b0a1c8a315fd231c3fhttp://hdl.handle.net/20.500.11940/21589reponame:RUNA. Repositorio da Consellería de Sanidade e Sergasinstname:Servizo Galego de Saúde (SERGAS)Ingléshttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:runa.sergas.gal:20.500.11940/215892026-06-12T08:40:47Z
dc.title.none.fl_str_mv Identifying advanced MAFLD in a cohort of T2DM and clinical features
title Identifying advanced MAFLD in a cohort of T2DM and clinical features
spellingShingle Identifying advanced MAFLD in a cohort of T2DM and clinical features
Sánchez Bao, Ana María
Humans
Non-alcoholic Fatty Liver Disease
Liver Cirrhosis
Fibrosis
Elasticity Imaging Techniques
Diabetes Mellitus, Type 2
AS Ferrol
CHUF
AS A Coruña
CHUAC
AS A Coruña
CHUAC
AS A Coruña
INIBIC
AS Ferrol
CHUF
title_short Identifying advanced MAFLD in a cohort of T2DM and clinical features
title_full Identifying advanced MAFLD in a cohort of T2DM and clinical features
title_fullStr Identifying advanced MAFLD in a cohort of T2DM and clinical features
title_full_unstemmed Identifying advanced MAFLD in a cohort of T2DM and clinical features
title_sort Identifying advanced MAFLD in a cohort of T2DM and clinical features
dc.creator.none.fl_str_mv Sánchez Bao, Ana María
Soto Gonzalez, Alfonso
Delgado Blanco, Manuel
Balboa Barreiro, Vanesa
Bellido Guerrero, Diego
author Sánchez Bao, Ana María
author_facet Sánchez Bao, Ana María
Soto Gonzalez, Alfonso
Delgado Blanco, Manuel
Balboa Barreiro, Vanesa
Bellido Guerrero, Diego
author_role author
author2 Soto Gonzalez, Alfonso
Delgado Blanco, Manuel
Balboa Barreiro, Vanesa
Bellido Guerrero, Diego
author2_role author
author
author
author
dc.subject.none.fl_str_mv Humans
Non-alcoholic Fatty Liver Disease
Liver Cirrhosis
Fibrosis
Elasticity Imaging Techniques
Diabetes Mellitus, Type 2
AS Ferrol
CHUF
AS A Coruña
CHUAC
AS A Coruña
CHUAC
AS A Coruña
INIBIC
AS Ferrol
CHUF
topic Humans
Non-alcoholic Fatty Liver Disease
Liver Cirrhosis
Fibrosis
Elasticity Imaging Techniques
Diabetes Mellitus, Type 2
AS Ferrol
CHUF
AS A Coruña
CHUAC
AS A Coruña
CHUAC
AS A Coruña
INIBIC
AS Ferrol
CHUF
description Background: MAFLD is the most common cause of chronic liver disease, affecting 25% of the global population. Patients with T2DM have an increased risk of developing MAFLD. In addition, patients with T2DM have a higher risk of advanced forms of steatohepatitis and fibrosis. Identifying those patients is critical in order to refer them to specialist and appropriate management of their disease. Aims and Objectives: To estimate advanced fibrosis prevalence in a cohort of patients with T2DM and to identify possible predictors. Methods: subjects with T2DM during regular health check-up were enrolled. Demographic and general characteristics were measured, including metabolic parameters and homeostasis model assessment of insulin resistance (HOMA2-IR). Four non-invasive fibrosis scores (NAFLD fibrosis scores, FIB-4, APRI, Hepamet fibrosis score) were measure and compared with transient elastography (TE). Results: 96 patients (21%) presented risk of significant fibrosis (?F2) measured by TE and 45 patients (10%) presented with risk of advanced fibrosis F3-F4. Liver fibrosis was related to BMI, AC, HOMA2-IR. The results of the non-invasive fibrosis scores have been validated with the results obtained in the TE. It is observed that the index with the greatest area under the curve (AUC) is APRI (AUC=0.729), with a sensitivity of 62.2% and a specificity of 76.1%. However, the test with better positive likelihood ratio (LR+) in our study is NAFLD fibrosis score. Conclusions: Our results show that in a general T2DM follow up, 10% of patients were at risk of advanced fibrosis. We found a positive correlation between liver fibrosis and BMI, AC and HOMA2-IR. Non-invasive fibrosis markers can be useful for screening, showing NAFLD Fibrosis score a better LHR+ compared to TE. Further studies are needed to validate these results and elucidate the best screening approach to identify those patients at risk of advanced MAFLD.
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://portalcientifico.sergas.gal//documentos/642b36b0a1c8a315fd231c3f
http://hdl.handle.net/20.500.11940/21589
url https://portalcientifico.sergas.gal//documentos/642b36b0a1c8a315fd231c3f
http://hdl.handle.net/20.500.11940/21589
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:RUNA. Repositorio da Consellería de Sanidade e Sergas
instname:Servizo Galego de Saúde (SERGAS)
instname_str Servizo Galego de Saúde (SERGAS)
reponame_str RUNA. Repositorio da Consellería de Sanidade e Sergas
collection RUNA. Repositorio da Consellería de Sanidade e Sergas
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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