2026-10-11T21:18:25Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34031373 2026-09-30T10:52:15Z category_7 portal_147 item_type_3 month_year_09_2026

Supplemental Material for: Detecting Early Liver Fibrosis in Obesity: A Head-to-Head Comparison of Five Clinical Scores in Metabolic Dysfunction-Associated Steatotic Liver Disease figshare admin karger (2628495) Giovani Schulte Farina (25143205) Bárbara Brambilla (10446051) Laura Kalil Nader Lazzaretti (25143209) Emanuelle Mendonça Pandolfo (25143212) Carlos Henrique Dal Bem Fistarol (25143216) Stéfano Matheus Schio Kuiava (25143219) Ana Maria Graciolli (25143220) Henrique Prataviera Giovanardi (25143223) Augusto Cardoso Sgarioni (25143229) Aline Caldart Tregnago (25143230) Floriano Rodrigues Riva Netod (25143231) Cassiano da Silva Scholze (25143243) Daniel Cecconi Agostini (25143245) Bruno Schmidt Dellamea (10446054) Lessandra Michelin Rodriguez Lins (25143250) Jonathan Soldera (10445862) Medicine Medicine <p dir="ltr">Introduction: Obesity is a major driver of metabolic dysfunction-associated steatotic liver disease (MASLD) and liver fibrosis, creating an urgent need for accurate, non-invasive tools to identify fibrosis in this high-risk population. We compared five clinical fibrosis scores (FIB-4, NFS, APRI, BARD, Hepamet) for detecting any fibrosis (F1–F4) in obese individuals at risk of MASLD and to assess whether metabolic syndrome (MetS) modifies score performance.</p><p dir="ltr">Methods: We performed a cross-sectional study of 95 individuals undergoing bariatric surgery with intraoperative liver biopsy as reference. FIB-4, NFS, APRI, BARD, and Hepamet were calculated using pre-operative clinical and laboratory data. Fibrosis was staged by NASH CRN criteria. Diagnostic performance was evaluated using AUROC analysis and diagnostic measures with published and optimized (Youden index) cut-offs. The interaction between MetS and score performance was tested using logistic regression.</p><p dir="ltr">Results: Fibrosis was present in 10.5% of participants. Using published cut-offs, FIB-4 (AUROC 0.752) and Hepamet (AUROC 0.746) showed fair discrimination, while NFS and APRI performed poorly and BARD showed no meaningful discrimination. Optimized cut-offs improved performance of FIB-4 (AUROC 0.789) and Hepamet (AUROC 0.781), both yielding high negative predictive values (>95%). BARD remained suboptimal. MetS did not significantly modify the association between any score and fibrosis.</p><p dir="ltr">Conclusions: In obese patients at risk of MASLD, FIB-4 and Hepamet provided the most reliable detection of biopsy-proven fibrosis, including early disease. Population-specific cut-offs improved accuracy, while MetS did not affect score performance. These findings support FIB-4 and Hepamet as practical tools for early fibrosis risk stratification in obese MASLD.</p> 2026-09-30T10:52:15Z Dataset Dataset 10.6084/m9.figshare.34031373.v1 https://figshare.com/articles/dataset/Supplemental_Material_for_Detecting_Early_Liver_Fibrosis_in_Obesity_A_Head-to-Head_Comparison_of_Five_Clinical_Scores_in_Metabolic_Dysfunction-Associated_Steatotic_Liver_Disease/34031373 CC BY 4.0