{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["20(11)"],"submitter":["Huang D"],"pubmed_abstract":["<h4>Background</h4>The Framingham Steatosis Index (FSI) is a diagnostic indicator of hepatic steatosis. Although prior studies have established associations between hepatic steatosis and chronic kidney disease (CKD) and between FSI and CKD, the association between FSI and proteinuria remains unexplored. This study investigated the association between FSI and albuminuria, addressing this research gap.<h4>Patients and methods</h4>Data were obtained from the National Health and Nutrition Examination Survey (NHANES) database. The association between FSI and albuminuria was examined using multivariable logistic regression and stratified analyses. Nonlinearity was assessed using smoothing curves, and inflection points were located with a recursive algorithm. Subgroup analyses were conducted to e"],"journal":["PloS one"],"pagination":["e0337104"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12633878"],"repository":["biostudies-literature"],"pubmed_title":["Association of Framingham Steatosis Index with Albuminuria: A cross-sectional study."],"pmcid":["PMC12633878"],"pubmed_authors":["Zou H","Huang D","Zhang Y"],"additional_accession":[]},"is_claimable":false,"name":"Association of Framingham Steatosis Index with Albuminuria: A cross-sectional study.","description":"<h4>Background</h4>The Framingham Steatosis Index (FSI) is a diagnostic indicator of hepatic steatosis. Although prior studies have established associations between hepatic steatosis and chronic kidney disease (CKD) and between FSI and CKD, the association between FSI and proteinuria remains unexplored. This study investigated the association between FSI and albuminuria, addressing this research gap.<h4>Patients and methods</h4>Data were obtained from the National Health and Nutrition Examination Survey (NHANES) database. The association between FSI and albuminuria was examined using multivariable logistic regression and stratified analyses. Nonlinearity was assessed using smoothing curves, and inflection points were located with a recursive algorithm. Subgroup analyses were conducted to e","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025","modification":"2026-06-05T17:11:23.172Z","creation":"2026-05-19T03:11:52.47Z"},"accession":"S-EPMC12633878","cross_references":{"pubmed":["41264588"],"doi":["10.1371/journal.pone.0337104"]}}