{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T05:00:02Z","timestamp":1790312402235,"version":"4.1.0"},"reference-count":27,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:00:00Z","timestamp":1790294400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Clin. Diabetes Healthc."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed non-alcoholic fatty liver disease (NAFLD), is the hepatic presentation of metabolic syndrome. It shares the common pathophysiology of insulin resistance with type 2 diabetic mellitus (T2DM). The aim of this study was to establish the predictive ability of non-invasive liver fat indices\u2014Fatty Liver Index (FLI), Hepatic Steatosis Index (HSI), Visceral Adiposity Index (VAI), Triglyceride and Glucose Index (TyG), and NAFLD-Liver Fat Score (NAFLD-LFS)\u2014to determine fatty liver among patients with T2DM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methodology<\/jats:title>\n                    <jats:p>A cross-sectional analytical study was conducted on 260 newly diagnosed patients with type 2 diabetes. Anthropometric measurements were taken, while ultrasound scan was performed to determine fatty liver; its grade and blood samples were used to determine biochemical parameters. Liver fat index scores were calculated using standardized equations and analyzed using the statistical software SPSS version 23.0.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The incidence of MASLD among patients with T2DM was 69.2%. Three of the liver fat indices\u2014FLI, HSI, and NAFLD-LFS\u2014showed strong statistically significant correlations (\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.001) with liver ultrasonographic findings while the remaining indices\u2014VAI and TyG\u2014showed moderately significant correlations (\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.01). The cutoff values, sensitivities, and specificities of each index were determined by receiver operating characteristic (ROC) curve analysis. FLI showed the highest diagnostic performance [area under the curve (AUC) = 0.947; 95% confidence interval (CI): 0.923\u20130.971] with 75% sensitivity and 100% specificity with a cutoff value of 46.12. Both HSI (AUC\u00a0=\u00a00.847; 95% CI: 0.812\u20130.902) and NAFLD-LFS (AUC = 0.847; 95% CI: 0.800\u20130.894) showed good diagnostic performance with sensitivities of 68.3% and 76.1%, specificities of 95.5% and 85%, and cutoff values of 37.02 and 0.906, respectively. A moderate diagnostic performance was observed in the remaining indices: TyG (AUC = 0.707; 95% CI: 0.642\u20130.772) and VAI (AUC = 0.670; 95% CI: 0.602\u20130.739). Based on the multivariable logistic regression analysis, both FLI [adjusted odds ratio (aOR) = 1.144, 95% CI: 1.090\u20131.201,\n                      <jats:italic>p<\/jats:italic>\n                      \u2264 0.001] and HSI (aOR = 1.366, 95% CI: 1.157\u20131.614,\n                      <jats:italic>p<\/jats:italic>\n                      \u2264 0.001) were able to independently predict the presence or absence of fatty liver.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The current study showed that all five liver fat indices have the ability to predict the presence or absence of fatty liver among patients with T2DM. FLI and HSI showed the highest performance among the five indices, which can be used as screening tools for fatty liver more efficiently. The findings provide reliable alternative methods for detecting fatty liver in a resource-limited clinical setting simplifying patient management.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcdhc.2026.1916533","type":"journal-article","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T04:27:19Z","timestamp":1790310439000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Prediction of metabolic dysfunction-associated steatotic liver disease among patients with type 2 diabetes mellitus using liver fat indices in a resource-limited clinical setting"],"prefix":"10.3389","volume":"7","author":[{"given":"KKDSD","family":"Kannangara","sequence":"first","affiliation":[{"name":"Faculty of Graduate Studies, General Sir John Kotelawala Defence University","place":["Rathmalana, Sri Lanka"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"WAC","family":"Karunarathne","sequence":"additional","affiliation":[{"name":"Department of Medical Laboratory Science, Faculty of Allied Health Sciences, General Sir John Kotelawala Defence University","place":["Werahera, Sri Lanka"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"NRP","family":"Perera","sequence":"additional","affiliation":[{"name":"Faculty of Allied Health Sciences, General Sir John Kotelawala Defence University","place":["Werahera, Sri Lanka"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Uditha","family":"Bulugahapitiya","sequence":"additional","affiliation":[{"name":"Diabetic and Endocrinology Unit, National Hospital","place":["Colombo, Sri Lanka"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"JMKB","family":"Jayasekara","sequence":"additional","affiliation":[{"name":"Department of Medical Laboratory Science, Faculty of Allied Health Sciences, General Sir John Kotelawala Defence University","place":["Werahera, Sri Lanka"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nimantha","family":"Karunathilaka","sequence":"additional","affiliation":[{"name":"Department of Nursing and Midwifery, Faculty of Allied Health Sciences, General Sir John Kotelawala Defence University","place":["Werahera, Sri Lanka"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,25]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1016\/j.jhep.2024.04.031","article-title":"EASL-EASD-EASO clinical practice guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD)","volume":"81","year":"2024","journal-title":"J Hepatol"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1097\/HEP.0000000000000520","article-title":"A multisociety Delphi consensus statement on new fatty liver disease nomenclature","volume":"78","author":"Rinella","year":"2023","journal-title":"Hepatol (Baltimore Md)"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.2337\/dc08-s055","article-title":"Diagnosis and classification of diabetes mellitus","volume":"33","year":"2010","journal-title":"Diabetes Care"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.2337\/dci24-0094","article-title":"Metabolic dysfunction-associated steatotic liver disease (MASLD) in people with diabetes: The need for screening and early intervention. 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