Eslam, M. et al. A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement. J. Hepatol. 73, 202–209 (2020).
Google Scholar
Eslam, M., Sanyal, A. J. & George, J. M. A. F. L. D. A consensus-driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 158, 1999–2014 .e1991 (2020).
Huang, Q., Zou, X., Wen, X., Zhou, X. & Ji, L. NAFLD or MAFLD: which has closer association with all-cause and cause-specific mortality?-Results from NHANES III. Front. Med. 8, 693507 (2021).
Google Scholar
Nguyen, V. H., Le, M. H., Cheung, R. C. & Nguyen, M. H. Differential clinical characteristics and mortality outcomes in persons with NAFLD and/or MAFLD. Clin. Gastroenterol. Hepatol. 19, 2172–2181e2176 (2021).
Google Scholar
Wong, R. J. & Cheung, R. Trends in the prevalence of metabolic dysfunction-associated fatty liver disease in the United States, 2011–2018. Clin. Gastroenterol. Hepatol. 20, e610–e613 (2022).
Google Scholar
Liu, J. et al. Estimating global prevalence of metabolic dysfunction-associated fatty liver disease in overweight or obese adults. Clin. Gastroenterol. Hepatol. 20, e573–e582 (2022).
Google Scholar
Kim, D. et al. Metabolic dysfunction-associated fatty liver disease is associated with increased all-cause mortality in the United States. J. Hepatol. 75, 1284–1291 (2021).
Google Scholar
Wen, W. et al. Metabolic dysfunction-associated fatty liver disease and cardiovascular disease: A meta-analysis. Front. Endocrinol. 13, 934225 (2022).
Google Scholar
Jia, Y. et al. Multi-system diseases and death trajectory of metabolic dysfunction-associated fatty liver disease: findings from the UK biobank. BMC Med. 21, 398 (2023).
Google Scholar
Wei, S. et al. The relationship between metabolic dysfunction-associated fatty liver disease and the incidence rate of extrahepatic cancer. Front. Endocrinol. 14, 985858 (2023).
Google Scholar
Lin, H., Zhang, X., Li, G., Wong, G. L. & Wong, V. W. Epidemiology and clinical outcomes of metabolic (Dysfunction)-associated fatty liver disease. J. Clin. Transl. Hepatol. 9, 972–982 (2021).
Google Scholar
Chen, X. et al. MAFLD is associated with increased all-cause mortality in low cardiovascular-risk individuals but not in intermediate to high-risk individuals. Nutr. Metab. Cardiovasc. Dis. 33, 376–384 (2023).
Google Scholar
Yang, Z. et al. The transition of cardiovascular disease risks from NAFLD to MAFLD. Rev. Cardiovasc. Med. 24, 157 (2023).
Google Scholar
Song, R., Li, Z., Zhang, Y., Tan, J. & Chen, Z. Comparison of NAFLD, MAFLD and MASLD characteristics and mortality outcomes in united States adults. Liver Int. 44, 1051–1060 (2024).
Google Scholar
Yoo, T. K. et al. Comparison of cardiovascular mortality between MAFLD and NAFLD: A cohort study. Nutr. Metab. Cardiovasc. Dis. 33, 947–955 (2023).
Google Scholar
Moon, J. H., Kim, W., Koo, B. K. & Cho, N. H. Metabolic dysfunction-associated fatty liver disease predicts Long-term mortality and cardiovascular disease. Gut Liver. 16, 433–442 (2022).
Google Scholar
Huang, J. et al. The prognostic role of diet quality in patients with MAFLD and physical activity: data from NHANES. Nutr. Diabetes. 14, 4 (2024).
Google Scholar
Cheng, W. C., Chen, H. F., Cheng, H. C. & Li, C. Y. Comparison of all-cause mortality associated with non-alcoholic fatty liver disease and metabolic dysfunction-associated fatty liver disease in Taiwan MJ cohort. Epidemiol. Health. 46, e2024024 (2024).
Google Scholar
Chen, P., Li, Y., Yang, C. & Zhang, Q. Machine learning models integrating dietary data predict all-cause mortality in U.S. NAFLD patients: an NHANES-based study. Nutr. J. 24, 100 (2025).
Google Scholar
Roh, E. et al. Impact of type 2 diabetes on the risk of cardiovascular disease and cardiovascular mortality in patients with non-alcoholic fatty liver disease: a nationwide population-based study. BMJ Public. Health. 3, e002020 (2025).
Google Scholar
Carrillo-Larco, R. M. et al. Phenotypes of non-alcoholic fatty liver disease (NAFLD) and all-cause mortality: unsupervised machine learning analysis of NHANES III. BMJ Open. 12, e067203 (2022).
Google Scholar
Bonfiglio, C. et al. Development and internal validation of a model for predicting overall survival in subjects with MAFLD: A cohort study. J. Clin. Med. 13, 1181 (2024).
Google Scholar
Trejo, M. J. et al. Association of liver related biomarkers with incident cardiovascular disease and all-cause mortality in the Hispanic community health study/study of Latinos (HCHS/SOL), a population-based cohort study. BMC Gastroenterol. 25, 543 (2025).
Google Scholar
Seo, Y. G., Polyzos, S. A., Park, K. H. & Mantzoros, C. S. Noninvasive hepatic steatosis and fibrosis indices differentially predict mortality in the adult Korean population. Clin. Gastroenterol. Hepatol. 23, 1366–1376 (2025).
Google Scholar
Han, H. et al. Non-linear associations of circulating total bilirubin concentration with the risk of nonalcoholic fatty liver disease and all-cause mortality. Ann. Hepatol. 29, 101177 (2024).
Google Scholar
Zhang, F., Liu, L. & Li, W. Developing and validating a predictive model for all-cause mortality in patients with metabolic dysfunction-associated steatotic liver disease. Diabetol. Metab. Syndr. 17, 161 (2025).
Google Scholar
Ou, Y., Qin, Z., Wang, P. & Zou, F. Serum uric acid to high-density lipoprotein cholesterol ratio predicts all-cause mortality in adults with metabolic dysfunction associated steatotic liver disease. Sci. Rep. 15, 11278 (2025).
Google Scholar
Yang, S. et al. Association of serum uric acid with all-cause and cardiovascular mortality among adults with nonalcoholic fatty liver disease. Clin. Endocrinol. 98, 49–58 (2023).
Google Scholar
Takaya, H. et al. Aspartate aminotransferase to platelet ratio index has utility as a biomarker of COVID-19 severity in patients with nonalcoholic fatty liver disease. Hepatol. Res. 53, 1047–1058 (2023).
Google Scholar
Wang, K. et al. Interpretable prediction of 3-year all-cause mortality in patients with heart failure caused by coronary heart disease based on machine learning and SHAP. Comput. Biol. Med. 137, 104813 (2021).
Google Scholar
Han, K. et al. Machine learning models including insulin resistance indexes for predicting liver stiffness in united States population: data from NHANES. Front. Public. Health. 10, 1008794 (2022).
Google Scholar
Kim, D., Manikat, R., Shaikh, A., Cholankeril, G. & Ahmed, A. Depression in nonalcoholic fatty liver disease and all-cause/cause-specific mortality. Eur. J. Clin. Investig. 54, e14087 (2024).
Google Scholar
Yu, X. et al. Construction of a depression risk prediction model for type 2 diabetes mellitus patients based on NHANES 2007–2014. J. Affect. Disord. 349, 217–225 (2024).
Google Scholar
National Center for Health Statistics. National Health and Nutrition Examination Survey. Access online at: https://www.cdc.gov/nchs/nhanes.htm [Accessed May 22, 2025 (2025)].
Xie, Z. Q. et al. Trends in prevalence and all-cause mortality of metabolic dysfunction-associated fatty liver disease among adults in the past three decades: results from the NHANES study. Eur. J. Intern. Med. 110, 62–70 (2023).
Google Scholar
Xie, J., Huang, H., Chen, Y., Xu, L. & Xu, C. Skipping breakfast is associated with an increased long-term cardiovascular mortality in metabolic dysfunction-associated fatty liver disease (MAFLD) but not MAFLD-free individuals. Aliment. Pharmacol. Ther. 55, 212–224 (2022).
Google Scholar
National Death Index. NCHS Data Linked to NDI Mortality Files.https://www.cdc.gov/nchs/data-linkage/mortality.htm (accessed 22 May 2025).
He, Y., Zou, J., Hong, T. & Feng, D. Association between Di-2-ethylhexyl phthalate and nonalcoholic fatty liver disease among US adults: mediation analysis of body mass index and waist circumference in the NHANES. Food Chem. Toxicol. 179, 113968 (2023).
Google Scholar
Pan, J., Hu, Y., Pang, N. & Yang, L. Association between dietary niacin intake and nonalcoholic fatty liver disease: NHANES 2003–2018. Nutrients 15, 4128 (2023).
Google Scholar
Zhao, X., Shi, X., Gu, H., Zhou, W. & Zhang, Q. Association between handgrip strength, nonalcoholic fatty liver disease, advanced hepatic fibrosis and its modifiers: evidence from the NHANES database of the USA. J. Gastroenterol. Hepatol. 38, 1734–1742 (2023).
Google Scholar
Dao, A. D., Nguyen, V. H., Ito, T., Cheung, R. & Nguyen, M. H. Prevalence, characteristics, and mortality outcomes of obese and Nonobese MAFLD in the united States. Hepatol. Int. 17, 225–236 (2023).
Google Scholar
Razouki, Z. A., Zhang, X., Hwang, J. P. & Heredia, N. I. Clinical factors associated with non-obese nonalcoholic fatty liver disease detected among US adults in the NHANES 2017–2018. J. Clin. Med. 11, 4260 (2022).
Google Scholar
Salehi, F. et al. ExSMART-PreRA: explainable survival and risk assessment using machine learning for time Estimation in preclinical rheumatoid arthritis. IEEE J. Biomed. Health Inf. 29, 6017–6028 (2025).
Google Scholar
Nhu, N. T. et al. Predicting 14-day readmission in middle-aged and elderly patients with pneumonia using emergency department data: a multicentre retrospective cohort study with a survival machine learning approach. BMJ Open. 15, e102711 (2025).
Google Scholar
Kang, H. Y. J., Ko, M. & Ryu, K. S. Prediction model for survival of younger patients with breast cancer using the breast cancer public staging database. Sci. Rep. 14, 25723 (2024).
Google Scholar
Moreno-Sánchez, P. A. Improvement of a prediction model for heart failure survival through explainable artificial intelligence. Front. Cardiovasc. Med. 10, 1219586 (2023).
Google Scholar
Duan, S. et al. Development of interpretable machine learning models associated with environmental chemicals to predict all-cause and specific-cause mortality: A longitudinal study based on NHANES. Ecotoxicol. Environ. Saf. 270, 115864 (2024).
Google Scholar
Tang, R. et al. Predicting mortality risk in alzheimer’s disease using machine learning based on lifestyle and physical activity. Sci. Rep. 15, 26928 (2025).
Google Scholar
Uno, H., Cai, T., Pencina, M. J., D’Agostino, R. B. & Wei, L. J. On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data. Stat. Med. 30, 1105–1117 (2011).
Google Scholar
Steyerberg, E. W. & Vergouwe, Y. Towards better clinical prediction models: seven steps for development and an ABCD for validation. Eur. Heart J. 35, 1925–1931 (2014).
Google Scholar
de Ruijter, W. et al. Use of Framingham risk score and new biomarkers to predict cardiovascular mortality in older people: population based observational cohort study. BMJ 338, a3083 (2009).
Google Scholar
Xu, C. et al. Interpretable prediction of 3-year all-cause mortality in patients with chronic heart failure based on machine learning. BMC Med. Inf. Decis. Mak. 23, 267 (2023).
Google Scholar
Zhou, H. et al. Machine learning for the prediction of all-cause mortality in patients with sepsis-associated acute kidney injury during hospitalization. Front. Immunol. 14, 1140755 (2023).
Google Scholar
Tran, N. T. D. et al. Prediction of all-cause mortality for chronic kidney disease patients using four models of machine learning. Nephrol. Dial Transpl. 38, 1691–1699 (2023).
Google Scholar
Decraecker, M. et al. Long-term prognosis of patients with metabolic (dysfunction)-associated fatty liver disease by non-invasive methods. Aliment. Pharmacol. Ther. 55, 580–592 (2022).
Google Scholar
Li, Z. et al. Development and validation of questionnaire-based machine learning models for predicting all-cause mortality in a representative population of China. Front. Public. Health. 11, 1033070 (2023).
Google Scholar
Khalid, Y. S. et al. Increased cardiovascular events and mortality in females with NAFLD: a meta-analysis. Am. J. Cardiovasc. Dis. 10, 258–271 (2020).
Google Scholar
Jitrukthai, S. et al. Long-term outcomes associated with NAFLD, ASCVD, and all-cause mortality of patients with metabolic syndrome. J. Clin. Med. 11, 4627 (2022).
Google Scholar
de Avila, L. et al. Nonalcoholic fatty liver disease is independently associated with higher all-cause and cause-specific mortality. Clin. Gastroenterol. Hepatol. 21, 2588–2596e2583 (2023).
Google Scholar
Huang, J., Wang, M., Wu, Y., Kumar, R. & Lin, S. Serum high-sensitive C-reactive protein is a simple indicator for all-cause among individuals with MAFLD. Front. Physiol. 13, 1012887 (2022).
Google Scholar
Liu, Z., Wang, Q., Huang, H., Wang, X. & Xu, C. Association between serum uric acid levels and long-term mortality of metabolic dysfunction-associated fatty liver disease: a nationwide cohort study. Diabetol. Metab. Syndr. 15, 27 (2023).
Google Scholar
Kim, D. et al. Physical activity, measured objectively, is associated with lower mortality in patients with nonalcoholic fatty liver disease. Clin. Gastroenterol. Hepatol. 19, 1240–1247e1245 (2021).
Google Scholar
Heredia, N. I. et al. Physical activity and diet quality in relation to non-alcoholic fatty liver disease: A cross-sectional study in a representative sample of U.S. Adults using NHANES 2017–2018. Prev. Med. 154, 106903 (2022).
Google Scholar
Kim, D., Wijarnpreecha, K., Dennis, B. B., Cholankeril, G. & Ahmed, A. Types of physical activity in nonalcoholic fatty liver disease and all-cause and cardiovascular mortality. J. Clin. Med. 12, 1923 (2023).
Vilar-Gomez, E. et al. Significant dose-response association of physical activity and diet quality with mortality in adults with suspected NAFLD in a population study. Am. J. Gastroenterol. 118, 1576–1591 (2023).
Google Scholar
Huang, H. et al. Remnant cholesterol predicts long-term mortality of patients with metabolic dysfunction-associated fatty liver disease. J. Clin. Endocrinol. Metab. 107, e3295–e3303 (2022).
Google Scholar
