Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches
European Journal of Medical Research BMCResearch Authors: Yangyang Zheng, Ting Li, Shiqi Guo & Jinghai SongAIIM Authors: Fadia Naqash, Annika KumarApproved by President Reda RiffiPublication Date: 2/14/2026Comprehensive Summary
Zheng et al. investigated the association between cardiovascular-kidney-metabolic (CKM) syndrome stages and metabolic dysfunction-associated steatotic liver disease (MASLD) and liver fibrosis severity in U.S. adults. They analyzed 3,084 participants from the National health and Nutrition Examination survey to categorize CKM syndrome into 4 stages, specifically analyzing burden of metabolic risk factors, kidney dysfunction, and cardiovascular disease. The researchers utilized machine-learning algorithms to evaluate these associations and predictive performance. There was a strong association found between higher CKM stages and MASLD, even after adjusting for demographic and clinical confounders. They also found that higher CKM stages were associated strongly with advanced liver fibrosis and cirrhosis prevalence, often found as precursors to hepatocellular carcinoma (HCC) with other risk factors including a multitude of cancers with similar metabolic pathways. The CKM stage acts as a potential oncological risk marker. This reframes MASLD as a systemic condition with advanced fibrosis serving as a strong predictor of liver-related mortality, decompensation, and HCC.
Outcomes and Implications
This study and algorithm utilized allow for a relationship between CKM and MASLD to be established, indicating higher rates of advanced fibrosis and cirrhosis. This allows the staging to be used as risk stratification tool to identify patients who should undergo liver fibrosis assessment and allows for closer monitoring and hepatology referrals. Moreover, this association can be used to predict liver-related mortality, liver decompensation, and HCC risk, using waist circumference, hypertriglyceridemia, low HDL, and poor glycemic control (HbA1c) as identifiers. This allows for a more integrated care model to be developed across various subspecialties of medicine to suggest possible benefits for liver cancer risk reduction in the future.
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