Evolving models of care in patients with metabolic dysfunction-associated steatotic liver disease, recognising its population burden and the impact of metabolic dysfunction on incident rates of hepatic and extrahepatic outcomes

Metabolic dysfunction-associated steatotic liver disease (MASLD) is associated with any one of five principal traits of the metabolic syndrome. MASLD is characterised by multimorbidity with liver-related and extrahepatic complications including cardiovascular and cardiac disease, chronic kidney disease and certain extrahepatic cancers. While increasing liver fibrosis severity is well-established as a major contributor to the hepatic complications of MASLD, emerging evidence demonstrates that the severity of associated metabolic dysfunction significantly influences adverse extrahepatic clinical outcomes and all-cause mortality. Changing models of care are needed for patients with MASLD, extending the focus beyond that of liver health and optimising the inherent (heterogeneous) cardiometabolic dysfunction. Such an approach requires multi-stakeholder and community-based engagement with improved identification and diagnosis, and better patient and healthcare provider education that also focuses on type 2 diabetes, hypertension, and obesity, to ameliorate the consequences of this highly prevalent global multisystem disease.

Authors

Institutions

Publication Details

Journal
Metabolism and Target Organ Damage
Published
2025-05-29
DOI
https://doi.org/10.20517/mtod.2025.28
Citations
2
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
2.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evolving models of care in patients with metabolic dysfunction-associated steatotic liver disease, recognising its population burden and the impact of metabolic dysfunction on incident rates of hepatic and extrahepatic outcomes

Josh Bilson, Daniel James Cuthbertson, Christopher D. Byrne
2 citations
Metabolism and Target Organ Damage
Liver Disease Diagnosis and Treatment
2.71
article

Evolving models of care in patients with metabolic dysfunction-associated steatotic liver disease, recognising its population burden and the impact of metabolic dysfunction on incident rates of hepatic and extrahepatic outcomes

Josh Bilson, Daniel James Cuthbertson, Christopher D. Byrne
article en
2 citations

Abstract

Metabolic dysfunction-associated steatotic liver disease (MASLD) is associated with any one of five principal traits of the metabolic syndrome. MASLD is characterised by multimorbidity with liver-related and extrahepatic complications including cardiovascular and cardiac disease, chronic kidney disease and certain extrahepatic cancers. While increasing liver fibrosis severity is well-established as a major contributor to the hepatic complications of MASLD, emerging evidence demonstrates that the severity of associated metabolic dysfunction significantly influences adverse extrahepatic clinical outcomes and all-cause mortality. Changing models of care are needed for patients with MASLD, extending the focus beyond that of liver health and optimising the inherent (heterogeneous) cardiometabolic dysfunction. Such an approach requires multi-stakeholder and community-based engagement with improved identification and diagnosis, and better patient and healthcare provider education that also focuses on type 2 diabetes, hypertension, and obesity, to ameliorate the consequences of this highly prevalent global multisystem disease.

Metabolism and Target Organ DamageVol. 5(2)
University Hospital Southampton NHS Foundation Trust (GB)
Openalex Percentile: Top 10%
Liver Disease Diagnosis and Treatment
2.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.