Algorithms for Early Detection of Silent Liver Fibrosis in the Primary Care Setting

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Abstract

More than one-third of the adult world population has steatotic liver disease (SLD), with a few percent of individuals developing cirrhosis after decades of silent liver fibrosis accumulation. Lack of systematic early detection causes most patients to be diagnosed late, after decompensation, when treatment has limited effect and survival is poor. Unfortunately, no isolated screening test in primary care can sufficiently predict advanced fibrosis from SLD. Recent efforts, therefore, combine several parameters into screening algorithms, to increase diagnostic accuracy. Besides patient selection, for example, by specific characteristics, algorithms include nonpatented or patented blood tests and liver stiffness measurements using elastography-based techniques. Algorithms can be composed as a set of sequential tests, as recommended by most guidelines on primary care pathways. Future use of algorithms that are easy to interpret, cheap, and semiautomatic will improve the management of patients with SLD, to the benefit of global health care systems.

OriginalsprogEngelsk
TidsskriftSeminars in Liver Disease
Vol/bind44
Udgave nummer1
Sider (fra-til)023-034
ISSN0272-8087
DOI
StatusUdgivet - 23. jan. 2024

Bibliografisk note

Thieme. All rights reserved.

Fingeraftryk

Dyk ned i forskningsemnerne om 'Algorithms for Early Detection of Silent Liver Fibrosis in the Primary Care Setting'. Sammen danner de et unikt fingeraftryk.

Citationsformater