Clinical assessment for high-risk patients with non-alcoholic fatty liver disease in primary care and diabetology practices
Recommended Citation
Younossi ZM, Corey KE, Alkhouri N, Noureddin M, Jacobson I, Lam B, Clement S, Basu R, Gordon S, Ravendhra N, Puri P, Rinella M, Scudera P, Singal AK, and Henry L. Clinical assessment for high-risk patients with non-alcoholic fatty liver disease in primary care and diabetology practices. Aliment Pharmacol Ther 2020.
Document Type
Article
Publication Date
6-29-2020
Publication Title
Alimentary pharmacology & therapeutics
Abstract
BACKGROUND: Primary care practitioners (PCPs) and diabetologists are at the frontline of potentially encountering patients with NASH. Identification of those at high risk for adverse outcomes is important.
AIM: To provide practical guidance to providers on how to identify these patients and link them to specialty care.
METHODS: US members of the Global Council on NASH evaluated the evidence about NASH and non-invasive tests and developed a simple algorithm to identify high-risk NASH patients for diabetologists and primary care providers. These tools can assist frontline providers in decision-making and referral to gastroenterology/hepatology practices for additional assessments.
RESULTS: The presence of NASH-related advanced fibrosis is an independent predictor of adverse outcomes. These patients with NASH are considered high risk and referral to specialists is warranted. Given that staging of fibrosis requires a liver biopsy, non-invasive tests for fibrosis would be preferred. Consensus recommendation from the group is to risk-stratify patients based on metabolic risk factors using the FIB-4 as the initial non-invasive test due to its simplicity and ease of use. A FIB-4 score ≥1.3 can be used for further assessment and linkage to specialty care where additional technology to assess liver stiffness or serum fibrosis test will be available.
CONCLUSION: Due to the growing burden of NAFLD and NASH, PCPs and diabetologists are faced with increased patient encounters in their clinical practices necessitating referral decisions. To assist in identifying high-risk NASH patients requiring specialty care, we provide a simple and easy to use algorithm.
PubMed ID
32598051
ePublication
ePub ahead of print
