Testing the ability of the nonalcoholic fatty liver disease fibrosis score to predict 1-year all-cause hospital admission. Issue 1 (2nd January 2019)

• Record Type: Journal Article
• Authors: Heavener, Trace; Memon, Ahmed; Khan, Shamyal; Davis, Sam; Sager, Lauren; DeMorrow, Sharon; Jeffries, Mark
• Is Part Of: Proceedings. Volume 32:Issue 1(2019)
• Page Start: 26
• Page End: 29
• Publication Date: 2019-01-02
• Subjects: Hospitalization -- hypertension -- nonalcoholic fatty liver disease fibrosis score -- preventive care -- tobacco use; Medicine -- Periodicals; Medicine; Medicine -- Periodicals; Periodicals; Electronic journals; 616.005
• DOI: 10.1080/08998280.2018.1543227
• Languages: English
• ISSNs: 0899-8280

Abstract

Abstract: The nonalcoholic fatty liver disease fibrosis score (NFS) has been shown to be a cost-effective screening strategy in the primary care setting to determine when gastroenterology referral is needed, but NFS as a predictor of hospitalization within 1 year is uncertain. This retrospective observational cohort study involved 1803 patients with a diagnosis of nonalcoholic fatty liver disease or nonalcoholic steatohepatitis. The NFS was categorized into the following: low (less than −1.455), moderate (between −1.455 and 0.676), and high (>0.676). The average NFS score by hospital admission was −0.760, the average number of admissions was 1.81, and the median number of days to hospital admission was 135.8 days (45.5−363, 25th to 75th percentile). A univariate logistic regression model showed that NFS significantly predicted hospital admission ( P = 0.007); however, a multivariate logistic regression model, after adjusting for hypertension and tobacco use, indicated that NFS was not significantly associated with hospital admission. Using the logistic regression model, hypertension predicted admission at low ( P < 0.0001) and moderate ( P = 0.0005) NFS. Using this same model, tobacco use also predicted admission at low ( P < 0.0001) and moderate ( P = 0.0002) NFS. The NFS should not be used to determine which patients are at increased risk of hospitalization.