Your browser doesn't support javascript.
loading
Timely diagnosis and staging of non-alcoholic fatty liver disease using transient elastography and clinical parameters.
Shieh, Christine; Halegoua-De Marzio, Dina L; Hung, Matthew L; Fenkel, Jonathan M; Herrine, Steven K.
Afiliación
  • Shieh C; Division of Gastroenterology and Hepatology Thomas Jefferson University Hospital Philadelphia Pennsylvania USA.
  • Halegoua-De Marzio DL; Division of Gastroenterology and Hepatology Thomas Jefferson University Hospital Philadelphia Pennsylvania USA.
  • Hung ML; Department of Radiology Hospital of the University of Pennsylvania Philadelphia Pennsylvania USA.
  • Fenkel JM; Division of Gastroenterology and Hepatology Thomas Jefferson University Hospital Philadelphia Pennsylvania USA.
  • Herrine SK; Division of Gastroenterology and Hepatology Thomas Jefferson University Hospital Philadelphia Pennsylvania USA.
JGH Open ; 4(5): 1002-1006, 2020 Oct.
Article en En | MEDLINE | ID: mdl-33102776
BACKGROUND AND AIM: There is no standardized guideline to screen, image, or refer patients with non-alcoholic fatty liver disease (NAFLD) to a specialist. In this study, we used transient elastography (TE) to examine the fibrosis stages at which patients are first diagnosed with NAFLD. Subsequently, we analyzed metabolic markers to establish cut-offs beyond which noninvasive imaging should be considered to confirm NAFLD/non-alcoholic steatohepatitis fibrosis in patients. METHODS: Charts spanning July 2015-April 2018 for 116 NAFLD patients who had TE performed were reviewed. Univariate and multivariate analysis of metabolic markers was conducted. RESULTS: At the first hepatology visit, TE showed 73% F0-F2 and 27% F3-F4. Univariate analysis showed that high-density lipoproteins (HDL), hemoglobin A1c (A1c), aspartate transaminase (AST), and alanine transaminase (ALT) were significantly different between the F0-F2 and F3-F4 groups. Multivariate analysis showed that AST (P = 0.01) and A1c (P = 0.05) were significantly different. Optimal cut-offs for these markers to detect liver fibrosis on TE were AST >43 U/L and A1c >6.6%. The logistic regression function combining these two variables to reflect the probability (P) of the patient having advanced fibrosis (F3-F4) on TE yielded the formula: P = e R /(1 + e R ), where R = -8.56 + 0.052 * AST + 0.89 * A1c. CONCLUSIONS: Our study suggested that >25% of patients presenting to a specialist for NAFLD may have advanced fibrosis (F3-F4). Diabetes (A1c >6.6%) and AST >43 U/L were the most predictive in identifying NAFLD patients with advanced fibrosis on imaging. We proposed a formula that may be used to prioritize NAFLD patients at higher risk of having advanced fibrosis for specialist referral and imaging follow-up.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Idioma: En Revista: JGH Open Año: 2020 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Idioma: En Revista: JGH Open Año: 2020 Tipo del documento: Article