共 50 条
- [1] Association of FIB-4 score with disease progression in real-world populations diagnosed with NAFLD/NASH or at risk of NASH in US clinical practiceJOURNAL OF HEPATOLOGY, 2020, 73 : S159 - S159Lai, MichelleBroestl, JeremyFrick, AndrewHaubrich, RichardKoch, BruceMilligan, ScottNatha, MackyYounossi, ZobairAfdhal, Nezam
- [2] ASSOCIATION OF FIB4 SCORE WITH MAJOR CARDIOVASCULAR EVENTS (MACE) IN REAL-WORLD POPULATIONS DIAGNOSED WITH NASH OR NAFLD IN US CLINICAL PRACTICEGASTROENTEROLOGY, 2020, 158 (06) : S1269 - S1270Lai, MichelleBroestl, JeremyFrick, AndrewHaubrich, RichardKoch, BruceMilligan, ScottNatha, MackyYounossi, Zobair M.Afdhal, Nezam H.
- [3] Association of FIB-4 score with major cardiovascular events (MACE) in real-world populations diagnosed with NASH or NAFLD in US clinical practiceJOURNAL OF HEPATOLOGY, 2020, 73 : S159 - S160Lai, MichelleBroestl, JeremyFrick, AndrewHaubrich, RichardKoch, BruceMilligan, ScottNatha, MackyYounossi, ZobairAfdhal, Nezam
- [4] Real-world evaluation of NASH in US clinical practice: Underutilization of liver biopsy and liverJOURNAL OF HEPATOLOGY, 2019, 70 (01) : E775 - E776Lai, MichelleMilligan, ScottWick, NicoleYounossi, ZobairAfdhal, Nezam
- [5] REAL-WORLD EVALUATION OF NASH IN US CLINICAL PRACTICE: UNDERUTILIZATION OF LIVER BIOPSY AND LIVER IMAGINGGASTROENTEROLOGY, 2019, 156 (06) : S1223 - S1223Lai, MichelleMilligan, ScottWick, Nicole M.Younossi, Zobair M.Afdhal, Nezam H.
- [6] Accuracy of the recommended algorithm using Fib4 Score and fibroscan to identify MASLD patients with low risk for advanced liver fibrosis in "real world" practiceJOURNAL OF HEPATOLOGY, 2024, 80 : S548 - S548Zuckerman, InbalAzulay, OrlyZuckerman, Eli
- [7] NASHmap: clinical utility of a machine learning model to identify patients at risk of NASH in real-world settingsSCIENTIFIC REPORTS, 2023, 13 (01)Schattenberg, Joern M.Balp, Maria-MagdalenaReinhart, BrendaTietz, AndreasRegnier, Stephane A.Capkun, GoranaYe, QinLoeffler, JuergenPedrosa, Marcos C.Docherty, Matt
- [8] NASHmap: clinical utility of a machine learning model to identify patients at risk of NASH in real-world settingsScientific Reports, 13Jörn M. SchattenbergMaria-Magdalena BalpBrenda ReinhartAndreas TietzStephane A. RegnierGorana CapkunQin YeJürgen LoefflerMarcos C. PedrosaMatt Docherty
- [9] HETEROGENEOUS DOCUMENTATION AND POOR CONCORDANCE OF NASH PATHOLOGY MAY LIMIT ITS CLINICAL UTILITY IN REAL-WORLD PRACTICEHEPATOLOGY, 2020, 72 : 971 - 971Kim, HannahIdowu, Michael O.Zink, Richard C.Mospan, AndreaRoden, MichaelNewsome, Philip N.Lok, Anna S.Thuluvath, Paul J.Taunk, Jawahar L.Fried, Michael W.Sanyal, Arun J.Barritt, Alfred Sidney
- [10] Increased Risk of Mortality in Nonalcoholic Fatty Liver Disease/Nonalcoholic Steatohepatitis (NAFLD/NASH) Patients: Real-World Analysis of 2007-2015 Medicare DataHEPATOLOGY, 2018, 68 : 1294A - 1294ALoomba, RohitFraysse, JeremyLi, SuyingHarrison, Stephen A.