Nonalcoholic steatohepatitis (NASH) with diabetes: predictors of liver fibrosis

Noninvasive laboratory tests proposed for predicting cirrhosis in patients with chronic hepatitis C are also useful in patients with non-alcoholic steatohepatitis

“…Although many researchers have examined the usefulness and diagnostic ability of AAR in patients with HCV, results have been conflicting [13,[29][30][31][32]. Some studies have demonstrated that AAR is useful for predicting cirrhosis in NASH [26,33,34]. In our study, AAR was a better predictor of cirrhosis in patients with NASH than in patients with HCV.…”

A Noninvasive Clinical Scoring Model Predicts Risk of Nonalcoholic Steatohepatitis in Morbidly Obese Patients

“…Several earlier studies investigated the clinical predictors of fibrosis in NASH subjects, and some constructed good predictive models based on those factors [17][18][19]. As the prevalence of significant fibrosis was low in our cohort (4%), this model could not be used to reliably predict the existence or severity of fibrosis.…”

“…While the generalizability of our findings may be limited by including only morbidly obese patients undergoing bariatric surgery, the proportion of obese individuals is growing in the United States and around the globe, which makes this data applicable to an ever growing segment of population. Moreover, the risk factors associated with NASH in this population, such as hypertriglyceridemia and diabetes, were also found to be associated with NASH in moderately obese and nonobese populations [7,19,27,28] thus making it likely that our scoring system would be relevant in most patients being evaluated for the possibility of having NASH. Further validation of our risk score in an independent population is necessary, as is an analysis of its performance in a nonobese population.…”

Prognostic implication of liver histology in patients with nonalcoholic fatty liver disease in diabetes

“…Several studies have assessed liver histology in diabetics and correlated this with risk factors (Amarapurkar et al, 2006; Gupte et al, 2004; Leite et al, 2011; Prashanth et al, 2009). We will review their findings and will discuss possible predictive factors.…”