1 ±230% vs 364±237%, p<0001) Overall participants with NAFL

1 ±2.30% vs. 36.4±2.37%, p<0.001). Overall participants with NAFLD had higher prevalence of H. pylori positivity in multivariable analysis (Odds ratio [OR]: 1.17; 95% confidence interval [CI]: 0.95-1.43) with marginal significance. With regard to presence of cagA protein, H. pylori and cagA positivity was not associated with NAFLD (OR: 1.05; 95% CI: 0.81-1.37) but, cagA negative H. pylori positivity was significantly associated with NAFLD in multivariable analysis (OR: 1.30; 95% CI: 1.01-1.67). CONCLUSIONS: The prevalence of NAFLD was higher in H. pylori positive subjects than in negative subjects. Especially,

cagA negative H. pylori positivity was significantly associated with NAFLD, independent of other known see more factors in the general population. Disclosures: The following people have nothing to disclose: Donghee Kim, Seung Joo Kang, Hwa Jung Kim, Won Kim, Yoon Jun Kim, Jung-Hwan Yoon Staging of hepatic fibrosis and steatosis is vital for prognosis and interventions in non-alcoholic steatohepatitis (NASH). Liver biopsy, the gold standard, is invasive, costly and prone to error. Non-invasive methods for hepatic fibrosis and steatosis have been proposed but their validation in NASH is unsatisfactory. We conducted a retrospective study

of consecutive patients with biopsy-proven buy Pifithrin-�� NASH seen between 2007 and 2012 in our Unit. APRI, FIB-4 and NAFLD fibrosis score were used to diagnose liver fibrosis (>F2) and cirrhosis (F4). Ultrasound, Xenon-133 scan and hepatic steatosis index (HSI) were used to diagnose severe hepatic steatosis (>66%, S3). The cut-off values of the original reports were selleck products applied. Non-invasive tests were done within 6 months from liver biopsy, used as gold standard. Variables associated with each outcome were determined by multivariate logistic regression. The performance of non-invasive methods was expressed as sensitivity, specificity, positive and negative predictive values (PPV, NPV), area under the curve (AUC). We also modelled the best combination

algorithm able to increase the accuracy of the single methods. Overall, 114 (mean age 49.6, 69.5% males) patients were included. Biopsy length range was 0.5-3.3cm, 57% of cases being >1.5cm. Fibrosis stages by Brunt were as follows: F0-F1=50%, F2=16.8%, F3 = 19.2%, F4=14%. Steatosis grades were as follows: S0-1=16%, S2=53.3%, S3=30.7%. The following variables were associated with the outcome measures: age (p<0.0001), diabetes (p=0.01) and steatosis (p=0.02) for >F2; female gender (p<0.05) and triglycerides (p=0.04) for F4; diabetes (p<0.05) and fibrosis (p=0.01) for S3. The performance of the non-invasive methods is depicted in the Table. Overall, the best method for detection of >F2 and F4 was FIB-4. Xenon scan outperformed the other methods but its AUC for S3 was <0.70. Notably, an algorithm combining gender and FIB-4 showed an AUC of 0.90, with 100% NPV to exclude cirrhosis.

Leave a Reply

Your email address will not be published. Required fields are marked *

*

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>