فهرست مطالب

Hepatitis - Volume:17 Issue: 12, Dec 2017

Hepatitis Monthly
Volume:17 Issue: 12, Dec 2017

  • تاریخ انتشار: 1396/09/25
  • تعداد عناوین: 7
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  • Hossein Ghanaati *, Kavous Firouznia, Faeze Salahshoor Page 1
  • Seyed Mohammad Tabatabaee, Seyed Moayed Alavian, Leila Ghalichi, Seyed Mohammad Miryounesi, Kazem Mousavizadeh, Shima Jazayeri, Mohammad Reza Vafa * Page 2
    Objectives
    Antioxidant treatment with Iron chelating agents is one of the suggested treatments for fatty liver disease, which has become an important health problem in the recent decades. In this study the authors evaluated the general antioxidant, iron chelating, and sugar and fat absorption characteristics of green tea.
    Methods
    Patients with non-alcoholic fatty liver disease were randomly assigned to 2 groups for a double blind clinical trial. Patients in the intervention group received 550 milligrams of green tea tablets daily as well as nutritional education for 3 months. The control group received the same protocol with green tea replaced with placebo tablets.
    Results
    After 3 months, 45 participants (21 in the intervention and 24 in the placebo group) completed the follow-up. The change in body mass index (BMI), aspartate aminotransferase (AST), and fasting blood sugar (FBS) was significantly different between the 2 groups, while the change in total iron binding capacity (TIBC), ferritin, alanine transaminase (ALT), HOMA, and weight did not show a significant difference.
    Conclusions
    The difference between the 2 groups was mainly observed in anthropometrics, liver enzyme, and metabolic indicators, although the difference might not have been highlighted due to the effectiveness of routine treatments, that both groups received.
    Keywords: Green Tea, NAFLD, Iron
  • Abdolhossein Zare, Mohammad Amin Zare, Neda Zarei, Ramin Yaghoobi, Mohammad Ali Zare, Saeede Salehi, Bita Geramizadeh, Seid Ali Malekhosseini, Negar Azarpira * Page 3
    Background
    Discovery of non-invasive methods for acute rejection in liver transplant patients would contribute to preservation of liver function in the graft. Recently, however, outcome prediction based on biostatistical models like artificial neural networks (ANNs) is increasingly becoming impressive in medicine.
    Objectives
    The aim of this study was to obtain a predictive model based on ANN technique and to figure out the best time for early prediction of acute allograft rejection after transplantation in liver transplant recipients.
    Methods
    Feed-forward, back-propagation neural network was developed to predict acute rejection in liver transplant recipients using clinical and biochemical data from 148 liver transplant recipients over days 3, 7, and 14 post-transplantation. Sensitivity and receiver-operating characteristic (ROC) analysis were done to reveal the importance of input variables and the performance of the neural network.
    Results
    The results were compared with a logistic regression (LR) model using the same data. Our results showed that the data related to day 7 gave the best results in terms of ANN performance; and the most important factors in the predictive model were aspartate aminotransferase (AST) and alanine aminotransferase (ALT). The ANN’s accuracy was 90%, sensitivity was 87%, specificity was 90% in the testing set, and the performance of the ANN was better than that of the LR model. The ANN recognized correctly eight out of ten acute rejection patients and 34 out of 36 non-rejection ones in the testing set.
    Conclusions
    This study suggests that ANN could be a valuable adjunct to conventional liver function tests for monitoring liver transplant recipients in the early postoperative period.
    Keywords: Liver Transplantation, Acute Rejection, Artificial Neural Networks, Logistic Regression
  • Ender Gunes Yegin *, Emrah Karatay, Gulce Celik, Belgin Aldag, Davut Tuney, Osman Cavit Ozdogan Page 4
    Background
    Periodic Upper Gastrointestinal Endoscopy (UGIE) for Oesophageal Varices (OVs) is recommended in all compensated cirrhotic patients. The prevalence of early stage cirrhosis is on the rise with the contribution of non-invasive models for liver fibrosis. The healthcare system needs to focus on cost-effective surveillance strategies re-channelling its efforts for high-risk OVs. This study evaluated whether non-invasive means for prediction of high-risk OVs could limit UGIEs among the the Child-Pugh class A cirrhosis population.
    Materials And Methods
    Endoscopic, clinical, and laboratory data were retrieved from medical records. Shear-Wave Elastography (SWE) and ultrasound spleen measurements, Platelet Count/Spleen Diameter (PC/SD) ratio and Child-Pugh score calculations were performed.
    Results
    Successful elasticity acquisitions were performed in 99 cirrhosis patients. Child-Pugh score was A in 67.2% cases. The PC/SD ratios were significantly associated with high-risk (grade ≥ II) OVs (P = 0.002), whereas elasticity measurements were not. No significant differences were found between Child-Pugh classes for both parameters (P > 0.05). The AUROC values for the prediction of high-risk (≥ grade II) OVs were moderate for PC/SD ratio (0.748), and poor for SWE (0.514). The PC/SD ratio cut-off level with best negative predictive function (93%) was 1298 to serve for excluding high-risk OVs in Child A patients.
    Conclusions
    For compensated cirrhosis patients, the SWE was limited in accuracy to predict high-risk OVs, while PC/SD ratio appeared as a useful tool to exclude high-risk OVs giving UGIE priority to those at greatest risk for bleeding. High-quality evidence is required to delineate and prioritize endoscopy indications for Child A patients in consensus guidelines to minimize the burden from unnecessary screening UGIE procedures.
    Keywords: High, Risk Esophageal Varices, Compensated Cirrhosis, Shear, Wave Elastography, Platelet Count, Spleen Diameter Ratio
  • Pinar Korkmaz *, Nese Demirturk, Ayse Batirel, Ahmet Cem Yardimci, Unal Cagir, Salih Atakan Nemli, Fatime Korkmaz, Fusun Zeynep Akcam, Huseyin Sener Barut, Burcu Bayrak, Faruk Karakecili Page 5
    Background
    Many noninvasive methods, including aspartate amino transaminase (AST)/alanine amino transaminase (ALT) ratio (AAR), AST-to-platelet ratio index (APRI), Bonacini cirrhosis discriminant score (CDS), fibrosis-4 (FIB4) index, and age-platelet index (API), have been described to determine the stage of hepatic fibrosis. However, these methods are developed for patients with chronic hepatitis C (CHC) and produce conflicting results in the prediction of liver fibrosis in patients with chronic hepatitis B (CHB).
    Objectives
    The aim of this study was to evaluate the relationship between 7 noninvasive models, including AAR, APRI, CDS, API, FIB-4, neutrophil-to-lymphocyte ratio (NLR), and red cell distribution width (RDW)-to-platelet ratio (RPR) in patients with CHB.
    Methods
    The study population included all patients with CHB, undergoing liver biopsy to determine HBsAg and HBV DNA positivity in more than 6 months.
    Results
    A total of 2520 treatment-naive CHB patients from 40 different centers were included in the study. In total, 62.6% of the patients were male, and the mean age was 40.60 ± 12.34 years (minimum, 18 years; maximum, 77 years). The Ishak fibrosis score was ≥ 3 in 29.8% of the patients, indicating significant fibrosis. The mean API, APRI, CDS, NLR, FIB4, and RPR scores in the noninvasive models were significantly different between the groups with significant and low fibrosis (P
    Conclusions
    In the present study, the role of noninvasive tests in the prediction of liver fibrosis stage and cirrhosis was evaluated in a large cohort of CHB patients. Overall, noninvasive models are gradually becoming more promising. Accordingly, the need for liver biopsy can be reduced with a combination of noninvasive methods in the future.
    Keywords: Chronic Hepatitis B, Liver, Fibrosis, Noninvasive Models
  • Masoud Mardani * Page 6
  • Masoud Maradani, Marefat Ghaffari Novin, Bita Pourkaveh * Page 7