Efficacy of Lianhuaqingwen capsule compared with oseltamivir for influenza A virus infection: a meta-analysis of randomized, controlled trials.

In this meta-analysis, the authors review the results of studies on the efficacy of lianhuaqingwen capsule (LHQW-C) compared with oseltamivir in treating influenza A virus infection. The authors searched PubMed, Embase, Wanfang Data, and the China National Knowledge Infrastructure (CNKI) from the date of inception until December 31, 2012. The Cochrane Central Register of Controlled Trials (CENTRAL) and the Cochrane Database of Systematic Reviews (CDSR) were also searched. Five randomized, controlled trials were finally included and analyzed in this review. Compared with individuals treated with oseltamivir, this metaanalysis showed that participants treated with LHQW-C had a shorter duration of (1) fever, weighted mean difference (WMD) = -4.65 (95% CI, -8.91 to -0.38; P = .030); (2) cough, WMD = -9.79 (95% CI, -14.61 to -4.97; P < .0001); (3) sore throat, WMD = -13.01 (95% CI, -21.76 to -4.27; P = .004); and (4) body ache, WMD = -16.68 (95% CI, -32.33 to -1.03; P = .040). The review also found that the efficacy of the 2 treatments on viral shedding was similar with WMD = -0.24 (95% CI, -4.79 to 4.31; P = .920). The authors conclude that LHQW-C was superior to oseltamivir in improving the symptoms of influenza A virus infection.

[Orthogonal design based optimization of a mouse model of acute liver failure induced by D-galactosamine and lipopolysaccharide].

OBJECTIVE: To apply an orthogonal design optimization strategy to a mouse model of acute liver failure induced by D-galactosamine (D-GalN) and lipopolysaccharide (LPS) exposure. METHODS: A four-level orthogonal array design (L16(45)) was constructed to test factors with potential impact on successful establishment of the model (D-GalN and LPS dosages, and dilution rate of the D-GalN/LPS mixture). The mortality rate of mice within 24 hours of D-GalN/LPS administration was determined by the Kaplan-Meier method. The model outcome was verified by changes in serum alanine transferase level, liver histology, and hepatocyte apoptosis. RESULTS: The orthogonal array identified the optimal model technique as intraperitoneal injection of a combination of D-GalN and LPS at dosages of 350 mg/kg and 30 mug/kg, respectively, and using a dilution rate of 3. The dosages tested had no effect on survival. The typical signs of liver failure appeared at 6 hrs after administration of the D-GalN/LPS combination. CONCLUSION: The orthogonal design optimization strategy provided a procedure for establishing a mouse model of acute liver failure induced by D-GalN and LPS that showed appropriate disease outcome and survival, and which will serve to improve future experimental research of acute liver failure.

Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.

PURPOSE: Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI preoperatively. METHODS: In total, 405 patients were included. A total of 7302 radiomic features and 17 radiological features were extracted by a radiomics feature extraction package and radiologists, respectively. We developed a XGBoost model based on radiomics features, radiological features and clinical variables and a three-dimensional convolutional neural network (3D-CNN) to predict MVI status. Next, we compared the efficacy of the two models. RESULTS: Of the 405 patients, 220 (54.3%) were MVI positive, and 185 (45.7%) were MVI negative. The areas under the receiver operating characteristic curves (AUROCs) of the Radiomics-Radiological-Clinical (RRC) Model and 3D-CNN Model in the training set were 0.952 (95% confidence interval (CI) 0.923-0.973) and 0.980 (95% CI 0.959-0.993), respectively (p = 0.14). The AUROCs of the RRC Model and 3D-CNN Model in the validation set were 0.887 (95% CI 0.797-0.947) and 0.906 (95% CI 0.821-0.960), respectively (p = 0.83). Based on the MVI status predicted by the RRC and 3D-CNN Models, the mean recurrence-free survival (RFS) was significantly better in the predicted MVI-negative group than that in the predicted MVI-positive group (RRC Model: 69.95 vs. 24.80 months, p < 0.001; 3D-CNN Model: 64.06 vs. 31.05 months, p = 0.027). CONCLUSION: The RRC Model and 3D-CNN models showed considerable efficacy in identifying MVI preoperatively. These machine learning models may facilitate decision-making in HCC treatment but requires further validation.

Predictors of liver failure in primary biliary cirrhosis.

BACKGROUND: The disease progression of patients with primary biliary cirrhosis (PBC) varies significantly, and the prognostic markers that identify those patients who will develop liver failure have been scarcely studied from a Chinese cohort. Aims. We aimed to determine the predictive factors of liver failure in patients with PBC. METHODS: Patients who were first diagnosed as PBC with hepatic compensation between January 2007 and December 2009 were enrolled in this cohort study. RESULTS: Altogether 398 patients were finally included. Of these patients, 80% were women, 98% had positive antimitochondrial antibodies, and 45% had positive antinuclear antibodies (ANA). To December 2012, a total of 38 patients developed liver failure. According to the outcome, patients who developed liver failure had had higher serum concentration of baseline total bilirubin (TBil) (p = 0.013) and total bile acid (TBA) (p < 0.001), and lower concentrations of baseline total cholesterol (Tch) (p = 0.008), than patients who did not develop liver failure. Additionally, the proportion of ANA positivity was statistically different between the two groups (p = 0.009). In the established model for predicting liver failure in PBC, three variables were finally selected out, including Tch (odds ratio (OR) 0.552, 95% confidence interval (CI) 0.394-0.774, p < 0.001), TBA (OR 1.006, 95% CI 1.002-1.010, p = 0.002), and ANA (+ versus -, OR 5.518, 95% CI 1.155-26.376, p = 0.032). CONCLUSIONS: ANA, Tch, and TBA are predictors of liver failure in PBC.

Granulocyte-colony stimulating factor therapy improves survival in patients with hepatitis B virus-associated acute-on-chronic liver failure.

AIM: To evaluate the safety and efficacy of granulocyte-colony stimulating factor (G-CSF) therapy in patients with hepatitis B virus (HBV)-associated acute-on-chronic liver failure (ACLF). METHODS: Fifty-five patients with HBV-associated ACLF were randomized into two groups: the treatment group and the control group. Twenty-seven patients in the treatment group received G-CSF (5 µg/kg per day, six doses) treatment plus standard therapy, and 28 patients in the control group received standard therapy only. The peripheral CD34(+) cell count was measured consecutively by flow cytometry. Circulating white blood cell count, biochemical parameters, and other clinical data of these patients were recorded and analyzed. All patients were followed up for a period of 3 mo to evaluate the changes in liver function and survival rate. RESULTS: The peripheral neutrophil and CD34(+) cell counts in the G-CSF group increased on day 3 from the onset of therapy, continued to rise on day 7, and remained elevated on day 15 compared to those of the control group. Child-Turcotte-Pugh score of patients in the treatment group was improved on day 30 from the onset of G-CSF therapy, compared to that in the controls (P = 0.041). Model for End-Stage of Liver Disease score of patients in the treatment group was improved on day 7 (P = 0.004) and remained high on day 30 from the onset of G-CSF therapy (P < 0.001) compared to that in controls. After 3 mo of follow-up observation, the survival rate in the treatment group (48.1%) was significantly higher than that in the control group (21.4%) (P = 0.0181). CONCLUSION: G-CSF therapy promoted CD34(+) cell mobilization in patients with HBV-associated ACLF, and improved the liver function and the survival rate of these patients.