Background: Endoscopy plays an important role in the management of acute variceal bleeding (AVB) in patients with cirrhosis. This study aimed at determining the optimal endoscopy timing for cirrhotic AVB. Methods: Patients with cirrhosis with AVB across 34 university hospitals in 30 cities from February 2013 to May 2020 who underwent endoscopy within 24 hours were included in this study. Patients were divided into an urgent endoscopy group (endoscopy <6 h after admission) and an early endoscopy group (endoscopy 6–24 h after admission). Multivariable analysis was performed to identify risk factors for treatment failure. Primary outcome was the incidence of 5-day treatment failure. Secondary outcomes included in-hospital mortality, need for intensive care unit, and length of hospital stay. A propensity score matching analysis was performed. In addition, we performed an analysis, in which we compared the 5-day treatment failure incidence and the in-hospital mortality among patients with endoscopy performed at <12 hours and 12–24 hours. Results: A total of 3319 patients were enrolled: 2383 in the urgent endoscopy group and 936 in the early endoscopy group. After propensity score matching, on multivariable analysis, Child-Pugh class was identified as an independent risk factor for 5-day treatment failure (HR, 1.61; 95% CI: 1.09–2.37). The incidence of 5-day treatment failure was 3.0% in the urgent endoscopy group and 2.9% in the early group (p = 0.90). The in-hospital mortality was 1.9% in the urgent endoscopy group and 1.2% in the early endoscopy group (p = 0.26). The incidence of need for intensive care unit was 18.2% in the urgent endoscopy group and 21.4% in the early endoscopy group (p = 0.11). The mean length of hospital stay was 17.9 days in the urgent endoscopy group and 12.9 days in the early endoscopy group (p < 0.05). The incidence of 5-day treatment failure in the <12-hour group was 2.3% and 2.2% in the 12–24 hours group (p = 0.85). The in-hospital mortality was 2.2% in the <12-hour group and 0.5% in the 12–24 hours group (p < 0.05). Conclusions: The data suggest that performance of endoscopy within 6–12 or within 24 hours of presentation among patients with cirrhosis with AVB led to similar treatment failure outcomes.

Background: Accumulating evidence indicates that elevated polyamine levels are closely linked to tumor initiation and progression. However, the precise role of polyamine metabolism in hepatocellular carcinoma (HCC) remains poorly understood.Methods: We conducted differential expression analysis on bulk RNA sequencing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to identify 65 polyamine metabolism-related genes. By employing unsupervised consensus clustering, AddModuleScore, single-sample gene set enrichment analysis (ssGSEA), and weighted gene co-expression network analysis (WGCNA), we identified polyamine metabolism-related genes at both the bulk RNA-seq and single-cell RNA-seq (scRNA-seq) levels. Utilizing 101 machine learning algorithms, we constructed a polyamine metabolism-related signature (PMRS) and validated its predictive power across training, testing, and external validation cohorts. Additionally, we developed a prognostic nomogram model by integrating PMRS with clinical variables. To explore immune treatment sensitivity, we assessed tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE) score, mutation frequency, and immune checkpoint genes expression. Immune cell infiltration was analyzed using the CIBERSORT algorithm. Finally, RT-qPCR experiments were conducted to validate the expression of key genes.Results: Using 101 machine learning algorithms, we established a polyamine metabolism-related signature comprising 9 genes, which exhibited strong prognostic value for HCC patients. Further analysis revealed significant differences in clinical features, biological functions, mutation profiles, and immune cell infiltration between high-risk and low-risk groups. Notably, TIDE analysis and immune phenotype scoring (IPS) demonstrated distinct immune treatment sensitivities between the two risk groups. RT-qPCR validation confirmed that these 9 genes were highly expressed in normal cells but significantly downregulated in tumor cells.Conclusions: Our study developed a polyamine metabolism-based prognostic risk signature for HCC, which may provide valuable insights for personalized treatment strategies in HCC patients.

Background: CEUS LI-RADS and CT/MRI LI-RADS have been used in clinical practice for several years. However, there is a lack of evidence-based study to compare the proportion of hepatocellular carcinomas (HCCs) in each category and the distribution of HCCs of these two categorization systems.Purpose: The purpose of this study was to compare the proportion of HCCs between corresponding CEUS LI-RADS and CT/MRI LI-RADS categories and the distribution of HCCs and non-HCC malignancies in each category.Methods: We searched PubMed, Embase, and Cochrane Central databases from January 2014 to December 2021. The proportion of HCCs and non-HCC malignancies and the corresponding sensitivity, specificity, accuracy, diagnostic odds ratio (DOR), and area under the curve (AUC) of the LR-5 and LR-M categories were determined using a random-effect model.Results: A total of 43 studies were included. The proportion of HCCs in CEUS LR-5 was 96%, and that in CECT/MRI LR-5 was 95% (p > 0.05). The proportion of non-HCC malignancy in CEUS LR-M was lower than that of CT/MRI LR-M (35% vs. 58%, p = 0.01). The sensitivity, specificity, and accuracy of CEUS LR-5 for HCCs were 73%, 92%, and 78%, respectively, and of CT/MRI LR-5 for HCCs, 69%, 92%, and 76%, respectively.Conclusion: With the upshift of the LI-RADS category, the proportion of HCCs increased. CEUS LR-3 has a lower risk of HCCs than CT/MRI LR-3. CEUS LR-5 and CT/MRI LR-5 have a similar diagnostic performance for HCCs. CEUS LR-M has a higher proportion of HCCs and a lower proportion of non-HCC malignancies compared with CT/MRI LR-M.

Aims. To develop a noninvasive score model to predict NASH in patients with combined CHB and NAFLD.Objective and Methods. 65 CHB patients with NAFLD were divided into NASH group (34 patients) and non-NASH group (31 patients) according to the NAS score. Biochemical indexes, liver stiffness, and Controlled Attenuation Parameter (CAP) were determined. Data in the two groups were compared and subjected to multivariate analysis, to establish a score model for the prediction of NASH.Results. In the NASH group, ALT, TG, fasting blood glucose (FBG), M30 CK-18, CAP, and HBeAg positive ratio were significantly higher than in the non-NASH group (P<0.05). Multivariate analysis showed that CK-18 M30, CAP, FBG, and HBVDNA level were independent predictors of NASH. Therefore, a new model combining CK18 M30, CAP, FBG, and HBVDNA level was established using logistic regression. The AUROC curve predicting NASH was 0.961 (95% CI: 0.920–1.00, cutoff value is 0.218), with a sensitivity of 100% and specificity of 80.6%.Conclusion. A noninvasive score model might be considered for the prediction of NASH in patients with CHB combined with NAFLD.