Project description:BackgroundHepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a life-threatening disease with high short-term mortality. Early and accurate prognosis is significant for clinical decisions, in which liver volume (LV) imparts important information. However, LV has not been considered in current prognostic models for HBV-ACLF.MethodsThree hundred and twenty-three patients were recruited to the deriving cohort, while 163 were enrolled to validation cohort. The primary end-point was death within 28 days since admission. Estimated liver volume (ELV) was calculated by the formula based on healthy population. Logistic regression was used to develop a prediction model. Accuracy of models were evaluated by receiver operating characteristic (ROC) curves.ResultsThe ratio of LV to ELV (LV/ELV%) was significantly lower in non-survivors, and LV/ELV% ≤82% indicated poor prognosis. LV/ELV%, Age, prothrombin time (PT), the grade of hepatic encephalopathy (HE), ln-transformed total bilirubin (lnTBil), and log-transformed HBV DNA (Log10 HBV DNA) were identified as independent predictors to develop an LV-based model, LEAP-HBV. The mean area under the ROC (AUC) of LEAP-HBV was 0.906 (95% CI, 0.904-0.908), higher than other non-LV-based models.ConclusionLiver volume was an independent predictor, and LEAP-HBV, a prediction model based on LV, was developed for the short-term mortality in HBV-ACLF. This study was registered on ClinicalTrails (NCT03977857).
Project description:Background & aimsThe molecular mechanisms driving the progression from early-chronic liver disease (CLD) to cirrhosis and, finally, acute-on-chronic liver failure (ACLF) are largely unknown. Our aim was to develop a protein network-based approach to investigate molecular pathways driving progression from early-CLD to ACLF.MethodsTranscriptome analysis was performed on liver biopsies from patients at different liver disease stages, including fibrosis, compensated cirrhosis, decompensated cirrhosis and ACLF, and control healthy livers. We created 9 liver-specific disease-related protein-protein interaction networks capturing key pathophysiological processes potentially related to CLD. We used these networks as a framework and performed gene set-enrichment analysis (GSEA) to identify dynamic gene profiles of disease progression.ResultsPrincipal component analyses revealed that samples clustered according to the disease stage. GSEA of the defined processes showed an upregulation of inflammation, fibrosis and apoptosis networks throughout disease progression. Interestingly, we did not find significant gene expression differences between compensated and decompensated cirrhosis, while ACLF showed acute expression changes in all the defined liver disease-related networks. The analyses of disease progression patterns identified ascending and descending expression profiles associated with ACLF onset. Functional analyses showed that ascending profiles were associated with inflammation, fibrosis, apoptosis, senescence and carcinogenesis networks, while descending profiles were mainly related to oxidative stress and genetic factors. We confirmed by qPCR the upregulation of genes of the ascending profile and validated our findings in an independent patient cohort.ConclusionACLF is characterized by a specific hepatic gene expression pattern related to inflammation, fibrosis, apoptosis, senescence and carcinogenesis. Moreover, the observed profile is significantly different from that of compensated and decompensated cirrhosis, supporting the hypothesis that ACLF should be considered a distinct entity.Lay summaryBy using transjugular biopsies obtained from patients at different stages of chronic liver disease, we unveil the molecular pathogenic mechanisms implicated in the progression of chronic liver disease to cirrhosis and acute-on-chronic liver failure. The most relevant finding in this study is that patients with acute-on-chronic liver failure present a specific hepatic gene expression pattern distinct from that of patients at earlier disease stages. This gene expression pattern is mostly related to inflammation, fibrosis, angiogenesis, and senescence and apoptosis pathways in the liver.
Project description:IntroductionIt is difficult to differentiate acute severe hepatitis (AH) with acute on chronic liver failure (ACLF). Aim was to study the role of transient elastography (Fibroscan) in identifying the patients with AH and ACLF.Materials and methodsConsecutive patients of severe AH or ACLF presented within two weeks of jaundice were enrolled. LSM and liver function tests were done at admission, week 1, 4 and at 6 months. Diagnosis of ACLF was based on documenting cirrhotic morphology on imaging and/or liver biopsy and follow-up of these patients for six months. Similarly, AH patients were diagnosed based on serology, no features of cirrhosis on imaging and follow-up of these patients for 6 months documenting reversal of liver stiffness measurement (LSM) to normal.Results104 patients were included in the final analysis (AH, n = 59, ACLF, n = 45). Out of 59 patients in severe AH group, etiology of acute hepatitis included hepatitis A (HAV, n = 22), hepatitis E (HEV, n = 21), hepatitis B (HBV, n = 4), indeterminate (n = 8) and drug induced liver injury (n = 4). Similarly for ACLF, the causes of chronic liver disease were alcohol (n = 26), hepatitis B (n = 7), hepatitis C (n = 2) and cryptogenic (n = 10). Patients with ACLF were significantly older, had low hemoglobin, low albumin, high bilirubin and lower transaminases level compared to severe AH at admission. LSM was higher in patients with ACLF compared to severe AH (61 ± 18 kPa vs 15 ± 6.4 kPa, P = 0.001) at admission. On multivariate analysis of noninvasive tests only LSM was found to differentiate AH with ACLF significantly. When we took a cutoff of 26 kPa the sensitivity and specificity of diagnosis of ACLF were 96% and 93%, respectively, with area under the curve was 0.98 (0.95-1.005), P = 0.001.ConclusionLSM could differentiate patients with severe AH and ACLF at admission.
Project description:ObjectivesCounseling patients with acute-on-chronic hepatitis B liver failure (ACHBLF) on their individual risk of short-term mortality is challenging. This study aimed to develop a conditional survival estimate (CSE) for predicting individualized mortality risk in ACHBLF patients.MethodsWe performed a large prospective cohort study of 278 ACHBLF patients from December 2010 to December 2013 at three participating medical centers. The Kaplan-Meier method was used to calculate the cumulative overall survival (OS). Cox proportional hazard regression models were used to analyze the risk factors associated with OS. 4-week CSE at "X" week after diagnostic established were calculated as CS4 = OS(X+4)/OS(X).ResultsThe actual OS at 2, 4, 6, 8, 12 weeks were 80.5%, 71.8%, 69.3%, 66.0% and 63.7%, respectively. Using CSE, the probability of surviving an additional 4 weeks, given that the patient had survived for 1, 3, 5, 7, 9 weeks was 74%, 86%, 92%, 93%, 97%, respectively. Patients with worse prognostic feathers, including MELD > 25, Child grade C, age > 45, HE, INR > 2.5, demonstrated the greatest increase in CSE over time, when compared with the "favorable" one (Δ36% vs. Δ10%; Δ28% vs. Δ16%; Δ29% vs. Δ15%; Δ60% vs. Δ12%; Δ33% vs. Δ12%; all P < 0.001; respectively).ConclusionsThis easy-to-use CSE can accurately predict the changing probability of survival over time. It may facilitate risk communication between patients and physicians.
Project description:The pathogenesis of hepatitis B virus (HBV)-induced acute-on-chronic liver failure (ACLF), a serious and prevalent medical condition, is not clear, particularly with regard to which proteins are expressed in the course of the disease. The aim of the present study was to identify the differences in hepatic tissue protein expression between normal human subjects and patients with ACLF using isobaric tags for relative and absolute quantification (iTRAQ)-based proteomic analysis and to verify the results using western blot analysis. The iTRAQ method was used to analyze the protein contents of hepatic tissue samples from 3 patients with HBV-induced ACLF and 3 normal healthy subjects. The results were verified by subjecting the hepatic tissues from 2 patients with HBV-induced ACLF and 4 healthy subjects to western blot analysis. In total, 57 proteins with ≥1.5-fold differences between patients with HBV-induced ACLF and healthy subjects were identified using iTRAQ. Among these 57 proteins, 4 with the most marked differences in their expression and the most significant association with liver disease were selected to be verified through western blot analysis: Keratin, type-I cytoskeletal 19; α-1-acid glycoprotein 1 (α1-AGP); carbonic anhydrase-1; and serpin peptidase inhibitor and clade A (α-1 anti proteinase, antitrypsin) member 1 (SERPINA1). The results of the western blot analyses were nearly identical to the iTRAQ results. Identifying the differences in liver protein expression in patients with HBV-induced ACLF may provide a basis for studies on the pathogenesis of ACLF. Future studies should focus particularly on α1-AGP, carbonic anhydrase 1 and SERPINA1.