45 research outputs found

    Circulating extracellular vesicles induce monocyte dysfunction and are associated with sepsis and high mortality in cirrhosis

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    BACKGROUND: Sepsis is common in cirrhosis and is often a result of immune dysregulation. Specific stimuli and pathways of inter-cellular communications between immune cells in cirrhosis and sepsis are incompletely understood. Immune cell-derived Extracellular Vesicles (EV) were studied to understand mechanisms of sepsis in cirrhosis. METHODS: Immune-cell derived EV were measured in cirrhosis patients [Child-Turcotte-Pugh (Child) score A, n=15; B n=16; C n=43 and Child-C with sepsis (n=38)], and healthy controls (HC, n=11). In-vitro and in-vivo functional relevance of EV in cirrhosis and associated sepsis was investigated. RESULTS: Monocyte, neutrophil and hematopoietic stem cells associated EV progressively increased with higher Child score (p0.3, p<0.001), which further increased in Child C sepsis than without sepsis(p<0.001); monocyte EV showing the highest association with disease stage [p=0.013; Odds ratio-4.14(1.34-12.42)]. A threshold level of monocyte EV of 53/µl predicted mortality in patients of Child C with sepsis [Odds ratio-6.2 (2.4-15.9), AUROC=0.76, p<0.01]. In vitro EV from cirrhotic with sepsis compared without sepsis, induced mobilization arrest in healthy monocytes within 4 hours (p=0.004), reduced basal oxygen consumption rate (p<0.001) and induced pro-inflammatory genes (p<0.05). The septic-EV on adoptive transfer to C57/BL6J mice, induced sepsis like condition within 24h with leukocytopenia (p=0.005), intrahepatic inflammation with increased CD11b+ cells (p=0.03) and bone marrow hyperplasia (p<0.01). CONCLUSION: Extracellular vesicles induce functional impairment in circulating monocytes and contribute to the development and perpetuation of sepsis. High levels of monocyte EV correlate with mortality and can help early stratification of sicker patients

    Model for End‐Stage Liver Disease‐Lactate and Prediction of Inpatient Mortality in Patients With Chronic Liver Disease

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163652/3/hep31199.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163652/2/hep31199_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163652/1/hep31199-sup-0001-Supinfo.pd

    Acute-on-chronic liver failure: consensus recommendations of the Asian Pacific Association for the Study of the Liver (APASL) 2014

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    Liver failure determines the outcome in patients of acute-on-chronic liver failure (ACLF): comparison of APASL ACLF research consortium (AARC) and CLIF-SOFA models

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    Background: Acute-on-chronic liver failure (ACLF) is a progressive disease associated with rapid clinical worsening and high mortality. Early prediction of mortality and intervention can improve patient outcomes. We aimed to develop a dynamic prognostic model and compare it with the existing models. Methods: A total of 1402 ACLF patients, enrolled in the APASL-ACLF Research Consortium (AARC) with 90-day follow-up, were analyzed. An ACLF score was developed in a derivation cohort (n = 480) and was validated (n = 922). Results: The overall survival of ACLF patients at 28 days was 51.7%, with a median of 26.3 days. Five baseline variables, total bilirubin, creatinine, serum lactate, INR and hepatic encephalopathy, were found to be independent predictors of mortality, with AUROC in derivation and validation cohorts being 0.80 and 0.78, respectively. AARC-ACLF score (range 5-15) was found to be superior to MELD and CLIF SOFA scores in predicting mortality with an AUROC of 0.80. The point scores were categorized into grades of liver failure (Gr I: 5-7; II: 8-10; and III: 11-15 points) with 28-day cumulative mortalities of 12.7, 44.5 and 85.9%, respectively. The mortality risk could be dynamically calculated as, with each unit increase in AARC-ACLF score above 10, the risk increased by 20%. A score of ≥11 at baseline or persisting in the first week was often seen among nonsurvivors (p = 0.001). Conclusion: The AARC-ACLF score is easy to use, dynamic and reliable, and superior to the existing prediction models. It can reliably predict the need for interventions, such as liver transplant, within the first week
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