HBV Associated Cirrhotic Patients Meeting Apasl Acute-On-Chronic Liver Failure Criteria Have Heterogeneous Outcome and Short Term Survival Rate

Abstract Introduction Patients with acutely decompensated (AD) cirrhosis are at risk for developing acute-on-chronic liver failure (ACLF) syndrome. This syndrome is associated with a high short-term mortality rate. The aim of our study was to identify reliable early predictors of developing ACLF in cirrhotic patients with AD. Patients and Methods We assessed 84 cirrhotic patients admitted for AD without ACLF on admission. We performed routine blood testing and detailed ultrasound Doppler studies of systemic arteries and mayor abdominal veins and arteries. We also calculated liver-specific and intensive care unit predictive scores. The area under the ROC curve (AUROC) was calculated for all variables that were significantly different between patients who developed ACLF and those who did not. Sensitivity, specificity, positive and negative predictive values, as well as diagnostic accuracy predicting the short-term development of ACLF were determined. Results of the 84 patients, 23 developed ACLF whereas 61 did not. In the univariate analysis, serum levels of creatinine and urea, prothrombin time ratio, MELD score, portal vein and femoral artery flow velocity as well as the renal and interlobar artery resistive indices (RI) were associated with the short-term development of ACLF. However, only interlobar artery RI had independent predictive value in the multivariate analysis. The AUROC value for RI of the interlobar arteries was 0.9971. Conclusion On the first day of admission, ultrasound measurement of the RI of the interlobar arteries recognizes with high predictive accuracy those cirrhotic patients admitted with AD who will develop ACLF during hospital admission.

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Fecal Microbiota Transplantation in Alcohol-Associated Acute on Chronic Liver Failure: An Open-label Clinical Trial

10.21203/rs.3.rs-408638/v1 ◽

2021 ◽

Author(s):

Anima Sharma ◽

Akash Roy ◽

Madhumita Premkumar ◽

Ajay Duseja ◽

Sunil Taneja ◽

...

Keyword(s):

Liver Failure ◽

Fecal Microbiota Transplantation ◽

Fecal Microbiota ◽

Chronic Liver ◽

Clinical Severity ◽

Chronic Liver Failure ◽

Short Term ◽

Open Label ◽

Term Survival ◽

Severity Scores

Abstract Background: Severe alcoholic hepatitis (SAH) presenting as acute-on-chronic liver failure (ACLF) carries a high short-term mortality. Alteration of gut microbiota is a crucial component implicated in its pathogenesis, whose modulation has been suggested as a potential therapeutic tool. We evaluated the safety of fecal microbiota transplantation (FMT) and its efficacy in improving short-term survival and clinical severity scores in patients with SAH-ACLF.Methods: Thirty-three patients [13 in the FMT arm;20 in the standard of care arm (SOC] with SAH-ACLF were included in this open-label study. A single FMT session was administered as a freshly prepared stool suspension from pre-identified healthy family member stool donors through a nasojejunal tube. Patients were followed up on days seven, twenty-eight, and ninety. Results: Survival at twenty-eight and ninety days was significantly better in the FMT arm (100% versus 60%, P=0.01; 53.84% versus 25%, P=0.02). Hepatic encephalopathy resolved in 100% versus 57.14% (FMT versus SOC, P=0.11) patients, while ascites resolved in 100% versus 40% survivors (P=0.04). Major adverse event rates, including spontaneous bacterial peritonitis and gastrointestinal bleeding, were similar in both groups (P=0.77; P=0.70). Median IL1beta decreased by21.39% (IQR -73.67-7.63) in the FMT group, whereas it increased in the SOC by 27.44% (IQR -0.88-128.11) (P=0.01). Percentage changes in bilirubin and ALT between baseline and day seven emerged as predictors of ninety-day mortality.Conclusion: FMT is safe, improves short-term and medium-term survival, and leads to improvement in clinical severity scores in patients with SAH-ACLF.

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Value of Liver Regeneration in Predicting Short-Term Prognosis for Patients with Hepatitis B-Related Acute-on-Chronic Liver Failure

BioMed Research International ◽

10.1155/2020/5062873 ◽

2020 ◽

Vol 2020 ◽

pp. 1-7

Author(s):

Xiaoping Wang ◽

Mengying Sun ◽

Xianjun Yang ◽

Liucun Gao ◽

Min Weng ◽

...

Keyword(s):

Prognostic Factors ◽

Hepatitis B ◽

Liver Failure ◽

Scoring System ◽

Chronic Liver ◽

Hepatic Regeneration ◽

Chronic Liver Failure ◽

Short Term ◽

Term Survival ◽

Hepatocyte Regeneration

Background and Aims. The value of hepatocyte regeneration in predicting the outcomes of hepatitis B-related acute-on-chronic liver failure (HBV-ACLF) is not fully assessed. The present study was aimed at establishing a novel scoring system to predict patients’ outcomes within 3 months by applying serological indicators of hepatic regeneration and liver injury. Methods. Patients with chronic hepatitis B who had a rapid deterioration were investigated. Patients were observed for 90 days, and the endpoint of follow-up was death or liver transplantation. Serum parameters were estimated on the diagnosis of acute-on-chronic liver failure (ACLF). Cox proportional hazard regression was used to identify independent prognostic factors and create a novel prognostic scoring system, and a receiver operating characteristic (ROC) curve was used to analyze the performance of the model. Results. A total of 308 patients with HBV-ACLF were incorporated and divided into the training cohort (n=206) and testing cohort (n=102) randomly. Creatine (Cre), age, total bilirubin (TBil), alpha-fetoprotein (AFP), and international normalized ratio (INR) were found to be independent prognostic factors. According to the results of Cox regression analysis, a new prognostic model (we named it the TACIA score) was calculated. The areas under ROC (AUROC) for the new model were 0.861 and 0.763 in the training and testing cohorts, respectively, and patients with lower TACIA scores (<4.34) would survive longer (P<0.001). Conclusions. A pertinent prognostic scoring system for patients with HBV-ACLF was established in our study, and the novel model could predict patients’ short-term survival effectively.

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Models To Predict The Short-Term Survival of Acute-On-Chronic Liver Failure Patients Following Liver Transplantation

10.21203/rs.3.rs-1066854/v1 ◽

2021 ◽

Author(s):

Min Yang ◽

Bo Peng ◽

Quan Zhuang ◽

Junhui Li ◽

Hong Liu ◽

...

Keyword(s):

Liver Transplantation ◽

Liver Disease ◽

Cox Regression ◽

Meld Score ◽

Chronic Liver ◽

Chronic Liver Failure ◽

Short Term ◽

Term Survival ◽

Conventional Models ◽

Short Term Survival

Abstract Background: Acute-on-chronic liver failure (ACLF) is featured with rapid deterioration of chronic liver disease and poor short-term prognosis. Liver transplantation (LT) is recognized as the curative option for ACLF. However, there is no standard in the prediction of the short-term survival among ACLF patients following LT.Method: Preoperative data of 132 ACLF patients receiving LT at our center were investigated retrospectively. Cox regression was performed to determine the risk factors for short-term survival among ACLF patients following LT. Five conventional score systems (the MELD score, ABIC, CLIF-C OFs, CLIF-SOFAs and CLIF-C ACLFs) in forecasting short-term survival were estimated through the receiver operating characteristic (ROC). Four machine-learning (ML) models, including support vector machine (SVM), logistic regression (LR), multi-layer perceptron (MLP) and random forest (RF), were also established for short-term survival prediction.Results: Cox regression analysis demonstrated that creatinine (Cr) and international normalized ratio (INR) were the two independent predictors for short-term survival among ACLF patients following LT. The ROC curves showed that the area under the curve (AUC) ML models was much larger than that of conventional models in predicting short-term survival. Among conventional models the model for end stage liver disease (MELD) score had the highest AUC (0.704), while among ML models the RF model yielded the largest AUC (0.940). Conclusion:Compared with the traditional methods, the ML models showed good performance in the prediction of short-term prognosis among ACLF patients following LT and the RF model perform the best. It is promising to optimize organ allocation and promote transplant survival based on the prediction of ML models.

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