الفهرس 
Acute-on-Chronic Liver FailureOnly 14 pages are availabe for public view
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Abstract
ACLF is a major cause of mortality in patients with cirrhosis and chronic liver disease worldwide. An international consensus definition for ACLF is currently lacking and thus there is heterogeneity in how these patients are identified and subsequently managed in different settings.
EASL defined ACLF as (a specific syndrome in patients with cirrhosis or chronic liver disease that is characterized by acute decompensation (AD), organ failure, and high short-term mortality.” The diagnosis of organ failures is based on the chronic Liver Failure-Consortium (CLIF-C) OF (CLIF-C OF) scoring system which assesses 6 organ systems (liver, kidney, brain, coagulation, circulation, and respiration)
ACLF is a dynamic syndrome with systemic inflammation, immune paralysis, and multi-organ failure being the hallmarks. Whilst it is clear that early diagnosis, prevention of precipitating factors, and aggressive ICU care with organ support improves prognosis; treatment for ACLF is currently broadly restricted essentially to supportive care, prevention and management of complications. Novel therapies targeting the various pathophysiological mechanisms in development of ACLF are desperately needed, Extracorporeal liver support devices have failed to reduce mortality in ACLF patients.
Prognostication is challenging given the dynamic course of ACLF and requires day-to-day assessment. it is critical to stratify patients according to prognosis in order to monitor treatment responsiveness, determine emergency for transplantation, and decide allocation in the ICU, It is important to develop predictive scores that can identify patients who are at high risk of mortality, enabling the early provision of effective treatment to reduce mortality, especially in diseases with high mortality rates As {MELD score, CHILD Pugh score, APACHE score, CLIF C OF score, CLIF C ACLF score } and here which the aim of our study is to assess the prognostic Accuracy of CLIF C ACLF score the modified simple score for CLIF SOFA score in predicting 28 day mortality in patients with ACLF. However, in the clinical setting, the prognosis is often hard to predict for certain patients because of different factors, such as etiology, disease stage, and complications. Previous studies have shown that many different scores have predictive value for mortality in ACLF patients. It is very important to choose the most efficient score for predicting mortality in patients in clinical treatment.
Our study suggested that the CLIF-C ACLF score was the best prognostic predictor that could predict 28-day, CLIF-c ACLF score is composed of both clinical parameters and laboratory profiles, this might explain the better performance in predicting prognosis over using a single laboratory profile alone.
The CLIF-C ACLF score combines CLIF-OF score with patients’ age and white blood cell (WBC) count to generate a composite score of 0–100 in a linear range with the following formula: {CLIF-C ACLF = 10 × (0.33 × CLIF-OFs + 0.04xAge +0.63 × (WBC count) – 2}.and according to specific calculator containing the following parameters of CLIF C OF added on to WBCS count and age.
Our study was a retrospective cohort study that was carried out in Ain shams university hospitals (Tropical Medicine Department, Intermediate Care unit Of Tropical medicine Department, Intensive care units Of Ain Shams University Hospital)
Our study was conducted on 70 patients (47 males, 23 females). All the 70 patients were studied in retrospective manner in the period from 12/2019 to 12/2021 in the form of collecting records of patients with Acute on top of chronic liver cell failure ACLF.
Of the 70 patients included in the study, 49 died within 28 days and 21 remained Alive after 28 days. The CLIF C ACLF score was compared between alive and died patients between days 1 and day 3 of admission and was higher in patients who died in comparison to whom who lived but doesn’t reach a statistically significant difference at day 1 in relation to day3 that showed statistically significant difference
Different causes and precipitating factors was assessed, in our study, HCV was the most common cause of chronic liver disease (55.7%). This is consistent with the fact that Egypt has the highest HCV prevalence in the world, which represents the main etiology of chronic liver disease among the Egyptian population.
Our study Also revealed that Acute infection was the most common precipitating event for Acute on top of chronic failure in 70 % of cases And this was attributed to the activation of immune system related inflammatory cells that lead to activation of inflammatory cascade and release of cytokines the entire cascade lead to SIRS that lead to hepatocyte death and liver dysfunction.
Our study showed that there is a significant change in grade of hepatic encephalopathy with more deterioration noted for died patients at day 3, elevation of patients laboratory findings as Total leucocytic count, bilirubin, INR, AST/ALT, and significant decrease in level of Albumin, platelets, pressured oxygen level at day 3 compared to day 1.
And finally there was statistically significant increase in the CLIF-c ACLF score and so probability of death within 28 days (%) in died patients than alive patients at day 1, Also CLIF-c ACLF score and probability of death at 28 days (%) was found higher in died patients than alive patients at day 3. also that the best cut off point for CLIF-c ACLF score at day 1 to predict mortality at 28 days was found >53 with sensitivity of 75.51%, and specificity of 95.24%,while the best cut off point for CLIF-c ACLF score at day 3 was found >54 with sensitivity of 97.96%, specificity of 100.0%.
Conclusively multivariate logistic regression analysis shows that the most important factor associated with mortality was found CLIF-c ACLF score > 53.
But we had some limitations in our study including being a single-center study. The high proportion of patients with HCV-related liver cirrhosis could hinder the generalization of the results. In addition, the small sample size represents a weak point in our study Also this study center was a university hospital; thus, our study was subjected to referral bias and had a higher proportion of severe cases. These factors possibly contributed to a worse prognosis than that of the general population.