The utilization of extracorporeal liver support systems is increasingly prevalent for the management of acute-on-chronic liver failure in clinical settings. Yet, the efficacy of these interventions in terms of tangible clinical benefits for patients remains a matter of debate, underscoring the need for meta-analysis.

An updated meta-analysis was performed to elucidate the relationship between the application of extracorporeal liver support versus standard pharmacological treatment and the prognostic endpoints of patient survival, specifically assessing 1-month and 3-month mortality rates, as well as the incidence of complications such as hepatic encephalopathy, spontaneous bacterial peritonitis, and hepatorenal syndrome. Literature were searched via PubMed, EMBASE, and Web of Science.

The meta-analysis revealed the following: the odds ratio for 1-month mortality was 0.63 (95% confidence interval [CIs]: 0.51-0.76), for 3-month mortality was 0.70 (95% CI: 0.61-0.81), for hepatic encephalopathy was 0.81 (95% CI: 0.67-0.97), for spontaneous bacterial peritonitis was 0.66 (95% CI: 0.44-0.99), and for hepatorenal syndrome was 0.68 (95% CI: 0.51-0.92). These results suggest that patients with acute-on-chronic liver failure undergoing extracorporeal liver support system therapy have significantly better survival rates and lower complication incidences compared to those receiving conventional drug therapy. Further subgroup analysis indicated that patients with lower model for end-stage liver disease (MELD) scores and reduced total bilirubin (Tbil) levels demonstrated greater benefits from extracorporeal hepatic support.

This study establishes that in the management of acute-on-chronic liver failure, extracorporeal liver support systems confer a survival advantage and reduce complications relative to standard pharmacotherapy.

Over the past six decades, liver transplantation (LT) has evolved from an experimental procedure into a standardized and life-saving intervention, reshaping the landscape of organ transplantation. Driven by pioneering breakthroughs, technological advancements, and a deepened understanding of immunology, LT has seen remarkable progress. Some of the most notable breakthroughs in the field include advances in immunosuppression, a revised model for end-stage liver disease, and artificial intelligence (AI)-integrated imaging modalities serving diagnostic and therapeutic roles in LT, paired with ever-evolving technological advances. Additionally, the refinement of transplantation procedures, resulting in the introduction of alternative transplantation methods, such as living donor LT, split LT, and the use of marginal grafts, has addressed the challenge of organ shortage. Moreover, precision medicine, guiding personalized immunosuppressive strategies, has significantly improved patient and graft survival rates while addressing emergent issues, such as short-term complications and early allograft dysfunction, leading to a more refined strategy and enhanced post-operative recovery. Looking ahead, ongoing research explores regenerative medicine, diagnostic tools, and AI to optimize organ allocation and post-transplantation car. In summary, the past six decades have marked a transformative journey in LT with a commitment to advancing science, medicine, and patient-centered care, offering hope and extending life to individuals worldwide.

Acute-on-chronic liver failure (ACLF) is a life-threatening hepatic syndrome. Therefore, this study aimed to develop a comprehensive model combining extracellular liver volume derived from spectral CT (ECVIC-liver) and sarcopenia, for the early prediction of short-term (90-day) disease progression in ACLF.

A retrospective cohort of 126 ACLF patients who underwent hepatic spectral CT scans was included. According to the Asia-Pacific Association for the Study of the Liver (APASL) criteria, patients were divided into the progression group (n = 70) and the stable group (n = 56). ECVIC-liver was measured on the equilibrium period (EP) images of spectral CT, and L3-SMI was measured on unenhanced CT images, with sarcopenia assessed. A comprehensive model was developed by combining independent predictors. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA).

In the univariate analysis, BMI, WBC, PLT, PTA, L3-SMI, IC-EP, Z-EP, K140-EP, NIC-EP, ECVIC-liver, and Sarcopenia demonstrated associations with disease progression status at 90 days in ACLF patients. In multivariate logistic regression, white blood cell count (WBC) (OR = 1.19, 95% CI: 1.02-1.40; P = 0.026), ECVIC-liver (OR = 1.27, 95% CI: 1.15-1.40; P < 0.001), sarcopenia (OR = 4.15, 95% CI: 1.43-12.01; P = 0.009), MELD-Na score (OR = 1.06, 95%CI: 1.01-1.13;P = 0.042), and CLIF-SOFA score (OR = 1.37, 95%CI:1.15-1.64; P<0.001) emerged as independent risk factors for ACLF progression. The combined model exhibited superior predictive performance (AUCs = 0.910, sensitivity = 80.4%, specificity = 90.0%, PPV = 0.865, NPV = 0.851) compared to CLIF-SOFA, MELD-Na, MELD and CTP scores(both P < 0.001). Calibration curves and DCA confirmed the high clinical utility of the combined model.

Patients without sarcopenia and/or with a lower ECVIC-liver have a better prognosis, and the integration of WBC, ECVIC-liver, Sarcopenia, CLIF-SOFA and MELD-Na scores in a composite model offers a concise and effective tool for predicting disease progression in ACLF patients.

Not Applicable.

Accurate prediction of survival in patients with cirrhosis is crucial, as patients who are unlikely to survive in the short-term need to be oriented to liver transplantation and to novel therapeutic approaches. Patients with acute decompensation of cirrhosis without or with organ dysfunction/failure, the so-called acute-on-chronic liver failure (ACLF), have a particularly high short-term mortality. Recognizing the specificity of this clinical situation, dedicated classifications and scores have been developed over the last 15 years, including variables (e.g. organ failures and systemic inflammation) not part of the formerly available cirrhosis severity scores, namely Child-Pugh score or MELD. For patients with acute decompensation of cirrhosis, it led to the development of a dedicated score, the Clif-C-AD score, independently validated. For more severe patients, three different scoring systems have been proposed, by European, Asian and North American societies namely Clif-C-ACLF, AARC score and NASCELD-ACLF respectively. These scores have been validated, and are widely used across the world. The differences and similarities between these scores, as well as their validation and limitations are discussed here. Even if these scores and classifications have been a step forward in favouring homogeneity between studies, and in helping making decisions for individual patients, their predictive value for mortality can still be improved as their area under the ROC curve does not exceed .8. Novel scores including biomarkers reflecting the pathophysiology of acute decompensation of cirrhosis might help reach that goal.

Acute on chronic liver failure (ACLF) reflects the development of organ failure(s) in a patient with cirrhosis and is associated with high short-term mortality. Given that ACLF has many different 'phenotypes', medical management needs to take into account the relationship between precipitating insult, organ systems involved and underlying physiology of chronic liver disease/cirrhosis. The goals of intensive care management of patients suffering ACLF are to rapidly recognize and treat inciting events (e.g. infection, severe alcoholic hepatitis and bleeding) and to aggressively support failing organ systems to ensure that patients may successfully undergo liver transplantation or recovery. Management of these patients is complex since they are prone to develop new organ failures and infectious or bleeding complications. ICU therapy parallels that applied in the general ICU population in some complications but differs in others. Given that liver transplantation in ACLF is an emerging and evolving field, multidisciplinary teams with expertise in critical care and transplant medicine best accomplish management of the critically ill ACLF patient. The focus of this review is to identify the common complications of ACLF and to describe the proper management in critically ill patients awaiting liver transplantation in our centres, including organ support, prognostic assessment and how to assess when recovery is unlikely.

Acute-on-chronic liver failure (ACLF) is a condition associated with high mortality in the absence of liver transplantation. There have been various definitions proposed worldwide. The first consensus report of the working party of the Asian Pacific Association for the Study of the Liver (APASL) set in 2004 on ACLF was published in 2009, and the "APASL ACLF Research Consortium (AARC)" was formed in 2012. The AARC database has prospectively collected nearly 10,500 cases of ACLF from various countries in the Asia-Pacific region. This database has been instrumental in developing the AARC score and grade of ACLF, the concept of the 'Golden Therapeutic Window', the 'transplant window', and plasmapheresis as a treatment modality. Also, the data has been key to identifying pediatric ACLF. The European Association for the Study of Liver-Chronic Liver Failure (EASL CLIF) and the North American Association for the Study of the End Stage Liver Disease (NACSELD) from the West added the concepts of organ failure and infection as precipitants for the development of ACLF and CLIF-Sequential Organ Failure Assessment (SOFA) and NACSELD scores for prognostication. The Chinese Group on the Study of Severe Hepatitis B (COSSH) added COSSH-ACLF criteria to manage hepatitis b virus-ACLF with and without cirrhosis. The literature supports these definitions to be equally effective in their respective cohorts in identifying patients with high mortality. To overcome the differences and to develop a global consensus, APASL took the initiative and invited the global stakeholders, including opinion leaders from Asia, EASL and AASLD, and other researchers in the field of ACLF to identify the key issues and develop an evidence-based consensus document. The consensus document was presented in a hybrid format at the APASL annual meeting in Kyoto in March 2024. The 'Kyoto APASL Consensus' presented below carries the final recommendations along with the relevant background information and areas requiring future studies.

Machine learning (ML) can identify the hidden patterns without hypothesis in heterogeneous diseases like acute-on-chronic live failure (ACLF). We employed ML to describe and predict yet unknown clusters in ACLF.

Clinical data of 1568 patients with ACLF from a tertiary care centre (2015-2023) were subjected to distance-, density- and model-based clustering algorithms. Final model was selected on best cluster separation, viz. Silhouette width and Dunn's index (for distance- or density-based algorithms) and minimum BIC (for model-based algorithms). Cluster assignments, patient trajectories and survival were analysed through inferential statistics. Supervised ML models were trained in 70% data that predicted clusters in remaining 30% data followed by an temporal validation.

The cohort was male-predominant (87%), aged 44.3 years, with alcohol-associated hepatitis (62.9%) and survival of 50.5%. Due to poor performance of distance- and density-based algorithms and better explainability, the latent class model (LCM) was selected for exploration. LCM revealed four clusters with distinct trajectories, reversibility and survival (independent of MELD, CLIF-C ACLF and AARC scores). Cluster1 had patients with none/one organ failure and highest reversibility. Cluster2 had females with viral hepatitis and two organ failures. More-than-one acute precipitant, severity, infections, organ failures and irreversibility escalated from clusters 1 to 4. Circulatory and renal failures critically influenced cluster assignments. Incorporating clusters to CLIF-C ACLF, infection and ACLF definition improved the discriminative accuracy of CLIF-C-ACLF by 11%. Extreme gradient boost and decision trees could predict clusters with AUCs of 0.989 (0.979-0.995) and 0.875 (0.865-0.890). MELD, CLIF-C-OF, haemoglobin, lactate, CLIF-C-ACLF and ALT were critical variables for cluster prediction. Clusters with distinct survival were documented in a temporal validation cohort.

ML for the first time could identify clusters with distinct phenotypes, trajectories and outcomes in ACLF. Stratification into clusters can address heterogeneity, guide prognosis, recruitment in trials, resource allocation and liver transplant discussions in ACLF.

Acute-on-chronic liver failure (ACLF) is a major public health concern. We aimed to assess the definitions, etiologic spectrum, organ failure (OF), and outcomes of ACLF globally.

Three databases were searched for studies on ACLF from 1990 until September 2022. Information regarding definitions, acute precipitants, underlying chronic liver disease (CLD), OF, and mortality were extracted. Meta-analyses were performed for pooled prevalence rates (95% confidence interval [CI]) using random-effects model for each definition of ACLF.

Of the 11,451 studies identified, 114 articles (142 cohorts encompassing 210,239 patients) met the eligibility criteria. Most studies (53.2%) used the European Association for the Study of the Liver (EASL) definition, followed by Asia-Pacific Association for the Study of the Liver (APASL) (33.3%). Systemic infection was the major acute precipitant, and alcohol use was the major cause of CLD in EASL-defined studies, whereas alcohol was both the major acute precipitant and cause of CLD in APASL-defined studies. Liver failure was the major OF in APASL-based studies, whereas renal failure was predominant in EASL-based studies. Thirty-day mortality varied across definitions: APASL: 38.9%, 95% CI, 31.2%-46.9%; EASL: 47.9%, 95% CI, 42.2%-53.5%; and NACSELD: 52.2%, 95% CI, 51.9%-52.5%. Diagnostic overlap between definitions ranged from 7.7% to 80.2%. Meta-regression suggested that the World Health Organization region influenced 30-day mortality in studies using EASL definition.

Heterogeneity in the definition of ACLF proposed by different expert societies and regional preferences in its use result in differences in clinical phenotype and outcomes. A uniform definition would enhance the comparability and interpretation of global data.

Early determination of prognosis in patients with acute-on-chronic liver failure (ACLF) is crucial for optimizing treatment options and liver allocation. This study aimed to identify risk factors associated with ACLF and to develop new prognostic models that accurately predict patient outcomes.

We retrospectively selected 1,952 hospitalized patients diagnosed with ACLF between January 2010 and June 2018. This cohort was used to develop new prognostic scores, which were subsequently validated in external groups.

The study included 1,386 ACLF patients and identified six independent predictors of 28-day mortality through multivariate analysis (all p < 0.05). The new score, based on a multivariate regression model, demonstrated superior predictive accuracy for both 28-day and 90-day mortalities, with Areas under the ROC curves of 0.863 and 0.853, respectively (all p < 0.05). This score can be used to stratify the risk of mortality among ACLF patients with ACLF, showing a significant difference in survival between patients categorized by the cut-off value (log-rank (Mantel-Cox) χ2 = 487.574 and 606.441, p = 0.000). Additionally, the new model exhibited good robustness in two external cohorts.

This study presents a refined prognostic model, the Model for end-stage liver disease-complication score, which accurately predicts short-term mortality in ACLF patients. This model offers a new perspective and tool for improved clinical decision-making and short-term prognostic assessment in ACLF patients.

Commonly used prognostic scores for acute on-chronic liver failure (ACLF) have complex calculations. We tried to compare the simple counting of numbers and types of organ dysfunction to these scores, to predict mortality in ACLF patients.

In this prospective cohort study, ACLF patients diagnosed on the basis of Asia Pacific Association for Study of the Liver (APASL) definition were included. Severity scores were calculated. Prognostic factors for outcome were analysed. A new score, the Number of Organ Dysfunctions in Acute-on-Chronic Liver Failure (NOD-ACLF) score was developed.

Among 80 ACLF patients, 74 (92.5%) were male, and 6 were female (7.5%). The mean age was 41.0±10.7 (18-70) years. Profile of acute insult was; alcohol 48 (60%), sepsis 30 (37.5%), variceal bleeding 22 (27.5%), viral 8 (10%), and drug-induced 3 (3.8%). Profiles of chronic insults were alcohol 61 (76.3%), viral 20 (25%), autoimmune 3 (3.8%), and non-alcoholic steatohepatitis 2 (2.5%). Thirty-eight (47.5%) were discharged, and 42 (52.5%) expired. The mean number of organ dysfunction (NOD-ACLF score) was ->4.5, simple organ failure count (SOFC) score was >2.5, APASL ACLF Research Consortium score was >11.5, Model for End-Stage Liver Disease-Lactate (MELD-LA) score was >21.5, and presence of cardiovascular and respiratory dysfunctions were significantly associated with mortality. NOD-ACLF and SOFC scores had the highest area under the receiver operating characteristic to predict mortality among all these.

The NOD-ACLF score is easy to calculate bedside and is a good predictor of mortality in ACLF patients performing similar or better to other scores.

Acute-on-chronic liver disease (AoCLD) accounts for the majority of patients hospitalized in the Department of Hepatology or Infectious Diseases.

To explore the characterization of AoCLD to provide theoretical guidance for the accurate diagnosis and prognosis of AoCLD.

Patients with AoCLD from the Chinese Acute-on-Chronic Liver Failure (ACLF) study cohort were included in this study. The clinical characteristics and outcomes, and the 90-d survival rate associated with each clinical type of AoCLD were analyzed, using the Kaplan-Meier method and the log-rank test.

A total of 3375 patients with AoCLD were enrolled, including 1679 (49.7%) patients with liver cirrhosis acute decompensation (LC-AD), 850 (25.2%) patients with ACLF, 577 (17.1%) patients with chronic hepatitis acute exacerbation (CHAE), and 269 (8.0%) patients with liver cirrhosis active phase (LC-A). The most common cause of chronic liver disease (CLD) was HBV infection (71.4%). The most common precipitants of AoCLD was bacterial infection (22.8%). The 90-d mortality rates of each clinical subtype of AoCLD were 43.4% (232/535) for type-C ACLF, 36.0% (36/100) for type-B ACLF, 27.0% (58/215) for type-A ACLF, 9.0% (151/1679) for LC-AD, 3.0% (8/269) for LC-A, and 1.2% (7/577) for CHAE.

HBV infection is the main cause of CLD, and bacterial infection is the main precipitant of AoCLD. The most common clinical type of AoCLD is LC-AD. Early diagnosis and timely intervention are needed to reduce the mortality of patients with LC-AD or ACLF.

Cirrhosis is a major cause of death worldwide, and is associated with significant health care costs. Even if milestones have been recently reached in understanding and managing end-stage liver disease (ESLD), the disease course remains somewhat difficult to prognosticate. These difficulties have already been acknowledged already in the past, when scores instead of single parameters have been proposed as valuable tools for short-term prognosis. These standard scores, like Child Turcotte Pugh (CTP) and model for end-stage liver disease (MELD) score, relying on biochemical and clinical parameters, are still widely used in clinical practice to predict short- and medium-term prognosis. The MELD score, which remains an accurate, easy-to-use, objective predictive score, has received significant modifications over time, in order to improve its performance especially in the liver transplant (LT) setting, where it is widely used as prioritization tool. Although many attempts to improve prognostic accuracy have failed because of lack of replicability or poor benefit with the comparator (often the MELD score or its variants), few scores have been recently proposed and validated especially for subgroups of patients with ESLD, as those with acute-on-chronic liver failure. Artificial intelligence will probably help hepatologists in the near future to fill the current gaps in predicting disease course and long-term prognosis of such patients.

Acute-on-chronic liver failure (ACLF) is a clinical syndrome characterized by severe hepatic dysfunction leading to multiorgan failure in patients with end-stage liver disease. ACLF is a challenging clinical syndrome with a rapid clinical course and high short-term mortality. There is no single uniform definition of ACLF or consensus in predicting ACLF-related outcomes, which makes comparing studies difficult and standardizing management protocols challenging. This review aims to provide insights into the common prognostic models that define and grade ACLF.

The reported burden of multidrug-resistant organism (MDRO) infections is highest in patients with cirrhosis from India. We evaluated whether colonisation at multiple barriers predisposes to such infections and poor outcomes in patients with cirrhosis.

We prospectively performed swab cultures, antimicrobial susceptibility testing (AST), and genotype testing for MDROs from various sites (rectum, nose, composite-skin, and central-line) in patients with cirrhosis (2020-2021) on admission and follow-up at a tertiary institute. We analysed clinical data, risk factors for MDROs, and patient outcomes.

Of 125 patients aged 49 years, 85.6% males, 60.8% with acute-on-chronic liver failure, 99 (79.2%) were identified as 'colonisers'. MDRO-colonisation at rectum, nose, skin, or central line was observed in 72.7% (88/121), 30.0% (36/120), 14.9% (18/121), and 3.3% (4/121) patients, respectively. Patients were colonised with the following types of bacteria: extended-spectrum beta-lactamase (71/125), carbapenem-resistant Enterobacterales (67/125), MDR-Enterococcus (48/125), MDR-Acinetobacter (21/125), or methicillin-resistant Staphylococcus aureus (4/125). Multiple precipitants of acute-decompensation (odds ratio [OR]: 3.4, p = 0.042), norfloxacin prophylaxis (OR: 3.9, p = 0.008), and MDRO infection at admission (OR: 8.9, p = 0.041) were the independent predictors of colonisation. Colonisation increased the risk of infection by MDROs at admission (OR: 8.5, p = 0.017) and follow up (OR: 7.5, p <0.001). Although any-site colonisers were at greater risk of cerebral failure and poorer Child-Pugh scores, the nasal and skin colonisers were at higher risk of cerebral and circulatory failures than non-colonisers (p <0.05).Patients with more than one site colonisation (prevalence: 30%) developed multi-organ failure (p <0.05), MDRO infection (OR: 7.9, p <0.001), and poorer 30-day survival (hazard ratio: 2.0, p = 0.005).

A strikingly high burden of MDRO colonisation among patients with cirrhosis in India necessitates urgent control measures. Multiple-site colonisation increases the risk of MDR-infections, multi-organ failure, and mortality in patients with cirrhosis.

Infections by bacteria resistant to multiple antibiotics are an emerging cause of death in cirrhosis. We showed that ∼70-80% of critically ill hospitalised patients with cirrhosis carry such bacteria with the highest rate in the rectum, nose, skin, and central line port. Carbapenem-resistant and vancomycin-resistant bacteria were amongst the most common colonising bacteria. The presence of these bacteria at multiple sites increased the risk of multidrug-resistant infections, multiple organ failures, and death in patients with cirrhosis.

Intensive care unit (ICU) admission is frequently required in patients with decompensated cirrhosis for organ support. This entity, known as acute-on-chronic liver failure (ACLF), is associated with high short-term mortality. ICU management of ACLF is complex, as these patients are prone to develop new organ failures and infectious or bleeding complications. Poor nutritional status, lack of effective liver support systems, and shortage of liver donors are also factors that contribute to increase their mortality. ICU therapy parallels that applied in the general ICU population in some complications but has differential characteristics in others. This review describes the current knowledge on critical care management of patients with ACLF including organ support, prognostic assessment, early liver transplantation, and futility rules. Certainties and knowledge gaps in this area are also discussed.

We hypothesized that artificial intelligence (AI) models are more precise than standard models for predicting outcomes in acute-on-chronic liver failure (ACLF).

We recruited ACLF patients between 2009 and 2020 from APASL-ACLF Research Consortium (AARC). Their clinical data, investigations and organ involvement were serially noted for 90-days and utilized for AI modelling. Data were split randomly into train and validation sets. Multiple AI models, MELD and AARC-Model, were created/optimized on train set. Outcome prediction abilities were evaluated on validation sets through area under the curve (AUC), accuracy, sensitivity, specificity and class precision.

Among 2481 ACLF patients, 1501 in train set and 980 in validation set, the extreme gradient boost-cross-validated model (XGB-CV) demonstrated the highest AUC in train (0.999), validation (0.907) and overall sets (0.976) for predicting 30-day outcomes. The AUC and accuracy of the XGB-CV model (%Δ) were 7.0% and 6.9% higher than the standard day-7 AARC model (p < .001) and 12.8% and 10.6% higher than the day 7 MELD for 30-day predictions in validation set (p < .001). The XGB model had the highest AUC for 7- and 90-day predictions as well (p < .001). Day-7 creatinine, international normalized ratio (INR), circulatory failure, leucocyte count and day-4 sepsis were top features determining the 30-day outcomes. A simple decision tree incorporating creatinine, INR and circulatory failure was able to classify patients into high (~90%), intermediate (~60%) and low risk (~20%) of mortality. A web-based AARC-AI model was developed and validated twice with optimal performance for 30-day predictions.

The performance of the AARC-AI model exceeds the standard models for outcome predictions in ACLF. An AI-based decision tree can reliably undertake severity-based stratification of patients for timely interventions.

Acute-on-chronic liver failure (ACLF) is a syndrome characterized by decompensation in individuals with chronic liver disease, generally secondary to one or more extra-hepatic organ failures, implying an elevated mortality rate. Acute decompensation (AD) is the term used for one or more significant consequences of liver disease in a short time and is the most common reason for hospital admission in cirrhotic patients. The European Association for the Study of Liver-Chronic-Liver Failure (EASL-CLIF) Group modified the intensive care Sequential Organ Failure Assessment score into CLIF-SOFA, which detects the presence of ACLF in patients with or without AD, classifying it into three grades.

To investigate the role of the EASL-CLIF definition for ACLF and the ability of CLIF-SOFA, CLIF-C ACLF, and CLIF-C AD scores for prognosticating ACLF or AD.

This study is a literature review using a standardized search method, conducted using the steps following the guidelines for reporting systematic reviews set out by the PRISMA statement. For specific keywords, relevant articles were found by searching PubMed, ScienceDirect, and BioMed Central-BMC. The databases were searched using the search terms by one reviewer, and a list of potentially eligible studies was generated based on the titles and abstracts screened. The data were then extracted and assessed on the basis of the Reference Citation Analysis (https://www.referencecitationanalysis.com/).

Most of the included studies used the EASL-CLIF definition for ACLF to identify cirrhotic patients with a significant risk of short-term mortality. The primary outcome in all reviewed studies was mortality. Most of the study findings were based on an area under the receiver operating characteristic curve (AUROC) analysis, which revealed that CLIF-SOFA, CLIF-C ACLF, and CLIF-C AD scores were preferable to other models predicting 28-d mortality. Their AUROC scores were higher and able to predict all-cause mortality at 90, 180, and 365 d. A total of 50 articles were included in this study, which found that the CLIF-SOFA, CLIF-C ACLF and CLIF-C AD scores in more than half of the articles were able to predict short-term and long-term mortality in patients with either ACLF or AD.

CLIF-SOFA score surpasses other models in predicting mortality in ACLF patients, especially in the short-term. CLIF-SOFA, CLIF-C ACLF, and CLIF-C AD are accurate short-term and long-term mortality prognosticating scores.

Acute-on-chronic liver failure (ACLF) is a syndrome that develops in patients with acutely decompensated chronic liver disease. It is characterised by high 28-day mortality, the presence of one or more organ failures (OFs) and a variable but severe grade of systemic inflammation. Despite the peculiarity of each one, every definition proposed for ACLF recognizes it as a proper clinical entity. In this paper, we provide an overview of the diagnostic criteria proposed by the different scientific societies and the clinical characteristics of the syndrome. Established and experimental treatments are also described. Among the former, the most relevant are directed to support organ failures, treat precipitating factors and carry out early assessment for liver transplantation (LT). Further studies are needed to better clarify pathophysiology of the syndrome and discover new therapies.