Development and validation of a dynamic outcome prediction model for paracetamol-induced acute liver failure: a cohort study

Future directions in acute liver failure

Acute liver failure (ALF) describes a clinical syndrome of rapid hepatocyte injury leading to liver failure manifested by coagulopathy and encephalopathy in the absence of pre-existing cirrhosis. The hallmark diagnostic features are a prolonged prothrombin time (ie, an international normalized ratio of prothrombin time of ≥1.5) and any degree of mental status alteration (HE). As a rare, orphan disease, it seemed an obvious target for a multicenter network. The Acute Liver Failure Study Group (ALFSG) began in 1997 to more thoroughly study and understand the causes, natural history, and management of ALF. Over the course of 22 years, 3364 adult patients were enrolled in the study registry (2614 ALF and 857 acute liver injury-international normalized ratio 2.0 but no encephalopathy-ALI) and >150,000 biosamples collected, including serum, plasma, urine, DNA, and liver tissue. Within the Registry study sites, 4 prospective substudies were conducted and published, 2 interventional ( N -acetylcysteine and ornithine phenylacetate), 1 prognostic [ 13 C-methacetin breath test (MBT)], and 1 mechanistic (rotational thromboelastometry). To review ALFSG's accomplishments and consider next steps, a 2-day in-person conference was held at UT Southwestern Medical Center, Dallas, TX, entitled "Acute Liver Failure: Science and Practice," in May 2022. To summarize the important findings in the field, this review highlights the current state of understanding of ALF and, more importantly, asks what further studies are needed to improve our understanding of the pathogenesis, natural history, and management of this unique and dramatic condition.

Acute Liver Failure: Biomarkers Evaluated by the Acute Liver Failure Study Group

There has been a growing interest in identifying prognostic biomarkers that alone or with available prognostic models (King's College Criteria, KCC; MELD and ALFSG Prognostic Index) would improve prognosis in acute liver failure (ALF) patients being assessed for liver transplantation. The Acute Liver Failure Study Group (ALFSG) has evaluated 15 potential prognostic biomarkers: serum AFP; apoptosis-associated proteins; serum actin-free Gc-globulin; serum glycodeoxycholic acid; sRAGE/RAGE ligands; plasma osteopontin; circulating MBL, M-, L-, H-ficolin and CL-1; plasma galectin-9; serum FABP1; serum Lct2; miRNAs; factor V; thrombocytopenia, and sCD163. The ALFSG also has reported on 4 susceptibility biomarkers: keratins 8 and 18 (K8/K18) gene variants; polymorphisms of genes encoding putative APAP-metabolizing enzymes ( UGT1A1 , UGT 1A0 , UGT 2B15 , SULT1A1 , CYP2E1 , and CYP3A5 ) as well as CD44 and BHMT1 ; single nucleotide polymorphisms (SNPs) of genes associated with human behavior, rs2282018 in the arginine vasopressin ( AVP ) gene and rs11174811 in the AVP receptor 1A gene. Finally, rs2277680 of the CSCL16 gene in HBV-ALF patients. In conclusion, we have reviewed the prognostic and susceptibility biomarkers studied by the ALFSG. We suggest that a better approach to predicting the clinical outcome of an ALF patient will require a combination of biomarkers of pathogenic processes such as cell death, hepatic regeneration, and degree of inflammation that could be incorporated into prognostic models such as KCC, MELD or ALFSG PI.

[Acute Liver Failure: Current Updates and Management]

Acute liver failure (ALF) is a rare disease condition with a dynamic clinical course and catastrophic outcomes. Several etiologies are involved in ALF. Hepatitis A and B infections and indiscriminate use of untested herbs or supplemental agents are the most common causes of ALF in Korea. Noninvasive neurological monitoring tools have been used in patients with ALF in recent times. Ongoing improvements in intensive care, including continuous renal replacement therapy, therapeutic plasma exchange, vasopressor, and extracorporeal membrane oxygenation, have reduced the mortality rate of patients with ALF. However, liver transplantation is still the most effective treatment for patients with intractable ALF. There is a need for further research in the areas of better prognostication and precise selection of patients for emergency transplantation.

Management of Acute Liver Failure: Update 2022

Abbreviated pathogenesis and clinical course of the acute liver failure syndrome. The pathogenesis and clinical course of the syndrome of acute liver failure (ALF) differs depending upon the etiology of the primary liver injury. In turn, the severity of the liver injury and resulting synthetic failure is often the primary determinant of whether a patient is referred for emergency liver transplantation. Injuries by viral etiologies trigger the innate immune system via pathogen-associated molecular patterns (PAMPs), while toxin-induced (and presumably ischemia-induced) injuries do so via damage-associated molecular patterns (DAMPs). The course of the clinical syndrome further depends upon the relative intensity and composition of cytokine release, resulting in an early proinflammatory phenotype (SIRS) and later compensatory anti-inflammatory response phenotype (CARS). The outcomes of overwhelming immune activation are the systemic (extrahepatic) features of ALF (cardiovascular collapse, cerebral edema, acute kidney injury, respiratory failure, sepsis) which ultimately determine the likelihood of death.Acute liver failure (ALF) continues to carry a high risk of mortality or the need for transplantation despite recent improvements in overall outcomes over the past two decades. Optimal management begins with identifying that liver failure is indeed present and its etiology, since outcomes and the need for transplantation vary widely across the different etiologies. Most causes of ALF can be divided into hyperacute (ischemia and acetaminophen) and subacute types (other etiologies), based on time of evolution of signs and symptoms of liver failure; the former evolve in 3 to 4 days and the latter typically in 2 to 4 weeks. Both involve intense release of cytokines and hepatocellular contents into the circulation with multiorgan effects/consequences.Management involves optimizing fluid balance and cardiovascular support, including the use of continuous renal replacement therapy, vasopressors, and pulmonary ventilation. Early evaluation for liver transplantation is advised particularly for acetaminophen toxicity, which evolves so rapidly that delay is likely to lead to death.Vasopressor support, high-grade hepatic encephalopathy, and unfavorable (subacute) etiologies heighten the need for urgent listing for liver transplantation. Prognostic scores such as Kings Criteria, Model for End-Stage Liver Disease, and the Acute Liver Failure Group prognostic index take these features into account and provide reasonable but imperfect predictive accuracy. Future treatments may include liver support devices and/or agents that improve hepatocyte regeneration.

Standard-Volume Plasma Exchange Improves Outcomes in Patients With Acute Liver Failure: A Randomized Controlled Trial

BACKGROUND

High volume plasma-exchange (HVPE) improves survival in patients with acute liver failure (ALF), but apprehension regarding volume overload and worsening of cerebral edema remain.

METHODS

In an open-label randomized controlled trial, 40 consecutive patients of ALF were randomized 1:1 to either standard medical treatment (SMT) or SMT with standard-volume plasma-exchange (SVPE). SVPE was performed using centrifugal apheresis [target volume of 1.5 to 2.0 plasma volumes per session] until desired response was achieved. Cerebral edema was assessed by brain imaging. Results were analyzed in an intention-to-treat analysis. Primary outcome was 21-day transplant-free survival. The levels of cytokines, damage-associated molecular patterns (DAMPs) and endotoxins were analyzed at baseline and day 5.

RESULTS

ALF patients [aged 31.5 ± 12.2 years, 60% male, 78% viral, 83% hyperacute, 70% with SIRS were included. At day 5, SVPE [mean sessions 2.15 ± 1.42, median plasma volume replaced 5.049 L] compared to SMT alone, resulted in higher lactate clearance (p = .02), amelioration of SIRS (84% vs. 26%; P = .02), reduction in ammonia levels [(221.5 ± 96.9) vs.(439 ± 385.6) μg/dl, P = .02) and SOFA scores [9.9(±3.3) vs. 14.6(±4.8); P = .001]. There were no treatment related deaths. SVPE was associated with a higher 21-day transplant free-survival [75% vs. 45%; P = .04, HR 0.30, 95%CI 0.01-0.88]. A significant decrease in levels of pro-inflammatory cytokines and an increase in anti-inflammatory cytokines along with a decrease in endotoxin and DAMPs was seen with SVPE.

CONCLUSION

In ALF patients with cerebral edema, SVPE is safe and effective and improves survival possibly by a reduction in cytokine storm and ammonia.

CLINICALTRIAL

gov (identifier: NCT02718079).

State of the Art of Machine Learning-Enabled Clinical Decision Support in Intensive Care Units: Literature Review

Background

Modern clinical care in intensive care units is full of rich data, and machine learning has great potential to support clinical decision-making. The development of intelligent machine learning–based clinical decision support systems is facing great opportunities and challenges. Clinical decision support systems may directly help clinicians accurately diagnose, predict outcomes, identify risk events, or decide treatments at the point of care.

Objective

We aimed to review the research and application of machine learning–enabled clinical decision support studies in intensive care units to help clinicians, researchers, developers, and policy makers better understand the advantages and limitations of machine learning–supported diagnosis, outcome prediction, risk event identification, and intensive care unit point-of-care recommendations.

Methods

We searched papers published in the PubMed database between January 1980 and October 2020. We defined selection criteria to identify papers that focused on machine learning–enabled clinical decision support studies in intensive care units and reviewed the following aspects: research topics, study cohorts, machine learning models, analysis variables, and evaluation metrics.

Results

A total of 643 papers were collected, and using our selection criteria, 97 studies were found. Studies were categorized into 4 topics—monitoring, detection, and diagnosis (13/97, 13.4%), early identification of clinical events (32/97, 33.0%), outcome prediction and prognosis assessment (46/97, 47.6%), and treatment decision (6/97, 6.2%). Of the 97 papers, 82 (84.5%) studies used data from adult patients, 9 (9.3%) studies used data from pediatric patients, and 6 (6.2%) studies used data from neonates. We found that 65 (67.0%) studies used data from a single center, and 32 (33.0%) studies used a multicenter data set; 88 (90.7%) studies used supervised learning, 3 (3.1%) studies used unsupervised learning, and 6 (6.2%) studies used reinforcement learning. Clinical variable categories, starting with the most frequently used, were demographic (n=74), laboratory values (n=59), vital signs (n=55), scores (n=48), ventilation parameters (n=43), comorbidities (n=27), medications (n=18), outcome (n=14), fluid balance (n=13), nonmedicine therapy (n=10), symptoms (n=7), and medical history (n=4). The most frequently adopted evaluation metrics for clinical data modeling studies included area under the receiver operating characteristic curve (n=61), sensitivity (n=51), specificity (n=41), accuracy (n=29), and positive predictive value (n=23).

Conclusions

Early identification of clinical and outcome prediction and prognosis assessment contributed to approximately 80% of studies included in this review. Using new algorithms to solve intensive care unit clinical problems by developing reinforcement learning, active learning, and time-series analysis methods for clinical decision support will be greater development prospects in the future.

The utility of biomarkers in prognosis assessment of patients with acute liver failure

BACKGROUND

Acute liver failure (ALF) is a rare but potential lethal condition characterized by the sudden development of jaundice, coagulopathy and hepatic encephalopathy in patients without underlying liver disease. In selected patients, emergency liver transplantation is required. Selection of these patients is based on clinical criteria such as the Kings College Criteria (KCC) or the Clichy criteria.

AIMS

The aim of this work is to provide an overview of potential biomarkers that could improve the prognostic value of KCC.

RESULTS

Several promising biomarkers involved in related pathophysiological processes have been identified. Some could be as stand-alone biomarkers; however, the best prognostic values have been observed in the combination of biomarkers with current models. Among these, the ALFSG Index that combines clinical parameters and circulating blood levels of CK18 claims a higher prognostic value than KCC.

CONCLUSIONS

In this review, all potential biomarkers for ALF have been summarized to give an overview of the work performed over the last years, and a glimpse of what to expect in this field in the coming years.

Acute liver failure

Acute liver failure is a rare syndrome and is primarily caused by paracetamol toxicity in developed nations. Survival for patients with acute liver failure has steadily improved over the last few decades from approximately 20% to greater than 60%. This marked improvement in survival has been due to a combination of improvements in medical practice and the use of emergency liver transplantation in selected patients. Early recognition and timely initial management in the non-specialist centre can significantly improve outcomes. Patients should be simultaneously discussed with a transplant centre and referred to critical care. Close liaison with transplant centres to ensure timely transfer in deteriorating patients is important.

Acute liver failure following paracetamol overdose

Background

Acute liver failure is a rare syndrome comprising a coagulopathy of liver origin, jaundice and encephalopathy in a patient with no prior history of liver disease. Paracetamol overdose is the leading cause of acute liver failure in the United Kingdom and often presents with extrahepatic organ dysfunction requiring critical care. Presentation: We present the case of a patient with hyper acute liver failure secondary to paracetamol overdose. Management and discussion: Management focused on ensuring the correct diagnosis had been made, administering N-acetyl cysteine, fluid resuscitation and broad spectrum antimicrobials. Early intubation and transfer to a transplant centre were undertaken following development of hepatic encephalopathy. Neuroprotective measures and hypertonic saline were instituted to reduce the risk of intracranial hypertension. High dose haemofiltration was also started to help reduce ammonia levels. Aggressive critical care therapies with specialised input results in good outcomes for patients admitted with paracetamol induced hyper acute liver failure. Liver transplant is reserved for those patients unlikely to survive with medical treatment alone.

Deep Learning Predicts Overall Survival of Patients With Unresectable Hepatocellular Carcinoma Treated by Transarterial Chemoembolization Plus Sorafenib

Objectives

To develop and validate a deep learning-based overall survival (OS) prediction model in patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) plus sorafenib.

Methods

This retrospective multicenter study consisted of 201 patients with treatment-naïve, unresectable HCC who were treated with TACE plus sorafenib. Data from 120 patients were used as the training set for model development. A deep learning signature was constructed using the deep image features from preoperative contrast-enhanced computed tomography images. An integrated nomogram was built using Cox regression by combining the deep learning signature and clinical features. The deep learning signature and nomograms were also externally validated in an independent validation set of 81 patients. C-index was used to evaluate the performance of OS prediction.

Results

The median OS of the entire set was 19.2 months and no significant difference was found between the training and validation cohort (18.6 months vs. 19.5 months, P = 0.45). The deep learning signature achieved good prediction performance with a C-index of 0.717 in the training set and 0.714 in the validation set. The integrated nomogram showed significantly better prediction performance than the clinical nomogram in the training set (0.739 vs. 0.664, P = 0.002) and validation set (0.730 vs. 0.679, P = 0.023).

Conclusion

The deep learning signature provided significant added value to clinical features in the development of an integrated nomogram which may act as a potential tool for individual prognosis prediction and identifying HCC patients who may benefit from the combination therapy of TACE plus sorafenib.

Development of a Prognostic Score to Predict Mortality in Patients With Pediatric Acute Liver Failure

OBJECTIVES

This study aims to develop a new prognostic score based on changes in serial laboratory data from patients with pediatric acute liver failure (PALF).

METHODS

We retrospectively reviewed data on 146 patients with PALF at the Seoul National University Children Hospital (SNUCH) and the Asan Medical Center (AMC). Daily morning laboratory records were obtained for up to 7 days after diagnosis of PALF: total bilirubin (TB) (mg/dL), international normalized ratio for prothrombin time (INR) at enrolment; peak TB, peak INR, peak ammonia (μmol/L); the difference between the peak TB and TB at enrollment (ie, Δpeak TB), the difference between the peak INR and INR at enrollment (ie, Δpeak INR), the maximum change in serial TB (ie, Δdaily TB), the maximum change in serial INR level (ie, Δdaily INR). We assigned nontransplanted patients in SNUCH and AMC to derivation and validation cohorts, respectively.

RESULTS

Δpeak TB, Δdaily TB, Δpeak INR, and Δdaily INR were significantly higher in the nonsurvival group. We developed a new score that can predict mortality in nontransplanted patients (derivation cohort n = 42, validation cohort n = 33). PALF-Delta score (PALF-Ds) = [0.232 × Δpeak TB (mg/dL)] + [2.263 × Δdaily INR] + [0.013 × peak ammonia (μmol/L)] - 4.498. The score yielded AUC 0.918 in the derivation cohort (sensitivity 81%, specificity 91%) and AUC 0.947 in the validation cohort (sensitivity 100%, specificity 89%).

CONCLUSION

A prognostic scoring system using the change of TB/INR may be useful for predicting mortality in patients with PALF.

Update on the management of acute liver failure

PURPOSE OF REVIEW

This review describes the current intensive care management of acute liver failure (ALF) and the latest evidence for emerging therapies.

RECENT FINDINGS

Mortality from ALF continues to improve and in some cases, medical therapy can negate the need for liver transplantation because of protocolized management in specialist centres. Liver transplantation remains the cornerstone of management for poor prognosis ALF. The reduced use of blood products in ALF reflects growing evidence of balanced haemostasis in severe liver disease. Prophylactic therapeutic hypothermia is no longer recommended for neuroprotection. In cases not suitable for liver transplantation, high-volume plasma exchange (HVP) has potential benefit, although further research on the optimal timing and dosing is needed. Although sepsis remains an important complication in ALF, the use of prophylactic antimicrobials is being questioned in the era of emerging bacterial resistance.

SUMMARY

ICU management of ALF has improved such that liver transplantation is not required in some cases. HVP has emerged as a potential therapy for patients who may not be good liver transplantation candidates. Nevertheless in suitable patients with poor prognosis liver transplantation remains the optimal therapy.

The MicroRNA-based Liquid Biopsy Improves Early Assessment of Lethal Acetaminophen Poisoning: A Case Report

BACKGROUND Acetaminophen overdose is the most common cause of acute liver failure. Nevertheless, new biomarker approaches enabling early prediction of the outcome of the acetaminophen overdose are needed. Recently, using next-generation sequencing analysis of serum from human study participants we uncovered injury-specific signatures of circulating microRNAs (miRNAs) that represented underlying molecular mechanisms of toxicity. This case study is first to show the application of miRNA profiling to assess prognosis of acetaminophen poisoning. CASE REPORT The patient was admitted to the hospital following supra therapeutic acetaminophen ingestion. The patient showed elevated levels of biomarkers of hepatocellular injury alanine aminotransferase, aspartate transaminase, and glutamate dehydrogenase. Even though treatment with N-acetyl cysteine was initiated 24 hours post-ingestion, levels of alanine-aminotransferase and aspartate transaminase peaked at about 40 hours post ingestion of acetaminophen. We analyzed global circulating miRNA levels from 24 consecutive serum samples from this study participant covering the period from admission to time of death. CONCLUSIONS The resulting global miRNA profiles were compared with profiles from study participants with non-lethal acetaminophen poisoning and healthy controls. At the admission, the miRNA profiles of both lethal and non-lethal acetaminophen poisoning showed induction of cellular stress and oxidative damage. Later, the miRNA profiles of the lethal poisoning featured fibrosis and coagulation pathways while profiles of non-lethal cases resembled those of healthy study participants. Although additional confirmatory studies are needed, our case study is first to indicate that global miRNA profiles to be used as liquid biopsies have potential to facilitate the assessment of acetaminophen poisoning.

Intensive Care Management of Acute Liver Failure: Considerations While Awaiting Liver Transplantation

Acute liver failure is a unique clinical phenomenon characterized by abrupt deterioration in liver function and altered mentation. The development of high-grade encephalopathy and multisystem organ dysfunction herald poor prognosis. Etiologic-specific treatments and supportive measures are routinely employed; however, liver transplantation remains the only chance for cure in those who do not spontaneously recover. The utility of artificial and bioartificial assist therapies as supportive care-to allow time for hepatic recovery or as a bridge to liver transplantation-has been examined but studies have been small, with mixed results. Given the severity of derangements, intensive critical care is needed to successfully bridge patients to transplant, and evaluation of candidates occurs rapidly in parallel with serial reassessments of operative fitness. Psychosocial assessment is often suboptimal and relative contraindications to transplant, such as ventilator-dependence may be overlooked. While often employed to guide evaluation, no single prognostic model discriminates those who will spontaneously recover and those who will require transplant. The purpose of this review will be to summarize approaches in critical care, prognostic modeling, and medical evaluation of the acute liver failure transplant candidate.

Comparison of Dynamic Changes Among Various Prognostic Scores in Viral Hepatitis-Related Acute Liver Failure

INTRODUCTION AND AIM

Multiple prognostic scores are available for acute liver failure (ALF). Our objective was to compare the dynamicity of model for end stage liver disease (MELD), MELD-sodium, acute liver failure early dynamic model (ALFED), chronic liver failure (CLIF)-consortium ACLF score and King's College Hospital Criteria (KCH) for predicting outcome in ALF.

MATERIALS AND METHODS

All consecutive patients with ALF at a tertiary care centre in India were included. MELD, MELD-Na, ALFED, CLIF-C ACLF scores and KCH criteria were calculated at admission and day 3 of admission. Area under receiver operator characteristic curves (AUROC) were compared with DeLong method. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), likelihood ratio (LR) and diagnostic accuracy (DA) were reported.

RESULTS

Of the 115 patients included in the study, 73 (63.5%) died. The discrimination of mortality with baseline values of prognostic scores (MELD, MELD-Na, ALFED, CLIF-C ACLF and KCH) was modest (AUROC: 0.65-0.77). The AUROC increased on day 3 for all scores, except KCH criteria. On day 3 of admission, ALFED score had the highest AUROC 0.95, followed by CLIF-C ACLF 0.88, MELD 0.81, MELD-Na 0.77 and KCH 0.52. The AUROC for ALFED was significantly higher than MELD, MELD-Na and KCH (P < 0.001 for all) and CLIF-C ACLF (P = 0.05). ALFED score ≥ 4 on day 3 had the best sensitivity (87.1%), specificity (89.5%), PPV (93.8%), NPV (79.1%), LR positive (8.3) and DA (87.9%) for predicting mortality.

CONCLUSIONS

Dynamic assessment of prognostic scores better predicts outcome. ALFED model performs better than MELD, MELD, MELD-Na, CLIF-C ACLF scores and KCH criteria for predicting outcome in viral hepatitis- related ALF.

Comparison of Prognostic Models in Acute Liver Failure: Decision is to be Dynamic

Background and aims

Acute liver failure (ALF) is a rare disease entity with a high mortality. Management is dependent on accurate prognostication.

Materials and methods

One hundred consecutive patients presenting with ALF were prospectively evaluated. The King's college criteria (KCC), ALF early dynamic model (ALFED), sequential organ failure assessment (SOFA) score, and acute physiology and health evaluation II (APACHE II) scores were compared to predict mortality.

Results

There were significant differences in means of all the scores between survivors and nonsurvivors. The SOFA 48 hours had the highest area under receiver operating characteristic curve (AUC) (0.857) closely followed by the ALFED score (0.844). The optimal cutoff for the SOFA score at 48 hours to predict subsequent survival outcome is ≥10 and for the ALFED score is ≥5. Sequential organ failure assessment 48 hours had a good sensitivity of 87%, and the ALFED score showed a good specificity of 84%. The decision curve analysis showed that between a threshold probability of 0.13 and 0.6, use of the SOFA score provided the maximum net benefit and at threshold probabilities of >0.6, the use of ALFED score provided the maximum clinical benefit.

Conclusion

Dynamic scoring results in better prognostication in ALF. The SOFA 48 hours and ALFED score have good prognostication value in nonacetaminophen-induced liver failure.

How to cite this article

Saluja V, Sharma A, Pasupuleti SSR, Mitra LG, Kumar G, Agarwal PM. Comparison of Prognostic Models in Acute Liver Failure: Decision is to be Dynamic. Indian J Crit Care Med 2019;23(12):574–581.

Outcome of Acetaminophen-Induced Acute Liver Failure Managed Without Intracranial Pressure Monitoring or Transplantation

Acetaminophen-induced acute liver failure (ALF) may require emergency liver transplantation (LT) in the presence of specific criteria, and its management may also include intracranial pressure (ICP) monitoring in selected patients at high risk of cerebral edema. We aimed to test the hypothesis that management of such patients without ICP monitoring or LT would yield outcomes similar to those reported with conventional management. We interrogated a database of all patients treated in an intensive care unit for acetaminophen-induced ALF between November 2010 and October 2016 and obtained relevant information from electronic medical records. We studied 64 patients (58 females) with a median age of 38 years. Such patients had a high prevalence of depression, substance abuse, or other psychiatric disorders and had ingested a median acetaminophen dose of 25 g. No patient received ICP monitoring or LT. Overall, 51 (79.7%) patients survived. Of the 42 patients who met King's College Hospital (KCH) criteria, 29 (69.0%) survived without transplantation. There were 45 patients who developed severe hepatic encephalopathy, and 32 (71.1%) of these survived. Finally, compared with the KCH criteria, the current UK Registration Criteria for Super-Urgent Liver Transplantation (UKRC) for super-urgent LT had better sensitivity (92.3%) and specificity (80.4%) for hospital mortality. In conclusion, in a center applying a no ICP monitoring and no LT approach to the management of acetaminophen-induced ALF, during a 6-year period, overall survival was 79.7%, and for patients fulfilling KCH criteria, it was 69.0%, which were both higher than for equivalent patients treated with conventional management as reported in the literature. Finally, the current UKRC may be a better predictor of hospital mortality in this patient population.

Beyond KCH selection and options in acute liver failure

The King’s prognostic criteria for patients with acute liver failure (ALF) introduced in 1989 have been used worldwide. This distinguished for the first time cases with ‘hyper-acute’ course (characteristically paracetamol overdose) where there is a better chance of recovery with medical supportive care alone from those etiologies with a less acute course and paradoxically lower chances of ‘spontaneous’ recovery. Ongoing use showed the limited sensitivity of the criteria to constitute a significant practical limitation. Subsequent models including the MELD score and composite ones with markers of necrosis, an apoptotic liver cell death, proposed to improve sensitivity did not have the required high specificity. Two recent models utilizing new availability of web- and app-based computing delivering outcome predication through sophisticated algorithms are described. The first is a dynamic model described for paracetamol-induced ALF based upon admission findings and sequential variables over the first 2 days. The new model of the US Acute Liver Failure group was devised to cover all etiologies of ALF for predicting ‘transplant-free’ survival and accurately predicated spontaneous survival in two-thirds of cases. Improved survival results with medical management, particularly in hyper-acute cases, now approach those obtained with successful liver transplant and have raised the question of transplant benefit. Also considered in the review are new non-transplant approaches to treatment including the use of plasma exchange and based on successful results in acute-on-chronic liver failure, agents to modulate and improve hepatic regeneration.

Prognostic Models in Acute Liver Failure

There is a strong imperative to develop valid and accurate prognostic modeling for acute liver failure (ALF). Despite the numerous clinical models that have been proposed thus far and the use of some such models, that is, King's College Criteria and Model for End-Stage Liver Disease, in clinical practice to aid decision-making, there is a significant need for improvement for determining patients' clinical course, survival, and requirement for liver transplantation. Future prognostic models shall need a stronger statistical foundation and accountability for time and variability in the clinical course of ALF and be applied for pretransplant and posttransplant outcomes.

Acetaminophen (APAP or N-Acetyl-p-Aminophenol) and Acute Liver Failure

Acetaminophen (APAP) is the leading cause of acute liver failure (ALF), although the worldwide frequency is variable. APAP hepatotoxicity develops either following intentional overdose or unintentional ingestion (therapeutic misadventure) in the background of several factors, such as concomitant use of alcohol and certain medications that facilitate the formation of reactive and toxic metabolites. Spontaneous survival is more common in APAP-induced ALF compared with non-APAP etiologies. N-acetylcysteine is recommended for all patients with APAP-induced ALF and it reduces mortality. Liver transplantation should be offered early to those who are unlikely to survive based on described prognostic criteria.