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PREDICT identifies precipitating events associated with the clinical course of acutely decompensated cirrhosis

Open AccessPublished:November 19, 2020DOI:https://doi.org/10.1016/j.jhep.2020.11.019

      Highlights

      • Bacterial infections and/or severe alcoholic hepatitis are the major precipitants of acute decompensation and ACLF.
      • The type of precipitating event had no association with survival.
      • The number of identifiable events was significantly associated with surrogates of systemic inflammation and increased 90-day mortality.
      • Adequate first-line antibiotic treatment of proven bacterial infections reduced ACLF development and improved 90-day survival.
      • Strategies to prevent or treat precipitating events may improve outcome in decompensated cirrhosis.

      Background & Aims

      Acute decompensation (AD) of cirrhosis may present without acute-on-chronic liver failure (ACLF) (AD-No ACLF), or with ACLF (AD-ACLF), defined by organ failure(s). Herein, we aimed to analyze and characterize the precipitants leading to both of these AD phenotypes.

      Methods

      The multicenter, prospective, observational PREDICT study (NCT03056612) included 1,273 non-electively hospitalized patients with AD (No ACLF = 1,071; ACLF = 202). Medical history, clinical data and laboratory data were collected at enrolment and during 90-day follow-up, with particular attention given to the following characteristics of precipitants: induction of organ dysfunction or failure, systemic inflammation, chronology, intensity, and relationship to outcome.

      Results

      Among various clinical events, 4 distinct events were precipitants consistently related to AD: proven bacterial infections, severe alcoholic hepatitis, gastrointestinal bleeding with shock and toxic encephalopathy. Among patients with precipitants in the AD-No ACLF cohort and the AD-ACLF cohort (38% and 71%, respectively), almost all (96% and 97%, respectively) showed proven bacterial infection and severe alcoholic hepatitis, either alone or in combination with other events. Survival was similar in patients with proven bacterial infections or severe alcoholic hepatitis in both AD phenotypes. The number of precipitants was associated with significantly increased 90-day mortality and was paralleled by increasing levels of surrogates for systemic inflammation. Importantly, adequate first-line antibiotic treatment of proven bacterial infections was associated with a lower ACLF development rate and lower 90-day mortality.

      Conclusions

      This study identified precipitants that are significantly associated with a distinct clinical course and prognosis in patients with AD. Specific preventive and therapeutic strategies targeting these events may improve outcomes in patients with decompensated cirrhosis.

      Lay summary

      Acute decompensation (AD) of cirrhosis is characterized by a rapid deterioration in patient health. Herein, we aimed to analyze the precipitating events that cause AD in patients with cirrhosis. Proven bacterial infections and severe alcoholic hepatitis, either alone or in combination, accounted for almost all (96-97%) cases of AD and acute-on-chronic liver failure. Whilst the type of precipitant was not associated with mortality, the number of precipitant(s) was. This study identified precipitants that are significantly associated with a distinct clinical course and prognosis of patients with AD. Specific preventive and therapeutic strategies targeting these events may improve patient outcomes.

      Graphical abstract

      Keywords

      Linked Article

      • Defining the prognosis of critically ill patients with alcohol-related liver disease
        Journal of HepatologyVol. 75Issue 4
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          We read with great interest the results of the PREDICT study, which identified that the most common precipitants (>96% of cases) of acute decompensation (AD) were bacterial infection (BI) and alcoholic hepatitis (AH), either alone or in combination with other precipitating events (PEs).1 Moreover, short-term outcomes, including development of ACLF and 90-day mortality, were related to number of PEs but independent of the type of PE. This important study suggests the importance of targeted strategies to manage organ failure rather than type of PE.
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      Introduction

      Acute decompensation of cirrhosis (hereafter called AD) defines the acute development of ascites, hepatic encephalopathy, gastrointestinal hemorrhage or bacterial infections, or any combination of these. In 2013, the CANONIC study identified the syndrome of acute-on-chronic liver failure (ACLF), the most severe phenotype of AD, in 20% of 1,343 consecutive patients non-electively hospitalized for the treatment of an episode of AD.
      • Moreau R.
      • Jalan R.
      • Gines P.
      • Pavesi M.
      • Angeli P.
      • Cordoba J.
      • et al.
      Acute-on-chronic liver failure is a distinct syndrome that develops in patients with acute decompensation of cirrhosis.
      ACLF was characterized by single or multiple organ failure and high 28-day mortality rate (30%).
      In 2020, the PREDICT study, a prospective observational investigation of 1,273 hospitalized patients with AD, showed that patients without ACLF (AD-No ACLF phenotype) comprised 3 distinct sub-phenotypes defined according to ACLF development and readmission within 3 months after AD.
      • Trebicka J.
      • Fernandez J.
      • Papp M.
      • Caraceni P.
      • Laleman W.
      • Gambino C.
      • et al.
      The PREDICT study uncovers three clinical courses in acutely decompensated cirrhosis with distinct pathophysiology.
      In brief, pre-ACLF patients developed ACLF and showed high short-term (90-day) mortality (67%); unstable decompensated cirrhosis (UDC) patients did not develop ACLF, but required readmission(s) and showed significant short-term mortality (35%); stable decompensated cirrhosis (SDC) patients presented an uncomplicated course during the 3-month follow-up period and showed lower 1-year mortality (9%).
      In the traditional view, the development of AD is initiated by an acute worsening of stable cirrhosis through different pathophysiological mechanisms considered as precipitants. Evidence from the CANONIC and the PREDICT studies challenges this view,
      • Moreau R.
      • Jalan R.
      • Gines P.
      • Pavesi M.
      • Angeli P.
      • Cordoba J.
      • et al.
      Acute-on-chronic liver failure is a distinct syndrome that develops in patients with acute decompensation of cirrhosis.
      ,
      • Trebicka J.
      • Fernandez J.
      • Papp M.
      • Caraceni P.
      • Laleman W.
      • Gambino C.
      • et al.
      The PREDICT study uncovers three clinical courses in acutely decompensated cirrhosis with distinct pathophysiology.
      and suggests that AD manifests mainly as a result of systemic inflammation, inducing multiple organ dysfunction and presents with different clinical phenotypes.
      • Arroyo V.
      • Moreau R.
      • Kamath P.S.
      • Jalan R.
      • Gines P.
      • Nevens F.
      • et al.
      Acute-on-chronic liver failure in cirrhosis.
      ,
      • Arroyo V.
      • Moreau R.
      • Jalan R.
      Acute-on-Chronic liver failure.
      Indeed, systemic inflammation increases across the sub-phenotypes of AD-no ACLF (SDC, UDC and pre-ACLF), and reaches its peak in patients with AD-ACLF.
      • Claria J.
      • Stauber R.E.
      • Coenraad M.J.
      • Moreau R.
      • Jalan R.
      • Pavesi M.
      • et al.
      Systemic inflammation in decompensated cirrhosis: characterization and role in acute-on-chronic liver failure.
      ,
      • Trebicka J.
      • Amoros A.
      • Pitarch C.
      • Titos E.
      • Alcaraz-Quiles J.
      • Schierwagen R.
      • et al.
      Addressing profiles of systemic inflammation across the different clinical phenotypes of acutely decompensated cirrhosis.
      Moreover, in AD-ACLF phenotype, the grade of systemic inflammation correlated with the number of organ failures, clinical course severity and prognosis.
      • Arroyo V.
      • Moreau R.
      • Kamath P.S.
      • Jalan R.
      • Gines P.
      • Nevens F.
      • et al.
      Acute-on-chronic liver failure in cirrhosis.
      ,
      • Arroyo V.
      • Moreau R.
      • Jalan R.
      Acute-on-Chronic liver failure.
      Hence, for a precipitant to be of importance, it must have the ability to impair end-organ function.
      Despite the fact that AD-ACLF phenotypes frequently develop in close chronological relationship with the precipitant(s), the critical time period prior to AD-ACLF has not yet been explored in detail. Moreover, no specific criteria for the diagnosis of precipitants have been identified to date. Consequently, many clinically relevant aspects of precipitants remain ill-defined.
      The current study is the second investigation derived from the PREDICT study. Its aim was to provide the rationale for the diagnosis of precipitants and to investigate the association of type and number of precipitants with early clinical course and prognosis in patients hospitalized with AD-No ACLF and AD-ACLF phenotypes.

      Patients and methods

      Patients

      The PREDICT study (ClinicalTrials.gov number, NCT03056612) is a European, investigator-initiated, multicenter, prospective, observational study performed in 48 university hospitals (approved by the respective ethics committees) from 15 countries and promoted by the European Foundation for the Study of Chronic Liver Failure. The design of the study has been reported in detail elsewhere.
      • Trebicka J.
      • Fernandez J.
      • Papp M.
      • Caraceni P.
      • Laleman W.
      • Gambino C.
      • et al.
      The PREDICT study uncovers three clinical courses in acutely decompensated cirrhosis with distinct pathophysiology.
      Briefly, 1,071 cirrhosis patients with AD-No ACLF phenotype and 202 with AD-ACLF phenotype non-electively hospitalized for treatment were enrolled from March 2017 to July 2018 after providing their informed consent. AD was diagnosed as previously described
      • Trebicka J.
      • Fernandez J.
      • Papp M.
      • Caraceni P.
      • Laleman W.
      • Gambino C.
      • et al.
      The PREDICT study uncovers three clinical courses in acutely decompensated cirrhosis with distinct pathophysiology.
      and ACLF according to the EASL-CLIF criteria.
      • Moreau R.
      • Jalan R.
      • Gines P.
      • Pavesi M.
      • Angeli P.
      • Cordoba J.
      • et al.
      Acute-on-chronic liver failure is a distinct syndrome that develops in patients with acute decompensation of cirrhosis.
      ,
      • Collaborators
      • Angeli P.
      • Bernardi M.
      • Villanueva C.
      • Francoz C.
      • et al.
      European Association for the Study of the Liver
      EASL Clinical Practice Guidelines for the management of patients with decompensated cirrhosis.
      Stratification of patients with the AD-No ACLF phenotype into the AD-pre-ACLF, AD-UDC and AD-SDC sub-phenotypes was performed using previously described criteria
      • Trebicka J.
      • Fernandez J.
      • Papp M.
      • Caraceni P.
      • Laleman W.
      • Gambino C.
      • et al.
      The PREDICT study uncovers three clinical courses in acutely decompensated cirrhosis with distinct pathophysiology.
      and outlined inFig. 1 (for detailed description please see supplementary information).
      Figure thumbnail gr1
      Fig. 1Schematic outline of the study.
      AD phenotype groups and subgroups included in each of the AD cohorts used for the study analysis. For more explanation see the text. ACLF, acute-on-chronic liver failure; AD, acute decompensation; SDC, stable decompensated cirrhosis; UDC, unstable decompensated cirrhosis.

      Study design

      The PREDICT study
      • Trebicka J.
      • Fernandez J.
      • Papp M.
      • Caraceni P.
      • Laleman W.
      • Gambino C.
      • et al.
      The PREDICT study uncovers three clinical courses in acutely decompensated cirrhosis with distinct pathophysiology.
      was designed to explore the last 90 days prior to hospital admission (especially the last 2 weeks), and the first 3 months after admission (follow-up period), in which the early clinical course of patients was assessed. Pre-specified clinical and standard laboratory data were obtained at enrolment and during follow-up visits. The design of the PREDICT study is described in detail in the supplementary information and elsewhere.
      • Trebicka J.
      • Fernandez J.
      • Papp M.
      • Caraceni P.
      • Laleman W.
      • Gambino C.
      • et al.
      The PREDICT study uncovers three clinical courses in acutely decompensated cirrhosis with distinct pathophysiology.

      Identification of precipitants of AD-No ACLF and AD-ACLF

      In order to identify the precipitants an adjudication committee of the PREDICT study, which included JT, JF, RM and VA, was nominated to elaborate a list of clinical events with the potential to precipitate AD or ACLF, and also the general principles and specific criteria for diagnosis. This committee identified precipitants according to the criteria defined below.

      General principles for precipitant identification

      • Precipitants should consist of events that have the potential to induce impairment in the function of the liver and/or other organs, either by direct organ injury (e.g. tissue hypoperfusion) or, indirectly, through significant dysregulation of important pathophysiological mechanisms (e.g. immune responses to microbial or endogenous factors).
      • When assessing the potential of hepatotoxic, nephrotoxic or neurotoxic drugs as precipitants, the lack of liver, kidney or brain dysfunction or failure, respectively, as defined by the CLIF-C organ failure score
        • Jalan R.
        • Saliba F.
        • Pavesi M.
        • Amoros A.
        • Moreau R.
        • Gines P.
        • et al.
        Development and validation of a prognostic score to predict mortality in patients with acute-on-chronic liver failure.
        rule out drug-induced organ toxicity as a precipitant.
      • As suggested by the results of the CANONIC study,
        • Moreau R.
        • Jalan R.
        • Gines P.
        • Pavesi M.
        • Angeli P.
        • Cordoba J.
        • et al.
        Acute-on-chronic liver failure is a distinct syndrome that develops in patients with acute decompensation of cirrhosis.
        ,
        • Collaborators
        • Angeli P.
        • Bernardi M.
        • Villanueva C.
        • Francoz C.
        • et al.
        European Association for the Study of the Liver
        EASL Clinical Practice Guidelines for the management of patients with decompensated cirrhosis.
        clinically identifiable, relevant and true precipitants should have a higher prevalence in patients with AD-ACLF than in those with AD-no ACLF.
      • Precipitants should precede or coincide with the onset of AD-ACLF. The time period between the precipitants and the onset of AD-ACLF, however, is heterogeneous, depending on the precipitants.
      • Any event developing after the onset of AD-ACLF is a complication or a coincidental event but not a precipitant.

      Specific criteria for the identification of precipitants from the list proposed by the adjudication committee (for detailed description see supplementary appendix)

      The adjudication committee evaluated the following events as potential precipitants as proposed by the CANONIC study and other investigations: bacterial infections, alcoholic hepatitis, gastrointestinal (GI) bleeding, drug-induced organ injury, therapeutic interventions.
      Bacterial infections (details in supplementary information). Infections were considered to be potential precipitants if they were diagnosed at the time of or solved within the 48-hour period that preceded the onset of AD. Proven bacterial infections were defined as previously described
      • Fernandez J.
      • Acevedo J.
      • Wiest R.
      • Gustot T.
      • Amoros A.
      • Deulofeu C.
      • et al.
      Bacterial and fungal infections in acute-on-chronic liver failure: prevalence, characteristics and impact on prognosis.
      and in accordance with the EASL guidelines
      • Collaborators
      • Angeli P.
      • Bernardi M.
      • Villanueva C.
      • Francoz C.
      • et al.
      European Association for the Study of the Liver
      EASL Clinical Practice Guidelines for the management of patients with decompensated cirrhosis.
      (detailed definition in the supplementary information).
      Alcohol-related liver injury (details in the supplementary information). Alcoholic hepatitis was diagnosed according to the clinical criteria of the NIAAA.
      • Crabb D.W.
      • Bataller R.
      • Chalasani N.P.
      • Kamath P.S.
      • Lucey M.
      • Mathurin P.
      • et al.
      Standard definitions and common data elements for clinical trials in patients with alcoholic hepatitis: recommendation from the NIAAA alcoholic hepatitis consortia.
      These criteria are in line with the clinical diagnosis of alcoholic hepatitis according to the existing EASL guidelines.
      European Association for the Study of the Liver
      Electronic address eee, European association for the study of the L. EASL clinical practice guidelines: management of alcohol-related liver disease.
      Alcoholic hepatitis was considered severe if patients had CLIF-C acute decompensation scores of ≥50 points,
      • Jalan R.
      • Pavesi M.
      • Saliba F.
      • Amoros A.
      • Fernandez J.
      • Holland-Fischer P.
      • et al.
      The CLIF Consortium Acute Decompensation score (CLIF-C ADs) for prognosis of hospitalised cirrhotic patients without acute-on-chronic liver failure.
      or ACLF (Table 1).
      Table 1Clinical events, precipitants and combinations of precipitants in patients with AD-No ACLF and with AD-ACLF.
      AD-No ACLF (n = 1,071)AD-ACLF (n = 202)p value
      Certain p value were not determined because of the low number of patients.
      Clinical events, precipitants, n (%)
      Bacterial infections
       Any infection314 (29.32)101 (50.00)<0.0001
       Suspected bacterial infection74 (6.91)12 (5.94)0.61
       Proven bacterial infections
      Underlined precipitants are those considered as precipitants of AD-ACLF.
      239 (22.32)89 (44.06)<0.0001
      Alcohol-related liver injury
       Alcoholic hepatitis275 (25.68)88 (43.56)<0.0001
       Severe alcoholic hepatitis
      Underlined precipitants are those considered as precipitants of AD-ACLF.
      200 (18.67)88 (43.56)<0.0001
      GI bleeding
       Any GI bleeding176 (16.43)40 (19.80)0.24
       GI bleeding with hypovolemic shock
      Underlined precipitants are those considered as precipitants of AD-ACLF.
      13 (1.21)12 (5.94)<0.0001
      Drug-induced brain injury
       Patients treated with neurotoxic drugs84 (7.84)17 (8.42)0.78
       Toxic encephalopathy
      Underlined precipitants are those considered as precipitants of AD-ACLF.
      13 (1.21)12 (5.94)<0.0001
      Other candidates, n (%)
      Paracentesis without albumin110 (10.28)21 (10.40)0.96
      TIPS49 (4.58)8 (3.96)0.69
      Drug-induced liver injury16 (1.49)4 (1.98)0.54
      Viral hepatitis or other viral Infections13 (1.21)3 (1.49)0.72
      Drug-induced kidney injury3 (0.28)1 (0.50)-
      Surgery3 (0.28)0 (0.00)-
      Decompensated cardiopulmonary disease4 (0.37)3 (1.49)-
      Dehydration3 (0.28)1 (0.50)-
      Large hematomas3 (0.28)0 (0.00)-
      Acute pancreatitis1 (0.09)1 (0.50)-
      Portomesenteric vein thrombosis2 (0.19)1 (0.50)-
      Extrahepatic autoimmune disease2 (0.19)0 (0.00)-
      Cerebrovascular accident0 (0.00)1 (0.50)-
      Bowel occlusion1 (0.09)0 (0.00)-
      Number of precipitants
      Indeterminate662 (61.81)59 (29.21)<0.0001
      1354 (33.05)93 (46.04)
      ≥255 (5.14)50 (24.75)
      Chi-square or Fisher’s tests performed in percentages comparisons. ACLF, acute-on-chronic liver failure; AD, acute decompensation; GI, gastrointestinal; TIPS, transjugular intrahepatic portosystemic shunt.
      a Certain p value were not determined because of the low number of patients.
      b Underlined precipitants are those considered as precipitants of AD-ACLF.
      GI bleeding (details in the supplementary information). GI bleeding was considered a precipitant if occurring within 7 days prior to the onset of AD-ACLF. Moreover, hemorrhagic shock was indicative of severe bleeding (Table 1).
      Drug-induced liver injury was considered a potential precipitant when the hepatotoxic drug was administered within 1 month prior to the onset of AD-ACLF and the patient presented with liver injury as defined by Hy´s law and FDA guidance as described in the recent EASL guidelines;
      European Association for the Study of the Liver
      Electronic address eee, clinical practice guideline panel C, panel m, representative EGB. EASL clinical practice guidelines: drug-induced liver injury.
      as well as liver dysfunction (in patients with AD-No ACLF, bilirubin >6 mg/dl) or liver failure (in patients with AD-ACLF, bilirubin >12 mg/dl). Only drugs from groups A and B of potential hepatotoxic drugs, described elsewhere,
      • Bjornsson E.S.
      • Hoofnagle J.H.
      Categorization of drugs implicated in causing liver injury: critical assessment based on published case reports.
      were considered potential candidates for liver toxicity.
      Drug-induced kidney injury was considered a potential precipitant when the nephrotoxic drug was administered within 7 days prior to the onset of AD-ACLF and patients presented with either renal dysfunction or renal failure according to the CLIF-C organ failure score. Diuretic-induced renal dysfunction or renal failure was not considered a nephrotoxic condition.
      Toxic encephalopathy was considered a potential precipitant when the neurotoxic drug was administered within 48 hours prior to the onset of AD-ACLF and the patient presented with encephalopathy in severity similar to brain dysfunction or brain failure according to the CLIF-C organ failure score.
      Therapeutic interventions including transjugular intrahepatic portosystemic shunt (TIPS), major surgical procedures and large volume paracentesis without albumin administration were considered as potential precipitants if performed within 7 days prior to the onset of AD-ACLF.

      Other potential precipitants identified by the investigators in the individual patients eCRF

      The adjudication committee assessed 9 additional, infrequent clinical events (details in the supplementary information).

      Statistical analysis

      Discrete variables are shown as counts (percentage) and continuous variables as mean ± SD. Non-normally distributed variables are summarized by the median (IQR). In univariate statistical comparisons, the chi-square test or Fisher’s exact test, when at least 25% of expected counts were below 5, were used for categorical variables, whereas the Student’s t test or analysis of variance were used for normally distributed continuous variables and the Wilcoxon rank-sum test or the Kruskal-Wallis test for continuous variables not normally distributed. For comparisons at different time-points in the same patients, paired tests were used: McNemar test was applied for dichotomic variables and a test of symmetry was performed for variables with 3 categories. In all statistical analyses, significance was set at p<0.05.
      Overall, the proportion of missing values in the main reported characteristics (demographics, clinical variables, laboratory values, precipitants and clinical outcomes) rounded 1% at most. Only complete clinical blood counts and total cholesterol showed higher proportions of missing data, which were mainly due to common problems with sample availability or with technical laboratory processes that occurred in several site laboratories and can be considered to be completely random. A simple imputation approach was used to impute the missing values for each of the 4 variables mentioned above (neutrophil, lymphocyte and monocyte counts and total cholesterol). SAS PROC MI was used assuming an arbitrary pattern for missing values and adopting a fully conditional specification (FCS) regression method. Model covariates included age, sex, CLIF-C organ failure score and number of precipitants or presence of bacterial infections or alcoholism or ACLF at inclusion, depending on the analysis that was to be performed. For each variable, missing values were imputed by computing the median of the values obtained by fitting the model on 100 repetitions generated from the original dataset.
      Cumulative incidence functions (CIF's) were used to estimate survival curves accounting for liver transplantation as an event 'competing' with mortality, as well as to estimate ACLF development accounting for both mortality and liver transplantation as events “competing” with ACLF development, using common non-parametric methods. The equality of CIFs across groups was evaluated by means of the Gray's test.
      • Gray R.
      A class of K-sample tests for comparing the cumulative incidence of a competing risk.
      Statistical analysis was performed using SAS v9.4 and plots were performed with R v1.2.5042 and GraphPad Prism v5 software.

      Results

      Identification of precipitants for AD at enrolment in the PREDICT study cohort

      The PREDICT study cohort includes 1,273 patients, of whom 202 patients presented with AD-ACLF and 1,071 patients with AD-No ACLF (Fig. 1). There were 4 main precipitants: bacterial infections, alcohol-related liver injury, GI bleeding and toxic encephalopathy (Table 1).
      The prevalence of patients with proven bacterial infections was significantly higher in AD-ACLF than in AD-No ACLF cases, while prevalence of suspected bacterial infections was very low and similar in both groups. Therefore, only proven bacterial infections were considered as precipitants of AD-ACLF, and this was the most common precipitant (44% in AD-ACLF and in 22.3% in AD-No ACLF [p<0.0001]).
      Prevalence of severe alcoholic hepatitis (alcoholic hepatitis associated with CLIF-C AD score ≥50 or ACLF) was significantly higher in patients with AD-ACLF (43.6% vs. 18.7% in AD-No ACLF). Overall, alcoholic hepatitis was not always associated with organ dysfunction. Therefore, only severe alcoholic hepatitis was identified as a precipitant, and was the second most frequent.
      Severe GI bleeding associated with hypovolemic shock was the third most frequent precipitant, although its prevalence in the AD-ACLF and the AD-No ACLF group (5.9% and 1.2%, respectively, p<0.0001) was low.
      Finally, of the 3 examined types of drug-induced organ injury, only the prevalence of toxic encephalopathy was significantly higher in the AD-ACLF group than in the AD-No ACLF group (5.9% and 1.2%, respectively, p<0.0001) and it thus qualified as a precipitant. All drugs associated with severe toxic encephalopathy were opioids or benzodiazepines.
      Neither therapeutic paracentesis without intravenous albumin nor TIPS qualified as precipitants, since their prevalence was not significantly higher in patients with AD-ACLF than in patients with AC-no ACLF.
      In total, 721 patients (56.6%) included in the PREDICT study cohort did not present any identifiable precipitant (indeterminate precipitant), 447 (35.1%) presented 1 precipitant, and 105 (8.2%) presented ≥2 precipitants.
      The clinical characteristics, laboratory data, prognostic scores, and 90-day mortality rate of patients with AD-No ACLF and AD-ACLF are presented in Table S1.

      Prevalence and association of precipitants with characteristics, clinical course and prognosis of patients included in the AD-No ACLF cohort

      Prevalence of precipitants and their combinations

      AD-No ACLF (n = 1,071) was associated with 1 precipitant in 354 patients (33.0%), and with ≥2 precipitants in 55 patients (5.1%), as illustrated in Fig. 2A. In the AD-No ACLF cohort, 662 patients (61.8%) presented with indeterminate precipitants (Table 1). Therefore, in 394 patients (96.3%), AD-No ACLF was related to proven bacterial infections or severe acute alcoholic hepatitis, either alone or in combination. AD-No ACLF was unrelated to bacterial infections or alcoholic hepatitis in only 15 (3.7%) patients.
      Figure thumbnail gr2
      Fig. 2Precipitants in AD-No ACLF.
      Combinations of PEs in the AD-No ACLF cohort shown in a 4-set circle Venn diagram (panel A). Cumulative incidence of mortality in patients with AD-No ACLF according to the type of precipitant (proven infections alone vs. severe alcoholic hepatitis alone; panel B) and the number of precipitants (indeterminate PE, 1 PE, and ≥2 PEs; panel C) p values were obtained from Gray's test. Blood levels of leukocytes (panel D), neutrophils (panel E), monocytes (panel F) and the serum concentration of CRP (panel G) in patients with AD-No ACLF and indeterminate PE, 1 PE and ≥2 PEs. Boxes show median and IQR and whiskers show 10-90 percentiles. Kruskal-Wallis test was performed with all values in each comparison. Differences were statistically significant (p<0.0001) for all biomarkers. ACLF, acute-on-chronic liver failure; AD, acute decompensation; CRP, C-reactive protein; PE(s), precipitant(s).

      Precipitants are associated with the clinical course and survival of patients with AD-No ACLF.

      Prevalence of patients with proven bacterial infections and severe alcoholic hepatitis at enrolment was higher in AD-pre-ACLF (29.4% and 26.6%, respectively) than in AD-UDC (21.0% and 19.3%) or AD-SDC (20.3%. and 15.6%) phenotypes. Moreover, the number of patients with indeterminate precipitants was significantly lower (50.9%) and the number of patients with 1 or ≥2 precipitants was higher (40.4% and 8.7%) in patients with AD-pre-ACLF than in those with AD-UDC (60.9%, 35.6% and 3.4%, respectively) and AD-SDC (66.0%, 29.5% and 4.5%). Moreover, these differences were even more pronounced, when UDC or SDC groups at baseline were compared with the AD-pre-ACLF group at the time point of ACLF development. These observations suggest that the presence and the number of precipitants at enrolment are important determinants in the development of AD-pre-ACLF, the most severe sub-phenotype in patients with AD-No ACLF (Table 2).
      Table 2Type and number of precipitants in patients with pre-ACLF, unstable decompensated cirrhosis and stable decompensated cirrhosis.
      Pre-ACLF (n = 218)UDC (n = 233)SDC (n = 620)
      At enrolmentAt ACLF development
      Type of precipitant, n (%)
       Proven bacterial infections64 (29.4)97 (44.5)∗∗49 (21.0) ∗,##126 (20.3) ∗∗,##
       Severe alcoholic hepatitis58 (26.6)57 (26.1)45 (19.3) +97 (15.6) ∗∗,#
       GI bleeding with shock $2 (0.9)8 (3.7)2 (0.9)9 (1.5)
       Toxic encephalopathy $3 (1.4)4 (1.8)3 (1.3)7 (1.1)
      Number of precipitants, n (%)
       Indeterminate111 (50.9)88 (40.4)∗∗142 (60.9) ∗,##409 (66.0) ∗∗,##
       One88 (40.4)98 (45.0)∗∗83 (35.6) ##183 (29.5) ##
       Two or more19 (8.7)32 (14.7)∗∗8 (3.4) ##28 (4.5) ##
      Comparison between all groups to the pre-ACLF group at enrolment is displayed by the following symbols:
      +p<0.07, ∗p<0.05 and ∗∗p<0.01 vs. the pre-ACLF group at enrolment.
      Comparison between all groups to the pre-ACLF group at ACLF development is displayed by the following symbols:
      #p<0.001 and ##p<0.0001 vs. pre-ACLF group at ACLF development.
      Chi-square or Fisher’s tests performed in percentages comparisons among groups.
      McNemar test used in paired comparisons for the types of precipitant between the 2 time-points in pre-ACLF group.
      Symmetry test used in paired comparisons for the number of precipitant between the 2 time-points in pre-ACLF group.
      $p value not determined due to the low number of patients.
      ACLF, acute-on-chronic liver failure; AD, acute decompensation; SDC, stable decompensated cirrhosis; UDC, unstable decompensated cirrhosis.
      Interestingly, patients with a single precipitant of the 2 major groups of precipitants (proven bacterial infection and severe alcoholic hepatitis) showed a comparable 90-day mortality (Fig. 2B). This is the case, despite the significant differences in clinical and laboratory parameters between patients with either proven bacterial infection or severe alcoholic hepatitis as sole precipitant (Table S2), indicating that the type of precipitant is not crucial for outcome, if correctly defined.
      As shown in Fig. 2C, 90-day mortality was highest in patients with ≥2 precipitants and lowest in patients without any identifiable precipitant (Fig. 2C). In parallel, levels of leukocytes, neutrophils, monocytes and C-reactive protein (CRP) (Fig. 2D-G), organ dysfunction and failures and overall scores increased with the number of precipitants (Table S3).

      Results derived from the integrated ACLF cohort

      This integrated cohort included 202 patients with AD-ACLF at the time of enrolment (AD-ACLF group) and 218 patients in AD-pre-ACLF group who developed AD-ACLF during the study and who were included at the time of development of ACLF (Fig. 1). The integrated AD-ACLF cohort was developed with 2 objectives: i) a further characterization of the AD-ACLF phenotype in patients with community-acquired and hospital-acquired ACLF; and ii) an analysis of precipitants in a sufficiently sized AD-ACLF cohort.

      Prevalence of precipitants and their combinations

      Of the 420 patients included in the integrated AD-ACLF cohort, AD-ACLF was triggered by 1 precipitant in 191 patients (45.5%), and by or ≥2 in 82 patients (19.5%), while precipitant was indeterminate in 147 patients (35.0%) (Table S4). Fig. 3A shows the different combinations of precipitants in the Integrated AD-ACLF cohort. Like the AD-No ACLF cohort, 266 (97.4%) of patients with identifiable precipitants had proven bacterial infections or severe acute alcoholic hepatitis as either a single or as combined precipitants.
      Figure thumbnail gr3
      Fig. 3Precipitants in AD-ACLF.
      Combinations of PEs in the integrated AD-ACLF cohort shown in a 4-set circle Venn diagram (panel A). Cumulative incidence of mortality in patients with AD-ACLF according to the type of PE (proven infections alone vs. severe alcoholic hepatitis alone; panel B) and the number of PEs (indeterminate PE, 1 PE, and ≥2 PEs; panel C); p-values were obtained from Gray’s test. Blood levels of leukocytes (panel D), neutrophils (panel E), monocytes (panel F) and the serum concentration of CRP (panel G) in patients with AD-ACLF and indeterminate PE, 1 PE and ≥2 PEs. Boxes show median and IQR and whiskers show 10-90 percentiles. Kruskal-Wallis test was performed with all values in each comparison. Differences were statistically significant (p<0.0001) for all biomarkers. ACLF, acute-on-chronic liver failure; AD, acute decompensation; CRP, C-reactive protein; PE(s), precipitant(s).

      The type of precipitant is significantly associated with clinical characteristics, but not clinical course and mortality of patients with AD-ACLF in the integrated cohort

      As in AD-No ACLF patients (Table S2), patients with AD-ACLF had different clinical characteristics (among others higher bilirubin but lower CRP values in severe alcoholic hepatitis) depending on the type of single precipitant: proven bacterial infections or severe alcoholic hepatitis (Table S5). Similar to AD-No ACLF patients, these differences did not impact the clinical course and prognosis, as shown in Fig. 3B.

      Number of precipitants is significantly associated with the clinical course and mortality of patients with AD-ACLF.

      The number of precipitants in patients included in the integrated AD-ACLF cohort (indeterminate, 1 precipitant, and 2 or 3 precipitants) correlated positively with the prevalence of liver, brain, coagulation and cardio-circulatory failure and inversely with the prevalence of renal failure. These findings were due to differences in the predominance of specific organ failures among patients with a distinct number of precipitants. The predominant organ failure in patients with an indeterminate precipitant or with only 1 precipitant was renal failure. By contrast, liver failure was the predominant organ failure in patients with 2 or 3 precipitants. Moreover, the prevalence of other organ failures was also higher in patients with 2 or 3 precipitants. Consistent with these results, the number of precipitants at diagnosis also correlated directly with the grade of severity of ACLF (I, II or III), the severity of prognostic scores, the need for intensive care, the frequency of treatment with mechanical ventilation or renal replacement therapy, and the 90-day cumulative incidence of mortality (Table 3, Fig. 3C). Systemic inflammation, as estimated by the white blood cell count and blood levels of neutrophils and monocytes, increased in parallel with the number of precipitants (Table 3, Fig. 3D-G). Serum levels of CRP were also significantly higher in patients with 1 or ≥2 precipitants than in patients with indeterminate precipitants.
      Table 3Demographic data and etiology, clinical and laboratory data at diagnosis, specific treatments during follow-up and mortality in patients included in the integrated AD-ACLF cohort according to the number of precipitants.
      Indeterminate precipitant (n = 147)1 precipitant (n = 191)≥2 precipitants (n = 82)p value
      Demographic data and etiology of cirrhosis
       Age, year, mean ± SD61.2 ± 11.3860.5 ± 11.0652.1 ± 11.41
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Male sex, n (%)99 (67.3)137 (71.7)52 (63.4)0.36
       Alcohol-related cirrhosis, n (%)81 (55.1)144 (75.4)
      p<0.05 vs. indeterminate precipitant.
      77 (93.9)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
      Data at ACLF diagnosis
      Systemic hemodynamics, mean ± SD
       Mean arterial pressure (mmHg)80.8 ± 12.5179.0 ± 13.0576.1 ± 13.65
      p<0.05 vs. indeterminate precipitant.
      0.0419
       Heart rate (bpm)79.4 ± 15.8082.0 ± 17.2692.9 ± 19.93
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
      Complications, n (%)
       Ascites90 (73.2)134 (74.9)71 (88.8)
      p<0.05 vs. no precipitant and 1 precipitant.
      0.0206
       Hepatic encephalopathy61 (49.6)112 (62.6)
      p<0.05 vs. indeterminate precipitant.
      62 (77.5)
      p<0.05 vs. no precipitant and 1 precipitant.
      0.0003
       GI bleeding16 (13.1)16 (8.9)19 (23.8)
      p<0.05 vs. 1 precipitant. Chi-square or Fisher’s tests performed in percentages comparisons. For continuous variables comparisons, analysis of variance for normally distributed variables or Kruskal-Wallis test for not normally distributed variables were used. ACLF, acute-on-chronic liver failure; AD, acute decompensation; GI, gastrointestinal; MELD, model for end-stage liver disease.
      0.0053
      Organ failures, n (%)
       Liver failure29 (23.6)60 (33.5)49 (61.3)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Renal failure84 (68.3)98 (54.7)
      p<0.05 vs. indeterminate precipitant.
      33 (41.3)
      p<0.05 vs. no precipitant and 1 precipitant.
      0.0006
       Brain failure13 (10.6)31 (17.3)27 (33.8)
      p<0.05 vs. no precipitant and 1 precipitant.
      0.0002
       Coagulation failure25 (20.3)41 (23.0)28 (35.0)
      p<0.05 vs. no precipitant and 1 precipitant.
      0.0474
       Cardiovascular failure6 (4.9)25 (14.0)
      p<0.05 vs. indeterminate precipitant.
      27 (33.8)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Respiratory failure3 (2.4)21 (11.9)
      p<0.05 vs. indeterminate precipitant.
      13 (16.3)
      p<0.05 vs. indeterminate precipitant.
      0.0022
      Biomarkers of systemic inflammation, median (IQR)
       White blood cell count, x109/L7.19 (5.03–9.40)9.72 (6.39–13.50)
      p<0.05 vs. indeterminate precipitant.
      12.14 (8.57–18.10)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Neutrophil count, x109/L4.23 (2.25–6.85)7.32 (4.60–10.45)
      p<0.05 vs. indeterminate precipitant.
      9.56 (6.44–15.50)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Lymphocyte count, x109/L0.85 (0.65–1.40)0.94 (0.56–1.56)1.20 (0.73–1.97)
      p<0.05 vs. indeterminate precipitant.
      0.0794
       Monocyte count, x109/L0.60 (0.40–0.92)0.92 (0.65–1.22)
      p<0.05 vs. indeterminate precipitant.
      1.32 (0.95–1.77)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Serum C-reactive protein, mg/L17.60 (8.80–32.00)32.30 (15.00–58.90)
      p<0.05 vs. indeterminate precipitant.
      36.15 (18.00–75.00)
      p<0.05 vs. indeterminate precipitant.
      <0.0001
      Measurements estimating organ function
       Serum bilirubin, mg/dl, median (IQR)2.29 (1.12–11.04)5.70 (2.12–14.80)
      p<0.05 vs. indeterminate precipitant.
      14.53 (6.55–23.08)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Serum albumin, g/dl, mean ± SD3.0 ± 0.822.9 ± 0.682.9 ± 0.650.45
       Total cholesterol, mg/dl, median (IQR)86.70 (57.75–123.80)70.50 (48.50–104.00)
      p<0.05 vs. indeterminate precipitant.
      64.50 (42.00–83.50)
      p<0.05 vs. indeterminate precipitant.
      0.0145
       International normalized ratio, median (IQR)1.53 (1.32–2.13)1.75 (1.45–2.34)
      p<0.05 vs. indeterminate precipitant.
      2.18 (1.80–2.78)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Serum creatinine, mg/dl, median (IQR)2.15 (1.54–2.80)2.00 (1.04–2.50)
      p<0.05 vs. indeterminate precipitant.
      1.55 (0.82–2.81)
      p<0.05 vs. indeterminate precipitant.
      0.0024
       Serum sodium, mEq/L, mean ± SD133.6 ± 6.77133.6 ± 6.36134.4 ± 8.710.70
      Prognostic scores, mean ± SD
       Child-Pugh score9.5 ± 2.4110.5 ± 2.18
      p<0.05 vs. indeterminate precipitant.
      11.8 ± 1.50
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       MELD score24.3 ± 6.2125.6 ± 6.4129.8 ± 6.13
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       MELD-Na score26.6 ± 6.1127.9 ± 5.8131.2 ± 5.83
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       CLIF-C organ failure score8.9 ± 1.709.7 ± 1.97
      p<0.05 vs. indeterminate precipitant.
      11.3 ± 2.20
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       CLIF-C ACLF score45.7 ± 7.4550.1 ± 8.05
      p<0.05 vs. indeterminate precipitant.
      54.1 ± 10.86
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
      ACLF grades, n (%)
       ACLF grade I93 (76.2)105 (59.7)
      p<0.05 vs. indeterminate precipitant.
      24 (30.0)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       ACLF grade II23 (18.9)53 (30.1)
      p<0.05 vs. indeterminate precipitant.
      34 (42.5)
      p<0.05 vs. no precipitant and 1 precipitant.
       ACLF grade III6 (4.9)18 (10.2)
      p<0.05 vs. indeterminate precipitant.
      22 (27.5)
      p<0.05 vs. no precipitant and 1 precipitant.
      Specific treatments and mortality
      Specific treatments from ACLF, n (%)
       Intensive care15 (10.2)41 (21.5)
      p<0.05 vs. indeterminate precipitant.
      32 (39.0)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Renal replacement8 (5.4)13 (6.8)14 (17.1)
      p<0.05 vs. no precipitant and 1 precipitant.
      0.0055
       Mechanical ventilation3 (2.4)22 (12.3)
      p<0.05 vs. indeterminate precipitant.
      22 (27.5)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       Vasopressors35 (23.8)72 (37.7)
      p<0.05 vs. indeterminate precipitant.
      52 (63.4)
      p<0.05 vs. no precipitant and 1 precipitant.
      <0.0001
       90-day liver transplantation19 (13.1)25 (13.4)5 (6.3)0.22
      Mortality after ACLF diagnosis, n (%)
       90-day mortality62 (42.2)95 (49.7)52 (63.4)
      p<0.05 vs. no precipitant and 1 precipitant.
      0.0087
      a p<0.05 vs. no precipitant and 1 precipitant.
      b p<0.05 vs. indeterminate precipitant.
      c p<0.05 vs. 1 precipitant. Chi-square or Fisher’s tests performed in percentages comparisons. For continuous variables comparisons, analysis of variance for normally distributed variables or Kruskal-Wallis test for not normally distributed variables were used. ACLF, acute-on-chronic liver failure; AD, acute decompensation; GI, gastrointestinal; MELD, model for end-stage liver disease.

      Role of treatment of precipitant in prevention of AD-ACLF and improvement of survival

      Proven bacterial infections (details in the supplementary information)

      A total of 376 patients (29.5%) developed 440 bacterial infections, of which 66.2% were culture positive. Nosocomial episodes and severe sepsis or shock predominated in infections diagnosed as a precipitant of ACLF during follow-up, while multidrug resistant (MDR) strains were involved in 18.9% of all infections and 29.4% of culture positive episodes. Also, prevalence of infections caused by MDR strains was significantly higher in infections precipitating ACLF during follow-up and in those causing severe sepsis/shock (Table S6). Overall, resolution of infection was significantly lower in episodes caused by MDR bacteria (57.8% vs. 82.1%, p<0.0001). The lower resolution rate of MDR-infections was associated with higher 28-day and 90-day mortality in patients with AD-ACLF, but not in infections precipitating AD (Table S7).
      Classic antibiotic strategies were used frequently as first-line therapy in community-acquired and healthcare-associated infections (Table 4). In contrast, nosocomial episodes were more frequently treated with piperacillin-tazobactam (20.4%) or with broader MDR-covering strategies (38.8%). Remarkably, a significant percentage of patients with severe sepsis/shock still received classic schemes not covering MDR strains (40.5%). Empirical MDR-covering strategies were more effective in infection resolution (with regard to clinical response and microbiological susceptibility) than classic schemes (Table 4, Table S8). Adequacy of empirical antibiotic therapy was defined as resolution of infection without further escalation or bacterial susceptibility to initial antibiotics in culture positive infections. Importantly, adequacy of first-line antibiotic strategies decreased the cumulative incidence of developing ACLF in patients with AD (21.3% vs. 39.2%, Fig. 4A) and 90-day mortality in both AD (16.9% vs. 36.5%, Fig. 4B) and ACLF patients (44.2% vs. 66.2%, Fig. 4C).
      Table 4Adequacy of initial antibiotic strategies.
      Type of empirical antibiotic strategiesTotalClassic∗Piperacillin-tazobactamMDR coverage∗∗p value
      Number of all proven bacterial infections4402737092
       Resolution of infection without further escalation or bacterial susceptibility to initial antibiotics in culture positive infections (%)62.554.268.682.6<0.0001
       Bacterial susceptibility to initial antibiotics in culture positive infections (%)61.648.370.793.4<0.0001
      Number of proven bacterial infections precipitating AD2651873439
       Resolution of infection without further escalation or bacterial susceptibility to initial antibiotics in culture positive infections (%)68.162.073.592.30.0008
       Bacterial susceptibility to initial antibiotics in culture positive infections (%)63.954.475.0100.0<0.0001
      Number of proven bacterial infections precipitating ACLF175863653
       Resolution of infection without further escalation or bacterial susceptibility to initial antibiotics in culture positive infections (%)54.337.263.975.5<0.0001
       Bacterial susceptibility to initial antibiotics in culture positive infections (%)

      58.536.766.789.2<0.0001
      Adequacy based on clinical criteria (resolution of infection without further escalation or bacterial susceptibility to initial antibiotics in culture positive infections) and the microbiological criterion (bacterial susceptibility to initial antibiotics in culture positive infections) in the whole series of proven infections and in infections precipitating AD and ACLF, according to empirical antibiotic strategies.
      ∗One to third generation cephalosporins, amoxicillin-clavulanic acid, quinolones; ∗∗carbapenem±glycopeptide/linezolid/daptomycin or tigecycline; Chi-square or Fisher’s tests used to compare percentages.
      ACLF, acute-on-chronic liver failure; AD, acute decompensation; MDR, multidrug resistant.
      Figure thumbnail gr4
      Fig. 4Treatment of bacterial infections.
      Prognostic impact of inappropriate empirical antibiotic therapy in patients with AD and ACLF. (A) Probability of ACLF at day 90 in infected patients with AD receiving adequate or inadequate empirical antibiotic strategies (B-C) Probability of death at day 90 in patients with AD (B) and ACLF (C). Inadequacy of empirical strategies significantly increased the probability of ACLF and death in the different populations. p values were obtained from Gray’s test. ACLF, acute-on-chronic liver failure; AD, acute decompensation.

      Severe alcoholic hepatitis

      Steroids were administered in 49 patients with severe alcoholic hepatitis (18.9%), 30 patients with AD and 19 patients with ACLF at inclusion. The 28-day and 90-day mortality rates were not significantly different between patients receiving or not receiving steroids, neither in the whole population nor in patients with AD or ACLF at inclusion (Table S9).

      Discussion

      The PREDICT study offers a comprehensive investigation characterizing the precipitants of AD and demonstrating their impact on the development of AD-ACLF and prognosis.
      The CANONIC study characterized the AD-ACLF phenotype and attributed an important role to precipitants in its development. The PREDICT study, designed to assess the period prior to ACLF,
      • Trebicka J.
      • Fernandez J.
      • Papp M.
      • Caraceni P.
      • Laleman W.
      • Gambino C.
      • et al.
      The PREDICT study uncovers three clinical courses in acutely decompensated cirrhosis with distinct pathophysiology.
      identified 3 different clinical courses in AD-No ACLF: pre-ACLF, AD-UDC and AD-SDC. Moreover, the PREDICT study assessed how type and number of precipitants influence the clinical course and the prognosis in patients with both AD-No ACLF and AD-ACLF. This prospective and detailed characterization offers diagnostic criteria for precipitants and rationalizes the identification of precipitants in patients with cirrhosis and AD. The criteria used for the diagnosis of precipitants considered the severity of the precipitant, the time interval between onset/resolution of the precipitant and onset of the AD episode, and their higher prevalence in patients with AD-ACLF than in patients with AD-No ACLF, which are more objective than the traditional principles of chronology and potential of organ injury.
      Among the events recorded and evaluated in the PREDICT study, only 4 fulfilled the properties of precipitants (chronology, severe organ injury or higher prevalence in the AD-ACLF phenotype): proven bacterial infections, severe alcoholic hepatitis, GI bleeding with shock and toxic encephalopathy. While paracentesis without intravenous albumin administration and TIPS did not induce organ impairment (TIPS even improves survival in GI bleeding and ACLF
      • Trebicka J.
      • Gu W.
      • Ibanez-Samaniego L.
      • Hernandez-Gea V.
      • Pitarch C.
      • Garcia E.
      • et al.
      Rebleeding and mortality risk are increased by ACLF but reduced by pre-emptive TIPS.
      ,
      • Kumar R.
      • Kerbert A.J.C.
      • Sheikh M.F.
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      Determinants of mortality in patients with cirrhosis and uncontrolled variceal bleeding.
      ), the prevalence of drug-induced liver or renal injury and of other potential precipitants proposed by the investigators was extremely low, frequently below 1%, suggesting that they could be coincidental rather than precipitants.
      Proven bacterial infections and severe alcoholic hepatitis were by far the most prevalent precipitants observed in the PREDICT study. Prevalence of GI bleeding associated with shock and toxic encephalopathy was considerably lower in both groups. In patients with AD-No ACLF, the prevalence of proven bacterial infections or severe alcoholic hepatitis and the number of precipitants present at enrolment were higher in patients with AD-Pre-ACLF than in patients with AD-UDC and AD-SDC. In contrast, no differences were found in the prevalence of these precipitants between patients with UDC or SDC. These findings suggest that precipitants are determinants of the development of the AD-Pre-ACLF sub-phenotype, which is associated with a worse clinical course and prognosis in patients with AD-No ACLF. Importantly, in >60% of the patients in the AD-No ACLF cohort, precipitating events were indetermined at enrolment, while this was the case in only 35% of the patients with AD-ACLF. These data suggest that AD-No ACLF develops more frequently in the context of endogenous mechanisms (e.g. progressive liver disease, bacterial translocation), confirming the CANONIC study and underlining the solidity of the PREDICT study.
      The type of precipitant was associated with different clinical characteristics, but a similar clinical course and mortality. This finding is not surprising, since reactivation or superimposed hepatitis, also showed different prevalences of specific organ failures in AD-ACLF, but similar outcome as AD-ACLF triggered by extrahepatic precipitants (e.g GI bleeding).
      • Shi Y.
      • Yang Y.
      • Hu Y.
      • Wu W.
      • Yang Q.
      • Zheng M.
      • et al.
      Acute-on-chronic liver failure precipitated by hepatic injury is distinct from that precipitated by extrahepatic insults.
      The explanation may be due to the sequence of mechanisms. Bacterial infections would induce systemic inflammation as the primary mechanism, leading to predominantly circulatory and renal dysfunction or failure. In contrast, the direct insult of alcohol toxicity induces hepatic inflammation and cell death as primary mechanisms culminating in liver and coagulation dysfunction or failure. Importantly, systemic inflammation aggravates and leads to an identical syndrome through distinct pathophysiological pathways. For this reason, the criterion of severity (either systemic inflammation or organ injury) of the event is crucial to identify the precipitant.
      Finally, our results show that the number of precipitants was an important determinant for the characteristics, the clinical course severity and the 90-day cumulative incidence of mortality. Not only that multiple (2 or more) precipitants trigger AD-ACLF (one in 5 patients) and is exceptional (one in 20 patients) in AD-No ACLF, but also the intensity of systemic inflammation, the prevalence of organ failures, the need for organ support, and the prognostic scores increased progressively from patients with indeterminate precipitants to patients with 1 and multiple precipitants. Therefore, when precipitants are defined according to these criteria, they are synergistic and additive in the worsening of outcome, despite different clinical characteristics.
      Almost all (>96%) patients with precipitants showed proven bacterial infection and/or severe alcoholic hepatitis, either alone or in combination with other precipitants. This overwhelming prevalence of proven bacterial infections and/or severe alcoholic hepatitis as precipitants suggests that diagnosing, preventing and treating these precipitants is paramount to improve the prognosis of patients with decompensated cirrhosis.
      PREDICT demonstrates that proven bacterial infections require specific and adequate treatment for prevention of AD-ACLF. This is of particular importance since MDR may challenge empirical treatments. The overall prevalence of MDR bacterial infections in PREDICT was in line with that reported in recently published multicenter investigations
      • Piano S.
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      and MDR bacterial infections were more severe (higher rate of severe sepsis/shock and of ACLF), associated with a lower resolution rate and higher 28-day and 90-day mortality,
      • Piano S.
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      underlining the importance of treatment of precipitants, thus confirming that definition and selection of precipitants has been chosen adequately. Importantly, classic antibiotics (1st-3rd generation cephalosporins, quinolones) have an unacceptable efficacy (<40%) in nosocomial infections, or in those with severe sepsis or shock. These findings support the current recommendations on the use of empirical broad schemes, according to specific epidemiological pattern of antibiotic resistance,
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      in the nosocomial setting and in severe sepsis/shock with rapid de-escalation strategies.
      European Association for the Study of the Liver
      Electronic address eee, clinical practice guideline panel C, panel m, representative EGB. EASL clinical practice guidelines: drug-induced liver injury.
      In summary, of the clinical events explored as potential precipitants in the PREDICT study, only 4 (proven bacterial infections, severe acute alcoholic hepatitis, GI bleeding associated with shock and toxic encephalopathy) fulfilled the diagnostic criteria of precipitants. Proven bacterial infections and severe alcoholic hepatitis were present in the absolute majority (>96%) of patients. However, no precipitating event could be identified in 2/3 of AD-No ACLF patients and in 1/3 AD-ACLF patients. The prevalence and number of precipitants increased with severity of the AD-sub-phenotype form SDC/UDC to pre-ACLF and ACLF, which were also directly related with clinical course severity and short-term mortality in patients with AD. Our data, therefore, strongly suggest that precipitants are significantly associated with the clinical course and prognosis of patients with AD and specific preventive and therapeutic strategies for these precipitants are required to improve outcomes in decompensated cirrhosis.

      Abbreviations

      ACLF, acute-on-chronic liver failure; ALT, alanine aminotransferase; AST, aspartate aminotransferase; CLIF, chronic liver failure; CIF, cumulative incidence of function; CRP, C-reactive protein; GI, gastrointestinal; OF, organ failure; MDR, multidrug resistant; MELD, model of end-stage liver disease; PE, precipitating event; SDC, stable decompensated cirrhosis; UDC, unstable decompensated cirrhosis.

      Financial support

      The study was supported by the European Foundation for the Study of Chronic Liver Failure (EF-Clif). EF-Clif is a non-profit private organization. EF-Clif receives unrestricted donations from Cellex Foundation and Grifols . EF-Clif is partner, contributor and coordinator in several EU Horizon 2020 program projects. JT was appointed visiting Professor in EF-Clif for the execution of the study by a grant from Cellex Foundation . The funders had no influence on study design, data collection and analysis, decision to publish or preparation of the manuscript.

      Authors’ contributions

      JT, JF, WL, JC, RJ, RM, PG, PA, VA: study concept and design, acquisition of data, analysis and interpretation of data, drafting of the manuscript, funding recipient, administrative, technical and material support, study supervision; EG, AA, AC, CP, MP, CS, AC, AM, FA: acquisition of data, analysis of data, technical and material support; TT, MB, PA, CA, FEU, CJ, MST, TG, DLS, AA, WL, ES, RB, MJ, CS, TR, JA, PG, WB, SZ, CR, TB, AS, KVD, MC, OR, RS, HZ, AC, GSP, AdG, HG, FS, CT, OCÖ, FS, SR, RA, MRG, HVV, CF, MM, MP, PC, SP, IG, MP, VV, RM, ZV, MB, EB: acquisition of data, interpretation of data, critical revision of the manuscript regarding important intellectual content

      Data availability statement

      While some of the data of this paper will be available upon request, the majority of the data are not suitable for posting as they are confidential.

      Conflict of interest

      None of the authors have conflicts of interest for the reported study.
      Please refer to the accompanying ICMJE disclosure forms for further details.

      Acknowledgements

      The authors are very grateful to the patients, their families and the personnel of the hospitals for making this possible. In addition, a special thank you is dedicated to Mrs. Yolanda Godoy, Dr. Anna Bosch, Dr. Josep-Maria Torner, Mrs. Cecilia Ducco and Montserrat Carreras for excellent assistance in the accomplishment of the study. We thank Marites Abans, Paul Sauerbruch, Gudrun Hack, Nadine Köstlmeier, Kristin Gehrmann for technical and administrative assistance.

      Appendix A. Supplementary data

      The following are the supplementary data to this article:

      Appendix

      Collaborators:

      Miriam Maschmeier1, David Semela2, Laure Elkrief3, Ahmed Elsharkawy4, Tamas Tornai5, Istvan Tornai5, Istvan Altorjay5, Agnese Antognoli6, Maurizio Baldassarre6, Martina Gagliardi6, Eleonora Bertoli7, Sara Mareso7, Alessandra Brocca7, Daniela Campion8, Giorgio Maria Saracco8, Martina Rizzo8, Jennifer Lehmann9, Alessandra Pohlmann9, Maximilian J. Brol9, Johannes Chang9, Robert Schierwagen18, Elsa Solà10, Nesrine Amari11, Miguel Rodriguez12, Frederik Nevens13, Ana Clemente14, Martin Janicko15, Daniel Markwardt16, Mattias Mandorfer17, Christoph Welsch18, Tanja M. Welzel18, Emanuela Ciraci19, Vish Patel20, Cristina Ripoll21, Adam Herber22, Paul Horn23, Flemming Bendtsen24, Lise Lotte Gluud24, Jelte Schaapman25, Oliviero Riggio26, Florian Rainer27, Jörg Tobiasch Moritz28, Mónica Mesquita29, Edilmar Alvarado-Tapias30, Osagie Akpata31, Luise Aamann32, Didier Samuel33, Sylvie Tresson33, Pavel Strnad34, Roland Amathieu35, Macarena Simón-Talero36, Francois Smits11, Natalie van den Ende13, Javier Martinez12, Rita Garcia14, Harald Rupprechter17, Cornelius Engelmann22, Osman Cavit Özdogan37

      Affiliations:

      1Munster University Hospital, Münster, Germany
      2University of Basel-St Gall Cantonal Hospital, Switzerland
      3Hôpitaux Universitaires de Genève, Genève, Switzerland
      4University of Birmingham, Birmingham, UK
      5University of Debrecen, Faculty of Medicine, Institute of Medicine, Department of Gastroenterology, Debrecen, Hungary
      6University of Bologna, Bologna, Italy
      7University of Padova, Padova, Italy
      8A.O.U. Città della Salute e della Scienza Torino, Torino, Italy
      9University Hospital Bonn, Bonn, Germany
      10Hospital Clinic of Barcelona, Barcelona, Spain
      11C.U.B. Erasme, Bruxelles, Belgium
      12Department of Gastroenterology, Hospital Universitario Ramón y Cajal, IRYCIS, University of Alcalá, CIBEREHD, Madrid, Spain
      13Department of Gastroenterology and Hepatology, Section of Liver and Biliopancreatic disorders, University of Leuven, Leuven, Belgium
      14 Hospital General Universitario Gregorio Marañón. Facultad de Medicina (Universidad Complutense of Madrid), CIBERehd, Madrid, Spain
      15Pavol Jozef Safarik University in Kosice, Kosice, Slovakia
      16Department of Medicine II, Liver Centre Munich, University Hospital, LMU, Munich, Germany
      17Medical University of Vienna, Vienna, Austria
      18Department of Internal Medicine I, Goethe University Frankfurt, Frankfurt Germany
      19Internal Medicine PO Ostuni, ASL Brindisi, Italy
      20King's College Hospital, London, UK
      21University Hospital Halle-Wittenberg, Halle(Saale), Germany
      22Division of Hepatology, Department of Medicine II, Leipzig University
      Medical Center, Leipzig, Germany
      23Jena University Hospital, Jena, Germany
      24Gastrounit, Medical Section, Hvidovre Hospital and Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
      25Leiden University Medical Center, Leiden, The Netherlands
      26Universitá Sapienza Roma, Roma, Italy
      27Medical University of Graz, Graz, Austria
      28Medical University of Innsbruck, Innsbruck, Austria
      29CHTMAD Vila Real-Blueclinical, Vila Real, Portugal
      30Hospital de la Santa Creu i Sant Pau and CIBERehd, Barcelona, Spain
      31UCL Medical School,Royal Free Hospital, London, UK
      32Aarhus University Hospital, Aarhus, Denmark
      33AP-HP Hôpital Paul Brousse, Centre Hépato-Biliaire, Universite Paris Saclay, INSERM Unit 1193, Villejuif, France
      34Aachen University Hospital, Aachen, Germany
      35AP-HP, Hôpital Jean Verdier, Service d’Hépatologie, Bondy; Université Paris 13, Sorbonne Paris Cité, “Equipe labellisée Ligue Contre le Cancer”, Saint-Denis; Inserm, UMR-1162, “Génomique fonctionnelle des tumeurs solides”, Paris, France
      36 Liver Unit, Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, CIBEREHD, Barcelona, Spain
      37Marmara University, Kadiköy, Turkey

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