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Background and Aims: Prognosticating outcomes such as hospitalizations in outpatients with cirrhosis is challenging, especially with changing etiologies and demographics. This study aims to determine the impact of multi-omic strategies on outcome prediction. Approach and Results: NACSELD3 enrolls outpatients with cirrhosis with controlled/eradicated etiologies from 10 centers and follows them systematically. At baseline, clinical/demographic and cirrhosis details were recorded and saliva and serum samples were collected for microbiome and metabolome analysis, respectively. Multi-omic bioinformatic studies to determine the interaction of microbiota and metabolites with the clinical prediction of 6-month hospitalizations were performed. Five hundred sixty-five patients (60.2 y, 68% men, 35% alcohol, 33% metabolic dysfunction-associated steatohepatitis, 21%, eradicated HCV with MELD 3.0 12) were enrolled. One hundred sixty-three (29%) required 6-month hospitalizations; most (75%) were liver-related. Those hospitalized had worse cirrhosis severity and comorbidity indices but similar demographics and oral health variables. Salivary microbiome alpha-diversity was lower (1.96±0.48 vs. 2.09±0.45, p =0.018) with greater pathobionts ( Streptococcus , Treponema, Enterococcaceae) and lower commensal genhospitalized/noera ( Veillonella, Prevotella, Haemophilus , Lachnospiraceae spp) at baseline. Serum metabolomics showed significant separation at baseline between hospitalized/non-hospitalized patients using supervised analyses with microbial-origin (phenyllactate, secondary bile acids, indoles), choline moieties, and polyamine/GABA (3-ureidopropionate/spermidine) metabolites being most prominent. Area under the curve using random forest for clinical, microbial, and metabolomic variables was higher than that of these individually. Latent factor analysis showed clinical variables (MELD 3.0, hemoglobin, and albumin) with the greatest impact, followed by salivary microbiota and then serum microbiome for hospitalization prediction. Conclusions: In a multicenter North American outpatient cirrhosis cohort with controlled etiologies, serum metabolomics and salivary microbiome add to clinical variables to prognosticate 6-month hospitalization.

Background and Aims: Reducing avoidable readmissions in cirrhosis is challenging. Enhanced engagement using health information technology (HIT) interventions and caregivers lowered readmissions in an open-label study of the Patient Buddy App (PBA). Aim : Multicenter trial of PBA versus standard of care (SOC) to reduce avoidable readmissions. Approach and Results: An open-label, randomized clinical trial was performed at 3 sites to study the effect of PBA (HIT) versus SOC in cirrhosis inpatients with adult caregivers (dyads). Initial randomization was 1:1:1 between SOC, HIT only, and HIT+ visits. However, due to COVID-19, an unplanned study redesign required a combined HIT versus SOC. Primary outcome : Avoidable readmissions (decided by a blinded monitoring board). Secondary outcomes were all-cause readmission and stakeholder input. PBA focused on medication adherence, cognitive testing, and symptoms, and was remotely monitored by study staff. In all, 464 subjects (232 dyads) were enrolled [Virginia Commonwealth University (VCU): 120, Mayo: 40, Department of Veterans Affairs (VA): 72; 116 dyads/group]. Avoidable readmissions were significantly higher in SOC versus HIT (19.8% vs. 10.3%, p =0.04) with OR of 2.14 (95% CI 1.01–4.54) and remained significant even after removing pre-COVID HIT+ visits patients (19.8% vs. 9.3%, p =0.040) with OR of 2.41 (95% CI 1.02–5.69). All-cause readmissions were higher in SOC versus HIT (48% vs. 30%, p =0.005). App evaluation/engagemen t : 1660 alerts were sent; mostly related to HE. Most dyads were satisfied with the app. Conclusions: In a multicenter randomized clinical trial of 464 cirrhosis inpatients and their CGs across several practice settings, the PBA was associated with lower avoidable readmissions at 30 days post-discharge compared to SOC.

Background: How parental alcohol use disorder and liver disease-related mortality influence the risk and the outcomes of alcohol-associated hepatitis (AH) in the offspring is unknown. Methods: We analyzed data from 2 prospective observational studies of AH cases and heavy drinking controls (HDCs). Family history of parental alcohol use disorder and liver disease mortality was assessed at the study entry. Logistic regression and Cox proportional hazard models were used to assess the influences of family history on AH development and outcome. Results: Data from 1356 participants in two prospective cohorts (926 AH cases and 430 HDC) were combined and analyzed. Parental alcohol use disorder was found in 56.9% of AH cases and 61.1% of HDC; parental death due to liver disease was reported in 7.5% of AH cases and 5.7% of HDC. Multivariable logistic regression showed that parental liver disease-related mortality was associated with more than a doubled risk of AH development in the offspring after controlling for their demographic characteristics and drinking behavior (OR=2.26, 95% CI: [1.22, 4.20]). Moreover, among the AH cases, having a parent die of liver disease significantly increased the 90-day mortality of study participants after adjusting for the effects of other risk factors (HR=2.26, 95% CI: [1.05, 4.86]). Conclusions: The study highlights the influences of parental death due to liver disease on AH development and mortality. Identifying patients at risk of AH through family history might help facilitate discussions on reducing alcohol consumption.

Background Severe alcohol-associated hepatitis (sAH) is a life-threatening condition with high mortality, where corticosteroid use is the only treatment that has shown short-term benefits. Pentoxifylline, an anti-tumour necrosis factor-alpha agent, has been proposed for its potential to improve outcomes, especially in patients with acute kidney injury (AKI). We aimed to evaluate the impact of pentoxifylline on mortality in patients with sAH and AKI in a well-characterised global cohort. Methods We conducted a retrospective, registry-based study including patients meeting the National Institute on Alcohol Abuse and Alcoholism clinical criteria for sAH and AKI. Mortality was the primary endpoint, with liver transplantation as a competing risk. Statistical analysis included Cox regression and Kaplan-Meier survival estimates. Results We included 525 patients from 20 centres across eight countries. The median age was 48 years, with 26.1% females, and 76.9% had a history of cirrhosis. Multivariable Cox regression models showed that pentoxifylline use was not associated with survival (HR 1.20, 95% CI 0.85 to 1.69, p=0.291). Factors associated with mortality included age (HR 1.23, 95% CI 1.10 to 1.36, p<0.001), Model for End-Stage Liver Disease score at admission (HR 1.06, 95% CI 1.04 to 1.08, p<0.001) and renal replacement therapy use (HR 1.39, 95% CI 1.05 to 1.84, p=0.019). The main causes of death were multiple organ failure (42%), infections (10%), oesophageal varices bleeding (7%) and renal failure (6%). Conclusion Pentoxifylline showed no significant benefit on mortality in patients with sAH and AKI. Further studies are needed to refine treatment strategies for this high-risk group.

Background: Severe alcohol-associated hepatitis (sAH) is a well-characterized disease with high short-term mortality. However, there is limited research on those with a “less severe condition” (moderate AH). This study aims to characterize in-depth patients with moderate AH (mAH), including the performance of mortality scoring systems, key prognostic factors, and survival over time. Methods: A multicenter retrospective cohort study (2009–2019) included patients with mAH (MELD score ≤20 at admission). Cox regression and receiver operating characteristic curves with AUC were used for analysis. Results: We included 1845 patients with AH (20 centers, 8 countries) between 2009 and 2019. mAH was defined as a MELD score ≤20 at admission. Twenty-four percent met the criteria for an mAH episode. Patients with mAH tend to be older and have a higher proportion of females, with a median MELD of 17 (15–19), Maddrey discriminant function (mDF) of 33 (22–40), the trajectory of serum bilirubin of 0.83 (0.60–1.21), and neutrophil-to-lymphocyte ratio (NLR) of 5 (2.96–8.60). The primary causes of death in mAH included multiple organ failure (34.1%) and infections (16.6%). The cumulative survival rates at 30, 90, and 180 days were 94.3%, 90.4%, and 88.2%, respectively. In multivariable analysis, age was the only significant predictor of 30-day mortality (HR 1.49, 95% CI: 1.27–1.76, p <0.001). Mortality prediction models showed poor performance, with AUC for MELD (0.671), mDF (0.726), trajectory of serum bilirubin (0.733), and NLR (0.697). Conclusions: Patients with moderate AH exhibited a mortality of 11.8% at 6 months, primarily driven by multiple organ failure and infections. These patients also exhibit a different clinical profile compared to those with sAH. Tailored models and therapeutic strategies are needed to improve long-term outcomes in mAH.

INTRODUCTION: Building on prior results, we hypothesized that an electrocardiogram (ECG)-enabled machine learning (ML) model could be used to detect advanced chronic liver disease (CLD). METHODS: A cohort with CLD and 12-lead ECGs was matched with controls from electronic health records. A ML model was trained as a binary classifier. RESULTS: There are 12,930 patients with CLD and 64,577 controls in the cohort. The model's discriminative ability to classify CLD showed an area under the receiver-operating characteristic curve 0.858 (95% confidence interval: 0.850–0.866), and at the chosen threshold, CLD ECGs had 12 times higher odds of being classified as CLD (diagnostic odds ratio 12.33, 95% confidence interval: 11.16–13.63). DISCUSSION: An ECG-enabled ML model affords great promise in identifying advanced CLD in low resource areas.

Background and Aims: Clinical hepatology research often faces limited data availability, underrepresentation of minority groups, and complex data-sharing regulations. Synthetic data—artificially generated patient records designed to mirror real-world distributions—offers a potential solution. We hypothesized that diffusion models, a state-of-the-art generative technique, could produce synthetic liver transplant waitlist data from the United Network for Organ Sharing database that maintains statistical fidelity, replicates clinical correlations and survival patterns, and ensures robust privacy protection. Approach and Results: Diffusion models were used to generate synthetic patient cohorts mirroring the United Network for Organ Sharing liver transplant waitlist database between the years 2019 and 2023. Statistical fidelity was assessed using maximum mean discrepancy (MMD) and Wasserstein distance, correlation analysis, and variable-level metrics. Clinical utility was evaluated by comparing transplant-free survival via Kaplan–Meier curves and the MELD score performance. Privacy was quantified using the Distance to Closest Record (DCR) and attribute disclosure risk assessments. The synthetic dataset was nearly indistinguishable from the original dataset (MMD=0.002, standardized Wasserstein distance <1.0), preserving clinically relevant correlations and survival patterns as evidenced by similar median survival times (110 vs. 101 days) and 5-year survival rates (22.2% vs. 22.8%). MELD-based 90-day mortality prediction was maintained (original AUC=0.839 vs. synthetic AUC=0.844). Privacy metrics indicated no identifiable patient matches, and mean DCR values ensured that synthetic individuals were not direct replicas of real patients. Conclusion: Artificial intelligence–generated synthetic data derived from diffusion models can faithfully replicate complex hepatology datasets, maintain key clinical signals, and ensure strong privacy safeguards. This approach can help address data scarcity, enhance model generalizability, foster multi-institutional collaboration, and accelerate progress in hepatology research.

ABSTRACTSeveral dynamic models predict mortality and corticosteroid response in alcohol‐associated hepatitis (AH), yet no consensus exists on the most effective model. This study aimed to assess predictive models for corticosteroid response and short‐term mortality in severe AH within a global cohort. We conducted a multi‐national study of patients with severe AH treated with corticosteroids for at least 7 days, enrolled between 2009 and 2019. Dynamic models—Lille‐4, Lille‐7, trajectory of serum bilirubin (TSB), and neutrophil‐to‐lymphocyte ratio (NLR)—were used to estimate 30‐ and 90‐day mortality. Lille‐7 demonstrated the highest accuracy for both 30‐ and 90‐day mortality.

ImportanceThere are no useful treatments to prevent the development of severe complications of liver cirrhosis. Simvastatin and rifaximin have shown beneficial effects in liver cirrhosis.ObjectiveTo assess whether simvastatin combined with rifaximin improves outcomes in patients with decompensated cirrhosis.Design, Setting, and ParticipantsDouble-blind, placebo-controlled, phase 3 trial conducted among patients with decompensated cirrhosis in 14 European hospitals between January 2019 and December 2022. The last date of follow-up was December 2022.InterventionsPatients were randomly assigned to receive simvastatin, 20 mg/d, plus rifaximin, 1200 mg/d (n = 117), or identical-appearing placebo (n = 120) for 12 months in addition to standard therapy, stratified according to Child-Pugh class B or C.Main Outcomes and MeasuresThe primary end point was incidence of severe complications of liver cirrhosis associated with organ failure meeting criteria for acute-on-chronic liver failure. Secondary outcomes included transplant or death and a composite end point of complications of cirrhosis (ascites, hepatic encephalopathy, variceal bleeding, acute kidney injury, and infection).ResultsAmong the 237 participants randomized (Child-Pugh class B: n = 194; Child-Pugh class C: n = 43), 72% were male and the mean age was 57 years. There were no differences between the 2 groups in terms of development of acute-on-chronic liver failure (21 [17.9%] vs 17 [14.2%] patients in the treatment and placebo groups, respectively; hazard ratio, 1.23; 95% CI, 0.65-2.34; P = .52); transplant or death (22 [18.8%] vs 29 [24.2%] patients in the treatment and placebo groups, respectively; hazard ratio, 0.75; 95% CI, 0.43-1.32; P = .32); or development of complications of cirrhosis (50 [42.7%] vs 55 [45.8%] patients in the treatment and placebo groups, respectively; hazard ratio, 0.93; 95% CI, 0.63-1.36; P = .70). Incidence of adverse events was similar in both groups (426 vs 419; P = .59), but 3 patients in the treatment group (2.6%) developed rhabdomyolysis.Conclusions and RelevanceThe addition of simvastatin plus rifaximin to standard therapy does not improve outcomes in patients with decompensated liver cirrhosis.Trial RegistrationClinicalTrials.gov Identifier: NCT03780673