Early liver transplantation (LT) is increasingly being adopted as a treatment for alcohol-associated hepatitis (AAH), but the optimal strategy for incorporating AAH into the existing organ allocation framework remains unclear. This retrospective cohort study used the United Network for Organ Sharing database (1/1/2018-12/31/2024) to compare adults waitlisted for first-time, single-organ LT for AAH against other alcohol-associated liver disease (ALD) and non-ALD. During the study period, waitlisting and LT for AAH increased more than six-fold, with 98.2% of centers performing LT for this indication. Compared to other ALD and non-ALD, patients with AAH experienced lower waitlist mortality (8.2% vs. 12.6% and 19.3%, respectively; p<0.001) and higher LT rates (81.2% vs. 69.0% and 67.0%, respectively; p<0.001). After adjusting for clinical and demographic characteristics on initial waitlist application, both other ALD and non-ALD were associated with higher waitlist mortality relative to AAH (adjusted hazard ratio [aHR]=1.23 with p=0.003 and aHR=1.86 with p<0.001, respectively). Among patients with AAH, waitlist mortality was not associated with MELD scores <40 (p=0.66). Across all MELD categories, non-ALD was associated with higher waitlist mortality than AAH (HR 1.83-3.23; all p≤0.005), while other ALD was associated with higher mortality at most MELD strata (p<0.05 at MELD 20-24 and ≥30). Of individual MELD components, serum sodium was not associated with AAH waitlist mortality (HR=1.01; p=0.53), while INR was a stronger predictor of mortality in AAH than other LT indications (HR=1.95 for AAH vs. HR=1.14 for other ALD vs. HR=1.23 for non-ALD; all p<0.001). Patients with AAH are disproportionately prioritized under the current organ allocation system, underscoring the need to revise allocation practices to ensure equitable LT access.

The liver is a highly spatially organized organ in which microanatomy underpins metabolism, immune regulation, and regenerative capacity. In liver transplantation, spatially defined processes, including ischemia reperfusion injury (IRI), alloimmune activation, and disease recurrence critically shape graft function and long-term outcomes. However, conventional bulk and single-cell transcriptomics and proteomics approaches lack the ability to resolve these events within their native tissue context. Recent advances in spatial transcriptomic and proteomic technologies enable high-resolution mapping of cellular interactions within healthy tissue, providing new insight into the microenvironmental niches that drive graft injury and repair. This review summarizes current spatial omics platforms, including sequencing-based, imaging-based, and microdissection approaches, with emphasis on technical and analytic considerations relevant to transplantation. It synthesizes emerging applications in key transplant settings, including IRI, machine perfusion-mediated graft reconditioning, alloimmune injury, chronic remodelling, and recurrent liver disease. Spatial studies demonstrate that liver graft injury arises within discrete immune-stromal-parenchymal niches that influence progression toward recovery or chronic dysfunction. Translation into clinical practice will require longitudinal sampling and harmonized workflows, and will be significantly enhanced by integration with artificial intelligence-driven analytics. Ultimately, spatially resolved molecular signatures may improve donor assessment, enable early risk stratification, and guide precision interventions, advancing a biology-informed approach to liver transplantation.

The choice between total intravenous anesthesia (TIVA) and volatile anesthesia for living donor hepatectomy remains controversial, with limited evidence comparing their impact on donor and recipient outcomes. This study evaluates the association between anesthetic technique and early postoperative outcomes using global prospective data. 1,466 donor-recipient pairs (September 2023-February 2025) from the International LDLT Registry (LDLTregistry.org) were analyzed. Donors were stratified by anesthetic technique (TIVA vs. volatile). Primary outcome was donor morbidity assessed by the Comprehensive Complication Index® (CCI®). Secondary outcomes included complication incidence (grouped by Clavien-Dindo grade), intraoperative blood loss, transfusion requirements, and biochemical markers. Multivariable regression analysis was adjusted for Human Development Index, surgical approach, and graft type. A linear mixed-effects model with a random intercept for transplant center, to account for outcome differences related to individual transplant center practices, was used to evaluate the association between anesthetic technique and donor CCI. TIVA was used for most donor hepatectomies (82.8%) but there was significant regional variation in its use (p<0.001). All seven centers contributing more than 50 cases (50.3% of the total cohort) used TIVA exclusively or predominantly. Use of volatile anesthesia was independently associated with higher donor CCI® scores (regression coefficient 1.69, 95% CI 0.29-3.09, p=0.018), more major complications (6.3% vs. 1.2%, p<0.001), and greater median blood loss (250 mL vs. 100 mL, p<0.001). TIVA was associated with lower transfusion rates (6.0% vs. 11.6%, p=0.002) and fewer biliary complications (2.5% vs. 8.3%, p<0.001). Recipient outcomes, including graft function and biochemical recovery, were comparable between groups. Our findings suggest an association between TIVA use and improved outcomes in living liver donors, with reduced morbidity in multivariable analysis accounting for transplant center and socioeconomic status of the countries where data originated. Further evaluation of this association with large scale international multicenter randomized trials is warranted.

Current liver transplantation (LT) guidelines recognize perceived health-related quality of life as an important outcome of long-term care, yet it remains unclear whether post-transplantation health literacy plays a role in patient-reported physical and mental health. We conducted a large-scale cross-sectional analysis using data from the U.S. All of Us Research Program of adults with documented LT before completing the "Overall Health" survey (n=1,042). Health literacy was assessed with the 3-item Brief Health Literacy Screen (BHLS; range, 3-15), and physical and mental health with PROMIS Global Health T-scores. Multivariable linear regression adjusted for age, sex at birth, race and ethnicity, and education. Associations were compared with those in adults with cirrhosis without LT (n=5,290) and the general All of Us comparator population. Among 747,029 participants, 1,042 LT recipients had evaluable BHLS scores. Marginal health literacy (BHLS ≤12) was present in 372 recipients (35.7%), including 131 (12.6%) with low health literacy (BHLS ≤9). LT patients displayed a lower health literacy compared to the general population (mean BHLS 12.8 vs. 13.4), but higher than adults with cirrhosis (12.4; all p<0.001). Each 3-point BHLS score increase associated with 3.22-point higher Physical Health (95% CI, 2.52-3.92) and 2.85-point higher Mental Health T-scores (95% CI, 2.09-3.60) after adjustment (both p<0.001). The strength of the association did not differ significantly between recipients and either comparator group. Transplant recipients displayed reduced health literacy, and post-transplant health literacy was strongly associated with better patient-reported physical and mental health. These findings identify health literacy as a modifiable dimension of long-term transplant survivorship and support its assessment in post-transplant care.

Biliary reconstruction is often considered the Achilles' heel of liver transplantation, yet risk factors and outcomes remain poorly defined, particularly in pediatric living donor liver transplantation (LDLT). This international multicenter study aims to identify predictors of biliary complications and evaluate their impact on long-term outcomes. 2,665 pediatric patients who underwent LDLT between January 2019 and December 2023 across 19 centers were included. Multivariable logistic regression was performed to identify risk factors, while time-dependent Cox models were used to assess impact on survival. The median recipient age was 11 months (IQR: 6.3-34.6) and biliary atresia was the most common diagnosis (59.7%). Bile leak and anastomotic stricture occurred in 3.6% (n=97) and 1.9% (n=51) of patients, respectively. For bile leak, higher donor BMI was an independent predictor (OR 1.09 per kg/m[2], 95% CI: 1.02-1.17). For anastomotic strictures, longer cold ischemia time was a significant predictor (OR 1.36 per hour, 95% CI: 1.03-1.79). Bile leak (aHR 4.39, 95% CI: 1.04-18.60) and biliary stricture (aHR 6.26, 95% CI: 1.58-24.80) were associated with worse graft survival. Patient survival was not significantly impacted by bile leak and stricture. Early complications more often required surgery, but survival and failure-to-rescue rates were similar regardless of treatment approach. Ultimately, bile leak and anastomotic stricture remain significant threats to graft survival. The identified risk factors offer insights for risk stratification and prevention strategies aimed at improving outcomes in children undergoing LDLT.

Liver transplantation (LT) is an ethically complex procedure that involves allocating a limited, life-saving resource. For over twenty years, the Model for End-Stage Liver Disease (MELD) score and its variations have implemented a sickest-first ethical approach, enhancing waitlist survival rates and adding objectivity to the process. Nonetheless, ongoing disparities based on sex, race, and other structural factors reveal the shortcomings of relying on simplified, static models of disease severity. As LT progresses into an era increasingly shaped by artificial intelligence (AI) and machine learning (ML), these algorithms offer better predictions of waitlist mortality, post-transplant outcomes, and donor-recipient matching. However, higher predictive accuracy does not automatically lead to more ethical distribution. In this Perspective, we explore AI-assisted deceased donor liver allocation through the ethical principles of justice, respect for persons, and humanism. We review emerging AI/ML models proposed for LT, highlighting their potential advantages and risks, including amplification of historical inequities embedded in training data, lack of transparency, erosion of informed consent, and overreliance on algorithmic outputs at the expense of clinical judgment. We contend that AI should serve as decision support rather than decision-maker, and that ethical implementation requires deliberate safeguards. We suggest a framework for responsibly integrating AI into liver allocation focused on fairness monitoring, transparency, and explainability, human oversight, and multi-stakeholder governance. When applied properly, AI can potentially enhance both utility and equity in liver transplantation-but only if its use is guided by clear ethical principles and ongoing evaluation in real-world clinical settings.