Kamath, Patrick

Purpose of review Hepatorenal syndrome (HRS) is the extreme manifestation of acute renal dysfunction in patients with cirrhosis, resulting from systemic vasodilation and renal vasoconstriction, leading to a reduction in the glomerular filtration rate. Recent findings The diagnostic criteria redefined diagnostic criteria for HRS-AKI (Hepatorenal syndrome -Acute kidney injury) as our understanding of disease progression has improved. This understanding of the HRS disease process guides current management, with the combination of intravascular volume expansion and vasoconstrictor therapy being the cornerstone of treatment. In addition to treatment selection, timing of treatment initiation, duration, dosage, and monitoring during treatment are decisive factors in HRS outcomes. Pathogenesis of HRS-AKI may be different in patients with acute-on-chronic liver failure (ACLF) in comparison to decompensated cirrhosis. Unfortunately, outcomes remain poor with medical therapies alone and a high risk of disease recurrence exists for HRS-AKI with persistence of the cirrhotic milieu. Liver transplantation remains the only definitive treatment of HRS-AKI. Given the critical nature of HRS-AKI, a multidisciplinary approach involving hepatologists, nephrologists, and intensive care physicians is essential for optimal clinical management. Summary Patients with HRS-AKI should be managed ideally in tertiary care centers and referred for liver transplantation promptly when eligible.

SummaryBackground and AimsMachine learning (ML) can identify the hidden patterns without hypothesis in heterogeneous diseases like acute‐on‐chronic live failure (ACLF). We employed ML to describe and predict yet unknown clusters in ACLF.MethodsClinical data of 1568 patients with ACLF from a tertiary care centre (2015–2023) were subjected to distance‐, density‐ and model‐based clustering algorithms. Final model was selected on best cluster separation, viz. Silhouette width and Dunn's index (for distance‐ or density‐based algorithms) and minimum BIC (for model‐based algorithms). Cluster assignments, patient trajectories and survival were analysed through inferential statistics. Supervised ML models were trained in 70% data that predicted clusters in remaining 30% data followed by an temporal validation.ResultsThe cohort was male‐predominant (87%), aged 44.3 years, with alcohol‐associated hepatitis (62.9%) and survival of 50.5%. Due to poor performance of distance‐ and density‐based algorithms and better explainability, the latent class model (LCM) was selected for exploration. LCM revealed four clusters with distinct trajectories, reversibility and survival (independent of MELD, CLIF‐C ACLF and AARC scores). Cluster1 had patients with none/one organ failure and highest reversibility. Cluster2 had females with viral hepatitis and two organ failures. More‐than‐one acute precipitant, severity, infections, organ failures and irreversibility escalated from clusters 1 to 4. Circulatory and renal failures critically influenced cluster assignments. Incorporating clusters to CLIF‐C ACLF, infection and ACLF definition improved the discriminative accuracy of CLIF‐C‐ACLF by 11%. Extreme gradient boost and decision trees could predict clusters with AUCs of 0.989 (0.979–0.995) and 0.875 (0.865–0.890). MELD, CLIF‐C‐OF, haemoglobin, lactate, CLIF‐C‐ACLF and ALT were critical variables for cluster prediction. Clusters with distinct survival were documented in a temporal validation cohort.ConclusionsML for the first time could identify clusters with distinct phenotypes, trajectories and outcomes in ACLF. Stratification into clusters can address heterogeneity, guide prognosis, recruitment in trials, resource allocation and liver transplant discussions in ACLF.

Small-for-size syndrome (SFSS) is a well-recognized complication following liver transplantation (LT), with up to 20% developing this following living donor LT (LDLT). Preventing SFSS involves consideration of factors before the surgical procedure, including donor and recipient selection, and factors during the surgical procedure, including adequate outflow reconstruction, graft portal inflow modulation, and management of portosystemic shunts. International Liver Transplantation Society, International Living Donor Liver Transplantation Group, and Liver Transplant Society of India Consensus Conference was convened in January 2023 to develop recommendations for the prediction and management of SFSS in LDLT. The format of the conference was based on the Grading of Recommendations, Assessment, Development, and Evaluation system. International experts in this field were allocated to 4 working groups (diagnosis, prevention, anesthesia, and critical care considerations, and management of established SFSS). The working groups prepared evidence-based recommendations to answer-specific questions considering the currently available literature. The working group members, independent panel, and conference attendees served as jury to edit and confirm the final recommendations presented at the end of the conference by each working group separately. This report presents the final statements and evidence-based recommendations provided by working group 2 that can be implemented to prevent SFSS in LDLT patients.

Background and Aims We conducted a comprehensive serum transcriptomic analysis to explore the roles of microRNAs (miRNAs) in alcohol‐associated hepatitis (AH) pathogenesis and their prognostic significance. Approach and Results Serum miRNA profiling was performed in 15 controls, 20 heavy drinkers without liver disease, and 65 patients with AH and compared to publicly available hepatic miRNA profiling in AH patients. Among the top 26 miRNAs, expression of miR‐30b‐5p, miR‐20a‐5p, miR‐146a‐5p, and miR‐26b‐5p were significantly reduced in both serum and liver of AH patients. Pathway analysis of the potential targets of these miRNAs uncovered the genes related to DNA synthesis and cell‐cycle progression pathways, including ribonucleotide reductase regulatory subunit M2 (RRM2), cyclin D1 (CCND1), cyclin D2 (CCND2), MYC proto‐oncogene (MYC), and phorbol‐12‐myristate‐13‐acetate‐induced protein 1 (PMAIP1). We found a significant increase in the protein expression of RRM2, CCND1, and CCND2, but not MYC and PMAIP1, in AH patients who underwent liver transplantation; miR‐26b‐5p and miR‐30b‐5p inhibited the 3′‐UTR (untranslated region) luciferase activity of RRM2 and CCND2, and miR‐20a‐5p reduced the 3′‐UTR luciferase activity of CCND1 and CCND2. During a median follow‐up of 346 days, 21% of AH patients died; these patients had higher body mass index (BMI), Model for End‐Stage Liver Disease (MELD), and serum miR‐30b‐5p, miR‐20a‐5p, miR‐146a‐5p, and miR‐26b‐5p than those who survived. Cox regression analysis showed that BMI, MELD score, miR‐20a‐5p, miR‐146a‐5p, and miR‐26b‐5p predicted mortality. Conclusions Patients with AH attempt to deal with hepatocyte injury by down‐regulating specific miRNAs and up‐regulating genes responsible for DNA synthesis and cell‐cycle progression. Higher expression of these miRNAs, suggestive of a diminished capacity in liver regeneration, predicts short‐term mortality in AH patients.