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Social determinants of health (SDOH) are known to lead to adverse health outcomes, including high acute care utilization. The mechanisms underlying healthcare disparities among children who have undergone liver transplantation (LT) are poorly understood. To elucidate the relationship between SDOH and healthcare utilization among children (<18 y old at time of LT) who have undergone LT, we performed a retrospective study merging data from the Organ Procurement and Transplantation Network (OPTN) and the Pediatric Hospital Information System (PHIS) database. Children with lower Child Opportunity Index (COI) scores, a composite measure of SDOH, were admitted for 28% more days in the first year and 29% more days over the first two years post-LT, as compared to children with higher COI. We also observed that in the second year post-LT, children with a lower COI were more often admitted with a complication of LT (23%) than those with a higher COI (18%). COI may be a useful composite screening instrument for clinical teams to target resources and limit acute care use post-LT., (Copyright © 2025 American Association for the Study of Liver Diseases.)

Introduction: Falls are a major threat to the well-being of patients with cirrhosis. We are performing a clinical trial to determine whether lactulose, TeleTai-Chi, or their combination will reduce falls in HE and improve health-related quality of life (HRQOL) among patients with cirrhosis., Methods and Analysis: Patients with cirrhosis and portal hypertension without HE will be enrolled in 3 US states and followed participants for 24 weeks. In stage 1 (12 wk), participants will be randomized to receive either lactulose therapy or enhanced usual care. In stage 2 (12 wk), participants will be randomized to either TeleTai-Chi or usual care. The primary outcome is a hierarchical composite: Injurious falls, noninjurious falls, incident HE, and death/transplantation. Secondary outcomes include cognitive function, days-alive and out-of-hospital, and HRQOL. After completion of the interventions, participants will be followed for 48 weeks for health and financial outcomes., Ethics and Dissemination: Our study has a central institutional review board with individual site IRB review. Dissemination includes the publication of study findings and patient-focused educational webinars., (Copyright © 2025 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Association for the Study of Liver Diseases.)

Background and Aims: The new steatotic liver disease (SLD) nomenclature introduced metabolic and alcohol-associated liver disease (MetALD), describing the intersection of metabolic dysfunction-associated steatotic liver disease and alcohol-associated liver disease. Waitlisting and liver transplantation for MetALD are not well defined. We aimed to develop and validate an algorithm for identifying SLD phenotypes and assessing trends in waitlisting and transplant outcomes., Approach and Results: We conducted a retrospective cohort study using the United Network for Organ Sharing registry, supplemented with detailed single-center data. We developed 5 candidate algorithms for SLD classification and calculated their diagnostic performance. Trends in waitlist registrations and transplants were estimated, and competing risk analyses and Cox regression models were conducted to assess waitlist removal and posttransplant outcomes among SLD phenotypes. The best-performing algorithm demonstrated substantial agreement (weighted kappa, 0.62) for SLD phenotypes, with acceptable sensitivity (73%) for MetALD. Between 2002 and 2022, waitlist registrations and transplants for MetALD increased 2.9-fold and 3.3-fold, respectively. Since 2013, there has been a significant increase in the absolute number of waitlist registrations (122 per year; 95% CI, 111-133) and transplants (107 per year; 95% CI, 94-120) for MetALD. Patients with MetALD experienced higher waitlist removal (adjusted subdistribution hazard ratio, 1.10; 95% CI, 1.03-1.17), all-cause mortality (adjusted hazard ratio, 1.13; 95% CI, 1.03-1.23), and graft failure (adjusted hazard ratio, 1.12; 95% CI, 1.03-1.21) than those with alcohol-associated liver disease., Conclusions: We developed and validated an algorithm for identifying SLD phenotypes in UNOS. MetALD is the third leading etiology among those waitlisted and underwent transplantation, exhibiting worse pretransplantation and posttransplantation outcomes compared to alcohol-associated liver disease. Identifying and addressing factors determining poor outcomes is crucial in this patient population., (Copyright © 2024 American Association for the Study of Liver Diseases.)

Background Aims: SBP leads to high rates acute kidney injury (AKI) -hepatorenal syndrome and mortality. Population-based studies on contemporary SBP epidemiology are needed to inform care. In a large, national cohort of patients diagnosed with SBP and confirmed by ascitic fluid criteria, we characterized ascitic fluid characteristics, in-hospital and 12-month mortality, AKI, and recurrent SBP., Approach Results: We investigated how individual and bundled quality measures for SBP associated with outcomes after multi-level adjustment for health-system, patient clinical factors and quality measures. Individual and bundled quality metrics were inpatient antibiotics within 48 hours, intravenous albumin, repeat paracentesis within 48 hours, recognition of SBP, and prophylactic antibiotics upon discharge. Among 4,330 patients with newly diagnosed SBP, in-hospital mortality was 15.5% and 12-month mortality was 56.6%. The incidence of Stage 1 AKI was 26.6%, 15.7% for Stage 2, and 22.8% for Stage 3. The cumulative incidence of recurrent SBP was 10.3%. Guideline-recommended albumin was the only individual metric associated with reduced in-hospital mortality (HR 0.73, 95%CI 0.59 - 0.91). Receipt of a higher number of metrics from the SBP bundle was associated with progressively lower 12-month post-discharge mortality: patients who received 3, 4, and 5 SBP bundle components had 20%, 38%, and 56% lower hazard of mortality, respectively, relative to those receiving 2 or fewer (all p <0.001). The SBP bundle was associated with lower incidence of Stage 3 versus Stage 0-2 AKI (OR 0.66, 95%CI 0.51-0.86)., Conclusion: Prospective implementation of evidence-based SBP bundles may improve care outcomes and mortality in SBP., (Copyright © 2025 American Association for the Study of Liver Diseases.)

Introduction: Although metabolic dysfunction-associated steatotic liver disease (MASLD) and MASLD with increased alcohol intake (MetALD) are identified as clinical entities; tools to identify patients from electronic health records (EHRs) to perform large outcome studies are lacking., Methods: In this retrospective study of participants from the Veterans Analysis of Liver Disease cohort assembled from 1/1/2013 to 12/31/2022, a rule-based natural language processing (NLP) algorithm searched EHRs for imaging evidence of hepatic steatosis. This was combined with identification of cardiometabolic risk factors and harmful alcohol use. Algorithm-derived diagnoses of MASLD, MetALD, alcohol-associated steatotic liver disease (ALD), and no steatotic liver disease (SLD) were validated using a blinded review of randomly selected charts., Results: Among 817,657 eligible veterans, SLD was present in over half (n = 438,209, 53.5%), including MASLD in 299,259 (36.5%), 99,163 with MetALD (12.1%), and 38,552 (4.7%) with ALD. The NLP algorithm had a high correlation with steatosis on chart review, with a κ of 0.86 (95% CI 0.82-0.90), sensitivity of 0.96, and specificity of 0.90. Classification of MASLD, MetALD, ALD, and no SLD by the algorithm also showed high correlation with chart review, with a κ of 0.87 (95% CI 0.82-0.91). This algorithm identified 299,259 (36.5%) of the study cohort with MASLD, compared with 23,218 patients (2.8%) identified using International Classification of Diseases-9/10 codes., Discussion: An algorithm combining rule-based NLP with cardiometabolic risk factors and alcohol use from EHRs accurately identifies and classifies SLD and can be applied in large epidemiologic studies of SLD in the Veterans Health Administration., (Copyright © 2025 by The American College of Gastroenterology.)

Nonalcoholic fatty liver disease (NAFLD) is the most common global cause of chronic liver disease and remains under-recognized within healthcare systems. Therapeutic interventions are rapidly advancing for its inflammatory phenotype, nonalcoholic steatohepatitis (NASH) at all stages of disease. Diagnosis codes alone fail to recognize and stratify at-risk patients accurately. Our work aims to rapidly identify NAFLD patients within large electronic health record (EHR) databases for automated stratification and targeted intervention based on clinically relevant phenotypes. We present a rule-based phenotyping algorithm for efficient identification of NAFLD patients developed using EHRs from 6.4 million patients at Columbia University Irving Medical Center (CUIMC) and validated at two independent healthcare centers. The algorithm uses the Observational Medical Outcomes Partnership (OMOP) Common Data Model and queries structured and unstructured data elements, including diagnosis codes, laboratory measurements, and radiology and pathology modalities. Our approach identified 16,006 CUIMC NAFLD patients, 10,753 (67%) previously unidentifiable by NAFLD diagnosis codes. Fibrosis scoring on patients without histology identified 943 subjects with scores indicative of advanced fibrosis (FIB-4, APRI, NAFLD-FS). The algorithm was validated at two independent healthcare systems, University of Pennsylvania Health System (UPHS) and Vanderbilt Medical Center (VUMC), where 20,779 and 19,575 NAFLD patients were identified, respectively. Clinical chart review identified a high positive predictive value (PPV) across all healthcare systems: 91% at CUIMC, 75% at UPHS, and 85% at VUMC, and a sensitivity of 79.6%. Our rule-based algorithm provides an accurate, automated approach for rapidly identifying, stratifying, and sub-phenotyping NAFLD patients within a large EHR system., (© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)