Wu, Tiffany

Acute-on-chronic liver failure (ACLF) has been associated with excellent post-liver transplant (LT) outcomes at 1 year; however, the impact of alcohol as ACLF precipitant, specifically alcohol-associated hepatitis (AH), and as etiology of chronic liver disease remains uncertain. This study aimed to assess the effect of alcohol as ACLF precipitant and chronic liver disease etiology (alcohol-associated liver disease vs. non–alcohol-associated liver disease) on posttransplant outcomes. We performed a retrospective study using the Multi-Organ Dysfunction and Evaluation for LT Consortium database and included 640 patients with ACLF who underwent LT across 15 transplant centers in North America. The primary outcome was 1-year posttransplant survival. We used logistic regression and Cox proportional hazards to compare posttransplant survival, mortality risk, and health care utilization, adjusting for age, ACLF grade, comorbid diabetes mellitus, chronic kidney disease, and HCC. The median follow-up from LT was 2.8 years (P25–P75, 2.2–5.5 y) for patients with AH-ACLF (n=42) and 3.1 years (P25–P75, 1.6–4.9 y) for patients without AH (n=598). No significant difference was observed in 1-year survival after LT in patients with AH-ACLF versus those without AH ( p =0.36). Patients with AH had significantly higher health care utilization evidenced by greater length of stay (28.5 vs. 19.0 d, p =0.004; adjusted linear estimate 16.89, 95% CI: 7.66–26.11, p <0.001), higher rates of rehabilitation placement (71.4% vs. 41.8%, p =0.002; adjusted odds ratio: 4.13, 95% CI: 2.04–8.89, p <0.001), and non-ambulatory status (39.0% vs. 21.0%, p =0.005; adjusted odds ratio: 4.54, 95% CI: 1.90–10.79, p <0.001). Compared with other etiologies, alcohol-associated liver disease was not associated with differences in 1-year mortality, mortality risk over time, or health care utilization, after excluding patients with AH as ACLF precipitant. While there were no differences in 1-year survival, AH-ACLF was associated with higher health care resource utilization compared with other ACLF precipitants. LT centers should ensure adequate resources are allocated for the management of these patients.

The rapid evolution of artificial intelligence and the widespread embrace of digital technologies have ushered in a new era of clinical research and practice in hepatology. Although its potential is far from realization, these significant strides have generated new opportunities to address existing gaps in the delivery of care for patients with liver disease. In this review, we discuss how artificial intelligence and opportunities for multimodal data integration can improve the diagnosis, prognosis, and management of alcohol-associated liver disease. An emphasis is made on how these approaches will also benefit the detection and management of alcohol use disorder. Our discussion encompasses challenges and limitations, concluding with a glimpse into the promising future of these advancements.

Background: Sensors within smartphones, such as accelerometer and location, can describe longitudinal markers of behavior as represented through devices in a method called digital phenotyping. This study aimed to assess the feasibility of digital phenotyping for patients with alcohol-associated liver disease and alcohol use disorder, determine correlations between smartphone data and alcohol craving, and establish power assessment for future studies to prognosticate clinical outcomes. Methods: A total of 24 individuals with alcohol-associated liver disease and alcohol use disorder were instructed to download the AWARE application to collect continuous sensor data and complete daily ecological momentary assessments on alcohol craving and mood for up to 30 days. Data from sensor streams were processed into features like accelerometer magnitude, number of calls, and location entropy, which were used for statistical analysis. We used repeated measures correlation for longitudinal data to evaluate associations between sensors and ecological momentary assessments and standard Pearson correlation to evaluate within-individual relationships between sensors and craving. Results: Alcohol craving significantly correlated with mood obtained from ecological momentary assessments. Across all sensors, features associated with craving were also significantly correlated with all moods (eg, loneliness and stress) except boredom. Individual-level analysis revealed significant relationships between craving and features of location entropy and average accelerometer magnitude. Conclusions: Smartphone sensors may serve as markers for alcohol craving and mood in alcohol-associated liver disease and alcohol use disorder. Findings suggest that location-based and accelerometer-based features may be associated with alcohol craving. However, data missingness and low participant retention remain challenges. Future studies are needed for further digital phenotyping of relapse risk and progression of liver disease.

SummaryBackgroundAlpha‐1 antitrypsin deficiency (AATD) is caused by mutations in SERPINA1, which encodes alpha‐1 antitrypsin, a protease inhibitor (Pi). Individuals with AATD and the homozygous Pi*ZZ genotype have variable risk of progressive liver disease but the influence of comorbid lung disease is poorly understood.AimsTo characterise patients with AATD Pi*ZZ and liver disease (AATD‐LD‐Pi*ZZ) with or without lung disease and describe liver disease‐related clinical events longitudinally.MethodsThis was an observational cohort study of patients in the Mayo Clinic Healthcare System (January 2000–September 2021). Patients were identified using diagnosis codes and natural language processing. Fibrosis stage (F0–F4) was assessed using a hierarchical approach at baseline (90 days before or after the index date) and follow‐up. Clinical events associated with liver disease progression were assessed.ResultsAATD‐LD‐Pi*ZZ patients with lung disease had a longer median time from AATD diagnosis to liver disease diagnosis versus those without lung disease (2.2 vs. 0.2 years, respectively). Compared to those without lung disease, patients with lung disease had a longer time to liver disease‐related clinical events (8.5 years and not reached, respectively). AATD‐LD‐Pi*ZZ patients without lung disease were more likely to undergo liver transplantation compared with those with lung disease.ConclusionIn patients with AATD and lung disease, there is a delay in the diagnosis of comorbid liver disease. Our findings suggest that liver disease may progress more rapidly in patients without comorbid lung disease.

Abstract The rise in innovative digital health technologies has led a paradigm shift in health care toward personalized, patient‐centric medicine that is reaching beyond traditional brick‐and‐mortar facilities into patients’ homes and everyday lives. Digital solutions can monitor and detect early changes in physiological data, predict disease progression and health‐related outcomes based on individual risk factors, and manage disease intervention with a range of accessible telemedicine and mobile health options. In this review, we discuss the unique transformation underway in the care of patients with liver disease, specifically examining the digital transformation of diagnostics, prediction and clinical decision‐making, and management. Additionally, we discuss the general considerations needed to confirm validity and oversight of new technologies, usability and acceptability of digital solutions, and equity and inclusivity of vulnerable populations.