Kamath, Patrick S.

Background and Aims: Alcohol-associated hepatitis (AH) poses significant short-term mortality. Existing prognostic models lack precision for 90-day mortality. Utilizing artificial intelligence in a global cohort, we sought to derive and validate an enhanced prognostic model. Approach and Results: The Global AlcHep initiative, a retrospective study across 23 centers in 12 countries, enrolled patients with AH per National Institute for Alcohol Abuse and Alcoholism criteria. Centers were partitioned into derivation (11 centers, 860 patients) and validation cohorts (12 centers, 859 patients). Focusing on 30 and 90-day postadmission mortality, 3 artificial intelligence algorithms (Random Forest, Gradient Boosting Machines, and eXtreme Gradient Boosting) informed an ensemble model, subsequently refined through Bayesian updating, integrating the derivation cohort’s average 90-day mortality with each center’s approximate mortality rate to produce posttest probabilities. The ALCoholic Hepatitis Artificial INtelligence Ensemble score integrated age, gender, cirrhosis, and 9 laboratory values, with center-specific mortality rates. Mortality was 18.7% (30 d) and 27.9% (90 d) in the derivation cohort versus 21.7% and 32.5% in the validation cohort. Validation cohort 30 and 90-day AUCs were 0.811 (0.779–0.844) and 0.799 (0.769–0.830), significantly surpassing legacy models like Maddrey’s Discriminant Function, Model for End-Stage Liver Disease variations, age-serum bilirubin-international normalized ratio-serum Creatinine score, Glasgow, and modified Glasgow Scores (p < 0.001). ALCoholic Hepatitis Artificial INtelligence Ensemble score also showcased superior calibration against MELD and its variants. Steroid use improved 30-day survival for those with an ALCoholic Hepatitis Artificial INtelligence Ensemble score > 0.20 in both derivation and validation cohorts. Conclusions: Harnessing artificial intelligence within a global consortium, we pioneered a scoring system excelling over traditional models for 30 and 90-day AH mortality predictions. Beneficial for clinical trials, steroid therapy, and transplant indications, it’s accessible at: https://aihepatology.shinyapps.io/ALCHAIN/.

ABSTRACT Objective: The aim of the study is to develop a predictive model for in-hospital mortality in critically ill patients with cirrhosis and sepsis, using clinical and laboratory data. Design: This is a retrospective cohort study. Setting: Medical and mixed intensive care units (ICUs) of a tertiary medical center. Patients: Cirrhotic adults were admitted with sepsis to the ICUs from January of 2007 to May of 2017. Interventions: None. Measurements and Main Results: Of 2,595 ICU admissions of patients with cirrhosis, 277 with first ICU admission for sepsis were included in the analysis, and 37% died in the hospital. Patients who stayed in the ICU for at least 6 h (n = 275) were considered for the multivariate model. Ten-fold cross-validation was used to estimate best parameter values and model performance, and the final model was chosen as the model maximizing area under the receiver-operating characteristic curve. Variables in order of impact were Acute Physiology and Chronic Health Evaluation (APACHE) III score, initial serum lactate, conjugated bilirubin, serum creatinine, model for end-stage liver disease score, age, body mass index, and serum hemoglobin. The final best model from cross-validation presented an area under the receiver operator characteristic curve (AUC) of 0.75, using a cut-point of 50% estimated probability, sensitivity and specificity were 0.46 and 0.90, respectively, with positive predictive value of 0.72 and negative predictive value of 0.74. These results were similar to the APACHE III only model (AUC = 0.74, sensitivity = 0.43, specificity = 0.89, positive predictive value = 0.69, negative predictive value = 0.73). Conclusion: The combination of initial serum lactate level, conjugated bilirubin, initial serum creatinine, model for end-stage liver disease score, age, body mass index, and serum hemoglobin did not yield meaningful improvement in the AUC and did not provide advantage over the APACHE III score for the prediction of in-hospital mortality in critically ill patients with cirrhosis and sepsis.

INTRODUCTION: Management of hepatic encephalopathy relies on self-titration of lactulose. In this feasibility trial, we assess an artificial intelligence–enabled tool to guide lactulose use through a smartphone application. METHODS: Subjects with hepatic encephalopathy on lactulose captured bowel movement pictures during lead-in and intervention phases. During the intervention phase, daily feedback on lactulose titration was delivered through the application. Goals were determined according to number of bowel movement and Bristol Stool Scale reports. RESULTS: Subjects completed the study with more than 80% satisfaction. In the lead-in phase, less compliant subjects achieved Bristol Stool Scale goal on 62/111 (56%) of days compared with 107/136 (79%) in the intervention phase ( P = 0.041), while the most compliant subjects showed no difference. Severe/recurrent hepatic encephalopathy group achieved Bristol Stool Scale goal on 80/104 (77%) days in the lead-in phase and 90/110 (82%) days in the intervention phase ( P = NS), compared with 89/143 (62%) days and 86/127 (68%) days in the stable group. DISCUSSION: Dieta application is a promising tool for objective Bowel Movement/Bristol Stool Scale tracking for hepatic encephalopathy and may potentially be used to assist with lactulose titration.

Background: The Sepsis-3 guidelines have incorporated serum lactate levels of >2 mmol/L in septic shock definition to account for higher observed mortality. Further evidence is needed to support this threshold in cirrhosis, as well as target mean arterial pressure (MAP) during resuscitation. Methods: This observational cohort study investigated the association between initial serum lactate and resuscitation MAP levels on in-hospital mortality in patients with and without cirrhosis. Patients admitted to the intensive care unit for the treatment of septic shock between 2006 and 2021 in a quaternary academic center were included. Patients with cirrhosis documented on imaging and International Classification of Disease codes (n=595) were compared to patients without cirrhosis (n=575). The association of intensive care unit admission lactate levels and median 2-hour MAP with in-hospital mortality and the need for continuous renal replacement therapy was assessed. The association between median 24-hour MAP and in-hospital mortality was analyzed post hoc. Results: Within the cirrhosis group, admission lactate levels of 2–4 and >4 mmol/L were associated with increased in-hospital mortality compared to lactate <2 mmol/L [adjusted odds ratio (aOR): 1.69, CI: 1.03–2.81, aOR: 4.02, CI: 2.53–6.52]. Median 24-hour MAP 60–65 and <60 mm Hg were also associated with increased in-hospital mortality compared with MAP >65 mm Hg (aOR: 2.84, CI: 1.64–4.92 and aOR: 7.34, CI: 3.17–18.76). In the noncirrhosis group, associations with in-hospital mortality were weaker for lactate 2–4 and >4 mmol/L (aOR: 1.32, CI: 0.77–2.27 and aOR: 2.25, CI: 1.40–3.67) and median 24-hour MAP 60–65 and <60 mm Hg (aOR: 1.70, CI: 0.65–4.14 and aOR: 4.41, CI: 0.79–29.38). Conclusions: These findings support utilizing lactate >2 mmol/L in the definition of septic shock, as well as a target MAP of >65 mm Hg during resuscitation in patients with cirrhosis.

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.

INTRODUCTION: Hospitalized patients with cirrhosis can develop respiratory failure (RF), which is associated with a poor prognosis, but predisposing factors are unclear. METHODS: We prospectively enrolled a multicenter North American cirrhosis inpatient cohort and collected admission and in-hospital data (grading per European Association for the Study of Liver-Chronic Liver Failure scoring system, acute kidney injury [AKI], infections [admission/nosocomial], and albumin use) in an era when terlipressin was not available in North America. Multivariable regression to predict RF was performed using only admission day and in-hospital events occurring before RF. RESULTS: A total of 511 patients from 14 sites (median age 57 years, admission model for end-stage liver disease [MELD]-Na 23) were enrolled: RF developed in 15%; AKI occurred in 24%; and 11% developed nosocomial infections (NI). At admission, patients who developed RF had higher MELD-Na, gastrointestinal (GI) bleeding/AKI-related admission, and prior infections/ascites. During hospitalization, RF developers had higher NI (especially respiratory), albumin use, and other organ failures. RF was higher in patients receiving albumin (83% vs 59%, P < 0.0001) with increasing doses (269.5 ± 210.5 vs 208.6 ± 186.1 g, P = 0.01) regardless of indication. Admission for AKI, GI bleeding, and high MELD-Na predicted RF. Using all variables, NI (odds ratio [OR] = 4.02, P = 0.0004), GI bleeding (OR = 3.1, P = 0.002), albumin use (OR = 2.93, P = 0.01), AKI (OR = 3.26, P = 0.008), and circulatory failure (OR = 3.73, P = 0.002) were associated with RF risk. DISCUSSION: In a multicenter inpatient cirrhosis study of patients not exposed to terlipressin, 15% of patients developed RF. RF risk was highest in those admitted with AKI, those who had GI bleeding on admission, and those who developed NI and other organ failures or received albumin during their hospital course. Careful volume monitoring and preventing nosocomial respiratory infections and renal or circulatory failures could reduce this risk.

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.

Abstract The Fontan procedure is the definitive treatment for patients with single-ventricle physiology. Surgical advances have led to a growing number of patients surviving into adulthood. Fontan-associated liver disease (FALD) encompasses a spectrum of pathologic liver changes that occur secondary to altered physiology including congestion, fibrosis, and the development of liver masses. Assessment of FALD is difficult and relies on using imaging alongside of clinical, laboratory, and pathology information. Ultrasound, computed tomography, and magnetic resonance imaging are capable of demonstrating physiologic and hepatic parenchymal abnormalities commonly seen in FALD. Several novel imaging techniques including magnetic resonance elastography are under study for use as biomarkers for FALD progression. Imaging has a central role in detection and characterization of liver masses as benign or malignant. Benign FNH-like masses are commonly encountered; however, these can display atypical features and be mistaken for hepatocellular carcinoma (HCC). Fontan patients are at elevated risk for HCC, which is a feared complication and has a poor prognosis in this population. While imaging screening for HCC is widely advocated, no consensus has been reached regarding an optimal surveillance regimen.