Cordova-Gallardo, Jacqueline

Introduction: Although the role of cardiometabolic risk factors (CMRF) has been characterized in steatotic liver disease, their role in the severity of alcohol-associated hepatitis (AH) remains unclear. We aimed to evaluate the impact of CMRF on mortality. Methods: Multinational prospective cohort study (2015–2024) including hospitalized patients with severe AH across 32 centers in 14 countries. Diagnosis of AH was made using the NIAAA criteria. Analyses included adjusted competing-risk models by age, sex, ethnicity, history of cirrhosis, CMRF, corticosteroid use, MELD, and ACLF grade, with liver transplantation as a competing risk. Results: 936 participants were included; mean age 48±11.2 years, and 88.9% were male. At least one CMRF was present in 46.6%; median body mass index (BMI) was 24.2 kg/m 2 [IQR: 22.8–28.2], prevalence of diabetes 17.6%, hypertension 16.5%, and dyslipidemia 5.8%. Median MELD was 24.4 [19.3–31.4], 86.7% had severe AH, and 180-day survival was 72.9%. Survival did not differ by CMRF status (log-rank p =0.453). In adjusted competing-risk models, higher age (sHR 1.02; 95%CI:1.01–1.04), greater alcohol intake (per g/day; sHR 1.001; 95%CI:1.000–1.002), MELD (sHR 1.04; 95%CI:1.01–1.06), and ACLF grade 2–3 (sHR 2.34 and 4.34) predicted mortality. However, no individual CMRF independently increased mortality. A prespecified non-linear BMI analysis showed modestly lower mortality between 25–40 kg/m², with a higher risk above 40 kg/m². Conclusion: Among patients with severe AH, metabolic dysfunction was not associated with increased mortality. Although a higher BMI was associated with slightly lower mortality in AH, this may reflect better nutritional status rather than a true protective effect.

INTRODUCTION: Nosocomial infections (NIs) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have failed to identify high-risk patients. We aimed to develop machine learning (ML) models to predict NI. METHODS: The CLEARED consortium consists of prospectively enrolled cirrhosis inpatients from >120 centers. Using day-of-admission clinical data, 3 ML approaches (random forest [RF], extreme gradient boosting, and neural networks [NNs]) were used to predict NI. Data were split 80:20 for training and testing stratified by the outcome. Models were compared using area under the receiver operating characteristic curve (AUC). RESULTS: In total, 8,263 patients (55.90 ± 13.34 years; 64.1% men) from 127 centers in 37 countries were included. NI developed in 869 (10.5%), a median of 6 (4–11) days of postadmission. Major NIs were respiratory (29.6%) and urinary tract infection (15.7%), and spontaneous bacterial peritonitis (13.5%). NIs occurred more frequently in patients from low/low-middle income countries and those with severe liver disease, alcohol etiology, and admission infections. NIs were associated with inpatient mortality (31.9% vs 8.1%, P < 0.001) and liver transplantation (4.8% vs 1.9%, P < 0.001). Although the RF model (AUC 0.69) showed good calibration (Brier score 0.09), outperforming extreme gradient boosting, neural network, and LR models (AUC 0.66 for all; LR comparison P = 0.043), no model achieved AUC ≥0.80 for clinical utility. At 10% predicted probability threshold, the RF model demonstrated only 75.4% sensitivity, 52.9% specificity, and 15.9% positive predictive value (PPV). DISCUSSION: NIs cannot be accurately predicted from day-of-admission data using ML models, even in a large, prospective, global cirrhosis cohort. Every hospitalized patient with cirrhosis should receive protocolized infection control measures.

Metabolic associated fatty liver disease (MAFLD) affects 20–30% of the worldwide population and is becoming the most common cause of chronic liver disease, cirrhosis and hepatocellular carcinoma (HCC). MAFLD is the hepatic expression of metabolic dysfunction correlated with a variety of metabolic comorbidities including obesity, dyslipidemia, hypertension and type 2 diabetes (T2DM). Obesity, altered gut permeability, chronic inflammation and dysbiosis related to MAFLD might predispose patients with cirrhosis to the development of acute-on-chronic liver failure (ACLF); however, this relationship remains unclear. ACLF is a syndrome with high short-term mortality, presenting with acute hepatic decompensation associated with organ failures in patients with underlying chronic liver disease with or without an identifiable precipitating event. While this syndrome can occur in any patient with cirrhosis, the increasing prevalence of cirrhosis due to MAFLD is of great concern because, in a recent analysis, MAFLD was the fastest rising cause of cirrhosis associated with ACLF among patients listed for LT in the US. In this review, we will discuss the current knowledge on MAFLD and the development of ACLF.