Two‐dimensional shear wave elastography (2D‐SWE) has proven to be efficient for the evaluation of liver fibrosis in small to moderate‐sized clinical trials. We aimed at running a larger‐scale meta‐analysis of individual data. Centers which have worked with Aixplorer ultrasound equipment were contacted to share their data. Retrospective statistical analysis used direct and paired receiver operating characteristic and area under the receiver operating characteristic curve (AUROC) analyses, accounting for random effects. Data on both 2D‐SWE and liver biopsy were available for 1,134 patients from 13 sites, as well as on successful transient elastography in 665 patients. Most patients had chronic hepatitis C (n = 379), hepatitis B (n = 400), or nonalcoholic fatty liver disease (n = 156). AUROCs of 2D‐SWE in patients with hepatitis C, hepatitis B, and nonalcoholic fatty liver disease were 86.3%, 90.6%, and 85.5% for diagnosing significant fibrosis and 92.9%, 95.5%, and 91.7% for diagnosing cirrhosis, respectively. The AUROC of 2D‐SWE was 0.022‐0.084 (95% confidence interval) larger than the AUROC of transient elastography for diagnosing significant fibrosis (P = 0.001) and 0.003‐0.034 for diagnosing cirrhosis (P = 0.022) in all patients. This difference was strongest in hepatitis B patients.Conclusion:2D‐SWE has good to excellent performance for the noninvasive staging of liver fibrosis in patients with hepatitis B; further prospective studies are needed for head‐to‐head comparison between 2D‐SWE and other imaging modalities to establish disease‐specific appropriate cutoff points for assessment of fibrosis stage. (Hepatology2018;67:260‐272).

Objectives: Recent studies suggest that cardiac dysfunction precedes development of the hepatorenal syndrome. In this follow-up study, we aimed to investigate the relation between cardiac and renal function in patients with cirrhosis and ascites and the impact of cardiac systolic function on survival. Patients and design: Twenty-four patients with cirrhosis and ascites were included. Cardiac function was investigated by gated myocardial perfusion imaging (MPI) for assessment of cardiac index (CI) and cardiac volumes. The renal function was assessed by determination of glomerular filtration rate (GFR) and renal blood flow (RBF) and the patients were followed up for 12 months. Results: In patients with a CI below 1.5 l/min/m² on MPI, GFR was lower (39 (SD 24) vs 63 (SD 23) ml/min, p = 0.03), RBF was lower (352 (SD 232) vs 561 (SD 229) ml/min, p = 0.06), and serum creatinine was higher (130 (SD 46) vs 78 (SD 29) μmol/l, p<0.01). The number of patients who developed hepatorenal syndrome type 1 within 3 months was higher in the group with low CI than in the high CI group (43% vs 5%, p = 0.04). Patients with the lowest CI (N = 8) had significantly poorer survival at 3, 9, and 12 months compared to those with a higher CI (N = 16), p<0.05. In contrast, the Model for End-stage Liver Disease (MELD) score failed to predict mortality in these patients. Conclusions: The development of renal failure and poor outcome in patients with advanced cirrhosis and ascites seem to be related to a cardiac systolic dysfunction. Other parameters may be more important than MELD score to predict prognosis.

Alcohol-related liver disease (ALD) is a major cause of liver-related death worldwide, yet understanding of the three key pathological features of the disease—fibrosis, inflammation and steatosis—remains incomplete. Here, we present a paired liver–plasma proteomics approach to infer molecular pathophysiology and to explore the diagnostic and prognostic capability of plasma proteomics in 596 individuals (137 controls and 459 individuals with ALD), 360 of whom had biopsy-based histological assessment. We analyzed all plasma samples and 79 liver biopsies using a mass spectrometry (MS)-based proteomics workflow with short gradient times and an enhanced, data-independent acquisition scheme in only 3 weeks of measurement time. In plasma and liver biopsy tissues, metabolic functions were downregulated whereas fibrosis-associated signaling and immune responses were upregulated. Machine learning models identified proteomics biomarker panels that detected significant fibrosis (receiver operating characteristic–area under the curve (ROC–AUC), 0.92, accuracy, 0.82) and mild inflammation (ROC–AUC, 0.87, accuracy, 0.79) more accurately than existing clinical assays (DeLong’s test, P < 0.05). These biomarker panels were found to be accurate in prediction of future liver-related events and all-cause mortality, with a Harrell’s C-index of 0.90 and 0.79, respectively. An independent validation cohort reproduced the diagnostic model performance, laying the foundation for routine MS-based liver disease testing.