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Objectives: To characterise the sketetal muscle metabolic phenotype during early critical illness., Methods: Vastus lateralis muscle biopsies and serum samples (days 1 and 7) were obtained from 63 intensive care patients (59% male, 54.7±18.0 years, Acute Physiology and Chronic Health Evaluation II score 23.5±6.5)., Measurements and Main Results: From day 1 to 7, there was a reduction in mitochondrial beta-oxidation enzyme concentrations, mitochondrial biogenesis markers (PGC1α messenger mRNA expression (-27.4CN (95% CI -123.9 to 14.3); n=23; p=0.025) and mitochondrial DNA copy number (-1859CN (IQR -5557-1325); n=35; p=0.032). Intramuscular ATP content was reduced compared tocompared with controls on day 1 (17.7mmol/kg /dry weight (dw) (95% CI 15.3 to 20.0) vs. 21.7 mmol/kg /dw (95% CI 20.4 to 22.9); p<0.001) and decreased over 7 days (-4.8 mmol/kg dw (IQR -8.0-1.2); n=33; p=0.001). In addition, the ratio of phosphorylated:total AMP-K (the bioenergetic sensor) increased (0.52 (IQR -0.09-2.6); n=31; p<0.001). There was an increase in intramuscular phosphocholine (847.2AU (IQR 232.5-1672); n=15; p=0.022), intramuscular tumour necrosis factor receptor 1 (0.66 µg (IQR -0.44-3.33); n=29; p=0.041) and IL-10 (13.6 ng (IQR 3.4-39.0); n=29; p=0.004). Serum adiponectin (10.3 µg (95% CI 6.8 to 13.7); p<0.001) and ghrelin (16.0 ng/mL (IQR -7-100); p=0.028) increased. Network analysis revealed a close and direct relationship between bioenergetic impairment and reduction in muscle mass and between intramuscular inflammation and impaired anabolic signaling. ATP content and muscle mass were unrelated to lipids delivered., Conclusions: Decreased mitochondrial biogenesis and dysregulated lipid oxidation contribute to compromised skeletal muscle bioenergetic status. In addition, intramuscular inflammation was associated with impaired anabolic recovery with lipid delivery observed as bioenergetically inert. Future clinical work will focus on these key areas to ameliorate acute skeletal muscle wasting., Trial Registration Number: NCT01106300., Competing Interests: Competing interests: ZAP has received consultancy fees from Lyric Pharmaceuticals, and attended Specialist Advisory Boards for GlaxoSmithKline and Fresenius Kabi. Other authors have no competing interest to declare., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Purpose: To develop a liver function-related risk prediction tool to identify acute-on-chronic liver failure patients at greatest risk of in-hospital mortality., Methods: The LiFe (liver, injury, failure, evaluation) score, was constructed based on the opinions of 157 intensivists within the European Society for Intensive Care Medicine. Experts were surveyed and instructed to weigh the diagnostic importance of each feature of a proposed prediction model. We performed a retrospective cohort study of 1916 patients with chronic liver disease admitted to a medical or surgical ICU between 1997, and 2011 in three large hospitals in Boston, USA, and London, UK, with arterial lactate, total bilirubin and INR drawn at ICU admission. The derivation cohort consisted of ICU patients from Brigham and Women's Hospital and Massachusetts General Hospital in Boston (n = 945), and the validation cohort comprised patients from Kings College Hospital, London, admitted to the Liver Intensive Therapy Unit (n = 971). A clinical prediction model was derived and validated based on a logistic regression model describing the risk of in-hospital mortality as a function of the predictors (arterial lactate 0-1.9, ≥2.0-3.9, ≥4.0-5.9, ≥6.0 mg/dL; total bilirubin 0-1.9, ≥2.0-3.9, ≥4.0-5.9, ≥6.0 mg/dL; INR 0-1.9, ≥2.0-3.9, ≥4.0-5.9, ≥6.0) at ICU admission. Performance analysis of the LiFe score against SOFA, CLIF-SOFA, APACHE II and SAPS II was completed in the validation cohort of critically ill cirrhotic patients., Results: The derivation cohort (n = 941) was 53% male with a mean age of 65 years and an in-hospital mortality rate of 30%. The validation cohort (n = 971) was 63% male with mean age of 51 years and an in-hospital mortality rate of 52%. The C statistic for the prediction model was 0.74 (95% CI 0.70-0.77) in the derivation cohort and 0.77 (95% CI 0.74-0.80) in the validation cohort. In the validation cohort, in-hospital mortality was 17% in the low-risk group (0 risk score points), 28% in the intermediate-risk group (1-3 points), 47% in the high-risk group (4-8 points), and 77% in the very high-risk group (>8 points). In the validation cohort, the C statistics for SOFA, CLIF-SOFA, APACHE II, and SAPS II were 0.80, 0.81, 0.77, and 0.78, respectively. Further, a significant positive correlation exists between LiFe score and acute-on-chronic liver failure grade, (r = 0.478, P < 0.001)., Conclusions: Our LiFe score calculated from arterial lactate, total bilirubin and INR at ICU admission is a simple, quick and easily understandable score that may increase clinical utility for risk prediction in ICU patients with acute-on-chronic liver failure. The LiFe score can be used in place of physiological based scores for early risk prediction in patients with chronic liver disease but is not intended to replace CLIF-SOFA as a benchmark for prognostication.