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AbstractBackgroundThe prognosis of acute kidney disease (AKD), defined as a glomerular filtration rate of <60 ml/min/1.73 m2 or a rise in serum creatinine (sCr) of <50% for <3 months, is not clearly known.AimTo study the prevalence, predictive factors and clinical outcomes in hospitalized cirrhotic patients with AKD.MethodsThe North American Consortium for the Study of End‐Stage Liver Disease prospectively enrolled hospitalized decompensated cirrhotic patients. Patients were separated into those with normal renal function (controls or C), AKD or stage 1 AKI as their worst renal dysfunction per International Club of Ascites definition and compared. Parameters assessed included demographics, laboratory data, haemodynamics, renal and patient outcomes.Results1244 patients with cirrhosis and ascites (C: 704 or 57%; AKD: 176 or 14%; stage 1 AKI: 364 or 29%) with similar demographics were enrolled. AKD patients had similar baseline sCr but higher hospital admission in the previous 6 months, and higher peak sCr, compared to controls, with their peak sCr being lower than that in stage 1 AKI patients (all P < .0001). The in‐hospital and 30‐day survival for AKD patients were intermediary between that for controls and stage 1 AKI patients (96% vs 91% vs 86%, P < .0001). The strongest predictors for AKD development while in hospital were the presence of a second infection (OR: 2.44) and diabetes (OR: 1.53).ConclusionsPatients with AKD had intermediate outcomes between stage 1 AKI and controls. AKD patients, especially those with diabetes and a second infection, need careful monitoring and prompt treatment for AKD to prevent negative outcomes.

In patients with cirrhosis and chronic liver disease, acute-on-chronic liver failure is emerging as a major cause of mortality. These guidelines indicate the preferred approach to the management of patients with acute-on-chronic liver failure and represent the official practice recommendations of the American College of Gastroenterology. The scientific evidence for these guidelines was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation process. In instances where the evidence was not appropriate for Grading of Recommendations, Assessment, Development, and Evaluation, but there was consensus of significant clinical merit, key concept statements were developed using expert consensus. These guidelines are meant to be broadly applicable and should be viewed as the preferred, but not only, approach to clinical scenarios.

Background and Aims Acute kidney injury (AKI) has a poor prognosis in cirrhosis. Given the variability of creatinine, the prediction of AKI and dialysis by other markers is needed. The aim of this study is to determine the role of serum and urine metabolomics in the prediction of AKI and dialysis in an inpatient cirrhosis cohort. Approach and Results Inpatients with cirrhosis from 11 North American Consortium of End‐stage Liver Disease centers who provided admission serum/urine when they were AKI and dialysis‐free were included. Analysis of covariance adjusted for demographics, infection, and cirrhosis severity was performed to identify metabolites that differed among patients (1) who developed AKI or not; (2) required dialysis or not; and/pr (3) within AKI subgroups who needed dialysis or not. We performed random forest and AUC analyses to identify specific metabolite(s) associated with outcomes. Logistic regression with clinical variables with/without metabolites was performed. A total of 602 patients gave serum (218 developed AKI, 80 needed dialysis) and 435 gave urine (164 developed AKI, 61 needed dialysis). For AKI prediction, clinical factor–adjusted AUC was 0.91 for serum and 0.88 for urine. Major metabolites such as uremic toxins (2,3‐dihydroxy‐5‐methylthio‐4‐pentenoic acid [DMTPA], N2N2dimethylguanosine, uridine/pseudouridine) and tryptophan/tyrosine metabolites (kynunerate, 8‐methoxykyunerate, quinolinate) were higher in patients who developed AKI. For dialysis prediction, clinical factor–adjusted AUC was 0.93 for serum and 0.91 for urine. Similar metabolites as AKI were altered here. For dialysis prediction in those with AKI, the AUC was 0.81 and 0.79 for serum/urine. Lower branched‐chain amino‐acid (BCAA) metabolites but higher cysteine, tryptophan, glutamate, and DMTPA were seen in patients with AKI needing dialysis. Serum/urine metabolites were additive to clinical variables for all outcomes. Conclusions Specific admission urinary and serum metabolites were significantly additive to clinical variables to predict AKI development and dialysis initiation in inpatients with cirrhosis. These observations can potentially facilitate earlier initiation of renoprotective measures.

Abstract Background Identifying biologic-treated patients with inflammatory bowel diseases (IBDs) at higher risk of serious infections is a priority. We conducted a retrospective cohort study evaluating frailty and risk of serious infections in biologic-treated patients with IBD. Methods Using an administrative claims database, we identified biologic-treated patients with IBD between 2014 and 2018 with follow-up 1 year before and after treatment initiation. Using a validated claims-based hospital frailty risk scoring system, patients were classified as frail and nonfrail. We compared the risk of serious infections (infections requiring hospitalization) between frail and nonfrail patients using Cox proportional hazard analysis adjusting for age, comorbidities, disease characteristics, health care utilization, use of corticosteroids, immunomodulators, and opiates. Results We included 5987 biologic-treated patients with IBD (4881 on TNFα antagonists, 1106 on vedolizumab), of whom 2350 (39.3%) were classified as frail; over 7115 person-years of follow-up was included, and 520 patients developed serious infection. Frailty was not associated with increased risk of serious infection (adjusted hazard ratio [aHR], 1.12; 95% CI, 0.93–1.36), whereas advanced age (older than 60 years), high comorbidity burden, corticosteroid use, opiate use, and prior serious infection were associated with increased risk of serious infection. On stratified analysis, frailty was associated with increased risk of serious infections in vedolizumab-treated patients (aHR, 1.69; 95% CI, 1.03–2.79) but not in TNFα antagonist-treated patients (aHR, 1.03; 95% CI, 0.83–1.27). Conclusions In biologic-treated patients with IBD, frailty assessed using a claims-based frailty index was not independently associated with increased risk of serious infections. Future studies evaluating objective and biological measures of frailty are warranted to risk-stratify older patients with IBD.

INTRODUCTION: Readmission and death in cirrhosis are common, expensive, and difficult to predict. Our aim was to evaluate the abilities of multiple artificial intelligence (AI) techniques to predict clinical outcomes based on variables collected at admission, during hospitalization, and at discharge. METHODS: We used the multicenter North American Consortium for the Study of End-Stage Liver Disease (NACSELD) cohort of cirrhotic inpatients who are followed up through 90-days postdischarge for readmission and death. We used statistical methods to select variables that are significant for readmission and death and trained 3 AI models, including logistic regression (LR), kernel support vector machine (SVM), and random forest classifiers (RFC), to predict readmission and death. We used the area under the receiver operating characteristic curve (AUC) from 10-fold crossvalidation for evaluation to compare sexes. Data were compared with model for end-stage liver disease (MELD) at discharge. RESULTS: We included 2,170 patients (57 ± 11 years, MELD 18 ± 7, 61% men, 79% White, and 8% Hispanic). The 30-day and 90-day readmission rates were 28% and 47%, respectively, and 13% died at 90 days. Prediction for 30-day readmission resulted in 0.60 AUC for all patients with RFC, 0.57 AUC with LR for women-only subpopulation, and 0.61 AUC with LR for men-only subpopulation. For 90-day readmission, the highest AUC was achieved with kernel SVM and RFC (AUC = 0.62). We observed higher predictive value when training models with only women (AUC = 0.68 LR) vs men (AUC = 0.62 kernel SVM). Prediction for death resulted in 0.67 AUC for all patients, 0.72 for women-only subpopulation, and 0.69 for men-only subpopulation, all with LR. MELD-Na model AUC was similar to those from the AI models. DISCUSSION: Despite using multiple AI techniques, it is difficult to predict 30- and 90-day readmissions and death in cirrhosis. AI model accuracies were equivalent to models generated using only MELD-Na scores. Additional biomarkers are needed to improve our predictive capability (See also the visual abstract at http://links.lww.com/AJG/B710).

Loss of muscle mass and function, or sarcopenia, is a common feature of cirrhosis and contributes significantly to morbidity and mortality in this population. Sarcopenia is a main indicator of adverse outcomes in this population, including poor quality of life, hepatic decompensation, mortality in patients with cirrhosis evaluated for liver transplantation (LT), longer hospital and intensive care unit stay, higher incidence of infection following LT, and higher overall health care cost. Although it is clear that muscle mass is an important predictor of LT outcomes, many questions remain, including the best modality for assessing muscle mass, the optimal cut‐off values for sarcopenia, the ideal timing and frequency of muscle mass assessment, and how to best incorporate the concept of sarcopenia into clinical decision making. For these reasons, we assembled a group of experts to form the North American Working Group on Sarcopenia in Liver Transplantation to use evidence from the medical literature to address these outstanding questions regarding sarcopenia in LT. We believe sarcopenia assessment should be considered in all patients with cirrhosis evaluated for liver transplantation. Skeletal muscle index (SMI) assessed by computed tomography constitutes the best‐studied technique for assessing sarcopenia in patients with cirrhosis. Cut‐off values for sarcopenia, defined as SMI < 50 cm 2 /m 2 in male and < 39 cm 2 /m 2 in female patients, constitute the validated definition for sarcopenia in patients with cirrhosis. Conclusion: The management of sarcopenia requires a multipronged approach including nutrition, exercise, and additional pharmacological therapy as deemed necessary. Future studies should evaluate whether recovery of sarcopenia with nutritional management in combination with an exercise program is sustainable as well as how improvement in muscle mass might be associated with improvement in clinical outcomes.

OBJECTIVES: Nosocomial infections (NIs) can be a major cause of morbidity and mortality in cirrhosis. This study aims to define the determinants of NI development and its impact on 30-day outcomes among hospitalized patients with cirrhosis. METHODS: North American Consortium for the Study of End-Stage Liver Disease enrolled patients with cirrhosis who were admitted nonelectively. Admission variables and 30-day outcomes were compared between patients with and without NI. These were also compared based on whether there was an isolated admission infection, NI, or both. Models were created for NI development using admission variables and for 30-day mortality. RESULTS: The study included 2,864 patients; of which, 15% (n = 436) developed NI. When comparing NI vs no NI, 1,866 patients were found to be infection free, whereas 562 had admission infections only, 228 had only NI, and 208 had both infections. At admission, patients with NI were more likely to be infected and have advanced cirrhosis. NIs were associated with higher rates of acute-on-chronic liver failure, death, and transplant regardless of admission infections. Patients with NI had higher respiratory infection, urinary tract infection, Clostridium difficile infection, fungal infections, and infection with vancomycin-resistant enterococci compared with patients without NI. Risk factors for NIs were admission infections, model for end-stage liver disease (MELD) > 20, systemic inflammatory response syndrome criteria, proton pump inhibitor, rifaximin, and lactulose use, but the regression model (sensitivity, 0.67; specificity, 0.63) was not robust. Age, alcohol etiology, admission MELD score, lactulose use, acute-on-chronic liver failure, acute kidney injury, intensive care unit, and NI increased the risk of death, whereas rifaximin decreased the risk of death. DISCUSSION: NIs are prevalent in hospitalized patients with cirrhosis and are associated with poor outcomes. Although higher MELD scores and systemic inflammatory response syndrome are associated with NI, all hospitalized patients with cirrhosis require vigilance and preventive strategies.

Background. We examined the association between sarcopenia and post-transplant mortality in acutely ill inpatients with cirrhosis who underwent urgent liver transplantation. Methods. Included were inpatients at 4 centers who were urgently listed as nonstatus 1 and transplanted from 2005 to 2017 with an abdominal computed tomography scan <90 days before transplantation. Skeletal muscle index (SMI) = total skeletal muscle cross-sectional area at the L3 vertebral level, normalized to height. Cox regression associated SMI with post-transplant mortality. Optimal search identified SMI cutoffs to detect survival. Results. Of 126 inpatients, 63% were male patients, model for end-stage liver disease (MELDNa) was 32, and follow up was 5.1 years. Among men, 23% died. Median SMI was lower in men who died versus survived (45 versus 51 cm2/m2). SMI was associated with post-transplant mortality (hazard ratio [HR] = 0.96 per cm2/m2, 95% CI 0.92-0.99). Patients with SMI ≤ 48 cm2/m2 versus >48 cm2/m2 experienced higher rates of death at 1 year (86% versus 95%) and 3 years (73% versus 95%) (Log-rank P = 0.01). In MELD-adjusted analysis, sarcopenia was strongly associated with post-transplant mortality (HR = 4.39, 95% CI 1.49-12.97). Among women, 35% died. Median SMI was similar in women who died versus survived (45 versus 44 cm2/m2). SMI was not associated with post-transplant mortality (HR = 1.02, 95% CI 0.96-1.09). Optimal search did not identify any SMI cutoff that predicted post-transplant mortality. Conclusions. Among patients who underwent urgent inpatient evaluation and liver transplantation, we identified an SMI cutoff value of 48 cm2/m2 to predict post-transplant mortality in men. Our data support the use of SMI as a tool to capture the impact of muscle depletion on post-transplant mortality in acutely ill men with cirrhosis undergoing urgent liver transplantation.