Statin prescriptions and progression of advanced fibrosis risk in primary care patients with MASLD.

OBJECTIVE: We aimed to determine the association of statins with progression to a high risk for advanced fibrosis in primary care patients with metabolic dysfunction-associated steatotic liver disease (MASLD). DESIGN: This retrospective cohort study of electronic health record data included patients with MASLD and an initial low or indeterminate risk for advanced fibrosis, determined by Fibrosis-4 Index (FIB-4) score (<2.67). Patients were followed from the index FIB-4 until the primary outcome of a high-risk FIB-4 (≥2.67) or the end of the study period. Prescription for a statin during follow-up was the primary exposure. We developed Cox regression models for the time to a high-risk FIB-4 score with statin therapy as the primary covariate and adjusting for baseline fibrosis risk, demographic and comorbidity variables. RESULTS: The cohort of 1238 patients with MASLD was followed for a mean of 3.3 years, with 47% of patients receiving a prescription for a statin, and 18% of patients progressing to a high-risk FIB-4. In the adjusted Cox model with statin prescription as the primary exposure, statins were associated with a lower risk (HR 0.60; 95% CI 0.45 to 0.80) of progressing to a FIB-4≥2.67. In the adjusted Cox models with statin prescription intensity as the exposure, moderate (HR 0.60; 95% CI 0.42 to 0.84) and high intensity (HR 0.61; 95% CI 0.42 to 0.88) statins were associated with a lower risk of progressing to a high-risk FIB-4. CONCLUSION: Statin prescriptions, and specifically moderate and high intensity statin prescriptions, demonstrate a protective association with fibrosis risk progression in primary care patients with MASLD.

H2FPEF Scores Are Increased in Patients with NASH Cirrhosis and Are Associated with Post-liver Transplant Heart Failure.

INTRODUCTION: Patients with cirrhosis are at risk for cardiac complications such as heart failure, particularly heart failure with preserved ejection fraction (HFpEF) due to left ventricular diastolic dysfunction (LVDD). The H2FPEF score is a predictive model used to identify patients with HFpEF. Our primary aim was to assess the H2FPEF score in patients with cirrhosis and determine its potential to identify patients at risk for heart failure after liver transplant. METHODS: This was a cohort study of patients undergoing liver transplant for cirrhosis from January 2010 and October 2018 who had a pre-transplant transthoracic echocardiogram. RESULTS: 166 cirrhosis subjects were included in the study. The majority were men (65%) and Caucasian (85%); NASH was the most common cause of cirrhosis (41%) followed by alcohol (34%). The median H2FPEF score was 2.0 (1.0-4.0). Patients with NASH cirrhosis had higher H2FPEF scores (3.22, 2.79-3.64) than those with alcohol induced cirrhosis (1.89, 1.5-2.29, p < 0.001) and other causes of cirrhosis (1.73, 1.28-2.18, p < 0.001). All subjects with a H2FPEF score > 6 had NASH cirrhosis. There was no association between the H2FPEF scores and measures of severity of liver disease (bilirubin, INR, or MELD score). Patients with heart failure after liver transplant had higher H2FPEF scores than those without heart failure (4.0, 3.1-4.9 vs. 2.3, 2.1-2.6, respectively; p = 0.015), but the score did not predict post-transplant mortality. CONCLUSION: H2FPEF scores are higher in cirrhosis patients with NASH and appear to be associated with post-transplant heart failure, but not death.

FIB-4 as a Time-varying Covariate and Its Association With Severe Liver Disease in Primary Care: A Time-dependent Cox Regression Analysis.

BACKGROUND AND GOALS: The Fibrosis-4 Index (FIB-4) has demonstrated a strong association with severe liver disease (SLD) outcomes in primary care, but previous studies have only evaluated this relationship using 1 or 2 FIB-4 scores. In this study, we determined the association of FIB-4 as a time-varying covariate with SLD risk using time-dependent Cox regression models. STUDY: This retrospective cohort study included primary care patients with at least 2 FIB-4 scores between 2012 and 2021. The outcome was the occurrence of an SLD event, a composite of cirrhosis, complications of cirrhosis, hepatocellular carcinoma, and liver transplantation. The primary predictor was FIB-4 advanced fibrosis risk, categorized as low-(<1.3), indeterminate-(1.3≤FIB to 4<2.67), and high-risk (≥2.67). FIB-4 scores were calculated and the index, last, and maximum FIB-4s were identified. Time-dependent Cox regression models were used to estimate hazard ratios (HR) and their corresponding 95% CI with adjustment for potentially confounding covariates. RESULTS: In the cohort, 20,828 patients had a median of 5 (IQR: 3 to 11) FIB-4 scores each and 3% (n=667) suffered an SLD outcome during follow-up. Maximum FIB-4 scores were indeterminate-risk for 34% (7149) and high-risk for 24% (4971) of the sample, and 32% (6692) of patients had an increase in fibrosis risk category compared with their index value. The adjusted Cox regression model demonstrated an association between indeterminate- (hazard ratio 3.21; 95% CI 2.33-4.42) and high-risk (hazard ratio 20.36; 95% CI 15.03-27.57) FIB-4 scores with SLD outcomes. CONCLUSIONS: Multiple FIB-4 values per patient are accessible in primary care, FIB-4 fibrosis risk assessments change over time, and high-risk FIB-4 scores (≥2.67) are strongly associated with severe liver disease outcomes when accounting for FIB-4 as a time-varying variable.

Chronic liver disease is not associated with statin prescription in a primary care cohort.

Statins have historically been underutilized in patients with chronic liver disease (CLD). We sought to investigate the association between CLD and statin prescription in a primary care setting. Our retrospective cohort study identified primary care patients with a low-density lipoprotein value and more than one office visit from 2012 through 2018. Indication for statin therapy was determined using the Third Adult Treatment Panel criteria prior to November 2016 and the American College of Cardiology and American Heart Association guidelines thereafter. Indication for statin prescription and statin therapy by year was determined. Patients with CLD were identified using ICD-9/10 diagnosis codes. In total, 2119 individuals with an indication for statin therapy were identified. Of these individuals, 354 (16.7%) had CLD. Alcoholic and nonalcoholic fatty liver disease comprised 44.9% and 28.5% of the CLD population, respectively; 27.7% had cirrhosis. There was no difference in the prevalence of statin prescriptions when comparing patients with a CLD diagnosis to those without one (57.9 vs 59.9%, p = 0.48). A diagnosis of CLD was also not significantly associated with statin prescription when adjusting for other covariates (odds ratio (OR) 1.02; 95% confidence interval (CI) 0.78-1.33). An alanine aminotransferase level greater than 45 U/L significantly reduced the odds of a statin prescription (OR 0.62; 95% CI 0.44-0.87). Overall, the presence of a CLD diagnosis was not associated with attenuated statin utilization compared to those without a CLD diagnosis. Nevertheless, adherence to guideline indicated statin therapy remains suboptimal and efforts to increase statin utilization in this high-risk population remain prudent.

Real-World Primary Care Data Comparing ALT and FIB-4 in Predicting Future Severe Liver Disease Outcomes.

BACKGROUND: Alanine aminotransferase (ALT) has long provided a cue for chronic liver disease (CLD) diagnostic evaluation, but the Fibrosis-4 Index (FIB-4), a serologic score used for predicting advanced fibrosis risk in CLD, may provide an alternative signal. OBJECTIVE: Compare the predictive performance of FIB-4 with ALT for severe liver disease (SLD) events while adjusting for potential confounders. DESIGN: Retrospective cohort study of primary care electronic health record data from 2012 to 2021. PATIENTS: Adult primary care patients with at least two sets of ALT and other lab values necessary for calculating two unique FIB-4 scores, excluding those patients with an SLD prior to their index FIB-4 value. MAIN MEASURES: The occurrence of an SLD event, a composite of cirrhosis, hepatocellular carcinoma, and liver transplantation, was the outcome of interest. Categories of ALT elevation and FIB-4 advanced fibrosis risk were the primary predictor variables. Multivariable logistic regression models were developed to evaluate the association of FIB-4 and ALT with SLD, and the areas under the curve (AUC) for each model were compared. KEY RESULTS: The cohort of 20,828 patients included 14% with an abnormal index ALT (≥40 IU/L) and 8% with a high-risk index FIB-4 (≥2.67). During the study period, 667 (3%) patients suffered an SLD event. Adjusted multivariable logistic regression models demonstrated an association between high-risk FIB-4 (OR 19.34; 95%CI 15.50-24.13), persistently high-risk FIB-4 (OR 23.85; 95%CI 18.24-31.17), abnormal ALT (OR 7.07; 95%CI 5.81-8.59), and persistently abnormal ALT (OR 7.58; 95%CI 5.97-9.62) with SLD outcomes. The AUC of the index FIB-4 (0.847, p < 0.001) and combined FIB-4 (0.849, p < 0.001) adjusted models exceeded the index ALT adjusted model (0.815). CONCLUSIONS: High-risk FIB-4 scores demonstrated superior performance compared to abnormal ALT in predicting future SLD outcomes.

Acute Liver Failure: Biomarkers Evaluated by the Acute Liver Failure Study Group.

There has been a growing interest in identifying prognostic biomarkers that alone or with available prognostic models (King's College Criteria, KCC; MELD and ALFSG Prognostic Index) would improve prognosis in acute liver failure (ALF) patients being assessed for liver transplantation. The Acute Liver Failure Study Group (ALFSG) has evaluated 15 potential prognostic biomarkers: serum AFP; apoptosis-associated proteins; serum actin-free Gc-globulin; serum glycodeoxycholic acid; sRAGE/RAGE ligands; plasma osteopontin; circulating MBL, M-, L-, H-ficolin and CL-1; plasma galectin-9; serum FABP1; serum Lct2; miRNAs; factor V; thrombocytopenia, and sCD163. The ALFSG also has reported on 4 susceptibility biomarkers: keratins 8 and 18 (K8/K18) gene variants; polymorphisms of genes encoding putative APAP-metabolizing enzymes ( UGT1A1 , UGT 1A0 , UGT 2B15 , SULT1A1 , CYP2E1 , and CYP3A5 ) as well as CD44 and BHMT1 ; single nucleotide polymorphisms (SNPs) of genes associated with human behavior, rs2282018 in the arginine vasopressin ( AVP ) gene and rs11174811 in the AVP receptor 1A gene. Finally, rs2277680 of the CSCL16 gene in HBV-ALF patients. In conclusion, we have reviewed the prognostic and susceptibility biomarkers studied by the ALFSG. We suggest that a better approach to predicting the clinical outcome of an ALF patient will require a combination of biomarkers of pathogenic processes such as cell death, hepatic regeneration, and degree of inflammation that could be incorporated into prognostic models such as KCC, MELD or ALFSG PI.

Identifying Patients at Risk for Fibrosis in a Primary Care NAFLD Cohort.

GOALS AND BACKGROUND: Using natural language processing to create a nonalcoholic fatty liver disease (NAFLD) cohort in primary care, we assessed advanced fibrosis risk with the Fibrosis-4 Index (FIB-4) and NAFLD Fibrosis Score (NFS) and evaluated risk score agreement. MATERIALS AND METHODS: In this retrospective study of adults with radiographic evidence of hepatic steatosis, we calculated patient-level FIB-4 and NFS scores and categorized them by fibrosis risk. Risk category and risk score agreement was analyzed using weighted κ, Pearson correlation, and Bland-Altman analysis. A multinomial logistic regression model evaluated associations between clinical variables and discrepant FIB-4 and NFS results. RESULTS: Of the 767 patient cohorts, 71% had a FIB-4 or NFS score in the indeterminate-risk or high-risk category for fibrosis. Risk categories disagreed in 43%, and scores would have resulted in different clinical decisions in 30% of the sample. The weighted κ statistic for risk category agreement was 0.41 [95% confidence interval (CI): 0.36-0.46] and the Pearson correlation coefficient for log FIB-4 and NFS was 0.66 (95% CI: 0.62-0.70). The multinomial logistic regression analysis identified black race (odds ratio=2.64, 95% CI: 1.84-3.78) and hemoglobin A1c (odds ratio=1.37, 95% CI: 1.23-1.52) with higher odds of having an NFS risk category exceeding FIB-4. CONCLUSIONS: In a primary care NAFLD cohort, many patients had elevated FIB-4 and NFS risk scores and these risk categories were often in disagreement. The choice between FIB-4 and NFS for fibrosis risk assessment can impact clinical decision-making and may contribute to disparities of care.

FIB-4 and incident severe liver outcomes in patients with undiagnosed chronic liver disease: A Fine-Gray competing risk analysis.

BACKGROUND AND AIMS: The Fibrosis-4 index (FIB-4) can reliably assess fibrosis risk in patients with chronic liver disease, and advanced fibrosis is associated with severe liver disease (SLD) outcomes. However, CLD is underdiagnosed in primary care. We examined the association between FIB-4 risk strata and the incidence of SLD preceding a CLD diagnosis while considering incident CLD diagnoses as competing risks. METHODS: Using primary care clinic data between 2007 and 2018, we identified patients with two FIB-4 scores and no liver disease diagnoses preceding the index FIB-4. Patients were followed from index FIB-4 until an incident SLD (a composite of cirrhosis, hepatocellular carcinoma or liver transplantation), CLD or were censored. Hazard ratios were computed using a Fine-Gray competing risk model. RESULTS: Of 20 556 patients, there were 54.8% in the low, 34.8% in the indeterminate, 6.6% in the high and 3.8% in the persistently high-risk FIB-4 strata. During a mean 8.2 years of follow-up, 837 (4.1%) patients experienced an SLD outcome and 11.5% of the sample received a CLD diagnosis. Of patients with an SLD event, 49% received no preceding CLD diagnosis. In the adjusted Fine-Gray model, the indeterminate (HR 1.41, 95% CI 1.17-1.71), high (HR 4.65, 95% CI 3.76-5.76) and persistently high-risk (HR 7.60, 95% CI 6.04-9.57) FIB-4 risk strata were associated with a higher incidence of SLD compared to the low-risk stratum. CONCLUSIONS: FIB-4 scores with indeterminate- and high-risk values are associated with an increased incidence of SLD in primary care patients without known CLD.

BiMM tree: A decision tree method for modeling clustered and longitudinal binary outcomes.

Clustered binary outcomes are frequently encountered in clinical research (e.g. longitudinal studies). Generalized linear mixed models (GLMMs) for clustered endpoints have challenges for some scenarios (e.g. data with multi-way interactions and nonlinear predictors unknown a priori). We develop an alternative, data-driven method called Binary Mixed Model (BiMM) tree, which combines decision tree and GLMM within a unified framework. Simulation studies show that BiMM tree achieves slightly higher or similar accuracy compared to standard methods. The method is applied to a real dataset from the Acute Liver Failure Study Group.

BiMM forest: A random forest method for modeling clustered and longitudinal binary outcomes.

Clustered binary outcomes and datasets with many predictor variables are frequently encountered in clinical research (e.g. longitudinal studies). Generalized linear mixed models (GLMMs) typically employed for clustered endpoints have challenges for some scenarios, particularly for complex datasets which contain many interactions among predictors and nonlinear predictors of outcome. We propose a new method called Binary Mixed Model (BiMM) forest, which combines random forest and GLMM methodology. BiMM forest offers a flexible and stable method which naturally models interactions among predictors and can be employed in the setting of clustered data. Simulation studies show that BiMM forest achieves similar or superior prediction accuracy compared to standard random forest, GLMMs and its tree counterpart (BiMM tree) for clustered binary outcomes. The method is applied to a real dataset from the Acute Liver Failure Study Group. BiMM forest offers an alternative method for modeling clustered binary outcomes which may be applied in myriad research settings.

Predicting daily outcomes in acetaminophen-induced acute liver failure patients with machine learning techniques.

BACKGROUND/OBJECTIVE: Assessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF) patients during the first week of hospitalization often presents significant challenges. Current models such as the King's College Criteria (KCC) and the Acute Liver Failure Study Group (ALFSG) Prognostic Index are developed to predict outcome using only a single time point on hospital admission. Models using longitudinal data are not currently available for APAP-ALF patients. We aim to develop and compare performance of prediction models for outcomes during the first week of hospitalization for APAP-ALF patients. METHODS: Models are developed for the ALFSG registry data to predict longitudinal outcomes for 1042 APAP-ALF patients enrolled 01/1998-02/2016. The primary outcome is defined as daily low versus high coma grade. Accuracy in prediction of outcome (AC), sensitivity (SN), specificity (SP) and area under the receiver operating curve (AUC) are compared between the following models: classification and regression tree, random forest, frequentist generalized linear mixed model (GLMM), Bayesian GLMM, BiMM tree, and BiMM forest using original and imputed datasets. RESULTS: BiMM tree offers predictive (test set) 63% AC, 72% SP and 53% SN for the original dataset, whereas BiMM forest offers predictive (test set) 69% AC, 63% SP and 74% SN for the imputed dataset. BiMM tree has the highest AUC for the original testing dataset (0.697), whereas BiMM forest and standard random forest have the highest AUC for the imputed testing dataset (0.749). The three most important predictors of daily outcome for the BiMM tree are pressor use, bilirubin and creatinine. The BiMM forest model identifies lactate, ammonia and ALT as the three most important predictors of outcome. CONCLUSIONS: BiMM tree offers a prognostic tool for APAP-ALF patients, which has good accuracy and simple interpretation of predictors which are consistent with clinical observations. BiMM tree and forest models are developed using the first week of in-patient data and are appropriate for predicting outcome over time. While the BiMM forest has slightly higher predictive AC, the BiMM tree model is simpler to use at the bedside.

Use of intra-aortic counterpulsation in cardiogenic shock post-liver transplantation.

Left ventricular dysfunction resulting in cardiogenic shock occurs infrequently following organ reperfusion in liver transplantation. The etiology of the cardiogenic shock is often multifactorial and difficult to manage due to the complex nature of the procedure and the patient's baseline physiology. Traditionally, this hemodynamic instability is managed medically using inotropic agents and vasopressor support. If medical treatment is insufficient, the use of an intra-aortic balloon pump for counterpulsation may be employed to improve the hemodynamics and stabilize the patient. Here, we analyze three cases and review the literature.

The Natural History of Severe Acute Liver Injury.

OBJECTIVES: Acute liver failure (ALF) is classically defined by coagulopathy and hepatic encephalopathy (HE); however, acute liver injury (ALI), i.e., severe acute hepatocyte necrosis without HE, has not been carefully defined nor studied. Our aim is to describe the clinical course of specifically defined ALI, including the risk and clinical predictors of poor outcomes, namely progression to ALF, the need for liver transplantation (LT) and death. METHODS: 386 subjects prospectively enrolled in the Acute Liver Failure Study Group registry between 1 September 2008 through 25 October 2013, met criteria for ALI: International Normalized Ratio (INR)≥2.0 and alanine aminotransferase (ALT)≥10 × elevated (irrespective of bilirubin level) for acetaminophen (N-acetyl-p-aminophenol, APAP) ALI, or INR≥2.0, ALT≥10x elevated, and bilirubin≥3.0 mg/dl for non-APAP ALI, both groups without any discernible HE. Subjects who progressed to poor outcomes (ALF, death, LT) were compared, by univariate analysis, with those who recovered. A model to predict poor outcome was developed using the random forest (RF) procedure. RESULTS: Progression to a poor outcome occurred in 90/386 (23%), primarily in non-APAP (71/179, 40%) vs. only 14/194 (7.2%) in APAP patients comprising 52% of all cases (13 cases did not have an etiology assigned; 5 of whom had a poor outcome). Of 82 variables entered into the RF procedure: etiology, bilirubin, INR, APAP level and duration of jaundice were the most predictive of progression to ALF, LT, or death. CONCLUSIONS: A majority of ALI cases are due to APAP, 93% of whom will improve rapidly and fully recover, while non-APAP patients have a far greater risk of poor outcome and should be targeted for early referral to a liver transplant center.

Development of a Model to Predict Transplant-free Survival of Patients With Acute Liver Failure.

BACKGROUND & AIMS: Patients with acute liver failure (ALF) have a high risk of death that can be substantially reduced with liver transplantation. It is a challenge to predict which patients with ALF will survive without liver transplant because available prognostic scoring systems are inadequate. We devised a mathematical model, using a large dataset collected by the Acute Liver Failure Study Group, which can predict transplant-free survival in patients with ALF. METHODS: We performed a retrospective analysis of data from 1974 subjects who met criteria for ALF (coagulopathy and hepatic encephalopathy within 26 weeks of the first symptoms, without pre-existing liver disease) enrolled in the Acute Liver Failure Study Group database from January 1, 1998 through June 11, 2013. We randomly assigned the subjects to development and validation cohorts. Data from the development cohort were analyzed to identify factors associated with transplant-free survival (alive without transplantation by 21 days after admission to the study). Statistically significant variables were used to create a multivariable logistic regression model. RESULTS: Most subjects were women (70%) and white (78%); acetaminophen overdose was the most common cause (48% of subjects). The rate of transplant-free survival was 50%. Admission values of hepatic encephalopathy grade, ALF etiology, vasopressor use, and log transformations of bilirubin and international normalized ratio were significantly associated with transplant-free survival, based on logistic regression analysis. In the validation cohort, the resulting model predicted transplant-free survival with a C statistic value of 0.84, 66.3% accuracy (95% confidence interval, 63.1%-69.4%), 37.1% sensitivity (95% confidence interval, 32.5%-41.8%), and 95.3% specificity (95% confidence interval, 92.9%-97.1%). CONCLUSIONS: Using data from the Acute Liver Failure Study Group, we developed a model that predicts transplant-free survival of patients with ALF based on easily identifiable hospital admission data. External validation studies are required.

Validation of blood phosphatidylethanol as an alcohol consumption biomarker in patients with chronic liver disease.

BACKGROUND: Blood phosphatidylethanol (PEth) is a promising biomarker of alcohol consumption. This study was conducted to evaluate its performance in patients with liver disease. METHODS: This study included 222 patients with liver disease. Patient-reported alcohol use was obtained as a reference standard, and PEth was measured by tandem mass spectrometry. Receiver operating characteristic (ROC) and contingency table analyses were used to assess the performance of PEth in detecting any drinking and averaging 4 or more drinks daily in the past 30 days. RESULTS: At the limit of quantitation (20 ng/ml), PEth was 73% sensitive (95% confidence interval [CI] 65 to 80) and 96% specific (95% CI 92 to 100) for any drinking in the past month. Subjects who drank but had a negative PEth result were mainly light drinkers. Subjects who reported 30-day abstinence but with quantifiable PEth either reported heavy drinking within the past 6 weeks or had data that suggested underreported drinking. At the optimal cutoff concentration of 80 ng/ml, PEth was 91% sensitive (95% CI 82 to 100) and 77% specific (95% CI 70 to 83) for averaging at least 4 drinks daily. CONCLUSIONS: PEth is a useful test for detecting alcohol use in patients with liver disease, but cutoff concentrations for heavy drinking will result in misclassification of some moderate to heavy drinkers.

Hepatopulmonary syndrome.

The hepatopulmonary syndrome (HPS) is a pulmonary complication of cirrhosis and/or portal hypertension whereby patients develop hypoxemia as a result of alterations in pulmonary microvascular tone and architecture. HPS occurs in up to 30% of patients with cirrhosis. Although the degree of hypoxemia does not reliably correlate with the severity of liver disease, patients with HPS have a higher mortality than do patients with cirrhosis without the disorder. There has been progress into defining the mechanisms that lead to hypoxemia in HPS, but to date there are no therapeutic options for HPS aside from liver transplantation.

Hepatopulmonary syndrome.

PURPOSE OF REVIEW: To discuss the advances in the understanding of the pathophysiology of experimental and human hepatopulmonary syndrome (HPS) and in the management of HPS, particularly regarding liver transplantation. RECENT FINDINGS: Advances have been made in defining the pathophysiology of HPS in experimental models as well as in human disease, including the role of endothelin-1, pulmonary monocytes, and angiogenesis. Additionally, the implications of the presence of HPS as it relates to prioritizing patients for liver transplantation and posttransplant outcomes will also be reviewed. SUMMARY: Mechanisms of disease continue to be defined in HPS, providing potential targets for pharmacologic intervention. Outcomes after liver transplantation are also becoming clearer, including the management of HPS with severe hypoxemia.

Sensitivity and specificity of urinary ethyl glucuronide and ethyl sulfate in liver disease patients.

BACKGROUND: It is important to monitor alcohol use in the care of patients with liver disease, but patient self-report can be unreliable. We therefore evaluated the performance of urine ethyl glucuronide (EtG) and ethyl sulfate (EtS) in detecting alcohol use in the days preceding a clinical encounter. METHODS: Subjects (n = 120) were recruited at a university-based hepatology clinic or during hospitalization. Alcohol consumption was ascertained by validated self-report measures. Urine EtG (cutoff 100 ng/ml) and EtS (cutoff 25 ng/ml) concentrations were assayed by a contracted laboratory using tandem mass spectrometry. The sensitivity and specificity of each biomarker in the detection of drinking during the 3 and 7 days preceding the clinic visit were determined, as well as the influence of liver disease severity on these results. RESULTS: Urine EtG (sensitivity 76%, specificity 93%) and urine EtS (sensitivity 82%, specificity 86%) performed well in identifying recent drinking, and liver disease severity does not affect biomarker performance. After elimination of 1 false-negative self-report, urine EtG > 100 ng/ml was 100% specific for drinking within the past week, whereas 9% of the subjects without evidence of alcohol drinking for at least 1 week had EtS > 25 ng/ml. CONCLUSIONS: Urine EtG and EtS can objectively supplement the detection of recent alcohol use in patients with liver disease. Additional research may determine optimal methods for integrating these tests into clinical care.