Fecal Carriage of Multidrug-Resistant Organisms Increases the Risk of Hepatic Encephalopathy in Cirrhotic Patients: Insights from Gut Microbiota and Metabolite Features

Fecal Carriage of Multidrug-Resistant Organisms Increases the Risk of Hepatic Encephalopathy in Cirrhotic Patients: Insights from Gut Microbiota and Metabolite Features | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Fecal Carriage of Multidrug-Resistant Organisms Increases the Risk of Hepatic Encephalopathy in Cirrhotic Patients: Insights from Gut Microbiota and Metabolite Features Peishan Wu, Pei-Chang Lee, Tien-En Chang, Yun-Cheng Hsieh, Jen-Jie Chiou, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4328129/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Impact of fecal colonization by multidrug-resistant organisms (MDROs) on changes in gut microbiota and associated metabolites, as well as its role in cirrhosis-associated outcomes, has not been thoroughly investigated. Methods Eighty-eight cirrhotic patients and 22 healthy volunteers were prospectively enrolled with analysis conducted on plasma metabolites, fecal MDROs, and microbiota. Patients were followed for a minimum of one year. Predictive factors for cirrhosis-associated outcomes were identified using Cox proportional hazards regression models, and risk factors for fecal MDRO carriage were assessed using logistic regression model. Correlations between microbiota and metabolic profiles were evaluated through Spearman's rank test. Results Twenty-nine (33%) cirrhotic patients exhibited MDRO carriage, with a notably higher rate of hepatic encephalopathy (HE) in MDRO carriers (20.7% vs. 3.2%, p = 0.008). Cox regression analysis identified higher serum lipopolysaccharide levels and fecal MDRO carriage as predictors for HE development. Logistic regression analysis showed that MDRO carriage is an independent risk factor for developing HE. Microbiota analysis showed a significant dissimilarity of fecal microbiota between cirrhotic patients with and without MDRO carriage ( p = 0.033). Thirty-two metabolites exhibiting significantly different expression levels among healthy controls, cirrhotic patients with and without MDRO carriage were identified. Six of the metabolites showed correlation with specific bacterial taxa expression in MDRO carriers, with isoaustin showing significantly higher levels in MDRO carriers experiencing HE compared to those who did not. Conclusion Fecal MDRO carriage is associated with altered gut microbiota, metabolite modulation, and an elevated risk of HE occurrence within a year. Multidrug resistant organisms cirrhosis complications microbiota metabolite hepatic encephalopathy Figures Figure 1 Figure 2 Figure 3 Introduction Cirrhosis is susceptible to infections [ 1 ]. The widespread use of antibiotics has rapidly increased the global prevalence of infections caused by multidrug-resistant organisms (MDROs) in patients with cirrhosis [ 2 – 4 ]. Moreover, the colonization of MDROs in such patients emerges as a critical factor for subsequent MDRO infections, contributing to a negative impact on overall survival [ 5 – 8 ]. The intestine serves as a main reservoir for MDROs [ 9 ], and high rates of asymptomatic intestinal carriage of MDROs have been documented in patients with cirrhosis, particularly among those awaiting liver transplantation, or experiencing hepatic decompensation or critical illness [ 6 , 7 , 10 ]. In non-cirrhotic hospitalized patients, the composition of intestinal bacteria differs between those with and without rectal MDRO carriage, showing decreased diversity in MDRO carriers [ 11 – 13 ]. Certain commensals may protect against resistant bacteria in the intestine [ 14 , 15 ]. The successful decolonization of resistant pathogens in the gut through fecal microbiota transplantation further supports the role of the gut microbiota [ 16 ]. The composition of the gut microbiota in patients with cirrhosis differs from that of the general population [ 17 , 18 ]. This microbiota alteration, coupled with the impaired gut barrier function found in cirrhosis, further contributes to cirrhosis-associated complications, such as spontaneous bacterial peritonitis (SBP), hepatic encephalopathy (HE), hepatorenal syndrome, and acute on chronic liver failure [ 18 – 20 ]. Some data have shown poor survival in cirrhotic patients colonized or infected with MDROs; however, the impact of long-term fecal colonization by MDROs on specific outcomes related to cirrhosis remains unclear. Therefore, this study aimed to investigate the roles of fecal MDRO colonization and the associated metabolites in influencing clinical outcomes associated with cirrhosis. Materials and Methods Participants and Data Collection This prospective study was conducted at Taipei Veterans General Hospital between October 2018 and April 2022. Liver cirrhosis was diagnosed based on histological, clinical, biochemical, endoscopic, and imaging findings suggestive of cirrhosis in patients with chronic liver disease [ 21 ]. Patients with previous history of HE, active hepatocellular carcinoma status; malignancies other than hepatocellular carcinoma; with human immunodeficiency virus infection or severe comorbidities, such as chronic renal failure, heart failure, or chronic obstructive pulmonary disease; and those who received proton pump inhibitor, nonsteroidal anti-inflammatory drugs, antibiotics, or probiotics within 1 month were excluded. Twenty-two healthy adults without underlying systemic disease were enrolled as healthy controls. This study was approved by the Institutional Review Board of Taipei Veterans General Hospital (IRB No., 2017-09-013C and 2019-08-013A). Written informed consent was obtained from each participant. Demographic characteristics, laboratory data, and medical history were collected. Blood and stool samples were collected on the day of enrollment. Stool samples from 18 hospitalized cirrhotic patients were collected in the ward, while samples from the remaining 70 cirrhotic outpatients and 22 healthy subjects were collected at home. Cirrhotic patients were followed for at least 1 year, or until death or liver transplant. During the follow-up period, clinical events were recorded, which included (1) complications of cirrhosis, such as SBP, overt HE [ 22 ], newly developed or worsening ascites, acute kidney injury, first or recurrent variceal bleeding; (2) newly diagnosed hepatocellular carcinoma; (3) bacterial infections; (4) death; or (5) liver transplant. Definition of MDROs The stool samples collected were inoculated onto selective agar plates at 37°C for 24 hours to detect MDROs. MDROs were defined as microorganisms that are resistant to at least one agent in three or more antimicrobial categories as characterized earlier [ 23 ]. MDROs include methicillin-resistant Staphylococcus aureus , vancomycin-resistant enterococci, and multidrug-resistant gram-negative bacilli, including Enterobacterales, Pseudomonas aeruginosa , and Acinetobacter baumannii . Details of MDRO detection, processing and analysis of stool bacterial genomic data, as well as metabolite analysis are provided in Supplementary Methods. Measurement of lipopolysaccharides Plasma lipopolysaccharides (LPS) were measured by enzyme-linked immunosorbent assay kits (Cloud-Clone Corp, Katy, TX, USA) according to the manufacturer’s instructions. Statistical Analysis Clinical data were expressed as median (25th − 75th percentiles) or as counts, as appropriate. The chi-square or Fisher’s exact test was used to analyze categorical variables and the Mann–Whitney U -test was applied to assess continuous variables between MDRO carriers and non-carriers in the cirrhotic population. Cox regression analysis was performed to identify potential predictors for clinical outcomes. A logistic regression model was used to identify the risk factors for fecal carriage of MDROs. The cutoff values of Model for End-Stage Liver Disease score (MELD) and lipopolysaccharides (LPS) levels are determined using Youden's index. Variables with p < 0.1 in the univariate analysis were included in the multivariable analysis. Statistical significance was defined as p < 0.05. The Kruskal–Wallis test was used to assess the metabolite differences among healthy controls, cirrhotic patients with and without MDROs, and among healthy controls, cirrhotic patients with and without HE. Data were considered significant when p < 0.05. All statistical analysis were performed using IBM SPSS Statistics for Windows, Version 24.0 (IBM Corp. Armonk, NY, USA). Detailed analyses for the gut microbiota and the metabolites are provided in Supplementary Methods. Results Fecal Microbiological Findings in Healthy Controls and Cirrhotic patients Eighty-eight patients with cirrhosis and twenty-two healthy volunteers were enrolled. The median age and gender distribution were similar between the two populations ( Suppl. Table 1) . Table 1 showed that the fecal MDRO colonization rate was higher in patients with cirrhosis than the healthy controls (33% vs. 9.1%, p = 0.026) Of the 29 cirrhotic patients with fecal MDRO carriage, 6 patients (30.7%) were colonized with ≥ 2 MDROs. The most commonly isolated MDRO was extended-spectrum beta-lactamase producing Escherichia coli (58.6%), followed by vancomycin-resistant Enterococcus spp. (48.3%). Table 1 Antimicrobial resistance in fecal cultures between healthy subjects and cirrhotic patients Healthy (n = 22) Cirrhosis (n = 88) MDRO colonized 2 (9.1) 29 (33.0) Microorganism Gram negative Escherichia coli (ESBL) 1 (50) 17 (58.6) Klebsiella pneumoniae (ESBL) 0 (0) 6 (20.7) Klebsiella pneumoniae (CRE) 0 (0) 1 (3.4) Gram positive Enterococcus spp. (VRE) 1 (50) 14 (48.3) Methicillin-Resistant Staphylococcus Aureus 0 (0) 0 (0) ≥ 2 MDROs 0 (0) 6 (30.7) The data are expressed as number (percent). MDRO, multidrug-resistant organism; ESBL, extended spectrum β-lactamase; CRE, Carbapenem-resistant Enterobacteriaceae; VRE, vancomycin-resistant Enterococcus Characteristics and Outcomes Between Cirrhotic Patients With and Without MDRO Carriage The demographic data of the cirrhotic patients with and without fecal carriage of MDROs are summarized in Table 2 . No differences in terms of age, gender, etiology of cirrhosis, underlying comorbidities, and severity of liver disease were observed between MDRO carriers and non-carriers. MDRO carriers had higher plasma LPS levels (15.1 vs 10.4 ng/L, p = 0.006) and a higher proportion of admission within 30 days (34.5% vs 13.6%, p = 0.002) compared to non-carriers. During a median of 16.4 months follow-up (range, 0.7–40.4 months), 36 patients (40.1%) developed cirrhosis-associated complications within 1 year after enrollment ( Table 3 ) . MDRO carriers had higher rates of HE occurrence than non-carriers (20.7 vs 3.4%, p = 0.008). However, other cirrhotic complications, including infectious events, did not show a significant difference between MDRO carriers and non-carriers. Regarding the infectious events, 5 patients experienced SBP, while ten encountered other types of infections. Among the 10 patients with non-SBP infections, five had bacteremia, two had intra-abdominal infections, two had aspiration pneumonia, and one had a urinary tract infection. The positive culture rate for these infectious events was 53%, but none of the bacterial cultures identified were MDROs. Table 2 Baseline characteristics in cirrhotic patients with and without fecal carriage of MDROs Variables MDRO - (n = 59) MDRO + (n = 29) p- value Age, years 61.75 (54.42–65.35) 56.36 (46.95–64.98) 0.067 Male 45 (76.3) 23 (79.3) 0.749 Etiology of cirrhosis (%) Viral/alcohol/others 42 (71.2)/ 12 (20.3)/ 5 (8.5) 15 (51.7)/ 8 (27.6)/ 6 (20.7) 0.142 Laboratory White blood cell (1000 /uL) 4.3 (3.2–5.3) 4.1 (3-5.45) 0.862 Platelet (1000/uL) 85 (58–120) 80 (46-117.5) 0.470 Sodium (mEq/L) 140 (138–142) 139 (136–141) 0.185 Creatinine (mg/dL) 0.84 (0.72–0.99) 0.80 (0.7-1) 0.535 Total bilirubin (mg/dL) 1.4 (1-2.2) 1.6 (0.9–3.7) 0.742 ALT (U/L) 27 (22–37) 32 (21.5–41) 0.260 Albumin (g/dL) 3.7 (3.3–4.1) 3.5 (3.1–3.95) 0.054 INR 1.26 (1.15–1.36) 1.34 (1.16–1.46) 0.131 LPS (ng/mL) 10.39 (8.73–15.1) 15.1 (9.99–20.91) 0.006 Comorbidity Diabetes mellitus 17 (28.8) 8 (28.4) 0.904 Hypertension 8 (13.6) 2 (6.9) 0.355 Hepatocellular carcinoma 10 (16.9) 5 (17.2) 0.973 Presence of ascites 31 (52.5) 14 (48.3) 0.707 Presence of varices 53 (89.8) 25 (86.2) 0.615 Child-Pugh score 6 (5–8) 7 (5–8) 0.177 Child-Pugh class A/B/C 35 (59.3)/ 19 (32.2)/ 5 (8.5) 13 (44.8)/12 (41.4)/4 (13.8) 0.417 MELD score 10.48 (8.98–13.43) 11.55 (8.37–16.44) 0.221 Prior admission < 30 days 8 (13.6) 10 (34.5) 0.022 < 60 days 15 (25.4) 11 (37.9) 0.247 < 90 days 19 (32.2) 13 (44.8) 0.227 The data are expressed as median (25th-75th percentiles), or number (percent). MDRO, multidrug-resistant organism; ALT, alanine aminotransferase; INR, international normalized ratio; LPS, lipopolysaccharide; MELD, Model for End-stage Liver Disease Table 3 Outcomes in cirrhotic patients with and without fecal carriage of MDROs within one year of follow-up Variables MDRO - (n = 59) MDRO + (n = 29) p- value SBP 3 (5.1) 2 (6.9) 1.000 Infections other than SBP 6 (10.2) 4 (13.8) 0.615 Hepatic encephalopathy 2 (3.4) 6 (20.7) 0.008 Variceal bleeding 2 (3.4) 1 (3.4) 1.000 Acute kidney injury 13 (22.0) 5 (17.2) 0.600 Newly onset ascites 3 (5.1) 2 (6.9) 1.000 Newly developed HCC 4 (6.8) 2 (6.9) 1.000 Mortality 1 (1.7) 2 (6.9) 0.252 Liver transplant 1 (1.7) 0 (0) 1.000 The data are expressed as number (percent). MDRO, multidrug-resistant organism; SBP, spontaneous bacterial peritonitis; HCC, hepatocellular carcinoma. To identify potential predictors associated with HE within 1 year, Cox regression analysis was performed (Table 4 ). Univariate analysis showed that higher serum LPS levels (≥ 14.9 ng/mL), Child-Pugh class C, and fecal MDRO carriage were independent predictors for HE occurrence. Importantly, LPS ≥ 14.9 ng/mL and fecal MDRO carriage maintained their statistical significance on multivariable analysis, further supporting their association with HE occurrence. Table 5 shows the risk factors associated with fecal colonization of MDROs in cirrhotic patients. In the univariate analysis, higher serum LPS levels (≥ 11.9 ng/mL) and prior admission in the last 30 days were significant risk factors for fecal MDRO colonization. However, on multivariable analysis, prior admission within 30 days did not predict MDRO colonization. Only serum levels of LPS ≥ 11.9 ng/mL (OR = 3.84; p = 0.009) remained an independent risk factor for MDRO colonization. Table 4 Cox regression for hepatic encephalopathy within one year in cirrhotic patients Variables Univariate analysis Multivariable analysis HR 95%CI p -value HR 95%CI p -value Age 1.01 0.94–1.08 0.826 Male sex 2.16 0.27–17.58 0.471 Type 2 diabetes mellitus 0.34 0.04–2.78 0.316 Albumin (< 3.5/ ≥ 3.5 g/dL) 1.81 0.45–7.23 0.403 Sodium (< 135 / ≥ 135mEq/L) 3.99 0.80-19.82 0.091 4.60 0.65–32.60 0.127 LPS (≥ 14.9/ < 14.9 ng/mL) 14.97 1.84-121.83 0.011 11.01 1.24–97.50 0.031 Child-Pugh class A Reference B 3.29 0.60-17.94 0.170 1.12 0.19–6.71 0.903 C 6.59 0.93–46.82 0.060 1.71 0.18–15.82 0.639 MELD scores (≥ 10/ < 10) 4.89 0.60-39.72 0.138 MDRO carriage 6.68 1.35–33.13 0.020 5.47 1.02–29.31 0.047 HR, hazard ratio; CI, confidence interval; LPS, lipopolysaccharide; MDRO, multidrug-resistant organism Table 5 Risk factors for fecal MDRO carriage Variables Univariate analysis Multivariable analysis OR 95%CI p -value OR 95%CI p -value Age 0.95 0.91–1.01 0.077 0.96 0.91-1.00 0.062 Male sex 1.19 0.41–3.51 0.749 Type 2 diabetes mellitus 0.94 0.35–2.53 0.904 Albumin (< 3.5/ ≥ 3.5 g/dL) 0.63 0.25–1.57 0.321 Sodium (< 135 / ≥ 135mEq/L ) 1.25 0.28–5.62 0.775 LPS (≥ 11.9/ < 11.9 ng/ml) 4.02 1.56–10.40 0.004 3.84 1.40-10.49 0.009 Child-Pugh class A Reference B 1.70 0.65–4.46 0.280 C 2.15 0.50–9.28 0.303 MELD scores (≥ 15/ < 15) 2.30 0.84–6.29 0.106 Prior admission within 30 days 3.36 1.15–9.77 0.026 1.04 0.38–2.85 0.945 Presence of ascites 0.84 0.35–2.05 0.707 OR, odds ratio; CI, confidence interval; LPS, lipopolysaccharide; MDRO, multidrug-resistant organism Fecal Microbiome Comparisons Among Healthy Adults, and Cirrhotic Patients With and Without Fecal MDRO Carriage Compared with healthy adults, Proteobacteria was predominant in the fecal samples of patients with liver cirrhosis (Fig. 1 a). At the family level, Bacteroidaceae, Enterobacteriaceae, Lactobacillaceae and Streptococcaceae were increased, while Lachnospiraceae and Ruminococcaceae were decreased in the feces of cirrhotic patients ( Fig. 1 b). The richness and evenness of fecal microbiota measured by Faith’s PD index and Shannon index were significantly reduced in cirrhotic patients (both p < 0.001; Fig. 1 c). Besides, the principal component analyses of unweighted UniFrac distance and Bray–Curtis distance showed a significant bacterial dissimilarity between these two groups (both p value = 0.001 by PERMANOVA test; Fig. 1 d). The phylogenetic diversity of fecal microbiota measured by Faith’s PD index and Shannon index decreased significantly in cirrhotic patients with and without MDRO carriage when compared with healthy controls (Fig. 2 a). No statistical significance was observed between patients with cirrhosis with and without MDROs; however, a trend toward decreased alpha diversity in patients with cirrhosis with MDROs was observed. According to the unweighted UniFrac metrics, a significant dissimilarity of fecal microbiota was observed both between healthy controls and cirrhotic patients regardless of MDRO carriage ( p = 0.001) and between cirrhotic patients with and without MDRO colonization ( p = 0.033). However, the MDRO-associated microbial dissimilarity was not significant when measured using the Bray–Curtis distance ( p = 0.134) (Fig. 2 b). Furthermore, the results of LEfSe analysis showed a prominent abundance of Streptococcus salivarius in MDRO carriers, while Megamonas genus was abundant in MDRO non-carriers (Fig. 2 c). Identification of Metabolomic Signature Associated with HE in Cirrhotic Patient With MDRO Carriage Total 4869 untargeted metabolites in the plasma of cirrhotic patients by metabolomic analysis, of which 1618 metabolites were named. Thirty-two of the named metabolites that exhibited statistically significant differences in expression levels among healthy controls, cirrhotic patients with fecal MDROs, and those without MDROs were selected ( Suppl. Table 2 ). The correlation analysis between the 32 metabolites and the dominant bacteria taxa in cirrhotic patients with MDRO carriage was performed ( Fig. 2 d ) . Six metabolites were identified to be correlated to specific microbiota expression patterns in patients carrying MDROs. A positive correlation between the presence of Clostridioides difficile and two metabolites—isoaustin and 2,3-butanediol glucoside—within cirrhotic patients carrying MDROs was observed ( Fig. 2 d ) . Notably, these 2 metabolites expressed significantly higher levels in MDRO carriers than in non-carriers ( Suppl. Table 2 ). Conversely, a negative correlation was found between Clostridioides difficile and three other metabolites—DG (14:0/18:0/0:0), thelephoric acid, and 5-(3',4',5'-trihydroxyphenyl)-gamma-valerolactone—exhibiting diminished expression levels in MDRO carriers compared to non-carriers. In addition, Streptococcus salivarius exhibited a negative correlation with a single metabolite, PE-NMe2(24:0/20:3(5Z,8Z,11Z)), which was downregulated compared with MDRO non-carriers ( Suppl. Table 2 ). There was no definitive positive correlation between Streptococcus salivarius and the broader spectrum of metabolites. The expression levels of these six metabolites in MDRO carriers who experienced HE and those who did not were further analyzed (Fig. 3 ); only isoaustin exhibited markedly higher expression in MDRO carriers who experienced HE than those who did not (Fig. 3 a). Discussion In this study, the cirrhotic patients with fecal MDRO colonization were at higher risk for occurrence of HE within 1 year compared to non-carriers. Furthermore, the presence of MDROs was associated with changes in gut microbiota diversity and alterations in specific metabolites, suggesting a connection between MDRO carriage and the increased risk of HE in cirrhotic patients. High prevalence of MDRO colonization has been reported in cirrhotic patients with different conditions [ 7 , 10 , 24 ]. In cirrhotic patients waiting for liver transplant, the prevalence of MDRO colonization (from skin, oral and rectal samples) at listing was 20% and increased to 37% at transplantation [ 10 ]. Prado et al . observed that, among critically ill patients in the intensive care unit, patients with cirrhosis had a higher MDRO colonization rate than patients without cirrhosis at admission (28.7% vs 18.2%, respectively) [ 7 ]. The present study also showed a high fecal MDRO colonization rate for cirrhotic patients with general condition (33%), which was higher than healthy subjects (9.1%). MDRO colonization, associated with subsequent MDRO infections, is an independent predictor for poor short-term survival for patients with cirrhosis [ 6 , 7 , 10 , 24 , 25 ]. Nevertheless, there was no difference in infection or mortality rates between MDRO carriers and non-carriers, and no MDRO infectious events occurred during the follow-up period in our patient population. Instead, we found a higher rate of overt HE in MDRO carriers. These differences may be attributed to variations in liver disease severity at enrollment, with previous studies mainly focusing on end-stage liver disease or critical conditions, often in hospitalized patients [ 6 , 7 , 10 , 24 ]. In contrast, our study enrolled cirrhotic patients across all severities, with half being Child–Pugh class A, and a majority (80%) being outpatients. Therefore, the present study provided important information regarding MDRO carriage on cirrhosis-associated outcomes for both hospitalized and community-dwelling patients with cirrhosis. In this study, higher serum LPS levels and fecal MDRO carriage helped to predict HE occurrence within the first year of follow-up. Patients with cirrhosis exhibit alteration of gut microbiota [ 17 , 18 , 26 ], which in turn increases the gut permeability and facilitates the translocation of bacterial products into systemic circulation, worsening endotoxemia. The altered microbiota compositions in cirrhotic patients might diminish the protective power of several c ommensals against colonization of pathogenic bacteria, including MDROs, in the host intestine [ 27 ]. LPS is a gut-derived endotoxin produced by Gram-negative bacteria that enters systemic circulation from the disrupted intestinal barrier in cirrhotic patients [ 28 ]. Therefore, patients with high LPS levels might have disturbed gut homeostasis and be more susceptible to colonization of pathogenic bacteria such as MDROs. Besides, a close correlation has been found between HE and the altered microbiota in cirrhosis [ 29 – 31 ]. Zhang et al. found a greater abundance of the gut ammonia-increasing bacteria Streptococcus salivarius in cirrhotic patients with minimal HE than in those without minimal HE [ 29 ]. Bajaj et al. reported that the colonic mucosal microbiota composition, rather than the stool microbiota, differed between patients with overt HE and without HE [ 30 , 31 ], with a greater abundance of Enterococcus, Veillonella, Megasphaera, Bifidobacterium, and Burkholderia in patients with HE; in that study, the presence of Enterococcus, Megasphaera, and Burkholderia were linked to poor cognition and inflammation [ 30 ]. Reduced microbial diversity and change in microbiota composition have been reported in non-cirrhotic patients with MDRO carriage in comparison with those without MDRO carriage [ 11 – 13 , 32 ]. Araos et al. showed that, in hospitalized non-cirrhotic patients, a greater abundance of Enterococcus spp. in MDRO carriers and microbiota belonging to Bacteroidales order in non-carriers, respectively [ 11 ]. Among older residents of nursing homes, Odoribacter laneus , and Akkermansia muciniphila were predominant in MDRO carriers, whereas Blautia hydrogenotrophica was predominant in non-carriers [ 32 ]. Consistently, in the present study, we observed that the gut microbiota composition was different between patients with and without MDRO carriage. We found a prominent abundance of Streptococcus salivarius in MDRO carriers, while Megamonas genus was abundant in MDRO non-carriers. Interestingly, the most abundant bacteria in MDRO carriers— Streptococcus salivarius — belongs to the urease-producing bacteria; this may partially explain why the rate of HE in this group was higher than that in the study by Zhang et al [ 29 ]. In addition to the gut microbiota, the bacterial associated metabolites can also influence the gut-liver-brain axis, which in turn contributes to HE development [ 33 – 36 ]. However, data regarding the interaction of MDROs and the gut bacteria associated metabolites with HE development in cirrhosis is limited. Our study demonstrated that of six of the metabolites correlated with the microbiota in MDRO carriers, a higher level of isoaustin was expressed in MDRO carriers with HE than in MDRO carriers without HE. However, the biological role of isoaustin in the human body has not yet been addressed. In our study, it remained unclear whether MDRO-associated metabolites are contributors or consequences of MDRO carriage. However, bacterial metabolism alterations could potentially contribute to antibiotic resistance by affecting energy production, modifying cell envelope compositions, and adjusting cell-to-cell interactions in biofilms [ 37 , 38 ]. The role of metabolites in antibiotic resistance was supported by Ji’s study [ 39 ]. They found a suppression of glutathione oxidized and citrulline abundances in Salmonella Derby with drug resistance to third-generation cephalosporin; the susceptibility of multidrug-resistant Salmonella Derby to third-generation cephalosporin was further restored by exogenous glutathione oxidized or citrulline [ 39 ]. Taken together, changes of gut microbiota in cirrhosis might contribute to the metabolite alterations, with both factors promoting the growth of resistant bacteria in a given selective environment and inducing HE development. This suggests a dynamic relationship between the gut microbiota, metabolic changes, bacterial resistance, and HE development. Though the precise interaction between these factors was not disclosed in our study, our results provide new insights into the impact of MDRO carriage and metabolites in the cirrhotic population with occurrence of HE. Further research in this domain is crucial to unravel the mechanisms and potential therapeutic strategies to mitigate the impact of these interactions. This study had some limitations. First, this was a single-center study performed in Taiwan. Therefore, the prevalence and distribution of MDROs might be different to those observed in other countries. Second, due to the observational nature of the study, detecting minimal HE events was challenging, preventing an assessment of the impact of microbiota and associated metabolites on patients with minimal HE. Third, many of the untargeted metabolites remained undiscovered, and only named metabolites were analyzed. Lastly, isoaustin was found to correlate with HE development in MDRO carriers; however, the biological role of isoaustin and its underlying mechanism remain unclear. The difficulty in obtaining these metabolites prevents us from conducting experimental studies to elucidate their roles. Nevertheless, our study uncovered a new impact on the correlation between MDROs, microbiota and the associated metabolites on HE. In conclusion, the present study demonstrated the association between fecal colonization of MDROs, altered gut microbiota, metabolite modulation, and an elevated risk of HE occurrence among cirrhotic patients. The findings provide information to identify patients who may benefit from aggressive surveillance of fecal MDROs and to establish a treatment policy for decolonization in cirrhotic patients. Declarations Acknowledgments The authors gratefully acknowledge Ms. Kai-Ting Wang, Yu-Chieh Tsai, Yi-Ru Huang, and Ching-Hsuan Chen for their excellent technical assistance. Author Contributions Pei-Shan Wu and Kuei-Chuan Lee conceived and designed the study. Pei-Shan Wu, Pei-Chang Lee, Tien-En Chang, Yun-Cheng Hsieh, Kuei-Chuan Lee, Yi-Tsung Lin, Teh-Ia Huo, and Ming-Chih Hou collected the data. Pei-Shan Wu, Pei-Chang Lee, Ueng-Cheng Yang, Jen-Jie Chiou, Chao-Hsiung Lin, Yi-Long Huang, Kuei-Chuan Lee and Bernd Schnabl analyzed and interpretated the data. Pei-Shan Wu and Kuei-Chuan Lee drafted the manuscript. Kuei-Chuan Lee, Ming-Chih Hou, and Bernd Schnabl provided critical revision during the drafting of the manuscript. All the authors read and approved the final manuscript. Funding Information This study was supported by the Taipei Veterans General Hospital (Grant No. V113B-022 and V113C-098), National Science and Technology Council (Grant No. NSTC 112-2314-B-075-032, and MOST 111-2314-B-075-051-MY3), and services provided by the San Diego Digestive Diseases Research Center (SDDRC) P30 DK120515. Data availability Data available on request from the authors. Conflict of interest The authors declare that they have no conflict of interests. Ethical approval This study was approval by the institutional research ethics committees at Taipei Veterans General Hospital (IRB No., 2017-09-013C and 2019-08-013A). Informed consent Written informed consent was obtained from each participant. References Arvaniti V, D'Amico G, Fede G, et al. Infections in patients with cirrhosis increase mortality four-fold and should be used in determining prognosis. Gastroenterology. 2010;139:1246-56, 1256.e1-5. Carlet J, Pulcini C, Piddock LJ. Antibiotic resistance: a geopolitical issue. Clin Microbiol Infect. 2014;20:949-53. Piano S, Singh V, Caraceni P, et al. Epidemiology and Effects of Bacterial Infections in Patients With Cirrhosis Worldwide. Gastroenterology. 2019;156:1368-1380.e10. Fernández J, Piano S, Bartoletti M, et al. 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Gut microbiome signatures and host colonization with multidrug-resistant bacteria. Trends Microbiol. 2022;30:853-865. Panwar RB, Sequeira RP, Clarke TB. Microbiota-mediated protection against antibiotic-resistant pathogens. Genes Immun. 2021;22:255-267. Saha S, Tariq R, Tosh PK, et al. Faecal microbiota transplantation for eradicating carriage of multidrug-resistant organisms: a systematic review. Clin Microbiol Infect. 2019;25:958-963. Bajaj JS, Khoruts A. Microbiota changes and intestinal microbiota transplantation in liver diseases and cirrhosis. J Hepatol. 2020;72:1003-1027. Bajaj JS, Heuman DM, Hylemon PB, et al. Altered profile of human gut microbiome is associated with cirrhosis and its complications. J Hepatol. 2014;60:940-7. Seo YS, Shah VH. The role of gut-liver axis in the pathogenesis of liver cirrhosis and portal hypertension. Clin Mol Hepatol. 2012;18:337-46. Goel A, Gupta M, Aggarwal R. Gut microbiota and liver disease. J Gastroenterol Hepatol. 2014;29:1139-48. Schuppan D, Afdhal NH. Liver cirrhosis. Lancet. 2008;371:838-51. Vilstrup H, Amodio P, Bajaj J, et al. Hepatic encephalopathy in chronic liver disease: 2014 Practice Guideline by the American Association for the Study of Liver Diseases and the European Association for the Study of the Liver. Hepatology. 2014;60:715-35. Magiorakos AP, Srinivasan A, Carey RB, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18:268-81. Kim M, Cardoso FS, Pawlowski A, et al. The impact of multidrug-resistant microorganisms on critically ill patients with cirrhosis in the intensive care unit: a cohort study. Hepatol Commun. 2023;7:e0038. Verma N, Divakar Reddy PV, Vig S, et al. Burden, risk factors, and outcomes of multidrug-resistant bacterial colonisation at multiple sites in patients with cirrhosis. JHEP Rep. 2023;5:100788. Qin N, Yang F, Li A, et al. Alterations of the human gut microbiome in liver cirrhosis. Nature. 2014;513:59-64. Buffie CG, Pamer EG. Microbiota-mediated colonization resistance against intestinal pathogens. Nat Rev Immunol. 2013;13:790-801. Tsiaoussis GI, Assimakopoulos SF, Tsamandas AC, et al. Intestinal barrier dysfunction in cirrhosis: Current concepts in pathophysiology and clinical implications. World J Hepatol. 2015;7:2058-68. Zhang Z, Zhai H, Geng J, et al. Large-scale survey of gut microbiota associated with MHE Via 16S rRNA-based pyrosequencing. Am J Gastroenterol. 2013;108:1601-11. Bajaj JS, Ridlon JM, Hylemon PB, et al. Linkage of gut microbiome with cognition in hepatic encephalopathy. Am J Physiol Gastrointest Liver Physiol. 2012;302:G168-75. Bajaj JS, Hylemon PB, Ridlon JM, et al. Colonic mucosal microbiome differs from stool microbiome in cirrhosis and hepatic encephalopathy and is linked to cognition and inflammation. Am J Physiol Gastrointest Liver Physiol. 2012;303:G675-85. Araos R, Battaglia T, Ugalde JA, et al. Fecal Microbiome Characteristics and the Resistome Associated With Acquisition of Multidrug-Resistant Organisms Among Elderly Subjects. Front Microbiol. 2019;10:2260. Iebba V, Guerrieri F, Di Gregorio V, et al. Combining amplicon sequencing and metabolomics in cirrhotic patients highlights distinctive microbiota features involved in bacterial translocation, systemic inflammation and hepatic encephalopathy. Sci Rep. 2018;8:8210. Bajaj JS, Tandon P, O'Leary JG, et al. Admission Serum Metabolites and Thyroxine Predict Advanced Hepatic Encephalopathy in a Multicenter Inpatient Cirrhosis Cohort. Clin Gastroenterol Hepatol. 2023;21:1031-1040.e3. Chen Z, Ruan J, Li D, et al. The Role of Intestinal Bacteria and Gut-Brain Axis in Hepatic Encephalopathy. Front Cell Infect Microbiol. 2020;10:595759. Bajaj JS, Fan S, Thacker LR, et al. Serum and urinary metabolomics and outcomes in cirrhosis. PLoS One. 2019;14:e0223061. Kok M, Maton L, van der Peet M, et al. Unraveling antimicrobial resistance using metabolomics. Drug Discov Today. 2022;27:1774-1783. Martínez JL, Rojo F. Metabolic regulation of antibiotic resistance. FEMS Microbiol Rev. 2011;35:768-89. Ji J, Wu S, Sheng L, et al. Metabolic reprogramming of the glutathione biosynthesis modulates the resistance of Salmonella Derby to ceftriaxone. iScience. 2023;26:107263. Supplementary Files supplementarydata0205.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4328129","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":296866925,"identity":"47bd278b-0f76-4615-bcb0-0783b8a5c62a","order_by":0,"name":"Peishan Wu","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Peishan","middleName":"","lastName":"Wu","suffix":""},{"id":296866926,"identity":"4235d99e-de0c-47d0-be22-759d275725e9","order_by":1,"name":"Pei-Chang Lee","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Pei-Chang","middleName":"","lastName":"Lee","suffix":""},{"id":296866927,"identity":"b8c6e86d-2791-4a93-abb3-0040b18c48b7","order_by":2,"name":"Tien-En Chang","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tien-En","middleName":"","lastName":"Chang","suffix":""},{"id":296866928,"identity":"978121fb-91cc-4701-a1ee-dcb9f88fd4da","order_by":3,"name":"Yun-Cheng Hsieh","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yun-Cheng","middleName":"","lastName":"Hsieh","suffix":""},{"id":296866929,"identity":"43e1ea78-afb5-48db-adc2-a2397bf046a6","order_by":4,"name":"Jen-Jie Chiou","email":"","orcid":"","institution":"EudaiBiome","correspondingAuthor":false,"prefix":"","firstName":"Jen-Jie","middleName":"","lastName":"Chiou","suffix":""},{"id":296866930,"identity":"c66c7430-5a39-4fdd-8403-d69e60b77cd8","order_by":5,"name":"Chao-Hsiung Lin","email":"","orcid":"","institution":"National Yang Ming Chiao Tung University - Yangming Campus","correspondingAuthor":false,"prefix":"","firstName":"Chao-Hsiung","middleName":"","lastName":"Lin","suffix":""},{"id":296866931,"identity":"b165248b-2961-4f8a-9beb-aab584522022","order_by":6,"name":"Yi-Long Huang","email":"","orcid":"","institution":"National Yang Ming Chiao Tung University - Yangming Campus","correspondingAuthor":false,"prefix":"","firstName":"Yi-Long","middleName":"","lastName":"Huang","suffix":""},{"id":296866932,"identity":"f488cc32-0c3f-4db7-8f5d-8fa444bb8ff4","order_by":7,"name":"Yi-Tsung Lin","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yi-Tsung","middleName":"","lastName":"Lin","suffix":""},{"id":296866933,"identity":"1bf1ced3-9377-4bde-84bf-4bfe200db387","order_by":8,"name":"Teh-Ia Huo","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Teh-Ia","middleName":"","lastName":"Huo","suffix":""},{"id":296866934,"identity":"66c3d11b-6152-47c0-8217-d4834f029b0f","order_by":9,"name":"Bernd Schnabl","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Bernd","middleName":"","lastName":"Schnabl","suffix":""},{"id":296866935,"identity":"e2267c48-8289-48be-82aa-38125fd9275f","order_by":10,"name":"Kuei-Chuan Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIie3RMQrCMBSA4VcCcQm4phTSK6R0cBEv4mIoeAYHlYqgS8G1Tp7BG0QKdRFdBR0KgnNHRREjom5p3QTzDyGE95FAAEymH4wCCgE69ceuNLEUWbXVDr3OkGb+RaxR8gWxx4tBluONmDUnaZZDj3FZTbWPdIgYejHZifk+qXgxLH0uEdYSRq2RQ+jO9+IAOwRSMQ0R3haQ8eXK109yLUMcdQuClmQuVQSgKyZQQOxIDO1IBozToOZFXPpVhGonHaHLZJGfbw3ixuKYnTp9hiuDA9eRd1wCVmtS+C2f3PBBoF923mQymf6oOwOeRJJntJFbAAAAAElFTkSuQmCC","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Kuei-Chuan","middleName":"","lastName":"Lee","suffix":""},{"id":296866936,"identity":"a773fda9-9423-4c3f-b749-a4e5981c6e57","order_by":11,"name":"Ming-Chih Hou","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ming-Chih","middleName":"","lastName":"Hou","suffix":""}],"badges":[],"createdAt":"2024-04-26 08:04:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4328129/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4328129/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56043770,"identity":"efa224f2-0e66-492b-988d-b202264aa4c1","added_by":"auto","created_at":"2024-05-07 20:25:56","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1934852,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe composition and diversity of fecal microbiota in healthy subjects and cirrhotic patients.\u003c/strong\u003e Stacked bar plots of phylogenetic composition of common bacterial taxa (\u0026gt; 0.1% abundance) at the (A) phylum level and (B) family level in fecal samples of normal subjects and cirrhotic patients by 16 S rRNA sequencing. \u003cstrong\u003e(C) \u003c/strong\u003eAlpha diversity indices of fecal bacteria measured by Faith’s PD index and Shannon index. (D) Principal coordinate analysis of fecal microbiota by unweighted Unifrac distance metrics and Bray–Curtis distance. ****\u003cem\u003e p \u003c/em\u003e\u0026lt;0.0001, *** \u003cem\u003ep\u003c/em\u003e \u0026lt;0.001\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328129/v1/60f347314f8e79a504ffc081.jpg"},{"id":56043769,"identity":"b967d8c2-d071-4734-8e7f-736adc7ff3d9","added_by":"auto","created_at":"2024-05-07 20:25:56","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1822447,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe composition and diversity of fecal microbiota among healthy subjects, cirrhotic patients with fecal MDRO carriage (MDRO+) and without MDRO carriage (MDRO-). \u003c/strong\u003e(A) Alpha diversity indices of fecal bacteria measured by Faith’s PD index and Shannon index. (B) Principal coordinate analysis of fecal microbiota by unweighted Unifrac distance metrics and Bray–Curtis distance. (C) Linear discriminant analysis (LDA) effect size (LEfSe) showing differential abundance of taxa between fecal MDRO+ and MDRO− in cirrhotic patients. (D) Heatmap of the correlation analysis between the predominant bacterial taxa and plasma metabolites in cirrhotic patients with fecal MDRO carriage. MDRO, multidrug-resistant organism. ****\u003cem\u003ep \u003c/em\u003e\u0026lt;0.0001, *** \u003cem\u003ep\u003c/em\u003e \u0026lt;0.001, ** \u003cem\u003ep\u003c/em\u003e \u0026lt;0.01\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328129/v1/fd7eff317e765b2cf670bb1c.jpg"},{"id":56043772,"identity":"3884dd07-53a9-4298-be7f-ffb3c45adc43","added_by":"auto","created_at":"2024-05-07 20:25:56","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":981733,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression levels of six metabolites associated fecal microbiota in healthy subjects and MDRO carriers with (HE+) and without hepatic encephalopathy (HE-). \u003c/strong\u003eHE, hepatic encephalopathy.\u003c/p\u003e","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4328129/v1/1e19bc64badcfb8aa30561de.jpg"},{"id":56766289,"identity":"4eb8c82f-46b4-4146-96f7-a06324fa71ce","added_by":"auto","created_at":"2024-05-20 08:23:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5853725,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4328129/v1/e926ab83-467f-444c-ae16-f03690183314.pdf"},{"id":56043771,"identity":"45912998-a8f0-428c-8a08-149791fa3ad7","added_by":"auto","created_at":"2024-05-07 20:25:56","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":29166,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarydata0205.docx","url":"https://assets-eu.researchsquare.com/files/rs-4328129/v1/7e63272a8c1d1887b4adac5c.docx"}],"financialInterests":"","formattedTitle":"Fecal Carriage of Multidrug-Resistant Organisms Increases the Risk of Hepatic Encephalopathy in Cirrhotic Patients: Insights from Gut Microbiota and Metabolite Features","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCirrhosis is susceptible to infections [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The widespread use of antibiotics has rapidly increased the global prevalence of infections caused by multidrug-resistant organisms (MDROs) in patients with cirrhosis [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, the colonization of MDROs in such patients emerges as a critical factor for subsequent MDRO infections, contributing to a negative impact on overall survival [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The intestine serves as a main reservoir for MDROs [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and high rates of asymptomatic intestinal carriage of MDROs have been documented in patients with cirrhosis, particularly among those awaiting liver transplantation, or experiencing hepatic decompensation or critical illness [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn non-cirrhotic hospitalized patients, the composition of intestinal bacteria differs between those with and without rectal MDRO carriage, showing decreased diversity in MDRO carriers [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Certain commensals may protect against resistant bacteria in the intestine [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The successful decolonization of resistant pathogens in the gut through fecal microbiota transplantation further supports the role of the gut microbiota [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe composition of the gut microbiota in patients with cirrhosis differs from that of the general population [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This microbiota alteration, coupled with the impaired gut barrier function found in cirrhosis, further contributes to cirrhosis-associated complications, such as spontaneous bacterial peritonitis (SBP), hepatic encephalopathy (HE), hepatorenal syndrome, and acute on chronic liver failure [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Some data have shown poor survival in cirrhotic patients colonized or infected with MDROs; however, the impact of long-term fecal colonization by MDROs on specific outcomes related to cirrhosis remains unclear. Therefore, this study aimed to investigate the roles of fecal MDRO colonization and the associated metabolites in influencing clinical outcomes associated with cirrhosis.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and Data Collection\u003c/h2\u003e \u003cp\u003eThis prospective study was conducted at Taipei Veterans General Hospital between October 2018 and April 2022. Liver cirrhosis was diagnosed based on histological, clinical, biochemical, endoscopic, and imaging findings suggestive of cirrhosis in patients with chronic liver disease [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Patients with previous history of HE, active hepatocellular carcinoma status; malignancies other than hepatocellular carcinoma; with human immunodeficiency virus infection or severe comorbidities, such as chronic renal failure, heart failure, or chronic obstructive pulmonary disease; and those who received proton pump inhibitor, nonsteroidal anti-inflammatory drugs, antibiotics, or probiotics within 1 month were excluded. Twenty-two healthy adults without underlying systemic disease were enrolled as healthy controls. This study was approved by the Institutional Review Board of Taipei Veterans General Hospital (IRB No., 2017-09-013C and 2019-08-013A). Written informed consent was obtained from each participant.\u003c/p\u003e \u003cp\u003eDemographic characteristics, laboratory data, and medical history were collected. Blood and stool samples were collected on the day of enrollment. Stool samples from 18 hospitalized cirrhotic patients were collected in the ward, while samples from the remaining 70 cirrhotic outpatients and 22 healthy subjects were collected at home. Cirrhotic patients were followed for at least 1 year, or until death or liver transplant. During the follow-up period, clinical events were recorded, which included (1) complications of cirrhosis, such as SBP, overt HE [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], newly developed or worsening ascites, acute kidney injury, first or recurrent variceal bleeding; (2) newly diagnosed hepatocellular carcinoma; (3) bacterial infections; (4) death; or (5) liver transplant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDefinition of MDROs\u003c/h2\u003e \u003cp\u003eThe stool samples collected were inoculated onto selective agar plates at 37\u0026deg;C for 24 hours to detect MDROs. MDROs were defined as microorganisms that are resistant to at least one agent in three or more antimicrobial categories as characterized earlier [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. MDROs include methicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, vancomycin-resistant enterococci, and multidrug-resistant gram-negative bacilli, including \u003cem\u003eEnterobacterales, Pseudomonas aeruginosa\u003c/em\u003e, and \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e. Details of MDRO detection, processing and analysis of stool bacterial genomic data, as well as metabolite analysis are provided in Supplementary Methods.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of lipopolysaccharides\u003c/h2\u003e \u003cp\u003ePlasma lipopolysaccharides (LPS) were measured by enzyme-linked immunosorbent assay kits (Cloud-Clone Corp, Katy, TX, USA) according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eClinical data were expressed as median (25th \u0026minus;\u0026thinsp;75th percentiles) or as counts, as appropriate. The chi-square or Fisher\u0026rsquo;s exact test was used to analyze categorical variables and the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e-test was applied to assess continuous variables between MDRO carriers and non-carriers in the cirrhotic population. Cox regression analysis was performed to identify potential predictors for clinical outcomes. A logistic regression model was used to identify the risk factors for fecal carriage of MDROs. The cutoff values of Model for End-Stage Liver Disease score (MELD) and lipopolysaccharides (LPS) levels are determined using Youden's index. Variables with \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in the univariate analysis were included in the multivariable analysis. Statistical significance was defined as \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The Kruskal\u0026ndash;Wallis test was used to assess the metabolite differences among healthy controls, cirrhotic patients with and without MDROs, and among healthy controls, cirrhotic patients with and without HE. Data were considered significant when \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All statistical analysis were performed using IBM SPSS Statistics for Windows, Version 24.0 (IBM Corp. Armonk, NY, USA).\u003c/p\u003e \u003cp\u003e Detailed analyses for the gut microbiota and the metabolites are provided in Supplementary Methods.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFecal Microbiological Findings in Healthy Controls and Cirrhotic patients\u003c/h2\u003e \u003cp\u003eEighty-eight patients with cirrhosis and twenty-two healthy volunteers were enrolled. The median age and gender distribution were similar between the two populations (\u003cb\u003eSuppl. Table\u0026nbsp;1)\u003c/b\u003e. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e showed that the fecal MDRO colonization rate was higher in patients with cirrhosis than the healthy controls (33% vs. 9.1%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.026) Of the 29 cirrhotic patients with fecal MDRO carriage, 6 patients (30.7%) were colonized with \u0026ge;\u0026thinsp;2 MDROs. The most commonly isolated MDRO was extended-spectrum beta-lactamase producing \u003cem\u003eEscherichia coli\u003c/em\u003e (58.6%), followed by vancomycin-resistant \u003cem\u003eEnterococcus\u003c/em\u003e spp. (48.3%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAntimicrobial resistance in fecal cultures between healthy subjects and cirrhotic patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCirrhosis\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;88)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDRO colonized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (33.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroorganism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e (ESBL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (58.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (ESBL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (20.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (CRE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGram positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEnterococcus spp.\u003c/em\u003e (VRE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (48.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethicillin-Resistant \u003cem\u003eStaphylococcus Aureus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2 MDROs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (30.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eThe data are expressed as number (percent).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eMDRO, multidrug-resistant organism; ESBL, extended spectrum β-lactamase; CRE, Carbapenem-resistant Enterobacteriaceae; VRE, vancomycin-resistant Enterococcus\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics and Outcomes Between Cirrhotic Patients With and Without MDRO Carriage\u003c/h2\u003e \u003cp\u003eThe demographic data of the cirrhotic patients with and without fecal carriage of MDROs are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. No differences in terms of age, gender, etiology of cirrhosis, underlying comorbidities, and severity of liver disease were observed between MDRO carriers and non-carriers. MDRO carriers had higher plasma LPS levels (15.1 vs 10.4 ng/L, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) and a higher proportion of admission within 30 days (34.5% vs 13.6%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) compared to non-carriers. During a median of 16.4 months follow-up (range, 0.7\u0026ndash;40.4 months), 36 patients (40.1%) developed cirrhosis-associated complications within 1 year after enrollment \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. MDRO carriers had higher rates of HE occurrence than non-carriers (20.7 vs 3.4%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008). However, other cirrhotic complications, including infectious events, did not show a significant difference between MDRO carriers and non-carriers. Regarding the infectious events, 5 patients experienced SBP, while ten encountered other types of infections. Among the 10 patients with non-SBP infections, five had bacteremia, two had intra-abdominal infections, two had aspiration pneumonia, and one had a urinary tract infection. The positive culture rate for these infectious events was 53%, but none of the bacterial cultures identified were MDROs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics in cirrhotic patients with and without fecal carriage of MDROs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMDRO -\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMDRO +\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge, years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.75 (54.42\u0026ndash;65.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.36 (46.95\u0026ndash;64.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (76.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (79.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEtiology of cirrhosis (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eViral/alcohol/others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (71.2)/ 12 (20.3)/ 5 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (51.7)/ 8 (27.6)/ 6 (20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell (1000 /uL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3 (3.2\u0026ndash;5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1 (3-5.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.862\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet (1000/uL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 (58\u0026ndash;120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (46-117.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium (mEq/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140 (138\u0026ndash;142)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139 (136\u0026ndash;141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84 (0.72\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80 (0.7-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bilirubin (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4 (1-2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6 (0.9\u0026ndash;3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (22\u0026ndash;37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (21.5\u0026ndash;41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7 (3.3\u0026ndash;4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (3.1\u0026ndash;3.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26 (1.15\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.34 (1.16\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLPS (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.39 (8.73\u0026ndash;15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.1 (9.99\u0026ndash;20.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHepatocellular carcinoma\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.973\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePresence of ascites\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (48.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePresence of varices\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (89.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (86.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild-Pugh score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5\u0026ndash;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (5\u0026ndash;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild-Pugh class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA/B/C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (59.3)/ 19 (32.2)/ 5 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (44.8)/12 (41.4)/4 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMELD score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.48 (8.98\u0026ndash;13.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.55 (8.37\u0026ndash;16.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;30 days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;60 days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;90 days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (32.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (44.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eThe data are expressed as median (25th-75th percentiles), or number (percent).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eMDRO, multidrug-resistant organism; ALT, alanine aminotransferase; INR, international normalized ratio; LPS, lipopolysaccharide; MELD, Model for End-stage Liver Disease\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOutcomes in cirrhotic patients with and without fecal carriage of MDROs within one year of follow-up\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMDRO -\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMDRO +\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfections other than SBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHepatic encephalopathy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariceal bleeding\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcute kidney injury\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNewly onset ascites\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNewly developed HCC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiver transplant\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eThe data are expressed as number (percent).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eMDRO, multidrug-resistant organism; SBP, spontaneous bacterial peritonitis; HCC, hepatocellular carcinoma.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo identify potential predictors associated with HE within 1 year, Cox regression analysis was performed (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Univariate analysis showed that higher serum LPS levels (\u0026ge;\u0026thinsp;14.9 ng/mL), Child-Pugh class C, and fecal MDRO carriage were independent predictors for HE occurrence. Importantly, LPS\u0026thinsp;\u0026ge;\u0026thinsp;14.9 ng/mL and fecal MDRO carriage maintained their statistical significance on multivariable analysis, further supporting their association with HE occurrence. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the risk factors associated with fecal colonization of MDROs in cirrhotic patients. In the univariate analysis, higher serum LPS levels (\u0026ge;\u0026thinsp;11.9 ng/mL) and prior admission in the last 30 days were significant risk factors for fecal MDRO colonization. However, on multivariable analysis, prior admission within 30 days did not predict MDRO colonization. Only serum levels of LPS\u0026thinsp;\u0026ge;\u0026thinsp;11.9 ng/mL (OR\u0026thinsp;=\u0026thinsp;3.84; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009) remained an independent risk factor for MDRO colonization.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCox regression for hepatic encephalopathy within one year in cirrhotic patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariable analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95%CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95%CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale sex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026ndash;17.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType 2 diabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u0026ndash;2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlbumin (\u0026lt;\u0026thinsp;3.5/ \u0026ge; 3.5 g/dL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45\u0026ndash;7.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSodium (\u0026lt;\u0026thinsp;135 / \u0026ge; 135mEq/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80-19.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.091\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65\u0026ndash;32.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLPS (\u0026ge;\u0026thinsp;14.9/ \u0026lt; 14.9 ng/mL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.84-121.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.24\u0026ndash;97.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild-Pugh class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.60-17.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19\u0026ndash;6.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u0026ndash;46.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.060\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.18\u0026ndash;15.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.639\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMELD scores (\u0026ge;\u0026thinsp;10/ \u0026lt; 10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.60-39.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMDRO carriage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.35\u0026ndash;33.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.02\u0026ndash;29.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eHR, hazard ratio; CI, confidence interval; LPS, lipopolysaccharide; MDRO, multidrug-resistant organism\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisk factors for fecal MDRO carriage\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariable analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95%CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eOR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95%CI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.077\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.91-1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale sex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.41\u0026ndash;3.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType 2 diabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.35\u0026ndash;2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlbumin (\u0026lt;\u0026thinsp;3.5/ \u0026ge; 3.5 g/dL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u0026ndash;1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSodium (\u0026lt;\u0026thinsp;135 / \u0026ge; 135mEq/L )\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u0026ndash;5.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLPS (\u0026ge;\u0026thinsp;11.9/ \u0026lt; 11.9 ng/ml)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56\u0026ndash;10.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.40-10.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild-Pugh class\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.65\u0026ndash;4.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50\u0026ndash;9.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMELD scores (\u0026ge;\u0026thinsp;15/ \u0026lt; 15)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84\u0026ndash;6.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrior admission within 30 days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15\u0026ndash;9.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.026\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.38\u0026ndash;2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePresence of ascites\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.35\u0026ndash;2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eOR, odds ratio; CI, confidence interval; LPS, lipopolysaccharide; MDRO, multidrug-resistant organism\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFecal Microbiome Comparisons Among Healthy Adults, and Cirrhotic Patients With and Without Fecal MDRO Carriage\u003c/h2\u003e \u003cp\u003eCompared with healthy adults, Proteobacteria was predominant in the fecal samples of patients with liver cirrhosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). At the family level, Bacteroidaceae, Enterobacteriaceae, Lactobacillaceae and Streptococcaceae were increased, while Lachnospiraceae and Ruminococcaceae were decreased in the feces of cirrhotic patients \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). The richness and evenness of fecal microbiota measured by Faith\u0026rsquo;s PD index and Shannon index were significantly reduced in cirrhotic patients (both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Besides, the principal component analyses of unweighted UniFrac distance and Bray\u0026ndash;Curtis distance showed a significant bacterial dissimilarity between these two groups (both \u003cem\u003ep\u003c/em\u003e value\u0026thinsp;=\u0026thinsp;0.001 by PERMANOVA test; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe phylogenetic diversity of fecal microbiota measured by Faith\u0026rsquo;s PD index and Shannon index decreased significantly in cirrhotic patients with and without MDRO carriage when compared with healthy controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). No statistical significance was observed between patients with cirrhosis with and without MDROs; however, a trend toward decreased alpha diversity in patients with cirrhosis with MDROs was observed. According to the unweighted UniFrac metrics, a significant dissimilarity of fecal microbiota was observed both between healthy controls and cirrhotic patients regardless of MDRO carriage (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and between cirrhotic patients with and without MDRO colonization (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033). However, the MDRO-associated microbial dissimilarity was not significant when measured using the Bray\u0026ndash;Curtis distance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.134) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Furthermore, the results of LEfSe analysis showed a prominent abundance of \u003cem\u003eStreptococcus salivarius\u003c/em\u003e in MDRO carriers, while Megamonas genus was abundant in MDRO non-carriers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of Metabolomic Signature Associated with HE in Cirrhotic Patient With MDRO Carriage\u003c/h2\u003e \u003cp\u003eTotal 4869 untargeted metabolites in the plasma of cirrhotic patients by metabolomic analysis, of which 1618 metabolites were named. Thirty-two of the named metabolites that exhibited statistically significant differences in expression levels among healthy controls, cirrhotic patients with fecal MDROs, and those without MDROs were selected (\u003cb\u003eSuppl. Table\u0026nbsp;2\u003c/b\u003e). The correlation analysis between the 32 metabolites and the dominant bacteria taxa in cirrhotic patients with MDRO carriage was performed \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed\u003cb\u003e)\u003c/b\u003e. Six metabolites were identified to be correlated to specific microbiota expression patterns in patients carrying MDROs. A positive correlation between the presence of \u003cem\u003eClostridioides difficile\u003c/em\u003e and two metabolites\u0026mdash;isoaustin and 2,3-butanediol glucoside\u0026mdash;within cirrhotic patients carrying MDROs was observed \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed\u003cb\u003e)\u003c/b\u003e. Notably, these 2 metabolites expressed significantly higher levels in MDRO carriers than in non-carriers (\u003cb\u003eSuppl. Table\u0026nbsp;2\u003c/b\u003e). Conversely, a negative correlation was found between \u003cem\u003eClostridioides difficile\u003c/em\u003e and three other metabolites\u0026mdash;DG (14:0/18:0/0:0), thelephoric acid, and 5-(3',4',5'-trihydroxyphenyl)-gamma-valerolactone\u0026mdash;exhibiting diminished expression levels in MDRO carriers compared to non-carriers. In addition, \u003cem\u003eStreptococcus salivarius\u003c/em\u003e exhibited a negative correlation with a single metabolite, PE-NMe2(24:0/20:3(5Z,8Z,11Z)), which was downregulated compared with MDRO non-carriers (\u003cb\u003eSuppl. Table\u0026nbsp;2\u003c/b\u003e). There was no definitive positive correlation between \u003cem\u003eStreptococcus salivarius\u003c/em\u003e and the broader spectrum of metabolites. The expression levels of these six metabolites in MDRO carriers who experienced HE and those who did not were further analyzed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e); only isoaustin exhibited markedly higher expression in MDRO carriers who experienced HE than those who did not (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the cirrhotic patients with fecal MDRO colonization were at higher risk for occurrence of HE within 1 year compared to non-carriers. Furthermore, the presence of MDROs was associated with changes in gut microbiota diversity and alterations in specific metabolites, suggesting a connection between MDRO carriage and the increased risk of HE in cirrhotic patients.\u003c/p\u003e \u003cp\u003eHigh prevalence of MDRO colonization has been reported in cirrhotic patients with different conditions [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In cirrhotic patients waiting for liver transplant, the prevalence of MDRO colonization (from skin, oral and rectal samples) at listing was 20% and increased to 37% at transplantation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Prado \u003cem\u003eet al\u003c/em\u003e. observed that, among critically ill patients in the intensive care unit, patients with cirrhosis had a higher MDRO colonization rate than patients without cirrhosis at admission (28.7% vs 18.2%, respectively) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The present study also showed a high fecal MDRO colonization rate for cirrhotic patients with general condition (33%), which was higher than healthy subjects (9.1%).\u003c/p\u003e \u003cp\u003eMDRO colonization, associated with subsequent MDRO infections, is an independent predictor for poor short-term survival for patients with cirrhosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Nevertheless, there was no difference in infection or mortality rates between MDRO carriers and non-carriers, and no MDRO infectious events occurred during the follow-up period in our patient population. Instead, we found a higher rate of overt HE in MDRO carriers. These differences may be attributed to variations in liver disease severity at enrollment, with previous studies mainly focusing on end-stage liver disease or critical conditions, often in hospitalized patients [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In contrast, our study enrolled cirrhotic patients across all severities, with half being Child\u0026ndash;Pugh class A, and a majority (80%) being outpatients. Therefore, the present study provided important information regarding MDRO carriage on cirrhosis-associated outcomes for both hospitalized and community-dwelling patients with cirrhosis.\u003c/p\u003e \u003cp\u003eIn this study, higher serum LPS levels and fecal MDRO carriage helped to predict HE occurrence within the first year of follow-up. Patients with cirrhosis exhibit alteration of gut microbiota [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], which in turn increases the gut permeability and facilitates the translocation of bacterial products into systemic circulation, worsening endotoxemia. The altered microbiota compositions in cirrhotic patients might diminish the protective power of several \u003cem\u003ec\u003c/em\u003eommensals against colonization of pathogenic bacteria, including MDROs, in the host intestine [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. LPS is a gut-derived endotoxin produced by Gram-negative bacteria that enters systemic circulation from the disrupted intestinal barrier in cirrhotic patients [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Therefore, patients with high LPS levels might have disturbed gut homeostasis and be more susceptible to colonization of pathogenic bacteria such as MDROs. Besides, a close correlation has been found between HE and the altered microbiota in cirrhosis [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Zhang \u003cem\u003eet al.\u003c/em\u003e found a greater abundance of the gut ammonia-increasing bacteria \u003cem\u003eStreptococcus salivarius\u003c/em\u003e in cirrhotic patients with minimal HE than in those without minimal HE [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Bajaj \u003cem\u003eet al.\u003c/em\u003e reported that the colonic mucosal microbiota composition, rather than the stool microbiota, differed between patients with overt HE and without HE [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], with a greater abundance of Enterococcus, Veillonella, Megasphaera, Bifidobacterium, and Burkholderia in patients with HE; in that study, the presence of Enterococcus, Megasphaera, and Burkholderia were linked to poor cognition and inflammation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Reduced microbial diversity and change in microbiota composition have been reported in non-cirrhotic patients with MDRO carriage in comparison with those without MDRO carriage [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Araos \u003cem\u003eet al.\u003c/em\u003e showed that, in hospitalized non-cirrhotic patients, a greater abundance of Enterococcus spp. in MDRO carriers and microbiota belonging to Bacteroidales order in non-carriers, respectively [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Among older residents of nursing homes, \u003cem\u003eOdoribacter laneus\u003c/em\u003e, and \u003cem\u003eAkkermansia muciniphila\u003c/em\u003e were predominant in MDRO carriers, whereas \u003cem\u003eBlautia hydrogenotrophica\u003c/em\u003e was predominant in non-carriers [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Consistently, in the present study, we observed that the gut microbiota composition was different between patients with and without MDRO carriage. We found a prominent abundance of \u003cem\u003eStreptococcus salivarius\u003c/em\u003e in MDRO carriers, while Megamonas genus was abundant in MDRO non-carriers. Interestingly, the most abundant bacteria in MDRO carriers\u0026mdash;\u003cem\u003eStreptococcus salivarius\u003c/em\u003e\u0026mdash; belongs to the urease-producing bacteria; this may partially explain why the rate of HE in this group was higher than that in the study by Zhang \u003cem\u003eet al\u003c/em\u003e [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to the gut microbiota, the bacterial associated metabolites can also influence the gut-liver-brain axis, which in turn contributes to HE development [\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, data regarding the interaction of MDROs and the gut bacteria associated metabolites with HE development in cirrhosis is limited. Our study demonstrated that of six of the metabolites correlated with the microbiota in MDRO carriers, a higher level of isoaustin was expressed in MDRO carriers with HE than in MDRO carriers without HE. However, the biological role of isoaustin in the human body has not yet been addressed. In our study, it remained unclear whether MDRO-associated metabolites are contributors or consequences of MDRO carriage. However, bacterial metabolism alterations could potentially contribute to antibiotic resistance by affecting energy production, modifying cell envelope compositions, and adjusting cell-to-cell interactions in biofilms [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The role of metabolites in antibiotic resistance was supported by Ji\u0026rsquo;s study [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. They found a suppression of glutathione oxidized and citrulline abundances in \u003cem\u003eSalmonella Derby\u003c/em\u003e with drug resistance to third-generation cephalosporin; the susceptibility of multidrug-resistant \u003cem\u003eSalmonella Derby\u003c/em\u003e to third-generation cephalosporin was further restored by exogenous glutathione oxidized or citrulline [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Taken together, changes of gut microbiota in cirrhosis might contribute to the metabolite alterations, with both factors promoting the growth of resistant bacteria in a given selective environment and inducing HE development. This suggests a dynamic relationship between the gut microbiota, metabolic changes, bacterial resistance, and HE development. Though the precise interaction between these factors was not disclosed in our study, our results provide new insights into the impact of MDRO carriage and metabolites in the cirrhotic population with occurrence of HE. Further research in this domain is crucial to unravel the mechanisms and potential therapeutic strategies to mitigate the impact of these interactions.\u003c/p\u003e \u003cp\u003eThis study had some limitations. First, this was a single-center study performed in Taiwan. Therefore, the prevalence and distribution of MDROs might be different to those observed in other countries. Second, due to the observational nature of the study, detecting minimal HE events was challenging, preventing an assessment of the impact of microbiota and associated metabolites on patients with minimal HE. Third, many of the untargeted metabolites remained undiscovered, and only named metabolites were analyzed. Lastly, isoaustin was found to correlate with HE development in MDRO carriers; however, the biological role of isoaustin and its underlying mechanism remain unclear. The difficulty in obtaining these metabolites prevents us from conducting experimental studies to elucidate their roles. Nevertheless, our study uncovered a new impact on the correlation between MDROs, microbiota and the associated metabolites on HE.\u003c/p\u003e \u003cp\u003eIn conclusion, the present study demonstrated the association between fecal colonization of MDROs, altered gut microbiota, metabolite modulation, and an elevated risk of HE occurrence among cirrhotic patients. The findings provide information to identify patients who may benefit from aggressive surveillance of fecal MDROs and to establish a treatment policy for decolonization in cirrhotic patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge Ms. Kai-Ting Wang, Yu-Chieh Tsai, Yi-Ru Huang, and Ching-Hsuan Chen for their excellent technical assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePei-Shan Wu and Kuei-Chuan Lee conceived and designed the study. Pei-Shan Wu, Pei-Chang Lee, Tien-En Chang, Yun-Cheng Hsieh, Kuei-Chuan Lee, Yi-Tsung Lin, Teh-Ia Huo, and Ming-Chih Hou collected the data. Pei-Shan Wu, Pei-Chang Lee, Ueng-Cheng Yang, Jen-Jie Chiou, Chao-Hsiung Lin, Yi-Long Huang, Kuei-Chuan Lee and Bernd Schnabl analyzed and interpretated the data. Pei-Shan Wu and Kuei-Chuan Lee drafted the manuscript. Kuei-Chuan Lee, Ming-Chih Hou, and Bernd Schnabl provided critical revision during the drafting of the manuscript. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Taipei Veterans General Hospital (Grant No. V113B-022 and V113C-098), National Science and Technology Council (Grant No. NSTC 112-2314-B-075-032, and MOST 111-2314-B-075-051-MY3), and services provided by the San Diego Digestive Diseases Research Center (SDDRC) P30 DK120515.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData available on request from the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approval by the institutional research ethics committees at Taipei Veterans General Hospital (IRB No., 2017-09-013C and 2019-08-013A).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from each participant.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArvaniti V, D\u0026apos;Amico G, Fede G, et al. 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Infect Dis Ther. 2019;8:469-482.\u003c/li\u003e\n\u003cli\u003eFerstl PG, Filmann N, Heilgenthal EM, et al. Colonization with multidrug-resistant organisms is associated with in increased mortality in liver transplant candidates. PLoS One. 2021;16:e0245091.\u003c/li\u003e\n\u003cli\u003eAraos R, Montgomery V, Ugalde JA, et al. Microbial Disruption Indices to Detect Colonization With Multidrug-Resistant Organisms. Infect Control Hosp Epidemiol. 2017;38:1312-1318.\u003c/li\u003e\n\u003cli\u003eAraos R, Tai AK, Snyder GM, et al. Predominance of Lactobacillus spp. Among Patients Who Do Not Acquire Multidrug-Resistant Organisms. Clin Infect Dis. 2016;63:937-943.\u003c/li\u003e\n\u003cli\u003eGarcia ER, Vergara A, Aziz F, et al. Changes in the gut microbiota and risk of colonization by multidrug-resistant bacteria, infection, and death in critical care patients. Clin Microbiol Infect. 2022;28:975-982.\u003c/li\u003e\n\u003cli\u003eIsles NS, Mu A, Kwong JC, et al. Gut microbiome signatures and host colonization with multidrug-resistant bacteria. Trends Microbiol. 2022;30:853-865.\u003c/li\u003e\n\u003cli\u003ePanwar RB, Sequeira RP, Clarke TB. Microbiota-mediated protection against antibiotic-resistant pathogens. Genes Immun. 2021;22:255-267.\u003c/li\u003e\n\u003cli\u003eSaha S, Tariq R, Tosh PK, et al. Faecal microbiota transplantation for eradicating carriage of multidrug-resistant organisms: a systematic review. Clin Microbiol Infect. 2019;25:958-963.\u003c/li\u003e\n\u003cli\u003eBajaj JS, Khoruts A. Microbiota changes and intestinal microbiota transplantation in liver diseases and cirrhosis. J Hepatol. 2020;72:1003-1027.\u003c/li\u003e\n\u003cli\u003eBajaj JS, Heuman DM, Hylemon PB, et al. Altered profile of human gut microbiome is associated with cirrhosis and its complications. J Hepatol. 2014;60:940-7.\u003c/li\u003e\n\u003cli\u003eSeo YS, Shah VH. 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Large-scale survey of gut microbiota associated with MHE Via 16S rRNA-based pyrosequencing. Am J Gastroenterol. 2013;108:1601-11.\u003c/li\u003e\n\u003cli\u003eBajaj JS, Ridlon JM, Hylemon PB, et al. Linkage of gut microbiome with cognition in hepatic encephalopathy. Am J Physiol Gastrointest Liver Physiol. 2012;302:G168-75.\u003c/li\u003e\n\u003cli\u003eBajaj JS, Hylemon PB, Ridlon JM, et al. Colonic mucosal microbiome differs from stool microbiome in cirrhosis and hepatic encephalopathy and is linked to cognition and inflammation. Am J Physiol Gastrointest Liver Physiol. 2012;303:G675-85.\u003c/li\u003e\n\u003cli\u003eAraos R, Battaglia T, Ugalde JA, et al. Fecal Microbiome Characteristics and the Resistome Associated With Acquisition of Multidrug-Resistant Organisms Among Elderly Subjects. Front Microbiol. 2019;10:2260.\u003c/li\u003e\n\u003cli\u003eIebba V, Guerrieri F, Di Gregorio V, et al. 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Drug Discov Today. 2022;27:1774-1783.\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez JL, Rojo F. Metabolic regulation of antibiotic resistance. FEMS Microbiol Rev. 2011;35:768-89.\u003c/li\u003e\n\u003cli\u003eJi J, Wu S, Sheng L, et al. Metabolic reprogramming of the glutathione biosynthesis modulates the resistance of Salmonella Derby to ceftriaxone. iScience. 2023;26:107263.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Multidrug resistant organisms, cirrhosis, complications, microbiota, metabolite, hepatic encephalopathy","lastPublishedDoi":"10.21203/rs.3.rs-4328129/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4328129/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eImpact of fecal colonization by multidrug-resistant organisms (MDROs) on changes in gut microbiota and associated metabolites, as well as its role in cirrhosis-associated outcomes, has not been thoroughly investigated.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eEighty-eight cirrhotic patients and 22 healthy volunteers were prospectively enrolled with analysis conducted on plasma metabolites, fecal MDROs, and microbiota. Patients were followed for a minimum of one year. Predictive factors for cirrhosis-associated outcomes were identified using Cox proportional hazards regression models, and risk factors for fecal MDRO carriage were assessed using logistic regression model. Correlations between microbiota and metabolic profiles were evaluated through Spearman's rank test.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTwenty-nine (33%) cirrhotic patients exhibited MDRO carriage, with a notably higher rate of hepatic encephalopathy (HE) in MDRO carriers (20.7% vs. 3.2%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008). Cox regression analysis identified higher serum lipopolysaccharide levels and fecal MDRO carriage as predictors for HE development. Logistic regression analysis showed that MDRO carriage is an independent risk factor for developing HE. Microbiota analysis showed a significant dissimilarity of fecal microbiota between cirrhotic patients with and without MDRO carriage (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033). Thirty-two metabolites exhibiting significantly different expression levels among healthy controls, cirrhotic patients with and without MDRO carriage were identified. Six of the metabolites showed correlation with specific bacterial taxa expression in MDRO carriers, with isoaustin showing significantly higher levels in MDRO carriers experiencing HE compared to those who did not.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eFecal MDRO carriage is associated with altered gut microbiota, metabolite modulation, and an elevated risk of HE occurrence within a year.\u003c/p\u003e","manuscriptTitle":"Fecal Carriage of Multidrug-Resistant Organisms Increases the Risk of Hepatic Encephalopathy in Cirrhotic Patients: Insights from Gut Microbiota and Metabolite Features","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-07 20:25:51","doi":"10.21203/rs.3.rs-4328129/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f13a7a5-2333-43ac-b731-0ff867fc36b2","owner":[],"postedDate":"May 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-20T08:15:50+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-07 20:25:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4328129","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4328129","identity":"rs-4328129","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}