Prevalence, risk factors, and impact on clinical outcome of extended-spectrum beta-lactamase-producing Escherichia coli bacteraemia: a five-year study

Denis, Brigitte; Lafaurie, Matthieu; Donay, Jean-Luc; Fontaine, Jean-Paul; Oksenhendler, Éric; Raffoux, Emmanuel; Hennequin, C.; Allez, Matthieu; Socié, G.; Maziers, Nicolas; Porcher, Raphaël; Molina, Jean Michel

doi:10.1016/j.ijid.2015.07.010

Cited by 88 publications

(74 citation statements)

References 19 publications

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“…Our study also demonstrated a significant association between previous antibiotic use and CTXNS-En bacteremia in the univariate analysis. Prior isolation of CTXNS-En also appears to be a potent risk factor [4, 6, 24], as shown in our study. These common risk factors found in both previous studies and our study may help to identify patients with CTXNS-En bacteremia.…”

Section: Discussionsupporting

confidence: 75%

Clinical and microbiologic characteristics of cefotaxime-non-susceptible Enterobacteriaceae bacteremia: a case control study

et al. 2017

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BackgroundCefotaxime plays an important role in the treatment of patients with bacteremia due to Enterobacteriaceae, although cefotaxime resistance is reported to be increasing in association with extended-spectrum β-lactamase (ESBL) and AmpC β-lactamase (AmpC).MethodsWe conducted a case-control study in a Japanese university hospital between 2011 and 2012. We assessed the risk factors and clinical outcomes of bacteremia due to cefotaxime-non-susceptible Enterobacteriaceae (CTXNS-En) and analyzed the resistance mechanisms.ResultsOf 316 patients with Enterobacteriaceae bacteremia, 37 patients with bacteremia caused by CTXNS-En were matched to 74 patients who had bacteremia caused by cefotaxime-susceptible Enterobacteriaceae (CTXS-En). The most common CTXNS-En was Escherichia coli (43%), followed by Enterobacter spp. (24%) and Klebsiella spp. (22%). Independent risk factors for CTXNS-En bacteremia included previous infection or colonization of CTXNS-En, cardiac disease, the presence of intravascular catheter and prior surgery within 30 days. Patients with CTXNS-En bacteremia were less likely to receive appropriate empirical therapy and to achieve a complete response at 72 h than patients with CTXS-En bacteremia. Mortality was comparable between CTXNS-En and CTXS-En patients (5 vs. 3%). CTXNS-En isolates exhibited multidrug resistance but remained highly susceptible to amikacin and meropenem. CTX-M-type ESBLs accounted for 76% of the β-lactamase genes responsible for CTXNS E. coli and Klebsiella spp. isolates, followed by plasmid-mediated AmpC (12%). Chromosomal AmpC was responsible for 89% of CTXNS Enterobacter spp. isolates.ConclusionsCTXNS-En isolates harboring ESBL and AmpC caused delays in appropriate therapy among bacteremic patients. Risk factors and antibiograms may improve the selection of appropriate therapy for CTXNS-En bacteremia. Prevalent mechanisms of resistance in CTXNS-En were ESBL and chromosomal AmpC.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-016-2150-6) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 75%

Clinical and microbiologic characteristics of cefotaxime-non-susceptible Enterobacteriaceae bacteremia: a case control study

et al. 2017

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“…Not surprisingly, risk factors and exposures associated with antimicrobial resistance in this study were largely consistent with previous reports [28][29][30][31][32][33][34][35]. The most important independent risk factors for both hospital and community acquisition of all three resistant bacteria were hospital prevalence of the resistant pathogen, admission source, and previous hospital admission within the prior 6 months [28][29][30][32][33][34][35]. All three of these factors capture time at risk in healthcare facilities among patient populations predisposed to infection by antibiotic-resistant pathogens [28][29][30][31][32][33][34][35] and highlight the importance of understanding the prevalence of a given antibiotic-resistant phenotype in an institution.…”

Section: -Gcr Mdrpsupporting

confidence: 92%

“…Using the Premier Hospital database, which included 124,068 hospital admissions from approximately 160 institutions that contributed microbiology data during the period from January 1, 2011, to October 1, 2015, we first identified the infection-, patient-, and hospital-level risk factors that increase the probability of having an infection due to 3GC-R, CRE, or MDRP. Not surprisingly, risk factors and exposures associated with antimicrobial resistance in this study were largely consistent with previous reports [28][29][30][31][32][33][34][35]. The most important independent risk factors for both hospital and community acquisition of all three resistant bacteria were hospital prevalence of the resistant pathogen, admission source, and previous hospital admission within the prior 6 months [28][29][30][32][33][34][35].…”

Section: -Gcr Mdrpsupporting

confidence: 91%

“…The most important independent risk factors for both hospital and community acquisition of all three resistant bacteria were hospital prevalence of the resistant pathogen, admission source, and previous hospital admission within the prior 6 months [28][29][30][32][33][34][35]. All three of these factors capture time at risk in healthcare facilities among patient populations predisposed to infection by antibiotic-resistant pathogens [28][29][30][31][32][33][34][35] and highlight the importance of understanding the prevalence of a given antibiotic-resistant phenotype in an institution. Another common risk factor for 3GC-R, CRE, and MDRP infection among individuals with hospital-acquired Gram-negative infections was the number of antibiotics received during the current admission [28][29][30][31][32][33][34][35].…”

Section: -Gcr Mdrpmentioning

confidence: 99%

“…All three of these factors capture time at risk in healthcare facilities among patient populations predisposed to infection by antibiotic-resistant pathogens [28][29][30][31][32][33][34][35] and highlight the importance of understanding the prevalence of a given antibiotic-resistant phenotype in an institution. Another common risk factor for 3GC-R, CRE, and MDRP infection among individuals with hospital-acquired Gram-negative infections was the number of antibiotics received during the current admission [28][29][30][31][32][33][34][35]. Constant and cumulative exposure to antibiotics disturbs the natural bacterial flora, in particular in the gastrointestinal tract, and predisposes patients to colonization by resistant phenotypes.…”

Section: -Gcr Mdrpmentioning

confidence: 99%

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Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections

Lodise

Bonine

et al. 2019

BMC Infect Dis

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Background We developed a clinical bedside tool to simultaneously estimate the probabilities of third-generation cephalosporin-resistant Enterobacteriaceae (3GC-R), carbapenem-resistant Enterobacteriaceae (CRE), and multidrug-resistant Pseudomonas aeruginosa (MDRP) among hospitalized adult patients with Gram-negative infections. Methods Data were obtained from a retrospective observational study of the Premier Hospital that included hospitalized adult patients with a complicated urinary tract infection (cUTI), complicated intra-abdominal infection (cIAI), hospital-acquired/ventilator-associated pneumonia (HAP/VAP), or bloodstream infection (BSI) due to Gram-negative bacteria between 2011 and 2015. Risk factors for 3GC-R, CRE, and MDRP were ascertained by multivariate logistic regression, and separate models were developed for patients with community-acquired versus hospital-acquired infections for each resistance phenotype ( N = 6). Models were converted to a singular user-friendly interface to estimate the probabilities of a patient having an infection due to 3GC-R, CRE, or MDRP when ≥ 1 risk factor was present. Results Overall, 124,068 patients contributed to the dataset. Percentages of patients admitted for cUTI, cIAI, HAP/VAP, and BSI were 61.6, 4.6, 16.5, and 26.4%, respectively (some patients contributed > 1 infection type). Resistant infection rates were 1.90% for CRE, 12.09% for 3GC-R, and 3.91% for MDRP. A greater percentage of the resistant infections were community-acquired relative to hospital-acquired (CRE, 1.30% vs 0.62% of 1.90%; 3GC-R, 9.27% vs 3.42% of 12.09%; MDRP, 2.39% vs 1.59% of 3.91%). The most important predictors of having an 3GC-R, CRE or MDRP infection were prior number of antibiotics; infection site; infection during the previous 3 months; and hospital prevalence of 3GC-R, CRE, or MDRP. To enable application of the six predictive multivariate logistic regression models to real-world clinical practice, we developed a user-friendly interface that estimates the risk of 3GC-R, CRE, and MDRP simultaneously in a given patient with a Gram-negative infection based on their risk (Additional file 1). Conclusions We developed a clinical prediction tool to estimate the probabilities of 3GC-R, CRE, and MDRP among hospitalized adult patients with confirmed community- and hospital-acquired Gram-negative infections. Our predictive model has been implemented as a user-friendly bedside tool for use by clinicians/healthcare professionals to predict the probability of resistant infections in individual patients, to guide early appropriate therapy. Electronic supplementary material The online version of this article (10.1186/s12879-019-4363-y) contains supplementary material, which is available to authorized users.

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Colonization with multidrug-resistant bacteria increases the risk of complications and a fatal outcome after allogeneic hematopoietic cell transplantation

et al. 2017

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Composition of the gut microbiota seems to influence early complications of allogeneic hematopoietic cell transplantation (HCT) such as bacterial infections and acute graft-versus-host disease (GVHD). In this study, we assessed the impact of colonization with multidrug-resistant bacteria (MDRB) prior to HCT and the use of antibiotics against anaerobic bacteria on the outcomes of HCT. We retrospectively analyzed the data of 120 patients who underwent HCT for hematologic disorders between 2012 and 2014. Fifty-one (42.5%) patients were colonized with MDRB and 39 (32.5%) had infections caused by MDRB. Prior colonization was significantly correlated with MDRB infections (P < 0.001), especially bacteremia (P = 0.038). A higher incidence of MDRB infections was observed in patients with acute (P = 0.014) or chronic (P = 0.002) GVHD and in patients aged > 40 years (P = 0.002). Colonization had a negative impact on overall survival (OS) after HCT (64 vs. 47% at 24 months; P = 0.034) and infection-associated mortality (P < 0.001). Use of metronidazole was correlated with an increased incidence of acute GVHD (P < 0.001) and lower OS (P = 0.002). Patients colonized with MDRB are more susceptible to life-threatening infections. Colonization with virulent flora is the most probable source of neutropenic infection; therefore, information about prior positive colonization should be crucial for the selection of empiric antibiotic therapy. The use of metronidazole, affecting the biodiversity of the intestinal microbiome, seems to have a significant impact on OS and acute GVHD.

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Prevalence, risk factors, and impact on clinical outcome of extended-spectrum beta-lactamase-producing Escherichia coli bacteraemia: a five-year study

Cited by 88 publications

References 19 publications

Clinical and microbiologic characteristics of cefotaxime-non-susceptible Enterobacteriaceae bacteremia: a case control study

Clinical and microbiologic characteristics of cefotaxime-non-susceptible Enterobacteriaceae bacteremia: a case control study

Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections

Colonization with multidrug-resistant bacteria increases the risk of complications and a fatal outcome after allogeneic hematopoietic cell transplantation

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