A model to predict mortality following Pseudomonas aeruginosa bacteremia

Hirsch, Elizabeth B.; Cottreau, Jessica; Chang, Kai Tai; Caeiro, Juan Pablo; Johnson, Michael L.; Tam, Vincent H.

doi:10.1016/j.diagmicrobio.2011.09.018

Cited by 24 publications

(11 citation statements)

References 22 publications

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“…Often, patients with a higher severity of illness receive therapy with multiple agents due to an increased risk of mortality (24). In our study, there were no differences in infection-related severity of illness between patients who received combination and monotherapy.…”

Section: Discussionmentioning

confidence: 37%

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Outcomes of Appropriate Empiric Combination versus Monotherapy for Pseudomonas aeruginosa Bacteremia

Bowers

Liew

Lye

et al. 2013

Antimicrob Agents Chemother

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e Pseudomonas aeruginosa bacteremia is associated with high hospital mortality. Empirical combination therapy is commonly used to increase the likelihood of appropriate therapy, but the benefits of employing >1 active agent have yet to be established. The purpose of this study was to compare outcomes of patients receiving appropriate empirical combination versus monotherapy for P. aeruginosa bacteremia. This was a retrospective, multicenter, cohort study of hospitalized adult patients with P. aeruginosa bacteremia from 2002 to 2011. The primary endpoint (30-day mortality) was assessed using multivariate logistic regression, adjusting for underlying confounding variables. Secondary endpoints of hospital mortality and time to mortality were assessed by Fisher's exact test and the Cox proportional hazards model, respectively. A total of 384 patients were analyzed. Thirtyday mortality was higher for patients receiving inappropriate therapy than for those receiving appropriate empirical therapy (43.8% versus 21.5%; P ‫؍‬ 0.03). However, there were no statistical differences in 30-day mortality following appropriate empirical combination versus monotherapy after adjusting for baseline APACHE II scores and lengths of hospital stay prior to the onset of bacteremia (P ‫؍‬ 0.55). Observed hospital mortality was 36.6% for patients administered combination therapy, compared with 28.7% for monotherapy patients (P ‫؍‬ 0.17). After adjusting for baseline APACHE II scores, the relationship between time to mortality and combination therapy was not statistically significant (P ‫؍‬ 0.59). Overall, no significant differences were observed for 30-day mortality, hospital mortality, and time to mortality between combination and monotherapy for P. aeruginosa bacteremia. Empirical combination therapy did not appear to offer an additional benefit, as long as the isolate was susceptible to at least one antimicrobial agent.

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Section: Discussionmentioning

confidence: 37%

“…Lastly, we did not stratify patients with MDR strains. Isolation of an MDR strain is an independent risk factor for 30-day mortality (24) and may have been a confounding variable in our study.…”

Section: Discussionmentioning

confidence: 76%

Outcomes of Appropriate Empiric Combination versus Monotherapy for Pseudomonas aeruginosa Bacteremia

Bowers

Liew

Lye

et al. 2013

Antimicrob Agents Chemother

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“…This latter effect is, in part, attributable to (i) the organism's intrinsically high resistance to many antimicrobials (Giamarellos-Bourboulis et al 2006) and (ii) the development of increased, particularly multidrug, resistance in health care settings (Bodro et al 2013(Bodro et al , 2014Chaisathaphol and Chayakulkeeree 2014;Chen et al 2013;Chittawatanarat et al 2014;Folgori et al 2014;Medell et al 2012;Pena et al 2013;Pourakbari et al 2012;Xiao et al 2012), both of which complicate antipseudomonal chemotherapy (Chaisathaphol and Chayakulkeeree 2014;Chittawatanarat et al 2014;Chung et al 2011;Folgori et al 2014;Hirsch et al 2012;Hirsch and Tam 2010;Kallen et al 2010;Keen et al 2010; Kerr and Snelling the Multidrug and Toxic Compound Export family, and the Resistance Nodulation Division (RND) family (Li and Nikaido 2009). While examples of all of these have been reported in P. aeruginosa (Poole 2013), by far the most significant contributors to resistance to clinically relevant agents and in clinical isolates are in the RND family (Poole 2001(Poole , 2004a(Poole , 2004b(Poole , 2005b(Poole , 2007Poole and Srikumar 2001).…”

Section: Pseudomonas Aeruginosa -A Very Resistant Organismmentioning

confidence: 97%

“…Pseudomonas aeruginosa is a common nosocomial pathogen (Azzopardi et al 2014;Bereket et al 2012;Berezin and Solorzano 2014;Bursle et al 2014;Chen and Hsueh 2012;Chung et al 2011;Hidron et al 2008;Hirsch et al 2012;Karakoc et al 2013;Ploypetch et al 2013;Ranjan et al 2014;Rattanaumpawan et al 2013;Rello et al 2014;Resende et al 2013;Sandiumenge and Rello 2012;Zhanel et al 2008Zhanel et al , 2010 that causes infections with a high mortality rate (Chung et al 2011;Kerr and Snelling 2009;Lambert et al 2011;Mahar et al 2010;Mutlu and Wunderink 2006;Ranjan et al 2014;Rattanaumpawan et al 2013). This latter effect is, in part, attributable to (i) the organism's intrinsically high resistance to many antimicrobials (Giamarellos-Bourboulis et al 2006) and (ii) the development of increased, particularly multidrug, resistance in health care settings (Bodro et al 2013(Bodro et al , 2014Chaisathaphol and Chayakulkeeree 2014;Chen et al 2013;Chittawatanarat et al 2014;Folgori et al 2014;Medell et al 2012;Pena et al 2013;Pourakbari et al 2012;Xiao et al 2012), both of which complicate antipseudomonal chemotherapy (Chaisathaphol and Chayakulkeeree 2014;Chittawatanarat et al 2014;Chung et al...…”

Section: Pseudomonas Aeruginosa -A Very Resistant Organismmentioning

confidence: 99%

Stress responses as determinants of antimicrobial resistance in Pseudomonas aeruginosa: multidrug efflux and more

Poole

2014

Can. J. Microbiol.

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Pseudomonas aeruginosa is a notoriously antimicrobial-resistant organism that is increasingly refractory to antimicrobial chemotherapy. While the usual array of acquired resistance mechanisms contribute to resistance development in this organism a multitude of endogenous genes also play a role. These include a variety of multidrug efflux loci that contribute to both intrinsic and acquired antimicrobial resistance. Despite their roles in resistance, however, it is clear that these efflux systems function in more than just antimicrobial efflux. Indeed, recent data indicate that they are recruited in response to environmental stress and, therefore, function as components of the organism's stress responses. In fact, a number of endogenous resistance-promoting genes are linked to environmental stress, functioning as part of known stress responses or recruited in response to a variety of environmental stress stimuli. Stress responses are, thus, important determinants of antimicrobial resistance in P. aeruginosa. As such, they represent possible therapeutic targets in countering antimicrobial resistance in this organism.

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“…Pseudomonas aeruginosa is a leading cause of nosocomial infections [1, 2], which are often life threatening [3]. Recently, actual minimal inhibitory concentrations (MICs) of fluoroquinolones [4], extended-spectrum penicillins [5], and carbapenems [6] have predicted patient outcomes more accurately than did the categorical classification of MICs as susceptible, intermediate, and resistant.…”

Section: Introductionmentioning

confidence: 99%

Influence of borderline cefepime MIC on the outcome of cefepime-susceptible Pseudomonas aeruginosa bacteremia treated with a maximal cefepime dose: a hospital-based retrospective study

Yang

et al. 2017

Ann Clin Microbiol Antimicrob

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BackgroundWe assessed the influence of current cefepime minimal inhibitory concentration (MIC) breakpoints and the maximal cefepime dose on treatment outcomes in patients with bacteremia caused by cefepime-susceptible Pseudomonas aeruginosa.MethodsAdult patients hospitalized between July 2010 and June 2014 with a positive blood culture for cefepime-susceptible P. aeruginosa and receipt of cefepime as the primary therapy throughout the course were reviewed. Cefepime Etest® MICs and clinical outcomes for P. aeruginosa bacteremia were reviewed to identify the MIC breakpoint influencing treatment outcomes.ResultsOf the 90 patients enrolled, 49 (54.4%) were male (mean age = 66.8 years). The mean Acute Physiology and Chronic Health Evaluation II score was 22.01. Sixty patients (66.7%) received a maximal cefepime dose, and the 30-day crude mortality rate was 36.7%. MIC90 of cefepime for P. aeruginosa was 8 mg/L. The cumulative survival rate at 30 days revealed that a lower cefepime MIC (<4 mg/L) for P. aeruginosa was associated with a higher survival rate than a higher MIC (≥4 mg/L) (72.6% vs. 23.5%, p < 0.0001). A cefepime MIC of ≥4 mg/L and age were independent risk factors for mortality, whereas the maximal cefepime dose was the independent protective factor. The use of a maximal cefepime dose did not improve the outcomes of patients with P. aeruginosa bacteremia at a MIC of ≥4 mg/L.ConclusionsA cefepime MIC of 4 mg/L may predict an unfavorable outcome among patients with serious infections caused by P. aeruginosa, even the MICs still within the CLSI susceptibility breakpoint.

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A model to predict mortality following Pseudomonas aeruginosa bacteremia

Cited by 24 publications

References 22 publications

Outcomes of Appropriate Empiric Combination versus Monotherapy for Pseudomonas aeruginosa Bacteremia

Outcomes of Appropriate Empiric Combination versus Monotherapy for Pseudomonas aeruginosa Bacteremia

Stress responses as determinants of antimicrobial resistance in Pseudomonas aeruginosa: multidrug efflux and more

Influence of borderline cefepime MIC on the outcome of cefepime-susceptible Pseudomonas aeruginosa bacteremia treated with a maximal cefepime dose: a hospital-based retrospective study

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