- Email: [email protected]
Rates, predictors and mortality of community-onset bloodstream infections due to Pseudomonas aeruginosa: systematic review and meta-analysis
Clinical Microbiology and Infection 25 (2019) 964e970
Contents lists available at ScienceDirect
Clinical Microbiology and Infection journal homepage: www.clinicalmicrobiologyandinfection.com
Systematic review
Rates, predictors and mortality of community-onset bloodstream infections due to Pseudomonas aeruginosa: systematic review and meta-analysis pez-Corte s 2, *, J. Rodríguez-Ban ~o 2 A. Rojas 1, Z.R. Palacios-Baena 2, L.E. Lo lica de Chile, Santiago, Chile Departamento de Enfermedades Infecciosas del Adulto, Facultad de Medicina, Pontificia Universidad Cato Unidad Clínica de Enfermedades Infecciosas, Microbiología y Medicina Preventiva, Hospital Universitario Virgen Macarena/Departamento de Medicina, Universidad de Sevilla/Instituto de Biomedicina de Sevilla (IBiS), Seville, Spain
1) 2)
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 January 2019 Received in revised form 25 March 2019 Accepted 5 April 2019 Available online 14 April 2019
Background: Pseudomonas aeruginosa is mostly a nosocomial pathogen affecting predisposed patients. However, community-onset bloodstream infections (CO-BSI) caused by this organism are not exceptional. Objectives: To assess the predisposing factors for CO-BSI due to P. aeruginosa (CO-BSI-PA) and the impact in mortality of inappropriate empirical antimicrobial therapy. Data source: A systematic literature search was performed in the Medline, Embase, Cochrane Library, Scopus and Web of Science databases. Study eligibility criteria and participants: Articles published between 1 January 2002 and 31 January 2018 reporting at least of 20 adult patients with CO-BSI due to P. aeruginosa were considered. Intervention: Empiric antimicrobial therapy for CO-BSI-PA. Methods: A systematic review and a meta-analysis were conducted for risk factors and to evaluate if inappropriate empiric antimicrobial therapy increased mortality in CO-BSI-PA using a Mantel-Haenszel effects model. Results: Twelve studies assessing data of 1120 patients were included in the systematic review. Solid tumour (33.1%), haematologic malignancy (26.4%), neutropenia (31.7%) and previous antibiotic use (44.8%) were the most prevalent predisposing factors. Septic shock was present in 42.3% of cases, and 30day crude mortality was 33.8%. Mortality in meta-analysis (four studies) was associated with septic shock at presentation (odds ratio, 22.31; 95% confidence interval, 3.52e141.35; p 0.001) and with inappropriate empiric antibiotic therapy (odds ratio, 1.83; 95% confidence interval, 1.12e2.98l p 0.02). Conclusions: CO-BSI-PA mostly occurred in patients with predisposing factors and had a 30-day mortality comparable to hospital-acquired cases. Inappropriate empirical antibiotic therapy was associated with increased mortality. Appropriate identification of patients at risk for CO-BSI-PA is needed for empirical treatment decisions. A. Rojas, Clin Microbiol Infect 2019;25:964 © 2019 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
Editor: L. Leibovici Keywords: Bacteraemia Bloodstream infection Community acquired Inappropriate antibiotic treatment Mortality Pseudomonas aeruginosa
Introduction Pseudomonas aeruginosa is an important human pathogen, particularly as a cause of nosocomial infections [1]. Several
pez-Corte s, Unidad de Gestio n Clínica de Enfer* Corresponding author. L, E, Lo medades Infecciosas y Microbiología, Hospital Universitario Virgen Macarena, Departamento de Medicina, Universidad de Sevilla, Instituto de Biomedicina e Sevilla (IBIS), Seville, Spain. pez-Corte s). E-mail address: [email protected] (L.E. Lo
published studies on bloodstream infections (BSI) in the last 20 years have ranked P. aeruginosa in the list of top 5 Gram-negative causal agents [2e5]. More recently, an increase in P. aeruginosa as the cause of BSI has been described in the United States [6]. Invasive infections due to P. aeruginosa are associated with considerable morbidity and mortality. In the 20th century, mortality due to P. aeruginosa BSI was reported to be higher than 20%, and even higher when appropriate antimicrobial therapy was delayed [7e9]. Despite advances in medical care, more recent clinical series still found similar mortality rates, ranging from 15% to 30% [2,3]. In
https://doi.org/10.1016/j.cmi.2019.04.005 1198-743X/© 2019 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
addition, P. aeruginosa is known for its ability to develop antimicrobial resistance. In fact, the World Health Organization categorized carbapenem-resistant P. aeruginosa as a critical priority pathogen [10]. Multiple factors have been assessed for this categorization, especially the notion that carbapenem-resistant-P. aeruginosa BSI is associated with increased mortality [11,12] and that it can develop further resistance during antibiotic treatment [13]. Typically, most P. aeruginosa infections occur in predisposed patients, e.g. hospitalized patients undergoing invasive procedures and immunocompromised patients. Therefore, P. aeruginosa is considered an infrequent cause of strict community-acquired (CA) BSI, typically causing 3% of such episodes [14e21]. In fact, the antipseudomonal b-lactams (ceftazidime, cefepime, piperacillin/ tazobactam, carbapenems except ertapenem, ceftolozane/tazobactam or ceftazidime/avibactam) are mostly reserved as empirical options for nosocomial infections, with some exceptions, to avoid their excessive use. However, this organism has been found to cause 6% to 10% of community-onset (CO) but healthcareassociated (HCA) BSI, similar to the proportion of nosocomial BSI [14e20]. Because of the increasing specialized ambulatory care of patients with severe conditions and the incremental use of immunosuppressive drugs, P. aeruginosa might be more often seen as a cause of community-onset BSI. However, to our knowledge, the features of patients and predictors for P. aeruginosa in CO-BSI, and specifically for CA and HCA episodes, have not been systematically assessed. Additionally, it would be important to estimate the impact of inappropriate empirical antimicrobial therapy for such infections. These data would be of interest to inform the empirical therapy protocols in patients with CO sepsis potentially caused by Gram-negative organisms. The aims of the present study were to systematically assess the information available about the predisposing factors and outcomes for CO (CA and HCA) BSI due to P. aeruginosa (CO-BSI-PA, CA-BSI-PA, HCA-BSI-PA) and the impact of inappropriate empirical antimicrobial therapy. Methods A systematic review and meta-analysis of scientific peerreviewed literature was performed; the recommendations from the Preferred Reporting Items for Systematic Reviews and Metaanalysis (PRISMA) guideline [22] were followed for this report. The systematic literature search was performed in the Medline, Embase, Cochrane Library, Scopus and Web of Science databases. The search strategy for CO-BSI-PA consisted of #1 (Pseudomonas OR Pseudomonas aeruginosa), #2 (Bacteraemia OR Bloodstream infection OR Blood-stream infection), #3 (Community-Acquired OR Community acquired OR Community-Associated OR Community associated OR Community-onset OR Community onset), #4 (Healthcare-acquired OR Healthcare acquired OR Healthcareassociated OR Healthcare associated OR Healthcare-onset or Healthcare onset). The search was conducted as #1 þ #2 þ #3 þ #4; no language restriction filter was applied. References from the retrieved articles were also screened for additional potential articles. Randomized trials, cohort studies, caseecontrol studies and case series reporting data with at least 20 patients with CO-BSI-PA and published between 1 January 2002 and 31 January 2018 were considered. This time frame was considered according to the first document stating significant definitions and differences among CO and healthcare-associated (HCA) bloodstream infections. Both monomicrobial and polymicrobial episodes were considered for inclusion. To be included, the studies needed to provide data on comorbidities, risk exposures and clinical presentation for patients
965
older than 16 years; and for the meta-analysis, an estimation of the impact of initial empirical antimicrobial therapy (IEAT) on mortality was needed to be specified. Data extraction and quality assessment Two independent reviewers performed a two-step selection process. First, titles and abstracts of the retrieved documents were analysed and nonrelevant studies excluded. Afterwards, full text analysis was performed and inclusion/exclusion criteria applied. Then the data were extracted, limited to published information according a prespecified questionnaire. Disagreements were solved by review and consensus; if discrepancies persisted, they were solved by a third reviewer. Data collected included study design, country of origin, period of data report, number of cases of CO-BSI-PA included, acquisition as CA and HCA, in concordance with Friedman et al. [23], in all but one study, which used its own definitions [32]. Demographic data, comorbidities, exposures of interest, resistance to ceftazidime and carbapenems, source of BSI, severity of presentation (Pitt bacteraemia score and presence of septic shock) and mortality were also collected. For the meta-analysis, CA-BSI-PA and HCA-BSI-PA data as well as mortality data (either 30-day mortality or in-hospital mortality) were considered. Any estimation about the impact of inappropriate empiric antibiotic therapy was also collected. Inappropriate empiric therapy was defined as any antibiotic therapy without adequate antimicrobial susceptibility. A quality assessment for the observational studies included in the meta-analysis was performed using the Newcastle-Ottawa scale [24]. Statistical analyses Data were collated and summarized, with core characteristics of both the studies and patients included. Frequency distributions are expressed in percentages. Heterogeneity of data included in the meta-analysis was assessed with the I2 test for inconsistency (heterogeneity was considered relevant if >50%). A MantelHaenszel fixed- or random-effects model was used, depending on whether low or high heterogeneity between the selected studies was present. Publication bias was assessed visually by funnel plot. SPSS 25.0 was used for descriptive statistical analysis [25], and RevMan 5.3 was used for the meta-analysis [26]. Results The electronic search of scientific peer-reviewed literature identified 2379 articles. After filtering by title and abstract, 36 studies were reviewed in full text for inclusion criteria. In total, 12 articles were deemed suitable for inclusion in the systematic review. There were two articles by the same author with the same database but analysed from different perspective, which were considered as only a single publication for the systematic review [27,38]. Four studies for the analysis of CA-BSI-PA vs. HCA-BSI-PA and four studies for the meta-analysis of CO-BSI-PA mortality predictors were included (Fig. 1). The characteristics of the selected articles are shown in Table 1. Studies were published between 2005 and 2018, and were from eight countries (Spain, United Kingdom, Canada, United States, China, Israel, South Korea and Australia) on four continents (Europe, North America, Asia and Oceania). All studies were observational; 11 were retrospective cohorts, and one was a prospective cohort. In total, 1120 cases of CO-BSI-PA were included. Regarding comorbidities, the most frequent ones were solid cancer (356/1076, 33.1%, from 11 studies), haematologic
966
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
Fig. 1. Flow diagram of selection process for included studies. BSI, bloodstream infection; CO, community onset.
malignancy (196/742, 26.4%, from six studies) and diabetes mellitus (219/1081, 20.3%, from 11 studies). Chronic obstructive pulmonary disease was found only in 37 (3.4%) of 1081 cases from 11 studies. Additionally, neutropenia was reported in 232 (31.7%) of 730 patients from ten studies (Table 2). Regarding other exposures, six studies reported previous antibiotic use, occurring in 216 (44.8%) of 482 cases, and three studies reported corticosteroid use in 92 (23.8%) of 385 cases. Considering antimicrobial susceptibility data, four studies reported resistance of P. aeruginosa isolates to ceftazidime in 47 (13.3%) of 354 cases, and four studies reported resistance to carbapenems in 28 (8.4%) of 332 cases (Table 2). Ten studies reported the source of BSI, with the top 5 being the following: urinary tract (187/992, 18.9%), respiratory tract (187/992, 18.9%), unknown (130/992, 13.1%), intra-abdominal (62/992, 6.25%) and vascular catheter (70/992, 7.1%). No other device-associated infections were reported. When considering BSI severity, Pitt score was reported in four studies, two of them as an absolute value with an average of 3.35 (standard deviation, 2.28), and two of them provided the proportion of cases with Pitt > 4 (28/62, 46.2%). Septic shock was reported in six studies, with a prevalence of 42.3% (146/ 345 cases; Table 2). Specific predisposing factors for CO-BSI-PA were described in four studies, two of them in comparison with CO-BSI due to other Gram-negative bacteria [30,38] and the other two with all-cause CO-BSI [33,35] (Table 3). Three studies provided adjusted
estimations [30,35,38]; in these, neutropenia and central venous catheter were found in two of them, and age <90 years, male gender, liver cirrhosis (protective), HCA, urinary device, recent antibiotics and presentation with septic shock in one. Among comorbidities, diabetes mellitus, chronic obstructive pulmonary disease, solid tumour, haematologic malignancy and neutropenia were more prevalent in HCA-BSI-PA than in CA-BSI-PA [3,31,32,36] (Table 2). Specifically, diabetes and haematologic malignancy had an odds ratio (OR) for CA-BSI-PA of 0.53 with a 95% confidence interval (CI) of 0.31e0.89 (p 0.02); and of an OR of 0.35 with a 95% CI of 0.18e0.68 (p 0.002), respectively. Neutropenia had an OR for CA-BSI-PA of 0.16 and a 95% CI of 0.05e0.53 (p 0.002) [3,31,32,36] (Supplementary Fig. S1). When analysed, previous antibiotic use and corticosteroid use were also found to be more prevalent in HCA-BSI-PA than in CABSI-PA [32,36] (Table 2). Additionally, when considering the source of BSI, urinary tract and unknown foci were most prevalent in both CA-BSI-PA and HCA-BSI-PA [3,31,32,36] (Table 2). CA-BSI-PA and HCA-BSI-PA were not shown to be associated with statistically significant differences in mortality rates in the two largest studies, with CA-BSI-PA vs. CA-BSI-HCA as follows: 26% vs. 36%, 30-day mortality, and 6% vs. 25%, 28-day mortality, respectively [32,36]. Parkins et al. [3] reported lower overall mortality in HCA-BSI-PA than in CA-BSI-PA, at 20% vs. 37%. No publication bias was detected (Supplementary Fig. S2). Thirty-day mortality was reported in four studies [28,32,33,38], at 105 (33.8%) of 331 cases (Table 2). Another two studies reported in-hospital mortality at 60 (29.2%) of 205 cases [3,29] (Table 2). Predisposing factors for mortality were analysed in a meta-analysis for studies reporting inappropriate empiric antimicrobial therapy [28,29,32,38]. Septic shock (pooled OR, 22.31; 95% CI, 3.52e141.35; p 0.001) and inappropriate empiric antimicrobial therapy (pooled OR, 1.83; 95% CI, 1.12e2.98; p 0.02) were found as mortality predictors (Fig. 2). Specific empiric antibiotic therapy was not reported, which precluded a pooled analysis. No statistically significant differences were found for age, male sex, malignancy (solid tumours and haematologic malignancy) and healthcare-associated infection. No publication bias was found for inappropriate empiric antimicrobial therapy (Supplementary Fig. S3). Resistance to ceftazidime and carbapenems was reported in only one study [32], so it was not possible to establish a significant association with mortality. Discussion In this systematic review, we found 12 observational articles that described patient cohorts with CO-BSI-PA published from 2005 to 2018 including 1120 patients, which is almost tenfold the number of patients included in the largest individual study. Among comorbidities present, the top three were associated with cancer and immunosuppression, being, in order of prevalence, solid tumour, neutropenia and haematologic malignancy. Regarding risk exposures, previous antibiotic use was the most frequent condition reported. From a clinical perspective, urinary and respiratory tracts were the predominant foci of origin. Despite a CO, disease severity was significant. When analysed, Pitt bacteraemia score was high, either as an average absolute value or in a stratified analysis (Pitt >4); in a third of cases, septic shock was detected. CO-BSI-PA predictors were reported in four studies, but each study used a different comparator, which precluded a pooled analysis. Predictors included mainly those related to immunosuppression and healthcare-associated infections. In addition to the articles included in the review, Kang et al. [39] studied risk factors for BSI due to both P. aeruginosa and Acinetobacter baumannii compared to Escherichia coli and Klebsiella pneumoniae in patients
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
967
Table 1 Characteristics of included studies in systematic review and meta-analysis Study
Year
Country
Study design
Study period
No. CO- BSI- PA
No. CA- BSI- PA (%)
No. HCA- BSI- PA (%)
Reference
Kang Cheong Schechner Parkins Schechner Enoch Hattemer ndez Herna Wolfe Lee McCarthy Yang
2005 2008 2009 2010 2011 2013 2013 2014 2014 2015 2017 2018
South Korea South Korea Israel/USA Canada Israel UK USA Spain USA Taiwan/China Australia Taiwan/China
Retrospective observational cohort Retrospective observational cohort Retrospective observational caseecontrol Retrospective observational cohort Retrospective observational cohort Retrospective observational cohort Retrospective observational cohort Retrospective observational cohort Retrospective observational cohort Retrospective observational caseecontrol Prospective observational cohort Retrospective observational cohort
1998e2002 2002e2005 2000e2005 2000e2006 2006e2008 2008e2011 1999e2010 2005e2011 2006e2008 2007e2012 2008e2011 2008e2013
39 106 151 156 76 62 150 44 84 40 190 22
NR 12 (11.3%) NR 60 (38.5%) 18 (23.7%) 10 (16.1%) 60 (40.0%) 4 (9.1%) NR NR 34 (17.9%) NR
NR 94 (88.7%) NR 96 (61.5%) 58 (76.3%) 52 (85.9%) 90 (60.0%) 40 (80.9%) NR NR 156 (82.1%) NR
[28] [27,38] [30] [3] [29] [31] [32] [33] [34] [35] [36] [37]
CA-BSI-PA, community-acquired Pseudomonas aeruginosa bloodstream infections; CO-BSI-PA, community-onset P. aeruginosa bloodstream infections; HCA, healthcareassociated P. aeruginosa bloodstream infections; NR, not reported.
Table 2 Summary data from included studies Characteristic
No. Studies
Comorbidities Diabetes mellitus 11 11 Chronic obstructive pulmonary disease Solid tumour 11 Haematologic 6 malignancy Neutropenia 10 Drug exposure and antimicrobial Previous 6 antibiotic use Corticosteroid 3 use Isolate resistant 4 to ceftazidime 3 Isolate resistant to carbapenems Clinical presentation Source 10 Urinary tract Respiratory Unknown Catheter related Intraabdominal Pitt bacteraemia 2 score Pitt > 4 2 Septic shock 6 Mortality 30-day mortality In-hospital mortality
No. patients
Prevalence
Reference
No. Studies
No. patients
Prevalence CA-BSI-PA
Prevalence HCA-BSI-PA
Reference
1081 1081
219 (20.3%) 37 (3.4%)
[3,27,29e38] [3,27,29e38]
4 3
558 368
22 (3.9%) 12 (3.3%)
85 (15.2%) 31 (8.4%)
[3,31,32,36] [3,31,32]
1076 742
356 (33.1%) 196 (26.4%)
4 3
558 402
28 (5.0%) 13 (3.2%)
103 (18.4%) 99 (24.6%)
[3,31,32,36] [31,32,36]
232 (31.7%)
[3,27e32,34e38] [27,28,31 e33,36,38] [3,27e31,33,35e38]
2
252
4 (1.6%)
66 (26.2%)
[31,36]
216 (44.8%)
[28e30,32,33,37]
1
150
24 (16%)
68 (45.3%)
[32]
385
92 (23.8%)
[29,33,36]
1
190
4 (2.1%)
57 ((30.0%)
[36]
354
47 (13.3%)
[27,29,32,37,38]
1
150
3 ((2.0%)
17 (11.3%)
[32]
332
28 (8.4%)
[27,29,32,38]
1
150
5 (3.3%)
8 (5.3%)
[32]
[3,27e32,35e38]
4
558
187 (18.9%) 187 (18.9%) 130 (13.1%) 70 (7.1%)
43 (7.7%) 28 (5.0%) 32 (5.7%) 1 (0.18%)
85 57 78 23
62 (6.25%)
11 (1.9%)
19 (3.4%)
730 resistance 482
992
[3,31,32,36] (15.2%) (10.2%) (14.0%) (4.1%)
296
X ¼ 3.35 ± 2.28
[27,36,38]
1
190
X¼1
X¼2
[36]
62 345
28 (46.2%) 146 (42.3%)
[35,37,38] [27 e29,31,35,37,38]
0 1
d 62
d 2 (3.2%)
d 21 (33.9%)
d [31]
4
311
105 (33.8%)
[27,28,32,33,38]
1
150
16 (10.6%)
32 (21.3%)
[32]
2
205
60 (29.2%)
[3,29]
1
156
16 (10.2%)
17 (21.2%)
[3]
CA-BSI-PA, community-acquired Pseudomonas aeruginosa bloodstream infections; CO-BSI-PA, community-onset P. aeruginosa bloodstream infections.
seeking care at an emergency unit. Male sex, solid tumour, haematologic malignancy, healthcare-associated infection and respiratory foci were identified as risk factors, which are in line with results found in this systematic review for CO-BSI-PA predictors. When comparing CA-BSI-PA with HCA-BSI-PA, we found that diabetes, haematologic malignancy, neutropenia and previous antibiotic use were more likely in the latter group; no statistically significant difference was found regarding the source of the BSI. This likely could be explained by the inclusion of a larger number of
patients in this analysis, because individual studies by Hattemer et al. [32] and McCarthy and Patterson [36] had only shown small differences between CA-BSI-PA and HCA-BSI-PA in multivariate analysis. Studies used slightly different definitions of CA-BSI-PA and HCA-BSI-PA, and they reported differently mortality, which precluded a pooled analysis. Data from the two largest studies showed no statistically significant difference in mortality; Parkins et al. [3] reported higher mortality for CA-BSI-PA, which was thought to be probably due to higher inappropriate empirical antibiotic therapy.
968
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
Table 3 Predictors for community-onset BSI due to Pseudomonas aeruginosa Study
Comparator
Type of analysis
Predictor
Prevalence
OR
95% CI
p
Cheong [38]
CO-BSI due to Escherichia coli
MV
Schechner [30]
CO-BSI due to any Enterobacteria
MV
Lee [35]
CO-BSI due to any microorganism
MV
1.05e4.75 1.09e3.94 1.28e6.69 5.1e23.71 2.53e18.26 1.91e15.17 1.87e7.36 1.31e6.73 3.20e17.47 0.98e5.03 0.14e0.74
CO-BSI due to any microorganism
UV
50e106 (47.7%) 56e106 (52.8%) 31e106 (29.2%) 94e106 (88.7%) 24e151 (15.9%) 14e151 (9.2%) 55e151 (36.4%) 36e151 (23.8%) 32e40 (80.0%) 30e40 (75.0%) 1e40 (2.5%) 32e44 (72.7%) 20e44 (45.5%) 40e44 (90.9%) 21e44 (47.7%) 5e44 (11.4%) 16e44 (36.4%) 6e44 (13.6%)
2.23 2.07 2.93 11.0 6.80 5.39 1.87 2.97 7.48 2.22 0.32
Hern andez [33]
Neutropenia Presentation with septic shock Central venous catheter Healthcare-associated infection Urinary device Age >90 years Recent antibiotic use Central venous catheter Neutropenia Male sex Liver cirrhosis Male sex Prior hospital admission Healthcare-associated infection Haematologic malignancy Haematopoietic stem-cell transplantation Neutropenia Haemodialysis
0.037 0.027 0.011 <0.001 <0.001 0.001 <0.001 0.009 <0.001 0.06 0.007 0.018 0.005 <0.001 0.008 0.015 0.001 0.020
BSI, bloodstream infections; CI, confidence interval; CO, community onset; MV, multivariate; OR, odds ratio; UV, univariate.
Fig. 2. Forest plot depicting odds ratios for 30-day mortality of patients (a) presenting with septic shock and (b) receiving inappropriate empiric antibiotic therapy for communityonset BSI due to Pseudomonas aeruginosa. Vertical line, no difference point between two therapies; squares, risk ratios; diamonds, pooled risk ratios; horizontal lines, 95% confidence interval. ATB, antibiotic; BSI, bloodstream infection; CI, confidence interval.
As a result of the observational nature of the included studies for this systematic review and meta-analysis, no standardized empiric antibiotic therapy was provided. An appropriate empiric antibiotic therapy was considered if it was provided according to antimicrobial susceptibility in a timely fashion. The included studies did not perform subgroup analysis, probably as a result of small sample sizes, which would have given us the opportunity to provide a stratified estimation according to baseline severity. Finally, we also found a high 30-day mortality (33.8%), which is comparable to mortality described for nosocomial P. aeruginosa BSI. Septic shock and inappropriate empiric antibiotic therapy were identified in the meta-analysis as significant
predictors for mortality in CO-BSI-PA. Septic shock presented with wide confidence intervals, most likely as a result of sparse data reported among the included studies. Individual studies included in the meta-analysis showed a trend towards increased mortality with inappropriate empiric antibiotic therapy, but, probably as a result of smaller numbers, it failed to reach robust statistical significance. Risk factors for inappropriate empiric antibiotic therapy were not homogenously analysed, precluding a pooled analysis of them. Nonetheless, in a striking way, inappropriate empiric antibiotic therapy for CO-BSI-PA was significantly linked with increased 30-day mortality in this meta-analysis.
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
Carrara et al. [40] had analysed in a meta-analysis the determinants of inappropriate empiric antimicrobial therapy and did not found, in a metaregression, a statistically significant association between all P. aeruginosa infections, including BSI and inappropriate empiric antibiotic therapy. Probably because a different population was analysed all microbiologically documented infections were included, thus selecting patients with less severe infections and lower levels of antibiotic resistance. Future research should focus on finding predictors for CO-BSI-PA in order to tailor empiric antibiotic therapy for Gram-negative CO-BSI and to avoid inappropriate empiric antimicrobial therapy to try to reduce mortality. The limitations in our study should be taken in consideration. All studies included are observational as a result of the nature of the research question; only one of them was conducted in a prospective cohort. This implies that causality associations should be taken with caution. Also, the number of studies and the information provided did not allow us to evaluate the impact of local epidemiologic situations. Not all variables of interest were reported in each study, which thus provides a fragmented picture of some of them. This was particularly relevant for antibiotic therapy and resistance, precluding a pooled analysis. Additionally, risk factors for inappropriate empiric antibiotic therapy were not analysed independently in the included studies, precluding further evaluations in their possible correlation with mortality. Studies included in the meta-analysis were of moderate and good quality according to the Newcastle-Ottawa scale for observational studies. Half of the studies included in the inappropriate empiric antimicrobial therapy meta-analysis were carried out in South Korea, so a generalization of their results should be taken cautiously, as they included only an Asian population. Nonetheless, we believe this study provides relevant information about CO-BSI due to P. aeruginosa. The fact that inappropriate empiric antimicrobial therapy is associated with mortality in CO- BSI-PA represents a clinical challenge; on the one hand, it seems imperative to try to appropriately cover this organism if highly probable, but on the other hand, overuse of antipseudomonal agents should be avoided in order to reduce the selective pressure on this and other microorganisms. Some data provided in this systematic review might be helpful for clinical decisions; however, specific studies including validated predictive scores or decision trees are needed to improve the decisions regarding empirical therapy. Acknowledgements AR received a scholarship for educational activities in Seville, and thanks the Oscar & Elsa Braun Foundation for funding it and lica de Chile for granting it. Pontificia Universidad Cato Transparency Declaration ZRP-B, LEL-C and JR-B received funding for research from Plan Nacional de IþDþi 2013-2016 and Instituto de Salud Carlos III, n General de Redes y Centros de Investigacio n CoopSubdireccio erativa, Ministerio de Economía, Industria y Competitividad, Spanish Network for Research in Infectious Diseases (REIPI RD16/ 0016/0001), cofinanced by European Development Regional Fund ‘A Way to Achieve Europe,’ Operative Programme Intelligent Growth, 2014e2020. JR-B received honoraria for accredited educational activities funded by Merck through unrestricted grants and for coordination of a noneproduct-related research project. ZRP-B received honoraria for educational talks by Gilead. LELC has served as speaker for Merck, Sharp & Dohme and Angelini, and has received research support from Novartis. The other authors report no conflicts of interest relevant to this article.
969
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.cmi.2019.04.005. References [1] European Centre for Disease Prevention and Control (ECDC). Point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals, 2011e2012. 2013. Available at: https://ecdc.europa.eu/ sites/portal/files/media/en/publications/Publications/healthcare-associatedinfections-antimicrobial-use-PPS.pdf. [2] Al-Hasan MN, Wilson JW, Lahr B, Eckel-Passow JE, Baddour L. Incidence of Pseudomonas aeruginosa bacteremia: a population based study. Am J Med 2008;121:702e8. [3] Parkins MD, Gregson DB, Pitout JD, Ross T, Laupland KB. Population-based study of the epidemiology and risk factors for Pseudomonas aeruginosa bloodstream infection. Infection 2010;38:25e32. [4] Diekema DJ, Pfaller MA, Jones MN, Doern GV, Winokur PL, Gales AC, et al. SENTRY Participants Group (Americas). Survey of bloodstream infections due to Gram-negative bacilii: frequency of ocurrence and antimicrobial susceptibility of isolates collected in the United States, Canada, and Latin America for the SENTRY Antimicrobial Surveillance Program, 1997. Clin Infect Dis 1999;29:595e607. [5] Deccouser JW, Pina P, Picot F, Delalande C, Pangon B, Courvalin P, et al., ColBVH Study Group. Frequency of isolation and antimicrobial susceptibility of bacterial pathogens isolated from patients with bloodstream infections: a French prospective national survey. J Antimicrob Chemother 2003;51: 1213e22. [6] Werth BJ, Carreno JJ, Reveles KR. Shifting trends in the incidence of Pseudomonas aeruginosa septicemia in hospitalized adults in the United States from 1996 to 2010. Am J Infect Control 2015;43:465e8. [7] Vidal F, Mensa J, Almela M, Martínez JA, Marco F, Casals C, et al. Epidemiology and outcome of Pseudomonas aeruginosa bacteremia, with special emphasis on the influence of antibiotic treatment. Analysis of 189 episodes. Arch Intern Med 1996;156:2121e6. [8] Chatzinikolau I, Abi-Said D, Bodey GP, Rolston KV, Tarrand JJ, Samonis G. Recent experience with Pseudomonas aeruginosa bacteremia in patients with cancer: retrospective analysis of 245 episodes. Arch Intern Med 2000;160: 501e9. [9] Osmon S, Ward S, Fraser VJ, Kollef MH. Hospital mortality for patients with bacteremia due to Staphylococcus aureus or Pseudomonas aeruginosa. Chest 2004;125:607e16. [10] Tacconelli E, Carrara E, Savoldi A, Harbarth S, Mendelson M, Monnet DL, et al. WHO Pathogens Priority List Working Group. Discovery, research and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis. Lancet Infect Dis 2018;18:318e27. ~ a C, Suarez C, Gozalo M, Murillos J, Almirante B, Pomar V, et al. Spanish [11] Pen Network for Research in Infectious Diseases (REIPI). Carbapenem resistance increases mortality in Pseudomonas aeruginosa bloodstream infections. Antimicrob Agents Chemother 2012;34:1265e72. [12] Zhang Y, Chen XL, Huang AW, Liu SL, Liu WJ, Zhang N, et al. Mortality attributable to carbapenem resistant Pseudomonas aeruginosa bacteremia: a meta-analysis of cohort studies. Emerg Microb Infect 2016;5:e27. [13] Carmeli Y, Troillet N, Eliopoulos GM, Samore MH. Emergence of antibiotic resistant Pseudomonas aeruginosa: comparison of risks associated with different antipseudomonal agents. Antimicrob Agents Chemother 1999;43: 1379e82. [14] Siegman-Igra Y, Fourer B, Orni-Wasserlauf R, Golan Y, Noy A, Schwartz D, et al. Reappraisal of community-acquired bacteremia: a proposal of a new classification for the spectrum of acquisition of bacteremia. Clin Infect Dis 2002;34: 1431e9. [15] McDonald JR, Friedman ND, Stout JE, Sexton DJ, Kaye KS. Risk factors for ineffective therapy in patients with bloodstream infection. Arch Intern Med 2005;165:308e13. [16] Shorr AF, Tabak YP, Killian AD, Gupta V, Liu LZ, Kollef MH. Healthcare-associated bloodstream infection: a distinct entity? Insights from a large US database. Crit Care Med 2006;34:2588e95. s J, Calbo E, Anoro E, Fontanals D, Xercavins M, Espejo E, et al. Blood[17] Valle stream infections in adults: importance of healthcare-associated infections. J Infect 2008;56:27e34. ~ o J, Lo pez-Prieto MD, Portillo MM, Retamar P, Natera C, Nun ~ o E, [18] Rodríguez-Ban et al. SAEI/SAMPAC Bacteraemia Group. Epidemiology and clinical features of community-acquired, healthcare-associated and nosocomial bloodstream infections in tertiary-care and community hospitals. Clin Microb Infect 2010;16: 1408e13. [19] Kollef MH, Zilberberg MD, Shorr AF, Vo L, Schein J, Micek ST, et al. Epidemiology, microbiology and outcomes of healthcare-associated and communityacquired bacteremia: a multicenter cohort study. J Infect 2011;62:130e5. [20] Al-Hasan MN, Eckel-Passow JE, Baddour LM. Impact of healthcare-associated acquisition on community-onset Gram-negative bloodstream infection: a population-based studydhealthcare-associated Gram-negative BSI. Eur J Clin Microbiol Infect Dis 2012;31:1163e71.
970
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
[21] Laupland KB, Gregson DB, Flemons WW, Hawkins D, Ross T, Church DL. Burden of community-onset bloodstream infection: a population-based assessment. Epidemiol Infect 2007;135:1037e42. [22] Moher D, Liberati A, Tetzlaff JM, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol 2009;62:1006e12. [23] Friedman ND, Kaye KS, Stout JE, McGarry SA, Trivette SL, Briggs JP, et al. Healthcare associated bloodstream infections in adults: a reason to change the accepted definition of community-acquired infections. Ann Intern Med 2002;137:791e7. [24] Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Available at: http://www.ohri.ca/programs/clinical_ epidemiology/oxford.asp. [25] SPSS Statistics for Windows, version 25.0 [computer program]. Armonk, NY: IBM Corp; 2017. [26] Review Manager (RevMan), version 5.3 [computer program]. Copenhagen: Nordic Cochrane Centre, Cochrane Collaboration; 2014. [27] Cheong HS, Kang CI, Wi YM, Ko KS, Chung DR, Lee NY, et al. Inappropiate antimicrobial therapy as a risk factor for mortality in patients with community onset Pseudomonas aeruginosa bacteremia. Eur J Clin Microb Infect Dis 2008;27:1219e25. [28] Kang CI, Kim SH, Park WB, Lee KD, Kim HB, Kim EC, et al. Clinical features and outcome of patients with community-acquired Pseudomonas aeruginosa bacteraemia. Clin Microb Infect 2005;11:415e8. [29] Schechner V, Gottesman T, Schwartz O, Korem M, Maor Y, Rahav G, et al. Pseudomonas aeruginosa bacteremia upon hospital admission: risk factors for mortality and influence of inadequate empirical antimicrobial therapy. Diagn Microbiol Infect Dis 2011;71:38e45. [30] Schechner V, Nobre V, Kaye KS, Leshno M, Giladi M, Rohner P, et al. Gramnegative bacteremia upon hospital admission: when should Pseudomonas aeruginosa be suspected? Clin Infect Dis 2009;48:580e6.
[31] Enoch DA, Kuzhively J, Sismey A, Grynik A, Karas JA. Pseudomonas aeruginosa bacteraemia in two UK district hospitals. Infect Dis Rep 2013;5:e4. [32] Hattemer A, Hausser A, Diaz M, Scheetz M, Shah N, Allen J, et al. Bacterial and clinical characteristics of health-care and community-acquired bloodstream infections due to Pseudomonas aeruginosa. Antimicrob Agents Chemother 2013;57:3969e75. [33] Hernandez C, Cobos-Trigueros N, Feher C, Morata L, De La Calle C, Marco F, et al. Community-onset bacteraemia of unknown origin: clinical characteristics, epidemiology and outcome. Eur J Clin Microbiol Infect Dis 2014;33: 1973e80. [34] Wolfe CM, Cohen B, Larson E. Prevalence and risk factors for antibioticresistant community-associated bloodstream infections. J Infect Public Health 2014;7:224e32. [35] Lee CC, Hsieh CC, Lee NY, Chan TY, Hong MY, Chi CH, et al. Different clinical presentation of community-onset bacteremia among neutropenic adults in the ED. Am J Emerg Med 2015;33:907e12. [36] McCarthy K, Patterson DL. Community acquired Pseudomonas aeruginosa bloodstream infection: a classification that should not falsely reassure the clinician. Eur J Clin Microbiol Infect Dis 2017;36:703e11. [37] Yang CY, Lee CH, Hsieh CC, Ko WC, Lee CC. Etiology of community-onset monomicrobial bacteremic pneumonia and its clinical presentation and outcome: Klebsiella and Pseudomonas matters. J Infect Chemother 2018;24:53e8. [38] Cheong HS, Kang CI, Wi YM, Kim ES, Lee JS, Soo KS, et al. Clinical significance and predictors of community-onset Pseudomonas aeruginosa bloodstream infections. Am J Med 2008;121:709e14. [39] Kang CI, Chung DR, Peck KR, Song JH. Korean Network for Study on Infectious Diseases (KONSID). Clinical predictors of Pseudomonas aeruginosa or Acinetobacter baumannii bacteremia in patients admitted to the ED. Am J Emerg Med 2012;30:1169e75. [40] Carrara E, Pfeffer I, Zusman O, Leibovici L, Paul M. Determinants of inappropriate empirical antibiotic treatment: systematic review and meta-analysis. Int J Antimicrob Agents 2018;5:548e53.
Contents lists available at ScienceDirect
Clinical Microbiology and Infection journal homepage: www.clinicalmicrobiologyandinfection.com
Systematic review
Rates, predictors and mortality of community-onset bloodstream infections due to Pseudomonas aeruginosa: systematic review and meta-analysis pez-Corte s 2, *, J. Rodríguez-Ban ~o 2 A. Rojas 1, Z.R. Palacios-Baena 2, L.E. Lo lica de Chile, Santiago, Chile Departamento de Enfermedades Infecciosas del Adulto, Facultad de Medicina, Pontificia Universidad Cato Unidad Clínica de Enfermedades Infecciosas, Microbiología y Medicina Preventiva, Hospital Universitario Virgen Macarena/Departamento de Medicina, Universidad de Sevilla/Instituto de Biomedicina de Sevilla (IBiS), Seville, Spain
1) 2)
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 January 2019 Received in revised form 25 March 2019 Accepted 5 April 2019 Available online 14 April 2019
Background: Pseudomonas aeruginosa is mostly a nosocomial pathogen affecting predisposed patients. However, community-onset bloodstream infections (CO-BSI) caused by this organism are not exceptional. Objectives: To assess the predisposing factors for CO-BSI due to P. aeruginosa (CO-BSI-PA) and the impact in mortality of inappropriate empirical antimicrobial therapy. Data source: A systematic literature search was performed in the Medline, Embase, Cochrane Library, Scopus and Web of Science databases. Study eligibility criteria and participants: Articles published between 1 January 2002 and 31 January 2018 reporting at least of 20 adult patients with CO-BSI due to P. aeruginosa were considered. Intervention: Empiric antimicrobial therapy for CO-BSI-PA. Methods: A systematic review and a meta-analysis were conducted for risk factors and to evaluate if inappropriate empiric antimicrobial therapy increased mortality in CO-BSI-PA using a Mantel-Haenszel effects model. Results: Twelve studies assessing data of 1120 patients were included in the systematic review. Solid tumour (33.1%), haematologic malignancy (26.4%), neutropenia (31.7%) and previous antibiotic use (44.8%) were the most prevalent predisposing factors. Septic shock was present in 42.3% of cases, and 30day crude mortality was 33.8%. Mortality in meta-analysis (four studies) was associated with septic shock at presentation (odds ratio, 22.31; 95% confidence interval, 3.52e141.35; p 0.001) and with inappropriate empiric antibiotic therapy (odds ratio, 1.83; 95% confidence interval, 1.12e2.98l p 0.02). Conclusions: CO-BSI-PA mostly occurred in patients with predisposing factors and had a 30-day mortality comparable to hospital-acquired cases. Inappropriate empirical antibiotic therapy was associated with increased mortality. Appropriate identification of patients at risk for CO-BSI-PA is needed for empirical treatment decisions. A. Rojas, Clin Microbiol Infect 2019;25:964 © 2019 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
Editor: L. Leibovici Keywords: Bacteraemia Bloodstream infection Community acquired Inappropriate antibiotic treatment Mortality Pseudomonas aeruginosa
Introduction Pseudomonas aeruginosa is an important human pathogen, particularly as a cause of nosocomial infections [1]. Several
pez-Corte s, Unidad de Gestio n Clínica de Enfer* Corresponding author. L, E, Lo medades Infecciosas y Microbiología, Hospital Universitario Virgen Macarena, Departamento de Medicina, Universidad de Sevilla, Instituto de Biomedicina e Sevilla (IBIS), Seville, Spain. pez-Corte s). E-mail address: [email protected] (L.E. Lo
published studies on bloodstream infections (BSI) in the last 20 years have ranked P. aeruginosa in the list of top 5 Gram-negative causal agents [2e5]. More recently, an increase in P. aeruginosa as the cause of BSI has been described in the United States [6]. Invasive infections due to P. aeruginosa are associated with considerable morbidity and mortality. In the 20th century, mortality due to P. aeruginosa BSI was reported to be higher than 20%, and even higher when appropriate antimicrobial therapy was delayed [7e9]. Despite advances in medical care, more recent clinical series still found similar mortality rates, ranging from 15% to 30% [2,3]. In
https://doi.org/10.1016/j.cmi.2019.04.005 1198-743X/© 2019 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
addition, P. aeruginosa is known for its ability to develop antimicrobial resistance. In fact, the World Health Organization categorized carbapenem-resistant P. aeruginosa as a critical priority pathogen [10]. Multiple factors have been assessed for this categorization, especially the notion that carbapenem-resistant-P. aeruginosa BSI is associated with increased mortality [11,12] and that it can develop further resistance during antibiotic treatment [13]. Typically, most P. aeruginosa infections occur in predisposed patients, e.g. hospitalized patients undergoing invasive procedures and immunocompromised patients. Therefore, P. aeruginosa is considered an infrequent cause of strict community-acquired (CA) BSI, typically causing 3% of such episodes [14e21]. In fact, the antipseudomonal b-lactams (ceftazidime, cefepime, piperacillin/ tazobactam, carbapenems except ertapenem, ceftolozane/tazobactam or ceftazidime/avibactam) are mostly reserved as empirical options for nosocomial infections, with some exceptions, to avoid their excessive use. However, this organism has been found to cause 6% to 10% of community-onset (CO) but healthcareassociated (HCA) BSI, similar to the proportion of nosocomial BSI [14e20]. Because of the increasing specialized ambulatory care of patients with severe conditions and the incremental use of immunosuppressive drugs, P. aeruginosa might be more often seen as a cause of community-onset BSI. However, to our knowledge, the features of patients and predictors for P. aeruginosa in CO-BSI, and specifically for CA and HCA episodes, have not been systematically assessed. Additionally, it would be important to estimate the impact of inappropriate empirical antimicrobial therapy for such infections. These data would be of interest to inform the empirical therapy protocols in patients with CO sepsis potentially caused by Gram-negative organisms. The aims of the present study were to systematically assess the information available about the predisposing factors and outcomes for CO (CA and HCA) BSI due to P. aeruginosa (CO-BSI-PA, CA-BSI-PA, HCA-BSI-PA) and the impact of inappropriate empirical antimicrobial therapy. Methods A systematic review and meta-analysis of scientific peerreviewed literature was performed; the recommendations from the Preferred Reporting Items for Systematic Reviews and Metaanalysis (PRISMA) guideline [22] were followed for this report. The systematic literature search was performed in the Medline, Embase, Cochrane Library, Scopus and Web of Science databases. The search strategy for CO-BSI-PA consisted of #1 (Pseudomonas OR Pseudomonas aeruginosa), #2 (Bacteraemia OR Bloodstream infection OR Blood-stream infection), #3 (Community-Acquired OR Community acquired OR Community-Associated OR Community associated OR Community-onset OR Community onset), #4 (Healthcare-acquired OR Healthcare acquired OR Healthcareassociated OR Healthcare associated OR Healthcare-onset or Healthcare onset). The search was conducted as #1 þ #2 þ #3 þ #4; no language restriction filter was applied. References from the retrieved articles were also screened for additional potential articles. Randomized trials, cohort studies, caseecontrol studies and case series reporting data with at least 20 patients with CO-BSI-PA and published between 1 January 2002 and 31 January 2018 were considered. This time frame was considered according to the first document stating significant definitions and differences among CO and healthcare-associated (HCA) bloodstream infections. Both monomicrobial and polymicrobial episodes were considered for inclusion. To be included, the studies needed to provide data on comorbidities, risk exposures and clinical presentation for patients
965
older than 16 years; and for the meta-analysis, an estimation of the impact of initial empirical antimicrobial therapy (IEAT) on mortality was needed to be specified. Data extraction and quality assessment Two independent reviewers performed a two-step selection process. First, titles and abstracts of the retrieved documents were analysed and nonrelevant studies excluded. Afterwards, full text analysis was performed and inclusion/exclusion criteria applied. Then the data were extracted, limited to published information according a prespecified questionnaire. Disagreements were solved by review and consensus; if discrepancies persisted, they were solved by a third reviewer. Data collected included study design, country of origin, period of data report, number of cases of CO-BSI-PA included, acquisition as CA and HCA, in concordance with Friedman et al. [23], in all but one study, which used its own definitions [32]. Demographic data, comorbidities, exposures of interest, resistance to ceftazidime and carbapenems, source of BSI, severity of presentation (Pitt bacteraemia score and presence of septic shock) and mortality were also collected. For the meta-analysis, CA-BSI-PA and HCA-BSI-PA data as well as mortality data (either 30-day mortality or in-hospital mortality) were considered. Any estimation about the impact of inappropriate empiric antibiotic therapy was also collected. Inappropriate empiric therapy was defined as any antibiotic therapy without adequate antimicrobial susceptibility. A quality assessment for the observational studies included in the meta-analysis was performed using the Newcastle-Ottawa scale [24]. Statistical analyses Data were collated and summarized, with core characteristics of both the studies and patients included. Frequency distributions are expressed in percentages. Heterogeneity of data included in the meta-analysis was assessed with the I2 test for inconsistency (heterogeneity was considered relevant if >50%). A MantelHaenszel fixed- or random-effects model was used, depending on whether low or high heterogeneity between the selected studies was present. Publication bias was assessed visually by funnel plot. SPSS 25.0 was used for descriptive statistical analysis [25], and RevMan 5.3 was used for the meta-analysis [26]. Results The electronic search of scientific peer-reviewed literature identified 2379 articles. After filtering by title and abstract, 36 studies were reviewed in full text for inclusion criteria. In total, 12 articles were deemed suitable for inclusion in the systematic review. There were two articles by the same author with the same database but analysed from different perspective, which were considered as only a single publication for the systematic review [27,38]. Four studies for the analysis of CA-BSI-PA vs. HCA-BSI-PA and four studies for the meta-analysis of CO-BSI-PA mortality predictors were included (Fig. 1). The characteristics of the selected articles are shown in Table 1. Studies were published between 2005 and 2018, and were from eight countries (Spain, United Kingdom, Canada, United States, China, Israel, South Korea and Australia) on four continents (Europe, North America, Asia and Oceania). All studies were observational; 11 were retrospective cohorts, and one was a prospective cohort. In total, 1120 cases of CO-BSI-PA were included. Regarding comorbidities, the most frequent ones were solid cancer (356/1076, 33.1%, from 11 studies), haematologic
966
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
Fig. 1. Flow diagram of selection process for included studies. BSI, bloodstream infection; CO, community onset.
malignancy (196/742, 26.4%, from six studies) and diabetes mellitus (219/1081, 20.3%, from 11 studies). Chronic obstructive pulmonary disease was found only in 37 (3.4%) of 1081 cases from 11 studies. Additionally, neutropenia was reported in 232 (31.7%) of 730 patients from ten studies (Table 2). Regarding other exposures, six studies reported previous antibiotic use, occurring in 216 (44.8%) of 482 cases, and three studies reported corticosteroid use in 92 (23.8%) of 385 cases. Considering antimicrobial susceptibility data, four studies reported resistance of P. aeruginosa isolates to ceftazidime in 47 (13.3%) of 354 cases, and four studies reported resistance to carbapenems in 28 (8.4%) of 332 cases (Table 2). Ten studies reported the source of BSI, with the top 5 being the following: urinary tract (187/992, 18.9%), respiratory tract (187/992, 18.9%), unknown (130/992, 13.1%), intra-abdominal (62/992, 6.25%) and vascular catheter (70/992, 7.1%). No other device-associated infections were reported. When considering BSI severity, Pitt score was reported in four studies, two of them as an absolute value with an average of 3.35 (standard deviation, 2.28), and two of them provided the proportion of cases with Pitt > 4 (28/62, 46.2%). Septic shock was reported in six studies, with a prevalence of 42.3% (146/ 345 cases; Table 2). Specific predisposing factors for CO-BSI-PA were described in four studies, two of them in comparison with CO-BSI due to other Gram-negative bacteria [30,38] and the other two with all-cause CO-BSI [33,35] (Table 3). Three studies provided adjusted
estimations [30,35,38]; in these, neutropenia and central venous catheter were found in two of them, and age <90 years, male gender, liver cirrhosis (protective), HCA, urinary device, recent antibiotics and presentation with septic shock in one. Among comorbidities, diabetes mellitus, chronic obstructive pulmonary disease, solid tumour, haematologic malignancy and neutropenia were more prevalent in HCA-BSI-PA than in CA-BSI-PA [3,31,32,36] (Table 2). Specifically, diabetes and haematologic malignancy had an odds ratio (OR) for CA-BSI-PA of 0.53 with a 95% confidence interval (CI) of 0.31e0.89 (p 0.02); and of an OR of 0.35 with a 95% CI of 0.18e0.68 (p 0.002), respectively. Neutropenia had an OR for CA-BSI-PA of 0.16 and a 95% CI of 0.05e0.53 (p 0.002) [3,31,32,36] (Supplementary Fig. S1). When analysed, previous antibiotic use and corticosteroid use were also found to be more prevalent in HCA-BSI-PA than in CABSI-PA [32,36] (Table 2). Additionally, when considering the source of BSI, urinary tract and unknown foci were most prevalent in both CA-BSI-PA and HCA-BSI-PA [3,31,32,36] (Table 2). CA-BSI-PA and HCA-BSI-PA were not shown to be associated with statistically significant differences in mortality rates in the two largest studies, with CA-BSI-PA vs. CA-BSI-HCA as follows: 26% vs. 36%, 30-day mortality, and 6% vs. 25%, 28-day mortality, respectively [32,36]. Parkins et al. [3] reported lower overall mortality in HCA-BSI-PA than in CA-BSI-PA, at 20% vs. 37%. No publication bias was detected (Supplementary Fig. S2). Thirty-day mortality was reported in four studies [28,32,33,38], at 105 (33.8%) of 331 cases (Table 2). Another two studies reported in-hospital mortality at 60 (29.2%) of 205 cases [3,29] (Table 2). Predisposing factors for mortality were analysed in a meta-analysis for studies reporting inappropriate empiric antimicrobial therapy [28,29,32,38]. Septic shock (pooled OR, 22.31; 95% CI, 3.52e141.35; p 0.001) and inappropriate empiric antimicrobial therapy (pooled OR, 1.83; 95% CI, 1.12e2.98; p 0.02) were found as mortality predictors (Fig. 2). Specific empiric antibiotic therapy was not reported, which precluded a pooled analysis. No statistically significant differences were found for age, male sex, malignancy (solid tumours and haematologic malignancy) and healthcare-associated infection. No publication bias was found for inappropriate empiric antimicrobial therapy (Supplementary Fig. S3). Resistance to ceftazidime and carbapenems was reported in only one study [32], so it was not possible to establish a significant association with mortality. Discussion In this systematic review, we found 12 observational articles that described patient cohorts with CO-BSI-PA published from 2005 to 2018 including 1120 patients, which is almost tenfold the number of patients included in the largest individual study. Among comorbidities present, the top three were associated with cancer and immunosuppression, being, in order of prevalence, solid tumour, neutropenia and haematologic malignancy. Regarding risk exposures, previous antibiotic use was the most frequent condition reported. From a clinical perspective, urinary and respiratory tracts were the predominant foci of origin. Despite a CO, disease severity was significant. When analysed, Pitt bacteraemia score was high, either as an average absolute value or in a stratified analysis (Pitt >4); in a third of cases, septic shock was detected. CO-BSI-PA predictors were reported in four studies, but each study used a different comparator, which precluded a pooled analysis. Predictors included mainly those related to immunosuppression and healthcare-associated infections. In addition to the articles included in the review, Kang et al. [39] studied risk factors for BSI due to both P. aeruginosa and Acinetobacter baumannii compared to Escherichia coli and Klebsiella pneumoniae in patients
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
967
Table 1 Characteristics of included studies in systematic review and meta-analysis Study
Year
Country
Study design
Study period
No. CO- BSI- PA
No. CA- BSI- PA (%)
No. HCA- BSI- PA (%)
Reference
Kang Cheong Schechner Parkins Schechner Enoch Hattemer ndez Herna Wolfe Lee McCarthy Yang
2005 2008 2009 2010 2011 2013 2013 2014 2014 2015 2017 2018
South Korea South Korea Israel/USA Canada Israel UK USA Spain USA Taiwan/China Australia Taiwan/China
Retrospective observational cohort Retrospective observational cohort Retrospective observational caseecontrol Retrospective observational cohort Retrospective observational cohort Retrospective observational cohort Retrospective observational cohort Retrospective observational cohort Retrospective observational cohort Retrospective observational caseecontrol Prospective observational cohort Retrospective observational cohort
1998e2002 2002e2005 2000e2005 2000e2006 2006e2008 2008e2011 1999e2010 2005e2011 2006e2008 2007e2012 2008e2011 2008e2013
39 106 151 156 76 62 150 44 84 40 190 22
NR 12 (11.3%) NR 60 (38.5%) 18 (23.7%) 10 (16.1%) 60 (40.0%) 4 (9.1%) NR NR 34 (17.9%) NR
NR 94 (88.7%) NR 96 (61.5%) 58 (76.3%) 52 (85.9%) 90 (60.0%) 40 (80.9%) NR NR 156 (82.1%) NR
[28] [27,38] [30] [3] [29] [31] [32] [33] [34] [35] [36] [37]
CA-BSI-PA, community-acquired Pseudomonas aeruginosa bloodstream infections; CO-BSI-PA, community-onset P. aeruginosa bloodstream infections; HCA, healthcareassociated P. aeruginosa bloodstream infections; NR, not reported.
Table 2 Summary data from included studies Characteristic
No. Studies
Comorbidities Diabetes mellitus 11 11 Chronic obstructive pulmonary disease Solid tumour 11 Haematologic 6 malignancy Neutropenia 10 Drug exposure and antimicrobial Previous 6 antibiotic use Corticosteroid 3 use Isolate resistant 4 to ceftazidime 3 Isolate resistant to carbapenems Clinical presentation Source 10 Urinary tract Respiratory Unknown Catheter related Intraabdominal Pitt bacteraemia 2 score Pitt > 4 2 Septic shock 6 Mortality 30-day mortality In-hospital mortality
No. patients
Prevalence
Reference
No. Studies
No. patients
Prevalence CA-BSI-PA
Prevalence HCA-BSI-PA
Reference
1081 1081
219 (20.3%) 37 (3.4%)
[3,27,29e38] [3,27,29e38]
4 3
558 368
22 (3.9%) 12 (3.3%)
85 (15.2%) 31 (8.4%)
[3,31,32,36] [3,31,32]
1076 742
356 (33.1%) 196 (26.4%)
4 3
558 402
28 (5.0%) 13 (3.2%)
103 (18.4%) 99 (24.6%)
[3,31,32,36] [31,32,36]
232 (31.7%)
[3,27e32,34e38] [27,28,31 e33,36,38] [3,27e31,33,35e38]
2
252
4 (1.6%)
66 (26.2%)
[31,36]
216 (44.8%)
[28e30,32,33,37]
1
150
24 (16%)
68 (45.3%)
[32]
385
92 (23.8%)
[29,33,36]
1
190
4 (2.1%)
57 ((30.0%)
[36]
354
47 (13.3%)
[27,29,32,37,38]
1
150
3 ((2.0%)
17 (11.3%)
[32]
332
28 (8.4%)
[27,29,32,38]
1
150
5 (3.3%)
8 (5.3%)
[32]
[3,27e32,35e38]
4
558
187 (18.9%) 187 (18.9%) 130 (13.1%) 70 (7.1%)
43 (7.7%) 28 (5.0%) 32 (5.7%) 1 (0.18%)
85 57 78 23
62 (6.25%)
11 (1.9%)
19 (3.4%)
730 resistance 482
992
[3,31,32,36] (15.2%) (10.2%) (14.0%) (4.1%)
296
X ¼ 3.35 ± 2.28
[27,36,38]
1
190
X¼1
X¼2
[36]
62 345
28 (46.2%) 146 (42.3%)
[35,37,38] [27 e29,31,35,37,38]
0 1
d 62
d 2 (3.2%)
d 21 (33.9%)
d [31]
4
311
105 (33.8%)
[27,28,32,33,38]
1
150
16 (10.6%)
32 (21.3%)
[32]
2
205
60 (29.2%)
[3,29]
1
156
16 (10.2%)
17 (21.2%)
[3]
CA-BSI-PA, community-acquired Pseudomonas aeruginosa bloodstream infections; CO-BSI-PA, community-onset P. aeruginosa bloodstream infections.
seeking care at an emergency unit. Male sex, solid tumour, haematologic malignancy, healthcare-associated infection and respiratory foci were identified as risk factors, which are in line with results found in this systematic review for CO-BSI-PA predictors. When comparing CA-BSI-PA with HCA-BSI-PA, we found that diabetes, haematologic malignancy, neutropenia and previous antibiotic use were more likely in the latter group; no statistically significant difference was found regarding the source of the BSI. This likely could be explained by the inclusion of a larger number of
patients in this analysis, because individual studies by Hattemer et al. [32] and McCarthy and Patterson [36] had only shown small differences between CA-BSI-PA and HCA-BSI-PA in multivariate analysis. Studies used slightly different definitions of CA-BSI-PA and HCA-BSI-PA, and they reported differently mortality, which precluded a pooled analysis. Data from the two largest studies showed no statistically significant difference in mortality; Parkins et al. [3] reported higher mortality for CA-BSI-PA, which was thought to be probably due to higher inappropriate empirical antibiotic therapy.
968
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
Table 3 Predictors for community-onset BSI due to Pseudomonas aeruginosa Study
Comparator
Type of analysis
Predictor
Prevalence
OR
95% CI
p
Cheong [38]
CO-BSI due to Escherichia coli
MV
Schechner [30]
CO-BSI due to any Enterobacteria
MV
Lee [35]
CO-BSI due to any microorganism
MV
1.05e4.75 1.09e3.94 1.28e6.69 5.1e23.71 2.53e18.26 1.91e15.17 1.87e7.36 1.31e6.73 3.20e17.47 0.98e5.03 0.14e0.74
CO-BSI due to any microorganism
UV
50e106 (47.7%) 56e106 (52.8%) 31e106 (29.2%) 94e106 (88.7%) 24e151 (15.9%) 14e151 (9.2%) 55e151 (36.4%) 36e151 (23.8%) 32e40 (80.0%) 30e40 (75.0%) 1e40 (2.5%) 32e44 (72.7%) 20e44 (45.5%) 40e44 (90.9%) 21e44 (47.7%) 5e44 (11.4%) 16e44 (36.4%) 6e44 (13.6%)
2.23 2.07 2.93 11.0 6.80 5.39 1.87 2.97 7.48 2.22 0.32
Hern andez [33]
Neutropenia Presentation with septic shock Central venous catheter Healthcare-associated infection Urinary device Age >90 years Recent antibiotic use Central venous catheter Neutropenia Male sex Liver cirrhosis Male sex Prior hospital admission Healthcare-associated infection Haematologic malignancy Haematopoietic stem-cell transplantation Neutropenia Haemodialysis
0.037 0.027 0.011 <0.001 <0.001 0.001 <0.001 0.009 <0.001 0.06 0.007 0.018 0.005 <0.001 0.008 0.015 0.001 0.020
BSI, bloodstream infections; CI, confidence interval; CO, community onset; MV, multivariate; OR, odds ratio; UV, univariate.
Fig. 2. Forest plot depicting odds ratios for 30-day mortality of patients (a) presenting with septic shock and (b) receiving inappropriate empiric antibiotic therapy for communityonset BSI due to Pseudomonas aeruginosa. Vertical line, no difference point between two therapies; squares, risk ratios; diamonds, pooled risk ratios; horizontal lines, 95% confidence interval. ATB, antibiotic; BSI, bloodstream infection; CI, confidence interval.
As a result of the observational nature of the included studies for this systematic review and meta-analysis, no standardized empiric antibiotic therapy was provided. An appropriate empiric antibiotic therapy was considered if it was provided according to antimicrobial susceptibility in a timely fashion. The included studies did not perform subgroup analysis, probably as a result of small sample sizes, which would have given us the opportunity to provide a stratified estimation according to baseline severity. Finally, we also found a high 30-day mortality (33.8%), which is comparable to mortality described for nosocomial P. aeruginosa BSI. Septic shock and inappropriate empiric antibiotic therapy were identified in the meta-analysis as significant
predictors for mortality in CO-BSI-PA. Septic shock presented with wide confidence intervals, most likely as a result of sparse data reported among the included studies. Individual studies included in the meta-analysis showed a trend towards increased mortality with inappropriate empiric antibiotic therapy, but, probably as a result of smaller numbers, it failed to reach robust statistical significance. Risk factors for inappropriate empiric antibiotic therapy were not homogenously analysed, precluding a pooled analysis of them. Nonetheless, in a striking way, inappropriate empiric antibiotic therapy for CO-BSI-PA was significantly linked with increased 30-day mortality in this meta-analysis.
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
Carrara et al. [40] had analysed in a meta-analysis the determinants of inappropriate empiric antimicrobial therapy and did not found, in a metaregression, a statistically significant association between all P. aeruginosa infections, including BSI and inappropriate empiric antibiotic therapy. Probably because a different population was analysed all microbiologically documented infections were included, thus selecting patients with less severe infections and lower levels of antibiotic resistance. Future research should focus on finding predictors for CO-BSI-PA in order to tailor empiric antibiotic therapy for Gram-negative CO-BSI and to avoid inappropriate empiric antimicrobial therapy to try to reduce mortality. The limitations in our study should be taken in consideration. All studies included are observational as a result of the nature of the research question; only one of them was conducted in a prospective cohort. This implies that causality associations should be taken with caution. Also, the number of studies and the information provided did not allow us to evaluate the impact of local epidemiologic situations. Not all variables of interest were reported in each study, which thus provides a fragmented picture of some of them. This was particularly relevant for antibiotic therapy and resistance, precluding a pooled analysis. Additionally, risk factors for inappropriate empiric antibiotic therapy were not analysed independently in the included studies, precluding further evaluations in their possible correlation with mortality. Studies included in the meta-analysis were of moderate and good quality according to the Newcastle-Ottawa scale for observational studies. Half of the studies included in the inappropriate empiric antimicrobial therapy meta-analysis were carried out in South Korea, so a generalization of their results should be taken cautiously, as they included only an Asian population. Nonetheless, we believe this study provides relevant information about CO-BSI due to P. aeruginosa. The fact that inappropriate empiric antimicrobial therapy is associated with mortality in CO- BSI-PA represents a clinical challenge; on the one hand, it seems imperative to try to appropriately cover this organism if highly probable, but on the other hand, overuse of antipseudomonal agents should be avoided in order to reduce the selective pressure on this and other microorganisms. Some data provided in this systematic review might be helpful for clinical decisions; however, specific studies including validated predictive scores or decision trees are needed to improve the decisions regarding empirical therapy. Acknowledgements AR received a scholarship for educational activities in Seville, and thanks the Oscar & Elsa Braun Foundation for funding it and lica de Chile for granting it. Pontificia Universidad Cato Transparency Declaration ZRP-B, LEL-C and JR-B received funding for research from Plan Nacional de IþDþi 2013-2016 and Instituto de Salud Carlos III, n General de Redes y Centros de Investigacio n CoopSubdireccio erativa, Ministerio de Economía, Industria y Competitividad, Spanish Network for Research in Infectious Diseases (REIPI RD16/ 0016/0001), cofinanced by European Development Regional Fund ‘A Way to Achieve Europe,’ Operative Programme Intelligent Growth, 2014e2020. JR-B received honoraria for accredited educational activities funded by Merck through unrestricted grants and for coordination of a noneproduct-related research project. ZRP-B received honoraria for educational talks by Gilead. LELC has served as speaker for Merck, Sharp & Dohme and Angelini, and has received research support from Novartis. The other authors report no conflicts of interest relevant to this article.
969
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.cmi.2019.04.005. References [1] European Centre for Disease Prevention and Control (ECDC). Point prevalence survey of healthcare-associated infections and antimicrobial use in European acute care hospitals, 2011e2012. 2013. Available at: https://ecdc.europa.eu/ sites/portal/files/media/en/publications/Publications/healthcare-associatedinfections-antimicrobial-use-PPS.pdf. [2] Al-Hasan MN, Wilson JW, Lahr B, Eckel-Passow JE, Baddour L. Incidence of Pseudomonas aeruginosa bacteremia: a population based study. Am J Med 2008;121:702e8. [3] Parkins MD, Gregson DB, Pitout JD, Ross T, Laupland KB. Population-based study of the epidemiology and risk factors for Pseudomonas aeruginosa bloodstream infection. Infection 2010;38:25e32. [4] Diekema DJ, Pfaller MA, Jones MN, Doern GV, Winokur PL, Gales AC, et al. SENTRY Participants Group (Americas). Survey of bloodstream infections due to Gram-negative bacilii: frequency of ocurrence and antimicrobial susceptibility of isolates collected in the United States, Canada, and Latin America for the SENTRY Antimicrobial Surveillance Program, 1997. Clin Infect Dis 1999;29:595e607. [5] Deccouser JW, Pina P, Picot F, Delalande C, Pangon B, Courvalin P, et al., ColBVH Study Group. Frequency of isolation and antimicrobial susceptibility of bacterial pathogens isolated from patients with bloodstream infections: a French prospective national survey. J Antimicrob Chemother 2003;51: 1213e22. [6] Werth BJ, Carreno JJ, Reveles KR. Shifting trends in the incidence of Pseudomonas aeruginosa septicemia in hospitalized adults in the United States from 1996 to 2010. Am J Infect Control 2015;43:465e8. [7] Vidal F, Mensa J, Almela M, Martínez JA, Marco F, Casals C, et al. Epidemiology and outcome of Pseudomonas aeruginosa bacteremia, with special emphasis on the influence of antibiotic treatment. Analysis of 189 episodes. Arch Intern Med 1996;156:2121e6. [8] Chatzinikolau I, Abi-Said D, Bodey GP, Rolston KV, Tarrand JJ, Samonis G. Recent experience with Pseudomonas aeruginosa bacteremia in patients with cancer: retrospective analysis of 245 episodes. Arch Intern Med 2000;160: 501e9. [9] Osmon S, Ward S, Fraser VJ, Kollef MH. Hospital mortality for patients with bacteremia due to Staphylococcus aureus or Pseudomonas aeruginosa. Chest 2004;125:607e16. [10] Tacconelli E, Carrara E, Savoldi A, Harbarth S, Mendelson M, Monnet DL, et al. WHO Pathogens Priority List Working Group. Discovery, research and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis. Lancet Infect Dis 2018;18:318e27. ~ a C, Suarez C, Gozalo M, Murillos J, Almirante B, Pomar V, et al. Spanish [11] Pen Network for Research in Infectious Diseases (REIPI). Carbapenem resistance increases mortality in Pseudomonas aeruginosa bloodstream infections. Antimicrob Agents Chemother 2012;34:1265e72. [12] Zhang Y, Chen XL, Huang AW, Liu SL, Liu WJ, Zhang N, et al. Mortality attributable to carbapenem resistant Pseudomonas aeruginosa bacteremia: a meta-analysis of cohort studies. Emerg Microb Infect 2016;5:e27. [13] Carmeli Y, Troillet N, Eliopoulos GM, Samore MH. Emergence of antibiotic resistant Pseudomonas aeruginosa: comparison of risks associated with different antipseudomonal agents. Antimicrob Agents Chemother 1999;43: 1379e82. [14] Siegman-Igra Y, Fourer B, Orni-Wasserlauf R, Golan Y, Noy A, Schwartz D, et al. Reappraisal of community-acquired bacteremia: a proposal of a new classification for the spectrum of acquisition of bacteremia. Clin Infect Dis 2002;34: 1431e9. [15] McDonald JR, Friedman ND, Stout JE, Sexton DJ, Kaye KS. Risk factors for ineffective therapy in patients with bloodstream infection. Arch Intern Med 2005;165:308e13. [16] Shorr AF, Tabak YP, Killian AD, Gupta V, Liu LZ, Kollef MH. Healthcare-associated bloodstream infection: a distinct entity? Insights from a large US database. Crit Care Med 2006;34:2588e95. s J, Calbo E, Anoro E, Fontanals D, Xercavins M, Espejo E, et al. Blood[17] Valle stream infections in adults: importance of healthcare-associated infections. J Infect 2008;56:27e34. ~ o J, Lo pez-Prieto MD, Portillo MM, Retamar P, Natera C, Nun ~ o E, [18] Rodríguez-Ban et al. SAEI/SAMPAC Bacteraemia Group. Epidemiology and clinical features of community-acquired, healthcare-associated and nosocomial bloodstream infections in tertiary-care and community hospitals. Clin Microb Infect 2010;16: 1408e13. [19] Kollef MH, Zilberberg MD, Shorr AF, Vo L, Schein J, Micek ST, et al. Epidemiology, microbiology and outcomes of healthcare-associated and communityacquired bacteremia: a multicenter cohort study. J Infect 2011;62:130e5. [20] Al-Hasan MN, Eckel-Passow JE, Baddour LM. Impact of healthcare-associated acquisition on community-onset Gram-negative bloodstream infection: a population-based studydhealthcare-associated Gram-negative BSI. Eur J Clin Microbiol Infect Dis 2012;31:1163e71.
970
A. Rojas et al. / Clinical Microbiology and Infection 25 (2019) 964e970
[21] Laupland KB, Gregson DB, Flemons WW, Hawkins D, Ross T, Church DL. Burden of community-onset bloodstream infection: a population-based assessment. Epidemiol Infect 2007;135:1037e42. [22] Moher D, Liberati A, Tetzlaff JM, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol 2009;62:1006e12. [23] Friedman ND, Kaye KS, Stout JE, McGarry SA, Trivette SL, Briggs JP, et al. Healthcare associated bloodstream infections in adults: a reason to change the accepted definition of community-acquired infections. Ann Intern Med 2002;137:791e7. [24] Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Available at: http://www.ohri.ca/programs/clinical_ epidemiology/oxford.asp. [25] SPSS Statistics for Windows, version 25.0 [computer program]. Armonk, NY: IBM Corp; 2017. [26] Review Manager (RevMan), version 5.3 [computer program]. Copenhagen: Nordic Cochrane Centre, Cochrane Collaboration; 2014. [27] Cheong HS, Kang CI, Wi YM, Ko KS, Chung DR, Lee NY, et al. Inappropiate antimicrobial therapy as a risk factor for mortality in patients with community onset Pseudomonas aeruginosa bacteremia. Eur J Clin Microb Infect Dis 2008;27:1219e25. [28] Kang CI, Kim SH, Park WB, Lee KD, Kim HB, Kim EC, et al. Clinical features and outcome of patients with community-acquired Pseudomonas aeruginosa bacteraemia. Clin Microb Infect 2005;11:415e8. [29] Schechner V, Gottesman T, Schwartz O, Korem M, Maor Y, Rahav G, et al. Pseudomonas aeruginosa bacteremia upon hospital admission: risk factors for mortality and influence of inadequate empirical antimicrobial therapy. Diagn Microbiol Infect Dis 2011;71:38e45. [30] Schechner V, Nobre V, Kaye KS, Leshno M, Giladi M, Rohner P, et al. Gramnegative bacteremia upon hospital admission: when should Pseudomonas aeruginosa be suspected? Clin Infect Dis 2009;48:580e6.
[31] Enoch DA, Kuzhively J, Sismey A, Grynik A, Karas JA. Pseudomonas aeruginosa bacteraemia in two UK district hospitals. Infect Dis Rep 2013;5:e4. [32] Hattemer A, Hausser A, Diaz M, Scheetz M, Shah N, Allen J, et al. Bacterial and clinical characteristics of health-care and community-acquired bloodstream infections due to Pseudomonas aeruginosa. Antimicrob Agents Chemother 2013;57:3969e75. [33] Hernandez C, Cobos-Trigueros N, Feher C, Morata L, De La Calle C, Marco F, et al. Community-onset bacteraemia of unknown origin: clinical characteristics, epidemiology and outcome. Eur J Clin Microbiol Infect Dis 2014;33: 1973e80. [34] Wolfe CM, Cohen B, Larson E. Prevalence and risk factors for antibioticresistant community-associated bloodstream infections. J Infect Public Health 2014;7:224e32. [35] Lee CC, Hsieh CC, Lee NY, Chan TY, Hong MY, Chi CH, et al. Different clinical presentation of community-onset bacteremia among neutropenic adults in the ED. Am J Emerg Med 2015;33:907e12. [36] McCarthy K, Patterson DL. Community acquired Pseudomonas aeruginosa bloodstream infection: a classification that should not falsely reassure the clinician. Eur J Clin Microbiol Infect Dis 2017;36:703e11. [37] Yang CY, Lee CH, Hsieh CC, Ko WC, Lee CC. Etiology of community-onset monomicrobial bacteremic pneumonia and its clinical presentation and outcome: Klebsiella and Pseudomonas matters. J Infect Chemother 2018;24:53e8. [38] Cheong HS, Kang CI, Wi YM, Kim ES, Lee JS, Soo KS, et al. Clinical significance and predictors of community-onset Pseudomonas aeruginosa bloodstream infections. Am J Med 2008;121:709e14. [39] Kang CI, Chung DR, Peck KR, Song JH. Korean Network for Study on Infectious Diseases (KONSID). Clinical predictors of Pseudomonas aeruginosa or Acinetobacter baumannii bacteremia in patients admitted to the ED. Am J Emerg Med 2012;30:1169e75. [40] Carrara E, Pfeffer I, Zusman O, Leibovici L, Paul M. Determinants of inappropriate empirical antibiotic treatment: systematic review and meta-analysis. Int J Antimicrob Agents 2018;5:548e53.