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Article

Pseudomonas Bacteremia in a Tertiary Hospital and Factors Associated with Mortality

by
Petros Ioannou
1,2,*,
Konstantinos Alexakis
2,
Sofia Maraki
3 and
Diamantis P. Kofteridis
1,2,*
1
School of Medicine, University of Crete, 71003 Heraklion, Greece
2
Internal Medicine Department, University Hospital of Heraklion, 71110 Heraklion, Greece
3
Department of Clinical Microbiology, University Hospital of Heraklion, 71110 Heraklion, Greece
*
Authors to whom correspondence should be addressed.
Antibiotics 2023, 12(4), 670; https://doi.org/10.3390/antibiotics12040670
Submission received: 26 February 2023 / Revised: 24 March 2023 / Accepted: 27 March 2023 / Published: 29 March 2023
Review Reports Versions Notes

Abstract

:
Pseudomonas aeruginosa is the third most commonly identified cause among gram-negative microorganisms causing bloodstream infection (BSI) and carries a very high mortality, higher than that by other gram-negative pathogens. The aim of the present study was to assess the epidemiological and microbiological characteristics of patients with BSI by Pseudomonas spp. in a tertiary hospital, characterize the resistance rates of different Pseudomonas strains to the most clinically relevant anti-microbials, estimate the mortality rate, and identify factors independently associated with mortality. In total, 540 cultures from 419 patients sent to the microbiology department of the hospital during the 8-year period of the study were positive. Patients had a median age of 66 years, and 262 (62.5%) were male. The blood culture was drawn in the ICU in 201 of the patients (48%). The infection was hospital-acquired in 329 patients (78.5%) and the median hospital day when the blood culture was drawn was 15, with a range of 0 to 267 days. Median duration of stay in the hospital was 36 days, hospital mortality was 44.2% (185 patients), and 30-day mortality was 29.6% (124 patients). The most commonly isolated Pseudomonas species were P. aeruginosa followed by P. putida and P. oryzihabitans. There was a statistically significant reduction of P. aeruginosa isolation relative to non-aeruginosa Pseudomonas species in the post-COVID-19 era. Antimicrobial resistance of P. aeruginosa in clinically relevant antimicrobials with anti-pseudomonal activity was similar before and after the onset of the COVID-19 pandemic with the exception of gentamicin and tobramycin, with P. aeruginosa being more susceptible to these two antimicrobials in the post-COVID-19 era. Rates of multi-drug resistant (MDR), extensively-drug resistant (XDR), and difficult-to-treat (DTR) P. aeruginosa isolation were lower after the onset of the COVID-19 pandemic, even though a carbapenem-focused antimicrobial stewardship program had been implemented in the meantime. Increased age, ICU-acquisition of BSI, and more days in the hospital when positive blood culture was drawn were positively associated with 30-day mortality of patients with Pseudomonas BSI. The fact that rates of MDR, XDR, and DTR P. aeruginosa isolation were lower late in the study period, with a carbapenem-focused antimicrobial stewardship intervention being implemented in the meantime, further increases the understanding that implementation of antimicrobial stewardship interventions may halt the increase in antimicrobial resistance noted previously.

1. Introduction

Pseudomonas aeruginosa is the third most commonly identified cause among gram-negative microorganisms causing bloodstream infection (BSI) and carries a very high mortality, higher than that by other gram-negative pathogens and also higher than that of Staphylococcus aureus, and is estimated to be at 30% after 30 days from the BSI episode [1,2,3,4]. BSI by Pseudomonas spp. is a universal problem and is more commonly hospital-acquired [5,6,7,8,9]. In specific settings, such as in intensive care units (ICU), the rate of Pseudomonas spp. isolation as pathogens causing BSIs is even higher. For example, in a study about ICU-acquired BSI, Pseudomonas aeruginosa was the second most common cause of BSI among gram-negative pathogens [10]. In another study regarding patients with liver transplantation, 35% of BSIs were due to P. aeruginosa and had an attributed mortality of 30% [11]. Commonly described risk factors for bacteremia by P. aeruginosa include recent antimicrobial use (most commonly involving the last three months), recent hospitalization, severe burns, pancreatobiliary disease, neutropenia or other immunodeficiency (such as hematologic malignancy or transplantation), and presence of an indwelling central venous or urinary catheter [6,8,12,13,14,15,16].
The coronavirus-disease 2019 (COVID-19) pandemic has caused pressure in healthcare systems, has led to increased rates of hospitalization, increased antimicrobial consumption, and has also led to a higher prevalence of multi-drug-resistant (MDR) pathogens [17,18]. This could be associated with increased rates of hospitalization, and at least to some extent, unnecessary antimicrobial use, healthcare personnel exhaustion, and possibly, a relative reduction in the implementation of antimicrobial stewardship practices [19]. Thus, due to the high mortality associated with Pseudomonas BSIs and the changing landscape in antimicrobial resistance and incidence of these infections in the post-COVID-19 era, studies evaluating the characteristics of these infections are warranted.
The aim of the present study was to assess the epidemiological and microbiological characteristics of patients with BSI by Pseudomonas spp. in a tertiary hospital, characterize the resistance rates of different Pseudomonas strains to the most clinically relevant antimicrobials, estimate the mortality rate, and identify factors independently associated with mortality.

2. Materials and Methods

2.1. Study Type and Ethics Approval

This is a retrospective single-center study including data regarding all cases of BSIs due to Pseudomonas spp. from patients hospitalized from 2015 to 2022 in the University Hospital of Heraklion, Heraklion, Greece, a tertiary hospital with 771 beds. All data were retrieved, retrospectively, from the database of the Department of Microbiology and were then evaluated. Data from blood cultures were included if the culture was positive for growth of Pseudomonas spp. Data collected and evaluated included type of sample that yielded a positive culture, date the culture was collected, microorganism identified, and antimicrobial resistance of the isolated microorganisms. Further information was extracted from the electronic health records regarding patients’ age, gender, duration of hospitalization, day of hospitalization the positive culture was taken, ward where the blood was drawn, outcome of hospitalization, and outcome at 30-days after the bacteremia. MDR and extensively-drug-resistant (XDR) pathogens were defined as previously published [20]. Difficult-to-treat (DTR) P. aeruginosa was defined as the strain resistant to all beta-lactams tested and fluoroquinolones as previously described [21]. Infection was considered hospital-acquired if the blood culture was drawn at least 48 h after admission. Post-COVID-19 era was defined as the era from 2020 until the end of the study. Conduction of the study was approved by the Institutional Review Board of the University Hospital of Heraklion.

2.2. Sample Collection, Transport, and Processing

Blood cultures were obtained from patients to investigate the possibility of bacteremia. Blood was collected in blood culture bottles that were promptly transported to the microbiology laboratory for further processing. Bottles were loaded and incubated on the BacT/Alert Virtuo system (BioMérieux, Marcy L’ Etoile, France) for five days unless growth was detected earlier. When a culture bottle signaled positive, gram stain and subcultures were then immediately performed. For the isolation of bacterial pathogens, specimens were inoculated onto Columbia blood, chocolate, MaC Conkey, and Schaedler blood agar (all products of bioMérieux SA, Marcy L’Étoile, France) and incubated at 36 °C. Identification of bacterial species was performed by standard biochemical assays and the Vitek 2 automated system and confirmed by the matrix-assisted laser desorption time of flight mass spectrometry (MALDI-TOF MS) (version 3.2) (both products of bioMérieux SA, Marcy L’Étoile, France). The Vitek 2 automated system was also used for antibiotic susceptibility testing and results were interpreted according to the 2021 Clinical and Laboratory Standards Institute (CLSI) criteria [22]. As quality control strains, Escherichia coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853, S. aureus ATCC 25923, and E. faecalis ATCC 29212 were used.

2.3. Statistics

Descriptive statistics were performed with GraphPad Prism 6.0 (GraphPad Software, Inc., San Diego, CA, USA). Qualitative data were presented as counts and percentages. Categorical data were analyzed with Fisher’s exact test. Continuous variables were compared using Student’s t-test for normally distributed variables and the Mann–Whitney U-test for non-normally distributed variables. All tests were two-tailed and p ≤ 0.05 was considered to be significant. Data are presented as numbers (%) for categorical variables and medians (interquartile range (IQR)) or means (±standard deviation (SD)) for continuous variables. A linear-regression analysis model was developed to evaluate the effect of several parameters (age, gender, P. aeruginosa BSI, antimicrobial resistance to specific antimicrobials, ward where positive blood culture was taken, day of hospitalization when positive blood culture was taken) with 30-day mortality. All the parameters mentioned above were calculated with GraphPad Prism 6.0 (GraphPad Software, Inc., San Diego, CA, USA). A multivariate logistic-regression analysis model was developed to evaluate the association of factors identified in the univariate analysis with a p ≤ 0.05 with mortality. Multivariate analysis was performed using the SPSS version 23.0 (IBM Corp., Armonk, NY, USA).

3. Results

3.1. Patients’ Characteristics

In total, 540 cultures from 419 patients that had been sent to the microbiology department of the hospital during the 8-year period of the study were positive. Patients had a median age of 66 years and 262 (62.5%) were male. The blood culture was drawn in the ICU in 201 (48%), in a medical ward in 142 (33.9%), and in a surgical ward in 76 (18.1%). The infection was hospital-acquired in 329 patients (78.5%) and the median hospital day the blood culture was drawn was 15 with a range of 0 to 267 days. Median duration of stay in the hospital was 36 days, and hospital mortality was 44.2% (185 patients), while mortality at 30-days after occurrence of bacteremia was 29.6% (124 patients).
Patients who died up to 30-days after the occurrence of bacteremia had a higher age, were more likely to have a hospital-acquired BSI, and more specifically, were more likely to have acquired the BSI later in their hospitalization, were less likely to be hospitalized in a surgical ward, more likely to be hospitalized in the ICU, and were more likely to have a longer duration of hospitalization. Table 1 shows the characteristics of patients with Pseudomonas spp. and shows a comparison among patients who survived and those who died up to 30-days after the occurrence of bacteremia.

3.2. Microbiology of Pseudomonas BSIs

The most commonly isolated Pseudomonas species were P. aeruginosa followed by P. putida and P. oryzihabitans. Table S1 from Supplementary shows the microbiology of the isolated species in total as well as the year of the study, while Table 2 shows the microbiology of Pseudomonas species isolated in total as well as whether the episode of BSI occurred in the pre-COVID-19 era or the post-COVID-19 era. Occurrence of BSIs by Pseudomonas spp. was relatively stable during the years of the study. There was a statistically significant reduction of P. aeruginosa isolation compared to non-aeruginosa Pseudomonas species in the post-COVID-19 era.
A comparison of the microbiology of Pseudomonas BSIs among patients who had community-acquired BSI compared to that of patients with hospital-acquired BSI shows a statistically significant higher rate of P. putida isolation relative to other Pseudomonas species in patients who had a hospital-acquired BSI. Table S2 from Supplementary shows the microbiology of Pseudomonas strains isolated from patients’ blood cultures as well as whether the BSI was acquired in the hospital or in the community.
Table S3 from Supplementary shows the microbiology of Pseudomonas strains isolated from patients’ blood cultures as well as whether the patient was hospitalized in a ward or in the intensive care unit at the time the blood culture was drawn. A comparison among these different groups of patients did not reveal any statistically significant difference.
A comparison of the microbiology of Pseudomonas BSIs among patients who survived with those who died shows a statistically significant higher rate of P. aeruginosa isolation relative to non-aeruginosa Pseudomonas species in patients who died. Table 3 shows the microbiology of Pseudomonas strains isolated from patients’ blood cultures compared to patients’ outcome at 30-days after the occurrence of bacteremia.

3.3. Antimicrobial Resistance of P. aeruginosa Isolated from BSI Episodes

Antimicrobial resistance of P. aeruginosa in clinically relevant antimicrobials with anti-pseudomonal activity was similar before and after the onset of the COVID-19 pandemic with the exception of gentamicin and tobramycin, with P. aeruginosa being more susceptible to these two antimicrobials in the post-COVID-19 era in a statistically significant manner. Table 4 shows the antimicrobial resistance to P. aeruginosa in total as well as whether isolation was before or after the onset of the COVID-19 pandemic. Interestingly, in the post-COVID-19 era, isolation of MDR, XDR, and DTR strains was less frequent.
A comparison of antimicrobial resistance of P. aeruginosa strains among patients who had community-acquired BSI with those who had hospital-acquired BSI showed a higher resistance of P. aeruginosa to aztreonam, meropenem, and ticarcillin in strains isolated from hospital-acquired BSIs. Table S4 from Supplementary shows the antimicrobial resistance of P. aeruginosa strains isolated from patients’ blood cultures as well as whether the BSI was community- or hospital-acquired.
A comparison of antimicrobial resistance of P. aeruginosa strains among patients hospitalized in the wards compared to those who were hospitalized in the ICU at the time the blood culture was drawn did not reveal any statistically significant differences. Table S5 from Supplementary shows the antimicrobial resistance of P. aeruginosa strains isolated from patients’ blood cultures compared to where the patient was hospitalized at the time the blood culture was drawn.
A comparison of antimicrobial resistance of P. aeruginosa strains among patients who survived with those who died showed that patients who died had more resistant strains causing BSI in a statistically significant way for all antimicrobials except for colistin. Table 5 shows the antimicrobial resistance of P. aeruginosa strains isolated from patients’ blood cultures compared to patients’ outcome at 30-days after the occurrence of bacteremia.
Table S6 from Supplementary shows the antimicrobial resistance of the different Pseudomonas species isolated during the study period. P. aeruginosa was the most resistant species among the clinically relevant anti-pseudomonal antimicrobials followed by P. putida and P. stutzeri.

3.4. Regression Analysis of 30-Day Mortality among Patients with BSI by Pseudomonas spp.

To identify factors associated with mortality at 30-days after the occurrence of bacteremia, we performed regression analysis as follows. First, we performed univariate linear-regression analysis to evaluate the effect of several parameters such as age, gender, P. aeruginosa BSI, pattern of antimicrobial resistance, ward where positive blood culture was taken, and day of hospitalization when positive blood culture was taken with mortality at 30-days after the occurrence of bacteremia. Age, ICU-acquisition, more days in the hospital when the positive blood culture was taken, P. aeruginosa BSI, MDR, XDR, and DTR phenotype were all found to be positively associated with mortality at 30-days after the occurrence of bacteremia. However, a multivariate logistic-regression model identified only increased age (p < 0.001, odds ratio 1.032), ICU-acquisition (p = 0.01, odds ratio 2.213), and more days in the hospital when positive blood culture was taken (p = 0.005, odds ratio 1.01) to be independently positively associated with mortality at 30-days after the occurrence of bacteremia. Table 6 shows the results of the regression analysis of 30-day mortality among patients with Pseudomonas spp. BSI.

4. Discussion

The present study investigated the microbiology and antimicrobial resistance of Pseudomonas spp. BSI in a tertiary hospital in Crete, Greece. The most common species was P. aeruginosa, which was also the most resistant to antimicrobials. Isolation of Pseudomonas spp. was stable throughout the study period. Mortality at 30-days after occurrence of BSI was high and patients who died had a higher age, were more likely to have hospital-acquired BSI, and more specifically, were more likely to have acquired the BSI later in their hospitalization, were less likely to be hospitalized in a surgical ward and more likely to be hospitalized in the ICU, were more likely to have a longer duration of hospitalization, and were also more likely to have a BSI by P. aeruginosa as well as increased antimicrobial resistance. Increased age, ICU-acquisition of BSI, and more days in the hospital when positive blood culture was drawn were independently positively associated with 30-day mortality.
BSIs by Pseudomonas spp. and more specifically, by P. aeruginosa, are commonly encountered in clinical practice, especially in patients with risk factors for acquisition of this pathogens, such as advanced age, neutropenia or other immunodeficiency (e.g., malignancy or transplantation), indwelling central venous or urinary catheter, severe burns, pancreatobiliary disease, previous receipt of antimicrobials, and previous or current hospitalization [5,6,7,8,9,12,16,23]. The clinical presentation includes the typical features noted for all patients with gram-negative sepsis, such as fever, tachycardia and tachypnea, hypotension, respiratory failure, and disorientation, even though these findings may also occur in cases of sepsis by other organisms as well, and they are not specific exclusively for gram-negative sepsis. The most common sources of P. aeruginosa sepsis and bacteremia include the respiratory tract, infected intravascular catheters, the gastrointestinal and hepatobiliary tract, the urinary tract, and the skin and soft tissues. However, in up to 40% of cases, the source of bacteremia is not evident [7,24,25].
In the present study, the most common species, as anticipated, was P. aeruginosa, which is the most clinically relevant species causing infection, and more specifically BSIs, in humans. Indeed, most studies on BSIs refer exclusively to P. aeruginosa so that it may be hard to compare data on non-aeruginosa species to others in the literature. A study referring to non-aeruginosa Pseudomonas species in respiratory samples of patients with cystic fibrosis identified P. fluorescens, P. putida, and P. stutzeri as the most common species with 33, 18, and 6 isolated strains, respectively, followed by P. alcaligenes, P. fragi, P. mendocina, P. nitroreducens, P. oleovorans, P, oryzihabitans, and P, veronii, each with one isolated stain [26]. In the same study, the clinical importance of the non-aeruginosa Pseudomonas species is discussed, suggesting that some of them may be of low pathogenicity. In the present study, the most commonly isolated species beyond P. aeruginosa were P. putida, P. oryzihabitans, and P. stutzeri. An older study evaluating non-aeruginosa Pseudomonas species as causes of BSI identified a small number of such species and discusses the clinical relevance their isolation may have, since most patients with such species did not receive antimicrobial treatment, with no mortality noted [27]. In the present study, even though there were no data regarding antimicrobial treatment of the patients, a statistically significant association between isolation of P. aeruginosa and 30-day mortality was noted, even though this was not identified as an independent factor associated with 30-day mortality in a multivariate logistic-regression analysis model.
Even though the number of Pseudomonas isolates identified in blood cultures remained stable through the years, there was a statistically significant reduction of P. aeruginosa strains in the post-COVID-19 era. Infection by non-aeruginosa Pseudomonas species is relatively uncommon and it mostly occurs in patients with underlying immunocompromise, or in association with an infected medical device [28,29,30].
Antimicrobial resistance among gram-negative microorganisms is a problem of increasing magnitude in medicine, associated with increased morbidity, mortality, and health costs [31,32]. Currently, for many pathogens, available antimicrobial treatments are limited, and choices include revived antibiotics or combinations of antimicrobials [33,34,35,36,37]. P. aeruginosa has many different mechanisms of antimicrobial resistance that may include production of antibiotic-inactivating enzymes, efflux systems, and modification of the permeability of the outer membrane [38]. In the present study, regarding antimicrobial resistance, P. aeruginosa has the highest rates of resistance to clinically relevant antimicrobials with anti-pseudomonal activity, such as piperacillin, ciprofloxacin, and cefepime. However, antimicrobial resistance to old antibiotics such as colistin is still low, meaning that even in cases of BSI by P. aeruginosa with multiple resistance mechanisms, there are still available options in terms of treatment. Nowadays, newer antimicrobials and antimicrobial combinations, such as the combination of ceftolozane with tazobactam, the combination of ceftazidime with avibactam, cefiderocol, the combination of imipenem with cilastatin and relebactam, or the combination of aztreonam with avibactam have emerged as important therapeutic options that should be preferred for the treatment of BSI by sensitive microorganisms such as Pseudomonas species [21,39,40,41]. In the present study, these newer antimicrobials were not tested; thus, no result can be drawn regarding their susceptibility in the isolated strains. Interestingly, other species such as P. putida also have high rates of antimicrobial resistance to the same antimicrobials. This is in line with studies showing that, even though non-aeruginosa Pseudomonas species may have been previously considered to have low pathogenicity, some of them, such as P. putida, are causing significant mortality in cases of BSI, and also have important antimicrobial resistance [30,42]. For example, P. putida has been identified as a nosocomial cause of infection with multi-drug-resistance and production of VIM-2 metallo-beta-lactamase, probably by independent horizontal transfer of resistance genes [43,44].
In the present study, antimicrobial resistance of P. aeruginosa seemed to have remained stable throughout the study period when studying each antimicrobial individually, with the exception of gentamicin and tobramycin, as, in the post-COVID-19 era, P. aeruginosa had less resistance against these two aminoglycosides. Interestingly, rates of MDR, XDR, and DTR were lower in patients with BSI by P. aeruginosa in the post-COVID-19 era. However, it is of note that, during the study period, a carbapenem-focused antimicrobial stewardship program was implemented and led to a reduction of use of carbapenems through unsolicited consultations of infectious disease physicians; this may have affected the time-course of development of antimicrobial resistance, by halting a possibly increasing trend [45,46]. This is of utmost importance since it increases the common understanding that implementation of antimicrobial stewardship interventions may lead to reduction of antimicrobial use, reduction of hospital costs, and reduction of antimicrobial resistance without an increase in mortality [47]. In some other studies, antimicrobial resistance of P. aeruginosa strains also remained stable during the COVID-19 pandemic [48,49,50]. More specifically, in some studies, an increase in infections by carbapenem-susceptible P. aeruginosa was noted, which could theoretically be associated with a higher consumption of third generation cephalosporins during the first wave of the COVID-19 pandemic [49]. In other studies, however, trends for antimicrobial resistance of P. aeruginosa was rising during the COVID-19 pandemic [51,52].
Interestingly, for all antimicrobials tested, with the single exception of colistin, there was a statistically significant association between antimicrobial resistance and 30-day mortality, while MDR, XDR, and DTR P. aeruginosa was more frequently isolated among patients with BSI who died within 30-days from the positive blood culture. However, this could have been a result of the higher likelihood of ICU-acquisition of Pseudomonas BSI among patients who died, as there was a non-statistically significant trend for higher antimicrobial resistance of P. aeruginosa strains isolated in the ICU. To that end, a multivariate logistic-regression analysis identified ICU-acquisition of Pseudomonas BSI to be independently associated with 30-day mortality, while antimicrobial resistance was not. Notably, the fact that diagnosis of the BSI in the ICU is associated with higher mortality is probably an epiphenomenon of the more severe clinical condition of the patients diagnosed in this setting. Indeed, patients admitted to the ICU have higher severity of illness and higher mortality when diagnosed with BSI [53]. However, since the present study is based mostly on microbiological data, a direct association of BSI mortality with the severity of the underlying illness addressed with clinical severity scores such as SOFA or APACHE could not have been performed.
The multivariate logistic-regression analysis identified also increased age and increased length of hospitalization before drawing the positive blood culture for Pseudomonas spp. to be independently associated with 30-day mortality. Increased age is well known to be associated with increased mortality in studies of hospitalized patients in general; thus, this finding was not a surprise [54]. On the other hand, length of hospitalization before the positive blood culture could also be an epiphenomenon, since length of hospitalization may also be a factor that could be theoretically associated with the clinical condition of the patient, as patients with more complex medical or surgical problems may have a need for more prolonged hospitalization and may have higher mortality, especially in the case of BSI by drug-resistant gram-negative pathogens [55]. However, the present study did not focus on the clinical characteristics of the patients; thus, this presumed association of length of hospitalization before drawing a blood culture in patients with BSI by Pseudomonas spp. and the severity of their clinical condition has not been confirmed in the present study. In other studies, though, prolonged hospitalization in general has also been associated with mortality [54].
This study has some limitations that should be acknowledged. First, it is a single-center study; thus, the results should be read cautiously as they represent the microbiology and antimicrobial resistance patterns of a specific area. Furthermore, as this study mostly included microbiological data, there are no data regarding patients’ clinical characteristics or treatment. For example, the criterion of hospital-acquired bacteremia was whether the blood culture was drawn after 48 h from admission, which may not necessarily coincide with the most appropriate definition of development of symptoms of infection after 48 h from the admission. Moreover, since clinical data were not collected, whether BSI episodes were primary or secondary was not addressed in the present study. On the other hand, clinical and laboratory data allowing estimation of the severity of the underlying disease through calculation of SOFA or APACHE scores was not possible in the present study. Moreover, the antimicrobials tested are not all that are available; thus, newer antimicrobial combinations, such as that of ceftazidime/avibactam or ceftolozane/tazobactam have not been included in the analysis. Finally, some of the Pseudomonas species were very few; thus, the data regarding antimicrobial resistance may not be reliable enough to draw safe conclusions.

5. Conclusions

BSIs by Pseudomonas spp. carry significant mortality. P. aeruginosa is the most commonly identified species and has significant antimicrobial resistance; however, other species such as P. putida may also resemble significant resistance. Increased age, ICU-acquisition of BSI, and more days in the hospital when positive blood culture was drawn were independently positively associated with 30-day mortality. The fact that rates of MDR, XDR, and DTR P. aeruginosa isolation were lower late during the study period, with a carbapenem-focused antimicrobial stewardship intervention being implemented in the meantime, further increases the understanding that implementation of antimicrobial stewardship interventions may halt the increase in antimicrobial resistance noted previously.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/antibiotics12040670/s1, Table S1: Microbiology of Pseudomonas strains isolated from patients’ blood cultures; Table S2: Microbiology of Pseudomonas strains isolated from patients’ blood cultures in regards to acquisition; Table S3: Microbiology of Pseudomonas strains isolated from patients’ blood cultures in regards to whether the patient was hospitalized in a ward or in the intensive care unit; Table S4: Antimicrobial resistance of Pseudomonas aeruginosa strains isolated from patients’ blood cultures in regards to whether bacteremia was community- or hospital-acquired; Table S5: Antimicrobial resistance of Pseudomonas aeruginosa strains isolated from patients’ blood cultures in regards to whether the patient was hospitalized in a ward or in the intensive care unit; Table S6: Antimicrobial resistance of the different Pseudomonas species isolated from patients’ blood.

Author Contributions

Conceptualization, P.I. and D.P.K.; Data curation, P.I.; Formal analysis, P.I.; Investigation, K.A. and S.M.; Methodology, P.I., K.A. and S.M.; Project administration, D.P.K.; Resources, S.M. and D.P.K.; Software, P.I. and K.A.; Supervision, D.P.K.; Validation, P.I.; Visualization, P.I.; Writing—original draft, P.I.; Writing—review & editing, K.A., S.M. and D.P.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of the University Hospital of Heraklion (protocol code 8/24-03-2021).

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Horino, T.; Chiba, A.; Kawano, S.; Kato, T.; Sato, F.; Maruyama, Y.; Nakazawa, Y.; Yoshikawa, K.; Yoshida, M.; Hori, S. Clinical Characteristics and Risk Factors for Mortality in Patients with Bacteremia Caused by Pseudomonas Aeruginosa. Intern. Med. 2012, 51, 59–64. [Google Scholar] [CrossRef] [PubMed]
  2. Kang, C.; Kim, S.; Kim, H.; Park, S.; Choe, Y.; Oh, M.; Kim, E.; Choe, K. Pseudomonas Aeruginosa Bacteremia: Risk Factors for Mortality and Influence of Delayed Receipt of Effective Antimicrobial Therapy on Clinical Outcome. Clin. Infect. Dis. 2003, 37, 745–751. [Google Scholar] [CrossRef] [PubMed]
  3. Magill, S.S.; Edwards, J.R.; Bamberg, W.; Beldavs, Z.G.; Dumyati, G.; Kainer, M.A.; Lynfield, R.; Maloney, M.; McAllister-Hollod, L.; Nadle, J.; et al. Multistate Point-Prevalence Survey of Health Care-Associated Infections. N. Engl. J. Med. 2014, 370, 1198–1208. [Google Scholar] [CrossRef] [PubMed]
  4. Thaden, J.T.; Park, L.P.; Maskarinec, S.A.; Ruffin, F.; Fowler, V.G.; van Duin, D. Results from a 13-Year Prospective Cohort Study Show Increased Mortality Associated with Bloodstream Infections Caused by Pseudomonas Aeruginosa Compared to Other Bacteria. Antimicrob Agents Chemother 2017, 61, e02671-16. [Google Scholar] [CrossRef]
  5. Wisplinghoff, H.; Bischoff, T.; Tallent, S.M.; Seifert, H.; Wenzel, R.P.; Edmond, M.B. Nosocomial Bloodstream Infections in US Hospitals: Analysis of 24,179 Cases from a Prospective Nationwide Surveillance Study. Clin. Infect. Dis. 2004, 39, 309–317. [Google Scholar] [CrossRef]
  6. Chatzinikolaou, I.; Abi-Said, D.; Bodey, G.P.; Rolston, K.V.; Tarrand, J.J.; Samonis, G. Recent Experience with Pseudomonas Aeruginosa Bacteremia in Patients with Cancer: Retrospective Analysis of 245 Episodes. Arch. Intern. Med. 2000, 160, 501–509. [Google Scholar] [CrossRef]
  7. Sifuentes-Osornio, J.; Gonzalez, R.; Ponce-de-Leon, A.; Guerrero, M.L. Epidemiology and Prognosis of Pseudomonas Aeruginosa Bacteremia in a Tertiary Care Center. Rev. Investig. Clin. 1998, 50, 383–388. [Google Scholar]
  8. Vidal, F.; Mensa, J.; Almela, M.; Martínez, J.A.; Marco, F.; Casals, C.; Gatell, J.M.; Soriano, E.; Jimenez de Anta, M.T. 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, 2121–2126. [Google Scholar] [CrossRef]
  9. Al-Hasan, M.N.; Wilson, J.W.; Lahr, B.D.; Eckel-Passow, J.E.; Baddour, L.M. Incidence of Pseudomonas Aeruginosa Bacteremia: A Population-Based Study. Am. J. Med. 2008, 121, 702–708. [Google Scholar] [CrossRef]
  10. Sligl, W.I.; Dragan, T.; Smith, S.W. Nosocomial Gram-Negative Bacteremia in Intensive Care: Epidemiology, Antimicrobial Susceptibilities, and Outcomes. Int. J. Infect. Dis. 2015, 37, 129–134. [Google Scholar] [CrossRef]
  11. Liu, T.; Zhang, Y.; Wan, Q. Pseudomonas Aeruginosa Bacteremia among Liver Transplant Recipients. Infect. Drug Resist. 2018, 11, 2345–2356. [Google Scholar] [CrossRef] [PubMed]
  12. Schechner, V.; Nobre, V.; Kaye, K.S.; Leshno, M.; Giladi, M.; Rohner, P.; Harbarth, S.; Anderson, D.J.; Karchmer, A.W.; Schwaber, M.J.; et al. Gram-Negative Bacteremia upon Hospital Admission: When Should Pseudomonas Aeruginosa Be Suspected? Clin. Infect. Dis. 2009, 48, 580–586. [Google Scholar] [CrossRef] [PubMed]
  13. Mendelson, M.H.; Gurtman, A.; Szabo, S.; Neibart, E.; Meyers, B.R.; Policar, M.; Cheung, T.W.; Lillienfeld, D.; Hammer, G.; Reddy, S. Pseudomonas Aeruginosa Bacteremia in Patients with AIDS. Clin. Infect. Dis. 1994, 18, 886–895. [Google Scholar] [CrossRef]
  14. Shepp, D.H.; Tang, I.T.; Ramundo, M.B.; Kaplan, M.K. Serious Pseudomonas Aeruginosa Infection in AIDS. J. Acquir. Immune. Defic. Syndr. 1994, 7, 823–831. [Google Scholar]
  15. Leigh, L.; Stoll, B.J.; Rahman, M.; McGowan, J. Pseudomonas Aeruginosa Infection in Very Low Birth Weight Infants: A Case-Control Study. Pediatr. Infect. Dis. J. 1995, 14, 367–371. [Google Scholar] [CrossRef] [PubMed]
  16. Vuotto, F.; Berthon, C.; Lemaitre, N.; Duhamel, A.; Balkaran, S.; Le Ray, E.; Micol, J.B.; Faure, K.; Alfandari, S. Risk Factors, Clinical Features, and Outcome of Pseudomonas Aeruginosa Bacteremia in Patients with Hematologic Malignancies: A Case-Control Study. Am. J. Infect. Control. 2013, 41, 527–530. [Google Scholar] [CrossRef]
  17. Jeon, K.; Jeong, S.; Lee, N.; Park, M.-J.; Song, W.; Kim, H.-S.; Kim, H.S.; Kim, J.-S. Impact of COVID-19 on Antimicrobial Consumption and Spread of Multidrug-Resistance in Bacterial Infections. Antibiotics 2022, 11, 535. [Google Scholar] [CrossRef]
  18. Langford, B.J.; Soucy, J.-P.R.; Leung, V.; So, M.; Kwan, A.T.H.; Portnoff, J.S.; Bertagnolio, S.; Raybardhan, S.; MacFadden, D.R.; Daneman, N. Antibiotic Resistance Associated with the COVID-19 Pandemic: A Systematic Review and Meta-Analysis. Clin. Microbiol. Infect. 2022, 29, 302–309. [Google Scholar] [CrossRef]
  19. Spernovasilis, N.A.; Kofteridis, D.P. COVID-19 and Antimicrobial Stewardship: What Is the Interplay? Infect. Control. Hosp. Epidemiol. 2021, 42, 378–379. [Google Scholar] [CrossRef]
  20. Magiorakos, A.-P.; Srinivasan, A.; Carey, R.B.; Carmeli, Y.; Falagas, M.E.; Giske, C.G.; Harbarth, S.; Hindler, J.F.; Kahlmeter, G.; Olsson-Liljequist, B.; et al. Multidrug-Resistant, Extensively Drug-Resistant and Pandrug-Resistant Bacteria: An International Expert Proposal for Interim Standard Definitions for Acquired Resistance. Clin. Microbiol. Infect. 2012, 18, 268–281. [Google Scholar] [CrossRef]
  21. Paul, M.; Carrara, E.; Retamar, P.; Tängdén, T.; Bitterman, R.; Bonomo, R.A.; de Waele, J.; Daikos, G.L.; Akova, M.; Harbarth, S.; et al. European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Guidelines for the Treatment of Infections Caused by Multidrug-Resistant Gram-Negative Bacilli (Endorsed by European Society of Intensive Care Medicine). Clin. Microbiol. Infect. 2022, 28, 521–547. [Google Scholar] [CrossRef]
  22. Clinical and Laboratory Standards Institute. Performance Standards for Antimicrobial Susceptibility Testing, 32nd ed.; (M100-S32); Clinical and Laboratory Standards Institute: Wayne, PA, USA, 2022. [Google Scholar]
  23. Dropulic, L.K.; Leslie, J.M.; Eldred, L.J.; Zenilman, J.; Sears, C.L. Clinical Manifestations and Risk Factors of Pseudomonas Aeruginosa Infection in Patients with AIDS. J. Infect. Dis. 1995, 171, 930–937. [Google Scholar] [CrossRef]
  24. Chen, S.C.; Lawrence, R.H.; Byth, K.; Sorrell, T.C. Pseudomonas Aeruginosa Bacteraemia. Is Pancreatobiliary Disease a Risk Factor? Med. J. Aust. 1993, 159, 592–597. [Google Scholar] [CrossRef]
  25. Centers for Disease Control and Prevention (CDC). Pseudomonas Aeruginosa Infections Associated with Transrectal Ultrasound-Guided Prostate Biopsies--Georgia, 2005. Morb. Mortal Wkly Rep. 2006, 55, 776–777. [Google Scholar]
  26. Moore, J.E.; McCaughan, J.; Rendall, J.C.; Millar, B.C. The Microbiology of Non-Aeruginosa Pseudomonas Isolated from Adults With Cystic Fibrosis: Criteria to Help Determine the Clinical Significance of Non-Aeruginosa Pseudomonas in CF Lung Pathology. Br. J. Biomed. Sci. 2022, 79, 10468. [Google Scholar] [CrossRef]
  27. Aoun, M.; Van der Auwera, P.; Devleeshouwer, C.; Daneau, D.; Seraj, N.; Meunier, F.; Gerain, J. Bacteraemia Caused by Non-Aeruginosa Pseudomonas Species in a Cancer Centre. J. Hosp. Infect. 1992, 22, 307–316. [Google Scholar] [CrossRef]
  28. Hsueh, P.R.; Teng, L.J.; Pan, H.J.; Chen, Y.C.; Sun, C.C.; Ho, S.W.; Luh, K.T. Outbreak of Pseudomonas Fluorescens Bacteremia among Oncology Patients. J. Clin. Microbiol. 1998, 36, 2914–2917. [Google Scholar] [CrossRef]
  29. Picollo, M.; Ferraro, D.K.; Pérez, G.; Reijtman, V.; Gomez, S.; Garcia, M.E.; Mastroianni, A.; Rosanova, M.T. Pseudomonas Putida Bacteremia in Pediatric Patients: A Case Series Study. Enferm. Infecc. Microbiol. Clin. 2022, in press. [CrossRef]
  30. Tan, G.; Xi, Y.; Yuan, P.; Sun, Z.; Yang, D. Risk Factors and Antimicrobial Resistance Profiles of Pseudomonas Putida Infection in Central China, 2010-2017. Medicine 2019, 98, e17812. [Google Scholar] [CrossRef]
  31. Breijyeh, Z.; Jubeh, B.; Karaman, R. Resistance of Gram-Negative Bacteria to Current Antibacterial Agents and Approaches to Resolve It. Molecules 2020, 25, 1340. [Google Scholar] [CrossRef]
  32. Kofteridis, D.P.; Andrianaki, A.M.; Maraki, S.; Mathioudaki, A.; Plataki, M.; Alexopoulou, C.; Ioannou, P.; Samonis, G.; Valachis, A. Treatment Pattern, Prognostic Factors, and Outcome in Patients with Infection Due to Pan-Drug-Resistant Gram-Negative Bacteria. Eur. J. Clin. Microbiol. Infect. Dis. 2020, 39, 965–970. [Google Scholar] [CrossRef]
  33. Bassetti, M.; Garau, J. Current and Future Perspectives in the Treatment of Multidrug-Resistant Gram-Negative Infections. J. Antimicrob. Chemother. 2021, 76, iv23–iv37. [Google Scholar] [CrossRef]
  34. Muller, A.E.; Theuretzbacher, U.; Mouton, J.W. Use of Old Antibiotics Now and in the Future from a Pharmacokinetic/Pharmacodynamic Perspective. Clin. Microbiol. Infect. 2015, 21, 881–885. [Google Scholar] [CrossRef]
  35. Nang, S.C.; Azad, M.A.K.; Velkov, T.; Zhou, Q.T.; Li, J. Rescuing the Last-Line Polymyxins: Achievements and Challenges. Pharmacol. Rev. 2021, 73, 679–728. [Google Scholar] [CrossRef]
  36. Giurazza, R.; Mazza, M.C.; Andini, R.; Sansone, P.; Pace, M.C.; Durante-Mangoni, E. Emerging Treatment Options for Multi-Drug-Resistant Bacterial Infections. Life 2021, 11, 519. [Google Scholar] [CrossRef]
  37. Theuretzbacher, U.; Van Bambeke, F.; Cantón, R.; Giske, C.G.; Mouton, J.W.; Nation, R.L.; Paul, M.; Turnidge, J.D.; Kahlmeter, G. Reviving Old Antibiotics. J. Antimicrob. Chemother. 2015, 70, 2177–2181. [Google Scholar] [CrossRef] [PubMed]
  38. Pang, Z.; Raudonis, R.; Glick, B.R.; Lin, T.-J.; Cheng, Z. Antibiotic Resistance in Pseudomonas Aeruginosa: Mechanisms and Alternative Therapeutic Strategies. Biotechnol. Adv. 2019, 37, 177–192. [Google Scholar] [CrossRef]
  39. Tamma, P.D.; Aitken, S.L.; Bonomo, R.A.; Mathers, A.J.; van Duin, D.; Clancy, C.J. Infectious Diseases Society of America 2022 Guidance on the Treatment of Extended-Spectrum β-Lactamase Producing Enterobacterales (ESBL-E), Carbapenem-Resistant Enterobacterales (CRE), and Pseudomonas Aeruginosa with Difficult-to-Treat Resistance (DTR-P. Aeruginosa). Clin. Infect. Dis. 2022, 75, 187–212. [Google Scholar] [CrossRef]
  40. Hakeam, H.A.; Askar, G.; Al Sulaiman, K.; Mansour, R.; Al Qahtani, M.M.; Abbara, D.; Aldhayyan, N.; Dyab, N.; Afaneh, L.; Islami, M.; et al. Treatment of Multidrug-Resistant Pseudomonas Aeruginosa Bacteremia Using Ceftolozane-Tazobactam-Based or Colistin-Based Antibiotic Regimens: A Multicenter Retrospective Study. J. Infect. Public Health 2022, 15, 1081–1088. [Google Scholar] [CrossRef]
  41. Karruli, A.; Catalini, C.; D’Amore, C.; Foglia, F.; Mari, F.; Harxhi, A.; Galdiero, M.; Durante-Mangoni, E. Evidence-Based Treatment of Pseudomonas Aeruginosa Infections: A Critical Reappraisal. Antibiotics 2023, 12, 399. [Google Scholar] [CrossRef]
  42. Kim, S.E.; Park, S.-H.; Park, H.B.; Park, K.-H.; Kim, S.-H.; Jung, S.-I.; Shin, J.-H.; Jang, H.-C.; Kang, S.J. Nosocomial Pseudomonas Putida Bacteremia: High Rates of Carbapenem Resistance and Mortality. Chonnam Med. J. 2012, 48, 91–95. [Google Scholar] [CrossRef] [PubMed]
  43. Treviño, M.; Moldes, L.; Hernández, M.; Martínez-Lamas, L.; García-Riestra, C.; Regueiro, B.J. Nosocomial Infection by VIM-2 Metallo-Beta-Lactamase-Producing Pseudomonas Putida. J. Med. Microbiol. 2010, 59, 853–855. [Google Scholar] [CrossRef]
  44. Lee, K.; Lim, J.B.; Yum, J.H.; Yong, D.; Chong, Y.; Kim, J.M.; Livermore, D.M. Bla(VIM-2) Cassette-Containing Novel Integrons in Metallo-Beta-Lactamase-Producing Pseudomonas Aeruginosa and Pseudomonas Putida Isolates Disseminated in a Korean Hospital. Antimicrob Agents Chemother 2002, 46, 1053–1058. [Google Scholar] [CrossRef] [PubMed]
  45. Spernovasilis, N.; Kritsotakis, E.I.; Mathioudaki, A.; Vouidaski, A.; Markaki, I.; Psaroudaki, D.; Ioannou, P.; Kofteridis, D.P. Antimicrobial Prescribing before and after the Implementation of a Carbapenem-Focused Antimicrobial Stewardship Program in a Greek Tertiary Hospital during the COVID-19 Pandemic. Antibiotics 2022, 12, 39. [Google Scholar] [CrossRef]
  46. Spernovasilis, N.; Kritsotakis, E.I.; Mathioudaki, A.; Vouidaski, A.; Spanias, C.; Petrodaskalaki, M.; Ioannou, P.; Chamilos, G.; Kofteridis, D.P. A Carbapenem-Focused Antimicrobial Stewardship Programme Implemented during the COVID-19 Pandemic in a Setting of High Endemicity for Multidrug-Resistant Gram-Negative Bacteria. J. Antimicrob. Chemother. 2023, dkad035. [Google Scholar] [CrossRef]
  47. Al-Omari, A.; Al Mutair, A.; Alhumaid, S.; Salih, S.; Alanazi, A.; Albarsan, H.; Abourayan, M.; Al Subaie, M. The Impact of Antimicrobial Stewardship Program Implementation at Four Tertiary Private Hospitals: Results of a Five-Years Pre-Post Analysis. Antimicrob. Resist. Infect. Control. 2020, 9, 95. [Google Scholar] [CrossRef]
  48. Sloot, R.; Nsonwu, O.; Chudasama, D.; Rooney, G.; Pearson, C.; Choi, H.; Mason, E.; Springer, A.; Gerver, S.; Brown, C.; et al. Rising Rates of Hospital-Onset Klebsiella Spp. and Pseudomonas Aeruginosa Bacteraemia in NHS Acute Trusts in England: A Review of National Surveillance Data, August 2020-February 2021. J. Hosp. Infect. 2022, 119, 175–181. [Google Scholar] [CrossRef]
  49. Meschiari, M.; Onorato, L.; Bacca, E.; Orlando, G.; Menozzi, M.; Franceschini, E.; Bedini, A.; Cervo, A.; Santoro, A.; Sarti, M.; et al. Long-Term Impact of the COVID-19 Pandemic on In-Hospital Antibiotic Consumption and Antibiotic Resistance: A Time Series Analysis (2015-2021). Antibiotics 2022, 11, 826. [Google Scholar] [CrossRef]
  50. Amarsy, R.; Trystram, D.; Cambau, E.; Monteil, C.; Fournier, S.; Oliary, J.; Junot, H.; Sabatier, P.; Porcher, R.; Robert, J.; et al. Surging Bloodstream Infections and Antimicrobial Resistance during the First Wave of COVID–19: A Study in a Large Multihospital Institution in the Paris Region. Int. J. Infect. Dis. 2022, 114, 90–96. [Google Scholar] [CrossRef]
  51. Mena Lora, A.J.; Sorondo, C.; Billini, B.; Gonzalez, P.; Bleasdale, S.C. Antimicrobial Resistance in Escherichia Coli and Pseudomonas Aeruginosa before and after the Coronavirus Disease 2019 (COVID-19) Pandemic in the Dominican Republic. Antimicrob Steward. Healthc Epidemiol 2022, 2, e191. [Google Scholar] [CrossRef]
  52. Bongiovanni, M.; Barilaro, G.; Zanini, U.; Giuliani, G. Impact of the COVID-19 Pandemic on Multidrug-Resistant Hospital-Acquired Bacterial Infections. J. Hosp. Infect. 2022, 123, 191–192. [Google Scholar] [CrossRef] [PubMed]
  53. Prowle, J.R.; Echeverri, J.E.; Ligabo, E.V.; Sherry, N.; Taori, G.C.; Crozier, T.M.; Hart, G.K.; Korman, T.M.; Mayall, B.C.; Johnson, P.D.R.; et al. Acquired Bloodstream Infection in the Intensive Care Unit: Incidence and Attributable Mortality. Crit Care 2011, 15, R100. [Google Scholar] [CrossRef] [PubMed]
  54. Ioannou, P.; Karakonstantis, S.; Kofteridis, D.P. Admissions in a Medical Ward and Factors Independently Associated with Mortality. Eur. J. Intern. Med. 2022, 98, 117–118. [Google Scholar] [CrossRef] [PubMed]
  55. Santoro, A.; Franceschini, E.; Meschiari, M.; Menozzi, M.; Zona, S.; Venturelli, C.; Digaetano, M.; Rogati, C.; Guaraldi, G.; Paul, M.; et al. Epidemiology and Risk Factors Associated with Mortality in Consecutive Patients With Bacterial Bloodstream Infection: Impact of MDR and XDR Bacteria. Open Forum Infect. Dis. 2020, 7, ofaa461. [Google Scholar] [CrossRef]
Table
Table 1. Characteristics of patients with Pseudomonas spp. bacteremia in all patients and in regard to mortality at 30-days.
Table 1. Characteristics of patients with Pseudomonas spp. bacteremia in all patients and in regard to mortality at 30-days.
2015–2022 (n = 419)Survived (n = 295)Died (n = 124)p
Age, years, median (IQR)66 (48–76.3)62 (39–75)72 (59–80)<0.0001
Male gender, n (%)262 (62.5)184 (62.4)78 (62.9)1.0000
Site where culture was collected
Medical ward, n (%)142 (33.9)95 (32.2)47 (37.9)0.2610
Surgical ward, n (%)76 (18.1)71 (24.1)5 (4.0)<0.0001
ICU, n (%)201 (48.0)129 (43.7)72 (58.1)0.0076
Hospital-acquired, n (%)329 (78.5)61 (20.7)124 (100)<0.0001
Hospital day when the positive culture was drawn, median (IQR)15 (4–32)14 (3–27)20 (5–43.8)0.0089
Duration of hospital stay, days, median (IQR)36 (19–71)42.5 (20–76.3)30.5 (15.3–51)0.0008
Hospital mortality, n (%)185 (44.2)
30-day mortality, n (%)124 (29.6)
ICU: intensive care unit; IQR: interquartile range.
Table
Table 2. Microbiology of Pseudomonas strains isolated from patients’ blood cultures.
Table 2. Microbiology of Pseudomonas strains isolated from patients’ blood cultures.
Pathogen2015–2022 (%)Pre-COVID-19 (%)Post-COVID-19 (%)p
P. aeruginosa357 (85.2)232 (88.6)125 (79.6)0.0155
P. alcaligenes2 (0.5)0 (0.0)2 (1.3)0.1398
P. fluorescens4 (1.0)2 (0.8)2 (1.3)0.6325
P. luteola1 (0.2)0 (0.0)1 (0.6)0.3747
P. mendocina2 (0.5)1 (0.4)1 (0.6)1.0000
P. oleovorans2 (0.5)0 (0.0)2 (1.3)0.1398
P. oryzihabitans17 (4.1)11 (4.2)6 (3.8)1.0000
P. putida26 (6.2)12 (4.6)14 (8.9)0.0938
P. stutzeri8 (1.9)4 (1.5)4 (2.6)0.4799
All Pseudomonas strains419 (100)262 (62.5)157 (37.5)NA
COVID-19: coronavirus-disease 2019; NA: not applicable.
Table
Table 3. Microbiology of Pseudomonas strains isolated from patients’ blood cultures, and patients’ outcome at 30 days after the occurrence of bacteremia.
Table 3. Microbiology of Pseudomonas strains isolated from patients’ blood cultures, and patients’ outcome at 30 days after the occurrence of bacteremia.
PathogenSurvived (%)Died (%)p
P. aeruginosa243 (82.4)114 (91.9)0.0106
P. alcaligenes2 (0.7)0 (0.0)1.0000
P. fluorescens4 (1.4)0 (0.0)0.3239
P. luteola1 (0.4)0 (0.0)1.0000
P. mendocina1 (0.4)1 (0.8)0.5048
P. oleovorans2 (0.7)0 (0.0)1.0000
P. oryzihabitans13 (4.4)4 (3.2)0.7873
P. putida22 (7.5)4 (3.2)0.1222
P. stutzeri7 (2.4)1 (0.8)0.44456
All Pseudomonas strains243 (70.4)124 (29.6)NA
NA: not applicable.
Table
Table 4. Antimicrobial resistance of Pseudomonas aeruginosa strains isolated from patients’ blood cultures.
Table 4. Antimicrobial resistance of Pseudomonas aeruginosa strains isolated from patients’ blood cultures.
Antibacterial2015–2022 (%)Pre-COVID-19 (%)Post-COVID-19 (%)p
Amikacin61 (17.1)45 (19.4)16 (12.6)0.1081
Aztreonam90 (25.3)62 (26.8)28 (22.1)0.3735
Cefepime78 (21.9)56 (24.1)22(17.3)0.1432
Ceftazidime83 (23.3)55 (23.7)28 (22.1)0.7939
Colistin3 (0.8)3 (1.3)0 (0.0)0.5550
Gentamicin51 (14.3)41 (17.7)10 (7.9)0.0112
Meropenem82 (23.0)57 (24.6)25 (19.7)0.3575
Piperacillin85 (23.8)61 (26.3)24 (18.9)0.1213
Ticarcillin123 (34.5)85 (36.6)38 (29.9)0.2448
Tobramycin69 (19.3)53 (22.8)16 (12.6)0.0244
Ciprofloxacin73 (23.0)58 (25.0)15 (17.1)0.1387
Pefloxacin74 (25.7)64 (27.6)10 (17.5)0.1306
MDR70 (19.6)53 (22.8)17 (13.6)0.0369
XDR44 (12.3)37 (15.9)7 (5.6)0.0040
DTR41 (11.5)36 (15.5)5 (4)0.0008
COVID-19: coronavirus-disease 2019; DTR: difficult-to-treat; MDR: multi-drug-resistant; XDR: extensively-drug-resistant.
Table
Table 5. Antimicrobial resistance of Pseudomonas aeruginosa strains isolated from patients’ blood cultures compared to patients’ outcome at 30 days after the occurrence of bacteremia.
Table 5. Antimicrobial resistance of Pseudomonas aeruginosa strains isolated from patients’ blood cultures compared to patients’ outcome at 30 days after the occurrence of bacteremia.
AntibacterialSurvived (%)Died (%)p
Amikacin27 (11.1)34 (29.8)<0.0001
Aztreonam42 (17.4)48 (42.1)<0.0001
Cefepime34 (14.0)44 (38.6)<0.0001
Ceftazidime37 (15.2)46 (40.4)<0.0001
Colistin1 (0.4)2 (1.8)0.2401
Gentamicin23 (9.5)28 (24.6)0.0003
Meropenem36 (14.8)46 (40.4)<0.0001
Piperacillin39 (16.0)46 (40.4)<0.0001
Ticarcillin64 (26.3)59 (51.8)<0.0001
Tobramycin30 (12.3)39 (34.2)<0.0001
Ciprofloxacin35 (16.2)38 (37.3)<0.0001
Pefloxacin37 (18.6)37 (41.6)<0.0001
MDR33 (13.6)37 (32.5)<0.0001
XDR15 (6.2)29 (25.4)<0.0001
DTR13 (5.3)28 (24.6)<0.0001
DTR: difficult-to-treat; MDR: multi-drug-resistant; XDR: extensively-drug-resistant.
Table
Table 6. Results of the regression analysis regarding patient mortality at 30 days after the occurrence of Pseudomonas spp. bacteremia.
Table 6. Results of the regression analysis regarding patient mortality at 30 days after the occurrence of Pseudomonas spp. bacteremia.
CharacteristicUnivariate Analysis pMultivariate Analysis pOR (95% CI)
Age (per year)<0.0001<0.0011.032 (1.019–1.045)
Acquired in ICU0.00730.012.213 (1.378–3.556)
Hospital day when the positive culture was drawn (per day)0.02310.0051.01 (1.003–1.017)
P. aeruginosa0.01180.0751.985 (0.933–4.224)
MDR<0.00010.6310.79 (0.302–2.065)
XDR<0.00010.1863.019 (0.587–15.527)
DTR<0.00010.2782.415 (0.491–11.865)
CI: confidence intervals; DTR: difficult-to-treat; ICU: intensive care unit; MDR: multi-drug-resistant; OR: odds ratio; XDR: extensively-drug-resistant.
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Ioannou, P.; Alexakis, K.; Maraki, S.; Kofteridis, D.P. Pseudomonas Bacteremia in a Tertiary Hospital and Factors Associated with Mortality. Antibiotics 2023, 12, 670. https://doi.org/10.3390/antibiotics12040670

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Ioannou P, Alexakis K, Maraki S, Kofteridis DP. Pseudomonas Bacteremia in a Tertiary Hospital and Factors Associated with Mortality. Antibiotics. 2023; 12(4):670. https://doi.org/10.3390/antibiotics12040670

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Ioannou, Petros, Konstantinos Alexakis, Sofia Maraki, and Diamantis P. Kofteridis. 2023. "Pseudomonas Bacteremia in a Tertiary Hospital and Factors Associated with Mortality" Antibiotics 12, no. 4: 670. https://doi.org/10.3390/antibiotics12040670

APA Style

Ioannou, P., Alexakis, K., Maraki, S., & Kofteridis, D. P. (2023). Pseudomonas Bacteremia in a Tertiary Hospital and Factors Associated with Mortality. Antibiotics, 12(4), 670. https://doi.org/10.3390/antibiotics12040670

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