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Open AccessArticle

Implementation of Antibiotic Stewardship in a University Hospital Setting

1
Department of Microbiology, University Hospital Olomouc, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic
2
Department of Pharmacology, University Hospital Olomouc, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic
3
Department of Medical Biophysics, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic
4
Department of Foreign Languages, Faculty of Medicine and Dentistry, Palacký University Olomouc, 779 00 Olomouc, Czech Republic
*
Author to whom correspondence should be addressed.
Received: 30 December 2020 / Revised: 13 January 2021 / Accepted: 14 January 2021 / Published: 19 January 2021

Abstract

The article describes activities of an antibiotic center at a university hospital in the Czech Republic and presents the results of antibiotic stewardship program implementation over a period of 10 years. It provides data on the development of resistance of Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus to selected antibiotic agents as well as consumption data for various antibiotic classes. The genetic basis of resistance to beta-lactam antibiotics and its clonal spread were also assessed. The study showed significant correlations between aminoglycoside consumption and resistance of Escherichia coli and Klebsiella pneumoniae to gentamicin (r = 0.712, r = 0.869), fluoroquinolone consumption and resistance of Klebsiella pneumoniae to ciprofloxacin (r = 0.896), aminoglycoside consumption and resistance of Pseudomonas aeruginosa to amikacin (r = 0.716), as well as carbapenem consumption and resistance of Pseudomonas aeruginosa to meropenem (r = 0.855). Genotyping of ESBL- positive isolates of Klebsiella pneumoniae and Escherichia coli showed a predominance of CTX-M-type; in AmpC-positive strains, DHA, EBC and CIT enzymes prevailed. Of 19 meropenem-resistant strains of Klebsiella pneumoniae, two were identified as NDM-positive. Clonal spread of these strains was not detected. The results suggest that comprehensive antibiotic stewardship implementation in a healthcare facility may help to maintain the effectiveness of antibiotics against bacterial pathogens. Particularly beneficial is the work of clinical microbiologists who, among other things, approve administration of antibiotics to patients with bacterial infections and directly participate in their antibiotic therapy.
Keywords: antibiotic stewardship; resistance; consumption of antibiotics; clonal spread antibiotic stewardship; resistance; consumption of antibiotics; clonal spread

1. Introduction

Antibiotic stewardship may be defined as a set of measures leading to rational antibiotic therapy based on the adequate selection of antibacterial agents, appropriate duration of their administration and a suitable route of administration [1,2,3,4]. The need for antibiotic stewardship implementation stems from the likely prospect of antibiotics losing their effectiveness and thus their ability to treat bacterial infections [5,6,7]. The increasing prevalence of bacteria resistant to antibacterial drugs, mainly those producing extended-spectrum beta-lactamases including metallo-beta-lactamases and carbapenemases opens the possibility of a new non-antibiotic era in which adequate antibiotics will be unavailable to treat infections caused by multidrug-resistant bacteria [8,9]. To prevent this, antibiotic stewardship programs have been developed as comprehensive systems comprising a range of activities that may be briefly characterized as follows:
  • early and adequate microbiological diagnosis including the correct interpretation of microbiological results,
  • early and reliable detection of the susceptibility/resistance of bacterial pathogens to antibiotics consistent with the European guidelines, namely those by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) [10],
  • immediate reporting of critical results (e.g., information on positive blood cultures),
  • regular assessment of the prevalence of pathogenic bacteria and their antibiotic resistance and development of local guidelines for initial antibiotic therapy based on these data,
  • adequate antibiotic prophylaxis.
It must be stressed, however, that the scope of antibiotic stewardship is much broader, involving numerous other activities that are also very important for adequate antibiotic therapy and preventing the spread of multidrug-resistant bacteria. These activities may be described as follows:
  • analyzing the routes of spread of multidrug-resistant bacteria using modern molecular methods,
  • providing antibiotic consultant service for clinical physicians and deciding on antibiotic administration based on microbiological results and the knowledge of primary resistance of bacterial pathogens in patients with bacterial infections,
  • assessing the consumption of antibiotics in the relevant epidemiological units and, if needed, introducing necessary regulatory measures,
  • close cooperation with hospital hygiene officers, epidemiologists and clinical pharmacologists.
At the University Hospital Olomouc, Czech Republic, antibiotic stewardship is coordinated by the Antibiotic Center, a section of the Department of Microbiology. Based on analyses of the development of bacterial resistance and antibiotic consumption, including the overall costs of this group of drugs, recommendations for initial antibiotic therapy and prophylaxis are formulated and quarterly presented to the hospital management who subsequently approve these recommendations and make them valid.
The article describes efforts of the Antibiotic Center and presents outcomes of its activity over a period of 10 years (2010–2019).

2. Materials and Methods

2.1. Characteristics of the Healthcare Facility

The University Hospital Olomouc is one of the largest inpatient healthcare facilities in the Czech Republic, dating back to 1896. It is part of a network of nine teaching hospitals directly controlled by the Ministry of Health of the Czech Republic. Basic data on the facility are shown in Table 1.

2.2. Process of Approving Antibiotic Administration

To better understand the study, it is reasonable to define the process of approving antibiotic administration at the University Hospital Olomouc. For a particular patient with a bacterial infection, the attending physician selects an antibiotic based on their own clinical reasoning and microbiological results (if available), while observing the hospital’s guidelines for initial antibiotic therapy. Alternatively, an adequate antibiotic is recommended by a clinical microbiologist based on a consultation with the attending physician. If an antibiotic is selected to treat a particular bacterial infection, its administration must be approved by an Antibiotic Center member. The approval is granted electronically using the hospital information system. The clinical microbiologist (always holding a specialist qualification in medical microbiology) verifies the selection of the antibiotic focusing on all microbiological test results and, if adequate, approves its administration. The Antibiotic Center member has the right to disapprove administration of an antibiotic in case:
  • some required data are missing (e.g., diagnosis of infection or antibiotic dosage),
  • they reasonably doubt that the antibiotic has been adequately selected,
  • ongoing microbiological tests have identified bacteria whose definitive susceptibility is yet to be determined but due to their primary resistance to the selected antibiotic, this cannot be approved.
In case of disapproval, the reason and a more adequate antibiotic or recommendations from a consultation with the Antibiotic Center clinical microbiologist are entered into the hospital information system. This takes place daily between 7 a.m. and 4 p.m. Outside these hours, antibiotic therapy is selected in line with the hospital’s guidelines and the antibiotic therapy is scrutinized on the following day.

2.3. Assessing Antibiotic Consumption

A computerized database of the hospital’s Department of Pharmacology was used to obtain data on antibiotic consumption during the study period. The data were processed according to the 2020 ATC/DDD system and expressed as numbers of defined daily doses for various antibiotic classes [11]. Antibiotic consumption was analyzed for both the entire hospital and its Department of Anesthesiology and Intensive Care Medicine with 25 intensive care beds.

2.4. Identification of Bacteria and Determination of Their Susceptibility/Resistance to Antibacterial Agents

Bacterial pathogens (Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Staphylococcus aureus) were isolated from clinical samples (tracheal secretion, bronchoalveolar lavage fluid, sputum, blood, urine, pus, puncture samples, wound secretion, bile, cerebrospinal fluid) obtained from hospitalized patients with a suspected bacterial infection. For each patient, only the first isolate from particular clinical samples was included.
The identification of bacteria was performed by MALDI-TOF MS (Biotyper Microflex, Bruker Daltonics, Bremen, Germany) [12].
The susceptibility/resistance to antibiotics was tested using a broth microdilution method according to the EUCAST [10]. The following reference strains were used as quality control organisms: Escherichia coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853 and Staphylococcus aureus ATCC 29213. All strains of Staphylococcus aureus were also tested for the resistance to methicillin using selective diagnostic chromogenic media (Colorex/TM/MRSA, TRIOS, Prague, Czech Republic) and an immunochromatographic assay for the detection of PBP2a (PBP2a SA Culture Colony Test, AlereTM, Abbott, Prague, Czech Republic). The production of beta-lactamases, such as ESBL and AmpC, was detected by phenotypic tests [13]. The production of carbapenemases was detected by the Carba NP test [14].
Additionally, methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from the Department of Anesthesiology and Intensive Care Medicine patients were confirmed by the mecA gene detection [15]. The production of ESBL and AmpC beta-lactamases in Escherichia coli and Klebsiella pneumoniae was confirmed by PCR detection of the bla genes only in pre-defined groups of strains/patients from above mentioned department (from tracheal aspirates in patients with hospital-acquired pneumonia, from stool in hospitalized patients etc.) [13]. The search for potential production of carbapenemases in the meropenem-resistant Klebsiella pneumoniae strains at this department was carried out by simplex PCR with primers targeting blaFRI, blaGES, blaGIM, blaIMI, blaIMP, blaKPC, blaNDM, blaVIM, blaOXA-23 and blaOXA-48. Detailed information on the primers is listed in Table 2. PCR assays were performed on Rotor-Gene TM 6000 (Corbett Research, Mortlake, Australia). PCR was run in a final volume of 25 µL using 100 ng of DNA template, 0.5 μM of forward and reverse primers, 200 μM of each dNTP, 2.5 mM of MgCl2 and 1.25 U Combi Taq Polymerase (Top-Bio, Vestec, Czech Republic) in 1× Buffer (Top-Bio, Vestec, Czech Republic). The PCR conditions were as follows: initial denaturation at 94 °C for 3 min, followed by 30 cycles at 94 °C for 30 s, 72 °C for different times (45 s to 60 s) with a final extension at 72 °C for 10 min. PCR products were then separated on a 1% agarose gel containing SYBR Safe (Invitrogen) and visualized on a UV transilluminator. Bacterial isolates for genetic analysis were stored in cryotubes at −80 °C (Cryobank B, ITEST, Hradec Králové, Czech Republic).

2.5. Clonality

The clonality of MRSA and meropenem-resistant isolates of Klebsiella pneumoniae detected at the Department of Anesthesiology and Intensive Care Medicine was assessed with pulsed-field gel electrophoresis (PFGE). Bacterial DNA extracted with a technique described by Husičková et al. [19] was digested by the XbaI restriction endonuclease (New England Biolabs, Ipswitch, MA, USA) for 24 h at 37 °C in Klebsiella pneumoniae isolates and by the SmaI restriction endonuclease (New England Biolabs, Ipswitch, MA, USA) for 24 h at 25 °C in Staphylococcus aureus strains. The obtained DNA fragments were separated by PFGE on 1.2% agarose gel for 24 h at 6 V/cm and pulse times of 2–35 s for both Klebsiella pneumoniae and Staphylococcus aureus strains. Subsequently, the gel was stained with ethidium bromide. The resulting restriction profiles were analyzed with the GelCompar II software (Applied Maths, Kortrijk, Belgium) using the Dice coefficient (1.2%) for comparing similarity and unweighted pair group method with arithmetic means for cluster analysis. The results were interpreted according to criteria described by Tenover et al. [20].

2.6. Statistical Analysis

Trends in the consumption of antibacterial agents, or antibiotic classes, bacterial resistance and their relationships were analyzed with Spearman’s correlation. The data were processed with IBM SPSS Statistics 22 (Armonk, NY, USA).

3. Results

Table 3, Table 4, Table 5 and Table 6 show the prevalence of Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus strains resistant to selected antibiotics over the 10-year period for the entire hospital. The results indicate an increase in resistance of Escherichia coli to piperacillin/tazobactam (r = 0.939), gentamicin (r = 0.826), ciprofloxacin (r = 0.816) and cefotaxime (r = 0.734). In Klebsiella pneumoniae, resistance to ciprofloxacin (r = 0.665) and cefotaxime increased (r = 0.644). Pseudomonas aeruginosa was shown to increase its resistance to colistin (r = 0.722) and amikacin (r = 0.691).
Consumption of antibiotics or antibiotic classes at the University Hospital Olomouc is shown in Table 7. The data indicate increasing consumption of carbapenems (r = 0.964), tigecycline (r = 0.879), third- and fourth-generation cephalosporins (r = 0.867) and fluoroquinolones (r = 0.733). Conversely, consumption of penicillins combined with beta-lactamase inhibitors decreased (r = −0.745). Analysis of the relationship between antibiotic consumption and resistance in the entire hospital showed significant correlations between aminoglycoside consumption and resistance of Escherichia coli to gentamicin (r = 0.712), fluoroquinolone consumption and resistance of Klebsiella pneumoniae to ciprofloxacin (r = 0.896) and aminoglycoside consumption and resistance of Pseudomonas aeruginosa to amikacin (r = 0.716) (Figure 1, Figure 2 and Figure 3).
Table 8, Table 9, Table 10 and Table 11 document resistance of particular bacterial species at the Department of Anesthesiology and Intensive Care Medicine over the study period. The results show increasing resistance of Escherichia coli to piperacillin/tazobactam (r = 0.845) and cefotaxime (r = 0.729), resistance of Klebsiella pneumoniae to cefotaxime (r = 0.778) and resistance of Pseudomonas aeruginosa to meropenem (r = 0.988).
At the Department of Anesthesiology and Intensive Care Medicine, consumption of tigecycline (r = 0.939), carbapenems (r = 0.879), third- and fourth-generation cephalosporins (r = 0.867) and glycopeptides (r = 0.636) increased (Table 12). There were significant correlations between carbapenem consumption and resistance of Pseudomonas aeruginosa to meropenem (r = 0.855) as well as between aminoglycoside consumption and resistance of Klebsiella pneumoniae to gentamicin (r = 0.869) (Figure 4 and Figure 5).
Genotyping of ESBL- positive isolates of Klebsiella pneumoniae and Escherichia coli in particular patient groups (from tracheal aspirates in patients with hospital-acquired pneumonia, from stool in hospitalized patients etc.) at the Department of Anesthesiology and Intensive Care Medicine showed a predominance of CTX-M-type, namely of the CTX-M-15 and CTX-M-9 types (data not shown). In AmpC-positive strains, EBC and CIT enzymes prevailed in Escherichia coli and the DHA type in Klebsiella pneumoniae (data not shown).
Between 2010 and 2019, a total of 19 meropenem-resistant strains of Klebsiella pneumoniae were detected in patients staying at the Department of Anesthesiology and Intensive Care Medicine. Only 2 strains were NDM-positive (data not shown). However, no other carbapenemase genes were detected. The total number of isolated MRSA at the Department of Anesthesiology and Intensive Care Medicine was 45 strains. In case of meropenem-resistant Klebsiella pneumoniae strains and MRSA, no significant clonal spread was noted. No identical clone was detected in meropenem-resistant Klebsiella pneumoniae isolates and only two pairs of identical MRSA strains were identified.

4. Discussion

Today’s medicine is characterized by exponentially expanding knowledge in all specialties, resulting in considerable improvements of both diagnostic and therapeutic activities. Despite past achievements, however, there is one issue posing a serious therapeutic challenge. It is the role of bacterial infections that have continued to increase in recent years. One reason is rising resistance of bacteria to the effects of antibacterial drugs and the associated risk of treatment failure. Numerous studies have been published documenting higher mortality and shorter survival of patients with infections caused by multidrug-resistant bacteria compared to those due to susceptible strains of the same species [21,22,23,24,25]. The present study yielded interesting results when compared with the national and European resistance rates as reported by the European Antimicrobial Resistance Surveillance Network (EARS-Net). In 2019, the mean prevalence of MRSA in the Czech Republic and Europe was 13% and 15%, respectively; the University Hospital Olomouc rates ranged from 3% to 6% [26,27]. Similarly, very low prevalence was also noted for meropenem-resistant strains of Klebsiella pneumoniae. According to the ECDC’s Annual Epidemiological Report for 2019, the mean prevalence of carbapenem-resistant strains of Klebsiella pneumoniae in Europe was 8%, with some European countries even reporting rates higher than 10% [26]. At the University Hospital Olomouc, however, the resistance of this species to meropenem did not exceed 1% or, in case of the Department of Anesthesiology and Intensive Care Medicine, 3%. Only two strains were found to produce NDM- carbapenemases. For meropenem-resistant isolates without the carbapenemase gene, we assume that the resistance is due to mechanisms such as loss or mutation of porins with AmpC beta-lactamase or ESBL hyperproduction or overexpression of the efflux pumps.
There were considerable differences in resistance of Klebsiella pneumoniae to third-generation cephalosporins in Europe (31%) and in the Czech Republic (50%) in 2019 [26,27]. The University Hospital Olomouc rate (43%) was below the mean rate for the entire country.
Resistance of Escherichia coli to cefotaxime and resistance of Pseudomonas aeruginosa to ceftazidime, aminoglycosides and fluoroquinolones at the University Hospital Olomouc do not greatly differ from the mean rates in Europe.
Of concern is the prevalence of Pseudomonas aeruginosa strains resistant to meropenem (34%), exceeding both the Czech (15%) and European (17%) mean rates [26,27]. However, carbapenems are mainly needed to treat infections caused by members of Enterobacterales producing ESBL and AmpC beta-lactamases; the resistance of these bacterial species to meropenem does not increase. Despite that, there will be efforts to reduce carbapenem consumption in the following years. It should be stated that carbapenems account for 6% of the overall antibiotic consumption at the University Hospital Olomouc (unpublished data).
With the exception of a higher prevalence of meropenem-resistant Pseudomonas aeruginosa, prevalence rates of other studied phenotypes are below the rates reported by the EUCAST [26,27]. The main causes of the development and spread of bacterial resistance are the administration of antibiotics and their selection pressure [28,29,30,31,32,33,34]. Therefore, the restriction of certain antibacterial agents and relevant antibiotic classes aimed to limit their selection pressure is a possible solution to the problem [35]. However, selection pressure is a more complex issue. Apparently, consumption of certain antibiotics may only be reduced if the consumption of others increases. Moreover, antibiotic resistance is often multiple, meaning that selection pressure of a particular antibiotic agent results in increased resistance to other antibiotics, for example, resistance of ESBL-positive enterobacteria to cephalosporins and fluoroquinolones or resistance of MRSA to clindamycin [36,37]. Another important aspect influencing the selective pressure is antibiotic concentration, that is the correct dosage of antibiotics and their distribution in the body. Clinical microbiologists and physicians care about the accurate dosage in terms of pharmacodynamic/pharmacokinetic parameters to achieve satisfactory outcomes in patients. However, the question is how the selected dosage and the final concentration of an antibiotic promotes the genesis of resistant mutants. The phenomenon of bacterial resistance represents a complex problem and the emergence of antibiotic-resistant mutants depends on different aspects such physiology, genetics, historical behavior of bacterial populations, antibiotic-bacterium dynamics and others [38,39].
Studies have shown that there may not be a direct relationship between the administration of selected antibiotics and bacterial resistance. Several studies failed to confirm correlations between bacterial resistance to particular antibiotic classes and their consumption [40,41,42]. Similarly, Htoutou Sedláková et al. reported decreasing consumption of third-generation cephalosporins and fluoroquinolones but increasing resistance of Enterobacteriaceae to these drugs [43]. This may be due to multiple mechanisms. Some authors claim that the relationship between antibiotic consumption and resistance disappears after a certain resistance threshold is exceeded, since mobile genetic elements (in particular plasmids and transposons) circulate in bacterial populations and a decrease in antibiotic selection pressure does not influence this phenomenon any more [44]. It is documented that transfer rates of ESBL-plasmids are highest in the absence of the antibiotic [45]. Another explanation could be the collateral effect of antibiotics, which means that not only subinhibitory concentrations of an antibiotic could stimulate the emergence and the dissemination of its corresponding resistant gene, but that collateral stimulation by other antibiotics is also possible. For example, the mobile genetic element carrying the gene for tetracycline resistance is able to exhibit a 1000-fold increase of its transfer frequency when exposed to subinhibitory concentrations of tetracyclines, but also macrolides, lincosamides and streptogramins [46].
Our findings suggest that the increasing bacterial resistance is mainly determined by the selection pressure of antibiotics. Neither significant horizontal clonal spread of multidrug-resistant bacteria nor increasing bacterial resistance to a particular antibiotic whose consumption decreases have been observed.
As part of antibiotic resistance surveillance, the Antibiotic Center not only controls the appropriate administration of antibiotics, that is the adequate indication and dosage in a particular patient, but also regularly monitors important bacterial resistance phenotypes and genotypes, in particular MRSA, vancomycin-resistant enterococci, ESBL- and AmpC-positive Enterobacterales, Gram-negative bacteria resistant to carbapenems, fluoroquinolones and others, as well as their clonal spread. For technical reasons, such surveillance is not performed in the entire hospital, but is mostly limited to selected departments and pre-defined patient groups and time periods. This approach to antibiotic stewardship has been reflected in numerous studies carried out at our department [47,48,49,50]. Based on their outcomes, certain conclusions have been drawn and relevant measures have been implemented such as evidence-based recommendations for consultant microbiologists and attending physicians concerning an adequate selection of antibiotic agents, guidelines for initial antibiotic therapy including antibiotic prophylaxis, restriction of certain antibiotic classes or improvement of hygiene and epidemiological measures.
The present study showed a significant relationship between aminoglycoside consumption and resistance of Escherichia coli and Klebsiella pneumoniae to gentamicin, results consistent with those in our 2014 study [43]. Moreover, there were correlations between fluoroquinolone consumption and resistance of Klebsiella pneumoniae to ciprofloxacin and between aminoglycoside consumption and resistance of Pseudomonas aeruginosa to amikacin, consistent with findings published by other authors [34,51]. Another reason for increasing bacterial resistance may be the horizontal or clonal spread of genetically identical strains of particular species among patients. In this case, the selection pressure of antibiotics may be of less importance and external environmental factors may play a role, for example, those related to healthcare staff. Examples include a study by Hricová et al. on vancomycin-resistant enterococci in patients with hematological malignancies at the University Hospital Olomouc reporting 67% clonality of isolated strains or outbreaks of epidemic MRSA clones in various parts of the world [48,52,53,54]. The present study, however, did not show a significant clonal spread of MRSA and meropenem-resistant strains of Klebsiella pneumoniae isolated from Department of Anesthesiology and Intensive Care Medicine patients, highlighting the role of horizontal resistance gene transfer in the spread of antibiotic resistance. Further, there is no doubt that the use of antibiotics contributes to the development of resistance by acquiring resistance genes and maintenance of chromosomal resistance-associated mutations [38]. However, determining the exact effect of antibiotic use on the development of resistance is problematic. Moreover, it is increasingly claimed that the emergence, maintenance and spread of resistance traits are also influenced by social, economic and genetic factors.

5. Conclusions

The presented data suggest low rates of bacterial resistance at the University Hospital Olomouc, with the only exception being an increased prevalence of meropenem-resistant strains of Pseudomonas aeruginosa. This confirms the importance of antibiotic stewardship and surveillance of antimicrobial resistance, including the use of molecular biology methods, for maintaining the effectiveness of antibiotics and limiting the spread of multidrug-resistant bacterial pathogens. Data on the prevalence of bacterial resistance and the results of molecular genetic analysis of multidrug-resistant strains must form the basis for practical antibiotic stewardship. These should include a definition of optimal regimens for initial antibiotic therapy and assessment of the sources and routes of spread of multidrug-resistant bacteria so that adequate hygiene and epidemiological measures may be introduced. It is apparent that besides obtaining data for the entire hospital, hospital departments need to be individually assessed and adequate antibiotic stewardship measures must be implemented based on the results.

Author Contributions

Conceptualization, M.K.; Data curation, M.H.S.; Formal analysis, J.Z.; Funding acquisition, M.K.; Investigation, M.H.S., K.U., P.M., M.R., K.H., K.M., P.K. (Pavla Kucova) and K.F.; Methodology, P.M.; Project administration, M.K.; Resources, M.H.S., K.U., P.K. (Pavla Kucova) and K.F.; Supervision, M.K.; Validation, M.R.; Visualization, M.K., M.H.S., K.U., P.M., M.R., K.H., K.M., P.K. (Pavla Kucova), K.F. and P.K. (Pavel Kurfurst); Writing—original draft, M.K., M.H.S., P.M., M.R., J.Z., and P.K. (Pavel Kurfurst); Writing—review & editing, M.K., M.H.S., K.U., P.M., M.R., K.H., K.M., P.K. (Pavla Kucova), J.Z., K.F. and P.K. (Pavel Kurfurst) All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Czech Health Research Council (project no. NV18-05-00340), project IGA_LF_2020_021, Junior Grant of UP in Olomouc JG_2019_005 and by MH CZ—DRO (FNOL, 00098892).

Data Availability Statement

Data sharing not applicable.

Acknowledgments

The authors thank med. Arne C. Rodloff (Facharzt für Mikrobiologie, Virologie und Infektionsepidemiologie, Krankenhaushygieniker, Germany) and Pavel Boštík (Faculty of Medicine, Charles University and University Hospital in Hradec Kralové) for critically reviewing the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Dyar, O.J.; Huttner, B.; Schouten, J.; Pulcini, C. ESGAP (ESCMID Study Group for Antimicrobial stewardshiP). What is antimicrobial stewardship? Clin. Microbiol. Infect. 2017, 23, 793–798. [Google Scholar] [CrossRef] [PubMed]
  2. Srinivasan, A. Antibiotic stewardship: Why we must, how we can. Clevel. Clin. J. Med. 2017, 84, 673–679. [Google Scholar] [CrossRef] [PubMed]
  3. Luyt, C.E.; Bréchot, N.; Trouillet, J.L.; Chastre, J. Antibiotic stewardship in the intensive care unit. Crit. Care 2014, 18, 480. [Google Scholar] [CrossRef] [PubMed]
  4. Barlam, T.F.; Cosgrove, S.E.; Abbo, L.M.; MacDougall, C.; Schuetz, A.N.; Septimus, E.J.; Srinivasan, A.; Dellit, T.H.; Falck-Ytter, Y.T.; Fishman, N.O.; et al. Implementing an Antibiotic Stewardship Program: Guidelines by the Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America. Clin. Infect. Dis. 2016, 62, 51–77. [Google Scholar] [CrossRef] [PubMed]
  5. Goff, D.A. Antibiotic Stewardship: The Health of the World Depends on It. Hosp. Pharm. 2018, 53, 214–216. [Google Scholar] [CrossRef]
  6. Karam, G.; Chastre, J.; Wilcox, M.H.; Vincent, J.L. Antibiotic strategies in the era of multidrug resistance. Crit. Care 2016, 20, 136. [Google Scholar] [CrossRef]
  7. Baur, D.; Gladstone, B.P.; Burkert, F.; Carrara, E.; Foschi, F.; Döbele, S.; Tacconelli, E. Effect of antibiotic stewardship on the incidence of infection and colonisation with antibiotic-resistant bacteria and Clostridium difficile infection: A systematic review and meta-analysis. Lancet Infect. Dis. 2017, 17, 990–1001. [Google Scholar] [CrossRef]
  8. Kollef, M.H.; Bassetti, M.; Francois, B.; Burnham, J.; Dimopoulos, G.; Garnacho-Montero, J.; Lipman, J.; Luyt, C.E.; Nicolau, D.P.; Postma, M.J.; et al. The intensive care medicine research agenda on multidrug-resistant bacteria, antibiotics, and stewardship. Intensive Care Med. 2017, 43, 1187–1197. [Google Scholar] [CrossRef]
  9. Laxminarayan, R.; Duse, A.; Wattal, C.; Zaidi, A.K.; Wertheim, H.F.; Sumpradit, N.; Vlieghe, E.; Hara, G.L.; Gould, I.M.; Goossens, H.; et al. Antibiotic resistance—the need for global solutions. Lancet Infect. Dis. 2013, 13, 1057–1098. [Google Scholar] [CrossRef]
  10. The European Committee on Antimicrobial Susceptibility Testing. Breakpoint Tables for Interpretation of MICs and Zone Diameters, Version 1.0 December 2009–Version 10.0 January 2020. Available online: https://www.eucast.org/ (accessed on 16 December 2020).
  11. WHO Collaborating Centre for Drug Statistics Methodology. ATC/DDD Index 2020. Available online: https://www.whocc.no/atc_ddd_index/ (accessed on 16 December 2020).
  12. Croxatto, A.; Prod’hom, G.; Greub, G. Applications of MALDI-TOF mass spectrometry in clinical diagnostic microbiology. FEMS Microbiol. Rev. 2012, 36, 380–407. [Google Scholar] [CrossRef]
  13. Htoutou Sedlakova, M.; Hanulik, V.; Chroma, M.; Hricova, K.; Kolar, M.; Latal, T.; Schaumann, R.; Rodloff, A.C. Phenotypic detection of broad-spectrum beta-lactamases in microbiological practice. Med. Sci. Monit. 2011, 17, BR147–BR152. [Google Scholar] [CrossRef] [PubMed]
  14. Nordmann, P.; Poirel, L.; Dortet, L. Rapid detection of carbapenemase-producing Enterobacteriaceae. Emerg. Infect. Dis. 2012, 18, 1503–1507. [Google Scholar] [CrossRef] [PubMed]
  15. Sila, J.; Sauer, P.; Kolar, M. Comparison of the prevalence of genes coding for enterotoxins, exfoliatins, Panton-Valentine leukocidin and TSST-1 between methicillin-resistant and methicillin-susceptible isolates of Staphylococcus aureus at the University Hospital in Olomouc. Biomed. Pap. Med. Fac. Univ. Palacky Olomouc Czechoslov. Repub. 2009, 153, 215–218. [Google Scholar] [CrossRef] [PubMed]
  16. Ellington, M.J.; Kistler, J.; Livermore, D.M.; Woodford, N. Multiplex PCR for rapid detection of genes encoding acquired metallo-beta-lactamases. J. Antimicrob. Chemother. 2007, 59, 321–322. [Google Scholar] [CrossRef] [PubMed]
  17. Mlynarcik, P.; Roderova, M.; Kolar, M. Primer evaluation for PCR and its application for detection of carbapenemases in Enterobacteriaceae. Jundishapur J. Microb. 2016, 9, e29314. [Google Scholar] [CrossRef] [PubMed]
  18. Mlynarcik, P.; Bardon, J.; Htoutou Sedlakova, M.; Prochazkova, P.; Kolar, M. Identification of novel OXA-134-like beta-lactamases in Acinetobacter lwoffii and Acinetobacter schindleri isolated from chicken litter. Biomed. Pap. Med. Fac. Univ. Palacky Olomouc Czech. Repub. 2019, 163, 141–146. [Google Scholar] [CrossRef]
  19. Husickova, V.; Cekanova, L.; Chroma, M.; Htoutou Sedlakova, M.; Hricova, K.; Kolar, M. Carriage of ESBL- and AmpC-positive Enterobacteriaceae in the gastrointestinal tract of community subjects and hospitalized patients in the Czech Republic. Biomed. Pap. Med. Fac. Univ Palacky Olomouc Czechoslov. Repub. 2012, 156, 348–353. [Google Scholar] [CrossRef]
  20. Tenover, F.C.; Arbeit, R.D.; Goering, R.V.; Mickelsen, P.A.; Murray, B.E.; Persing, D.H.; Swaminathan, B. Interpreting chromosomal DNA restriction patterns produced by pulsed-field gel electrophoresis: Criteria for bacterial strain typing. J. Clin. Microbiol. 1995, 33, 2233–2239. [Google Scholar] [CrossRef]
  21. Luna, C.M.; Vujacich, P.; Niederman, M.S.; Vay, C.; Gherardi, C.; Matera, J.; Jolly, E.C. Impact of BAL data on the therapy and outcome of ventilator-associated pneumonia. Chest 1997, 111, 676–685. [Google Scholar] [CrossRef]
  22. Tumbarello, M.; Sanguinetti, M.; Montuori, E.; Trecarichi, E.M.; Posteraro, B.; Fiori, B.; Citton, R.; D’Inzeo, T.; Fadda, G.; Cauda, R.; et al. Predictors of mortality in patients with bloodstream infections caused by extended-spectrum-ß-lactamase-producing Enterobacteriaceae: Importance of inadequate initial antimicrobial treatment. Antimicrob. Agents Chemother. 2007, 51, 1987–1994. [Google Scholar] [CrossRef]
  23. Kang, C.I.; Chung, D.R.; Ko, K.S.; Peck, K.R.; Song, J.H. Korean Network for Study of Infectious Diseases. Risk factors for infection and treatment outcome of extended-spectrum β-lactamase-producing Escherichia coli and Klebsiella pneumoniae bacteremia in patients with hematologic malignancy. Ann. Hematol. 2012, 91, 115–121. [Google Scholar] [CrossRef] [PubMed]
  24. Herkel, T.; Uvizl, R.; Doubravska, L.; Adamus, M.; Gabrhelik, T.; Htoutou Sedlakova, M.; Kolar, M.; Hanulik, V.; Pudova, V.; Langova, K.; et al. Epidemiology of hospital-acquired pneumonia: Results of a Central European multicenter, prospective, observational study compared with data from the European region. Biomed. Pap. Med. Fac. Univ. Palacky Olomouc Czechoslov. Repub. 2016, 160, 448–455. [Google Scholar] [CrossRef] [PubMed]
  25. De Kraker, M.E.; Wolkewitz, M.; Davey, P.G.; Koller, W.; Berger, J.; Nagler, J.; Icket, C.; Kalenic, S.; Horvatic, J.; Seifert, H.; et al. Clinical impact of antimicrobial resistance in European hospitals: Excess mortality and length of hospital stay related to methicillin-resistant Staphylococcus aureus bloodstream infections. Antimicrob. Agents Chemother. 2011, 55, 1598–1605. [Google Scholar] [CrossRef] [PubMed]
  26. European Centre for Disease Prevention and Control. Antimicrobial Resistance in the EU/EEA (EARS-Net)—Annual Epidemiological Report 2019; ECDC: Stockholm, Sweden, 2020.
  27. European Antimicrobial Resistance Surveillance Network (EARS-Net). Available online: https://www.ecdc.europa.eu/en/antimicrobial-resistance/surveillance-and-disease-data/data-ecdc (accessed on 16 December 2020).
  28. Urbanek, K.; Kolar, M.; Strojil, J.; Koukalová, D.; Čekanová, L.; Hejnar, P. Utilization of fluoroquinolones and Escherichia coli resistance in urinary tract infection: Inpatients and outpatients. Pharmacoepidemiol. Drug Saf. 2005, 14, 741–745. [Google Scholar] [CrossRef]
  29. Urbanek, K.; Kolar, M.; Loveckova, Y.; Strojil, J.; Santava, L. Influence of 3rd generation cephalosporin utilization on the occurrence of ESBL-positive Klebsiella pneumoniae strains. J. Clin. Pharm. Ther. 2007, 32, 403–408. [Google Scholar] [CrossRef]
  30. Kolar, M.; Urbanek, K.; Latal, T. Antibiotic selective pressure and development of bacterial resistance. Int. J. Antimicrob. Agents 2001, 17, 357–363. [Google Scholar] [CrossRef]
  31. Urbanek, K.; Kolar, M.; Cekanova, L. Utilisation of macrolides and the development of Streptococcus pyogenes resistance to erythromycin. Pharm. World Sci. 2005, 27, 104–107. [Google Scholar] [CrossRef]
  32. Bell, B.G.; Schellevis, F.; Stobberingh, E.; Goossens, H.; Pringle, M. A systematic review and meta-analysis of the effects of antibiotic consumption on antibiotic resistance. BMC Infectious Dis. 2014, 14, 13. [Google Scholar] [CrossRef] [PubMed]
  33. Kim, B.; Kim, Y.; Hwang, H.; Kim, J.; Kim, S.W.; Bae, I.G.; Choi, W.S.; Jung, S.I.; Jeong, H.W.; Pai, H. Trends and correlation between antibiotic usage and resistance pattern among hospitalized patients at university hospitals in Korea, 2004 to 2012: A nationwide multicenter study. Medicine 2018, 97, e13719. [Google Scholar] [CrossRef]
  34. Mladenovic-Antic, S.; Kocic, B.; Velickovic-Radovanovic, R.; Dinic, M.; Petrovic, J.; Randjelovic, G.; Mitic, R. Correlation between antimicrobial consumption and antimicrobial resistance of Pseudomonas aeruginosa in a hospital setting: A 10-year study. J. Clin. Pharm. Ther. 2016, 41, 532–537. [Google Scholar] [CrossRef]
  35. Zequinao, T.; Gasparetto, J.; dos Santos Oliveira, D.; Takahara Silva, G.; Telles, J.P.; Tuon, F.F. A broad-spectrum beta-lactam-sparing stewardship program in a middle-income country public hospital: Antibiotic use and expenditure outcomes and antimicrobial susceptibility profiles. Braz. J. Infect. Dis. 2020, 24, 221–230. [Google Scholar] [CrossRef] [PubMed]
  36. Falagas, M.E.; Karageorgopoulos, D.E. Extended-spectrum beta-lactamase-producing organisms. J. Hosp. Infect. 2009, 73, 345–354. [Google Scholar] [CrossRef] [PubMed]
  37. Che Hamzah, A.M.; Yeo, C.C.; Puah, S.M.; Chua, K.H.; Rahman, N.I.A.; Abdullah, F.H.; Othman, N.; Chew, C.H. Tigecycline and inducible clindamycin resistance in clinical isolates of methicillin-resistant Staphylococcus aureus from Terengganu, Malaysia. J. Med. Microbiol. 2019, 68, 1299–1305. [Google Scholar] [CrossRef] [PubMed]
  38. Martinez, J.L.; Baquero, F. Mutation Frequencies and Antibiotic Resistance. Antimicrob. Agents Chemother. 2000, 44, 1771–1777. [Google Scholar] [CrossRef]
  39. Zhao, X.; Drlica, K. Restricting the Selection of Antibiotic-Resistant Mutants: Measurement and Potential Uses of the Mutant Selection Window. JID 2002, 185, 561–565. [Google Scholar] [CrossRef]
  40. Ho, C.M.; Ho, M.W.; Liu, Y.C.; Toh, H.S.; Lee, Y.L.; Liu, Y.M.; Huang, C.C.; Lu, P.L.; Liu, C.E.; Chen, Y.H.; et al. Correlation between carbapenem consumption and resistance to carbapenems among Enterobacteriaceae isolates collected from patients with intra-abdominal infections at five medical centers in Taiwan, 2006–2010. Int. J. Antimicrob. Agents 2012, 40, S24–S28. [Google Scholar] [CrossRef]
  41. Lai, C.-C.; Wang, C.-Y.; Chu, C.-C.; Tan, C.-K.; Lu, C.-L.; Lee, Y.-C.; Huang, Y.-T.; Lee, P.-I.; Hsueh, P.-R. Correlation between antibiotic consumption and resistance of Gramnegative bacteria causing healthcare-associated infections at a university hospital in Taiwan from 2000 to 2009. J. Antimicrob. Chemother. 2011, 66, 1374–1382. [Google Scholar] [CrossRef]
  42. Altunsoy, A.; Aypak, C.; Azap, A.; Ergönül, Ö.; Balik, I. The impact of a nationwide antibiotic restriction program on antibiotic usage and resistance against nosocomial pathogens in Turkey. Int. J. Med. Sci. 2011, 8, 339–344. [Google Scholar] [CrossRef]
  43. Htoutou Sedlakova, M.; Urbanek, K.; Vojtova, V.; Suchankova, H.; Imwensi, P.; Kolar, M. Antibiotic consumption and its influence on the resistance in Enterobacteriaceae. BMC Res. Notes 2014, 7, 454. [Google Scholar]
  44. Barbosa, T.M.; Levy, S.B. The impact of antibiotic use on resistance development and persistence. Drug Resist. Updates 2000, 3, 303–311. [Google Scholar] [CrossRef]
  45. Händel, N.; Otte, S.; Jonker, M.; Brul, S.; ter Kuile, B.H. Factors that affect transfer of the IncI1 β-lactam resistance plasmid pESBL-283 between E. coli strains. PLoS ONE 2015, 10, e0123039. [Google Scholar] [CrossRef] [PubMed]
  46. Merlin, C. Reducing the Consumption of Antibiotics: Would That Be Enough to Slow Down the Dissemination of Resistances in the Downstream Environment? Front. Microbiol. 2020, 11, 33. [Google Scholar] [CrossRef] [PubMed]
  47. Kolar, M.; Cermak, P.; Hobzova, L.; Bogdanova, K.; Neradova, K.; Mlynarcik, P.; Bostik, P. Antibiotic Resistance in Nosocomial Bacteria Isolated from Infected Wounds of Hospitalized Patients in Czech Republic. Antibiotics 2020, 9, 342. [Google Scholar] [CrossRef] [PubMed]
  48. Hricová, K.; Štosová, T.; Kučová, P.; Fišerová, K.; Bardoň, J.; Kolář, M. Analysis of Vancomycin-Resistant Enterococci in Hemato-Oncological Patients. Antibiotics 2020, 9, 785. [Google Scholar] [CrossRef]
  49. Htoutou Sedlaková, M.; Fišerová, K.; Kolář, M. Bacteremia pathogens in the University Hospital Olomouc. Klin. Mikrobiol. Infekc. Lek. 2020, 26, 4–11. [Google Scholar]
  50. Kolar, M.; Htoutou Sedláková, M.; Pudova, V.; Roderova, M.; Novosad, J.; Senkyrikova, M.; Szotkowska, R.; Indrak, K. Incidence of fecal Enterobacteriaceae producing broad-spectrum beta-lactamases in patients with hematological malignancies. Biomed. Pap. Med. Fac. Univ. Palacky Olomouc Czechoslov. Repub. 2014, 159, 100–103. [Google Scholar] [CrossRef]
  51. Yang, P.; Chen, Y.; Jiang, S.; Shen, P.; Lu, X.; Xiao, Y. Association between antibiotic consumption and the rate of carbapenem-resistant Gram-negative bacteria from China based on 153 tertiary hospitals data in 2014. Antimicrob. Resist. Infect. Control 2018, 7, 137. [Google Scholar] [CrossRef]
  52. Uzunović, S.; Bedenić, B.; Budimir, A.; Kamberović, F.; Ibrahimagić, A.; Delić-Bikić, S.; Sivec, S.; Meštrović, T.; Varda Brkić, D.; Rijnders, M.I.; et al. Emergency (clonal spread) of methicillin-resistant Staphylococcus aureus (MRSA), extended spectrum (ESBL)--and AmpC beta-lactamase-producing Gram-negative bacteria infections at Pediatric Department, Bosnia and Herzegovina. Wien. Klin. Wochenschr. 2014, 126, 747–756. [Google Scholar] [CrossRef]
  53. Earls, M.R.; Coleman, D.C.; Brennan, G.I.; Fleming, T.; Monecke, S.; Slickers, P.; Ehricht, R.; Shore, A.C. Intra-Hospital, Inter-Hospital and Intercontinental Spread of ST78 MRSA From Two Neonatal Intensive Care Unit Outbreaks Established Using Whole-Genome Sequencing. Front. Microbiol. 2018, 9, 1485. [Google Scholar] [CrossRef]
  54. Strauß, L.; Stegger, M.; Akpaka, P.E.; Alabi, A.; Breurec, S.; Coombs, G.; Egyir, B.; Larsen, A.R.; Laurent, F.; Monecke, S.; et al. Origin, evolution, and global transmission of community-acquired Staphylococcus aureus ST8. Proc. Natl. Acad. Sci. USA 2017, 114, E10596–E10604. [Google Scholar] [CrossRef]
Figure 1. Correlation between aminoglycoside consumption (in numbers of defined daily doses) and resistance of Escherichia coli to gentamicin.
Figure 1. Correlation between aminoglycoside consumption (in numbers of defined daily doses) and resistance of Escherichia coli to gentamicin.
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Figure 2. Correlation between fluoroquinolone consumption (in numbers of defined daily doses) and resistance of Klebsiella pneumoniae to ciprofloxacin.
Figure 2. Correlation between fluoroquinolone consumption (in numbers of defined daily doses) and resistance of Klebsiella pneumoniae to ciprofloxacin.
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Figure 3. Correlation between aminoglycoside consumption (in numbers of defined daily doses) and resistance of Pseudomonas aeruginosa to amikacin.
Figure 3. Correlation between aminoglycoside consumption (in numbers of defined daily doses) and resistance of Pseudomonas aeruginosa to amikacin.
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Figure 4. Correlation between aminoglycoside consumption (in numbers of defined daily doses) and resistance of Klebsiella pneumoniae to gentamicin.
Figure 4. Correlation between aminoglycoside consumption (in numbers of defined daily doses) and resistance of Klebsiella pneumoniae to gentamicin.
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Figure 5. Correlation between carbapenem consumption (in numbers of defined daily doses) and resistance of Pseudomonas aeruginosa to meropenem.
Figure 5. Correlation between carbapenem consumption (in numbers of defined daily doses) and resistance of Pseudomonas aeruginosa to meropenem.
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Table 1. Basic information on the University Hospital Olomouc in 2019.
Table 1. Basic information on the University Hospital Olomouc in 2019.
No. of units68
No. of beds1198
No. of employees4199
No. of outpatients per year925,162
No. of inpatients per year53,633
Mean length of stay (days)5.6
No. of operations per year22,715
No. of units68
Table 2. Primer sequences used to detect the carbapenemase genes by PCR.
Table 2. Primer sequences used to detect the carbapenemase genes by PCR.
Target (Subtypes) Primer NameSequence (5′ to 3′ Direction) aAmplicon Size (bp)Tm (°C)Reference
FRI (8)FRI-F/RACAGACARGATGAGAGATTTCCT, CAGGTRCCTGTTTTATCGCC53858This study
GES (42)GES-F/RACGTTCAAGTTTCCGCTAG, GGCAACTAATTCGTCACGT62453This study
GIM (2)GIM-F/RTCGACACACCTTGGTCTGAA, AACTTCCAACTTTGCCATGC47755Ellington et al., 2007 [16]
IMI (11)IMI-F/RCTACGCTTTAGACACTGGC, AGGTTTCCTTTTCACGCTCA48254Mlynarcik et al., 2016 [17]
IMP (69)IMP-F1/R1GAGTGGCTTAATTCTCRATC, CCAAACYACTASGTTATCT18352Mlynarcik et al., 2016 [17]
IMP (2)IMP-F2/R2GCGGAATAGGGTGGCTTA, AGTTGCTTGGTTTTGATGGTT43552This study
IMP (3)IMP-F3/R3TGACGGGGTTAGTTATTGGCT, CGGTTTCGCTATGACCTGAA24857Mlynarcik et al., 2019 [18]
KPC (51)KPC-F/RGTTCTGCTGTCTTGTCTCTCA, CGGTCGTGTTTCCCTTTAG62556This study
NDM (29)NDM-F/RGGGGATTGCGACTTATGC, AGATTGCCGAGCGACTTG25853Mlynarcik et al., 2019 [18]
OXA-23-like (37)OXA(23-like)-F/RACTTGCTATGTGGTTGCTTCTC, ACCTTTTCTCGCCCTTCCAT31056Mlynarcik et al., 2016 [17]
OXA-48-like (31)OXA(48-like)-F/RAACGGGCGAACCAAGCATTTT, TGAGCACTTCTTTTGTGATGGCT59757Mlynarcik et al., 2016 [17]
VIM (68)VIM-F/RCGCGGAGATTGARAAGCAAA, CGCAGCACCRGGATAGAARA24757Mlynarcik et al., 2016 [17]
a For degenerate primers: R = A or G; S = G or C; Y = C or T.
Table 3. Resistance of Escherichia coli to antibiotics at the University Hospital Olomouc in 2010–2019.
Table 3. Resistance of Escherichia coli to antibiotics at the University Hospital Olomouc in 2010–2019.
2010201120122013201420152016201720182019
AMS28 (4118)23 (3552)28 (3558)19 (3464)22 (3529)22 (3905)25 (3998)26 (4145)24 (4133)26 (4350)
PPT10 (3121)9 (2652)11 (2624)11 (2482)13 (2525)14 (2751)16 (2953)14 (3256)15 (3078)18 (3091)
CTX9 (3143)8 (2650)13 (2624)12 (2480)14 (2522)15 (2748)16 (2950)13 (3236)14 (3084)15 (3077)
MER0 (3120)0 (2651)0 (2623)0 (2482)0 (2525)0 (2750)0 (2954)0 (3257)0 (3078)0 (3091)
GEN6 (4161)6 (3552)7 (3557)6 (3464)7 (3529)8 (3908)9 (3997)8 (4144)8 (4168)8 (4378)
AMI4 (3120)3 (2651)3 (2624)3 (2480)4 (2521)3 (2751)2 (2953)2 (3255)1 (3076)1 (3091)
CIP21 (3144)18 (2651)22 (2624)20 (2481)21 (2523)21 (2754)24 (2954)23 (3257)26 (3082)27 (3093)
COL0 (4129)1 (3250)0 (3558)0 (3463)1 (3529)1 (3905)0 (3999)0 (4143)0 (4147)0 (4354)
TIG1 (3080)0 (2645)1 (2623)4 (2480)2 (2520)4 (2744)1 (2948)0 (3234)1 (3079)1 (3071)
Legend: Resistance percentages (total number of isolates tested), AMS—ampicillin/sulbactam, PPT—piperacillin/tazobactam, CTX—cefotaxime, MER—meropenem, GEN—gentamicin, AMI—amikacin, CIP—ciprofloxacin, COL—colistin, TIG—tigecycline.
Table 4. Resistance of Klebsiella pneumoniae to antibiotics at the University Hospital Olomouc in 2010–2019.
Table 4. Resistance of Klebsiella pneumoniae to antibiotics at the University Hospital Olomouc in 2010–2019.
2010201120122013201420152016201720182019
AMS55 (2534)50 (1868)46 (2017)43 (2180)52 (2341)54 (2247)52 (2189)54 (2124)49 (2104)49 (2240)
PPT42 (2270)41 (1725)39 (1821)42 (1958)51 (2147)52 (2072)52 (1986)53 (1977)48 (1927)46 (2046)
CTX38 (2275)39 (1725)37 (1821)40 (1958)50 (2152)51 (2072)51 (1988)51 (1958)46 (1930)43 (2044)
MER0 (2270)<1 (1724)<1 (1818)<1 (1958)<1 (2147)0 (2069)<1 (1986)<1 (1975)<1 (1926)<1 (2047)
GEN35 (2554)36 (1867)31 (2017)35 (2180)42 (2337)45 (2247)44 (2191)45 (2123)37 (2106)36 (2243)
AMI11 (2269)7 (1725)5 (1821)5 (1954)6 (2147)4 (2070)3 (1985)2 (1976)2 (1926)1 (2044)
CIP40 (2275)42 (1725)37 (1821)40 (1958)48 (2147)52 (2072)54 (1988)54 (1978)49 (1927)46 (2048)
COL1 (2538)5 (1868)5 (2017)4 (2179)3 (2337)2 (2247)2 (2187)1 (2122)3 (2102)1 (2229)
TIG4 (2254)6 (1725)9 (1821)12 (1958)8 (2150)11 (2070)8 (1985)5 (1957)7 (1929)8 (2041)
Legend: Resistance percentages (total number of isolates tested).
Table 5. Resistance of Pseudomonas aeruginosa to antibiotics at the University Hospital Olomouc in 2010–2019.
Table 5. Resistance of Pseudomonas aeruginosa to antibiotics at the University Hospital Olomouc in 2010–2019.
2010201120122013201420152016201720182019
PPT8 (1360)23 (1353)24 (1627)30 (1677)26 (1529)28 (1664)17 (1689)13 (1541)13 (1472)14 (1725)
CTZ18 (1367)19 (1353)15 (1625)24 (1677)18 (1529)18 (1664)12 (1689)9 (1541)13 (1472)17 (1724)
MER28 (1367)39 (1353)36 (1627)40 (1677)36 (1529)39 (1664)37 (1688)32 (1541)28 (1471)34 (1724)
GEN22 (1367)23 (1350)22 (1626)26 (1678)25 (1529)25 (1664)20 (1689)16 (1540)16 (1471)11 (1722)
AMI1 (1367)5 (1352)4 (1627)4 (1677)4 (1528)5 (1664)7 (1689)5 (1541)6 (1470)5 (1725)
CIP34 (1366)35 (1353)34 (1627)38 (1675)34 (1528)32 (1664)26 (1689)24 (1540)24 (1471)23 (1725)
COL0 (1043)0 (1349)0 (1625)0 (1678)0 (1529)0 (1664)1 (1689)0 (1538)1 (1469)1 (1725)
Legend: Resistance percentages (total number of isolates tested), CTZ—ceftazidime.
Table 6. Resistance of Staphylococcus aureus to antibiotics at the University Hospital Olomouc in 2010–2019.
Table 6. Resistance of Staphylococcus aureus to antibiotics at the University Hospital Olomouc in 2010–2019.
2010201120122013201420152016201720182019
OXA3 (2129)4 (1744)3 (1794)4 (1825)3 (1860)4 (2031)4 (2111)6 (2149)4 (2559)4 (2615)
CIP5 (2125)5 (1746)5 (1794)6 (1825)7 (1860)7 (2029)7 (2110)8 (2150)7 (2560)7 (2615)
GEN4 (2106)8 (1739)11 (1792)8 (1826)10 (1858)8 (2005)6 (2100)6 (2148)6 (2560)7 (2608)
VAN0 (2127)0 (1742)0 (1793)0 (1822)0 (1856)0 (2002)0 (2072)0 (2146)0 (2556)0 (2610)
Legend: Resistance percentages (total number of isolates tested), OXA—oxacillin, VAN—vancomycin.
Table 7. Antibiotic consumption in defined daily doses (DDDs) at the University Hospital Olomouc.
Table 7. Antibiotic consumption in defined daily doses (DDDs) at the University Hospital Olomouc.
Antibiotic Class/Antibiotic2010201120122013201420152016201720182019
Penicillins combined with beta-lactamase inhibitors89,97780,21277,16876,80376,93781,88970,24871,77474,44676,427
3rd and 4th generation cephalosporins4497405637134018418846014812555362507716
Carbapenems4518521662236761995610,24210,91012,32213,19611,900
Aminoglycosides843310,63610,69510,657993710,91111,51711,20810,75610,413
Fluoroquinolones11,32210,87010,61811,36511,93513,64214,87512,95713,13312,421
Colistin714115312611738190522781648171418321669
Glycopeptides2921246430263167457840484012332231523088
Tigecycline554572426499131413022334268330192824
Table 8. Resistance of Escherichia coli to antibiotics at the Department of Anesthesiology and Intensive Care Medicine in 2010–2019.
Table 8. Resistance of Escherichia coli to antibiotics at the Department of Anesthesiology and Intensive Care Medicine in 2010–2019.
2010201120122013201420152016201720182019
AMS40 (115)48 (143)49 (140)28 (129)45 (110)42 (103)37 (97)45 (102)44 (116)34 (182)
PPT13 (116)21 (141)20 (138)16 (125)15 (107)23 (100)22 (98)25 (102)27 (117)25 (182)
CTX9 (116)16 (141)17 (138)14 (125)10 (107)20 (100)14 (97)18 (102)26 (117)31 (182)
MER0 (116)0 (141)0 (138)0 (125)0 (107)0 (100)0 (98)0 (102)0 (117)0 (182)
GEN6 (116)20 (143)16 (140)13 (129)12 (110)11 (103)12 (97)13 (102)18 (117)23 (182)
AMI7 (116)6 (141)9 (138)2 (125)8 (105)3 (100)5 (98)5 (102)1 (117)2 (182)
CIP35 (116)30 (141)27 (138)27 (125)29 (107)24 (100)30 (97)34 (102)36 (117)29 (182)
COL0 (116)3 (142)1 (140)0 (129)0 (110)1 (103)0 (98)0 (102)0 (116)0 (182)
TIG0 (115)2 (140)0 (138)4 (125)0 (107)8 (100)0 (97)1 (102)2 (117)3 (182)
Legend: Resistance percentages (total number of isolates tested).
Table 9. Resistance of Klebsiella pneumoniae to antibiotics at the Department of Anesthesiology and Intensive Care Medicine in 2010–2019.
Table 9. Resistance of Klebsiella pneumoniae to antibiotics at the Department of Anesthesiology and Intensive Care Medicine in 2010–2019.
2010201120122013201420152016201720182019
AMS72 (148)78 (181)75 (165)66 (247)70 (234)77 (222)77 (145)76 (127)80 (196)76 (404)
PPT58 (149)67 (181)61 (165)65 (247)62 (233)73 (222)71 (145)65 (126)67 (195)69 (401)
CTX49 (149)64 (181)58 (165)62 (247)60 (234)74 (222)71 (145)63 (126)74 (195)78 (404)
MER0 (149)3 (181)0 (165)<1 (247)<1 (233)0 (222)2 (145)2 (125)1 (195)1 (402)
GEN46 (149)64 (181)54 (165)63 (247)60 (233)75 (222)72 (145)60 (127)62 (195)71 (402)
AMI19 (149)14 (181)9 (165)13 (246)17 (233)6 (222)6 (145)4 (126)2 (195)7 (402)
CIP64 (149)71 (181)53 (165)63 (247)64 (233)76 (222)75 (145)67 (126)77 (195)72 (402)
COL3 (148)13 (181)10 (165)8 (247)9 (233)2 (222)7 (145)2 (127)6 (195)1 (398)
TIG7 (148)9 (181)13 (165)12 (247)7 (234)8 (222)17 (145)6 (126)12 (195)7 (403)
Legend: Resistance percentages (total number of isolates tested).
Table 10. Resistance of Pseudomonas aeruginosa to antibiotics at the Department of Anesthesiology and Intensive Care Medicine in 2010–2019.
Table 10. Resistance of Pseudomonas aeruginosa to antibiotics at the Department of Anesthesiology and Intensive Care Medicine in 2010–2019.
2010201120122013201420152016201720182019
PPT29 (106)32 (150)39 (188)41 (200)45 (224)42 (223)46 (150)44 (111)39 (142)43 (219)
CTZ32 (106)35 (150)39 (188)41 (200)48 (224)42 (223)35 (150)34 (111)31 (142)33 (218)
MER22 (106)31 (150)33 (188)38 (200)36 (224)44 (223)52 (149)53 (111)56 (142)59 (219)
GEN31 (106)42 (150)44 (188)37 (200)36 (224)43 (223)36 (150)26 (109)33 (141)32 (217)
AMI0 (106)5 (149)5 (188)2 (200)5 (224)7 (223)9 (150)12 (111)16 (141)3 (219)
CIP29 (106)33 (150)48 (188)47 (200)41 (224)43 (223)40 (150)35 (111)37 (142)35 (219)
COL0 (83)0 (150)0 (188)0 (200)0 (224)0 (223)0 (150)0 (109)2 (142)1 (217)
Legend: Resistance percentages (total number of isolates tested).
Table 11. Resistance of Staphylococcus aureus to antibiotics at the Department of Anesthesiology and Intensive Care Medicine in 2010–2019.
Table 11. Resistance of Staphylococcus aureus to antibiotics at the Department of Anesthesiology and Intensive Care Medicine in 2010–2019.
2010201120122013201420152016201720182019
OXA9 (46)5 (37)9 (56)14 (65)6 (47)16 (45)5 (43)6 (48)12 (49)5 (83)
CIP11 (46)8 (37)7 (56)20 (65)4 (47)18 (45)7 (43)6 (48)16 (49)11 (83)
GEN0 (45)0 (37)13 (56)5 (65)6 (47)5 (43)2 (43)6 (48)4 (49)11 (83)
VAN2 (46)0 (37)0 (56)0 (65)0 (47)0 (43)0 (42)0 (48)0 (48)0 (83)
Legend: Resistance percentages (total number of isolates tested).
Table 12. Antibiotic consumption in defined daily doses (DDD) at the Department of Anesthesiology and Intensive Care Medicine.
Table 12. Antibiotic consumption in defined daily doses (DDD) at the Department of Anesthesiology and Intensive Care Medicine.
Antibiotic Class/Antibiotic2010201120122013201420152016201720182019
Penicillins combined with beta-lactamase inhibitors1539146313691376135712881486151913391473
3rd and 4th generation cephalosporins125130234144428241260325394556
Carbapenems618739505946129014271298128014981822
Aminoglycosides209691629667682806812589677841
Fluoroquinolones589460514576501639670484398510
Colistin167253233410433498340190228478
Glycopeptides8375128204191237324158148249
Tigecycline55858070185230245275450415
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