Literature DB >> 30352640

Antimicrobial resistance of major clinical pathogens in South Korea, May 2016 to April 2017: first one-year report from Kor-GLASS.

Hyukmin Lee1,2, Eun-Jeong Yoon1,2, Dokyun Kim1, Seok Hoon Jeong1, Eun Jeong Won3, Jong Hee Shin3, Si Hyun Kim4, Jeong Hwan Shin5, Kyeong Seob Shin6, Young Ah Kim7, Young Uh8, Ji Woo Yang9, Il Hwan Kim9, Chan Park9, Kwang Jun Lee9.   

Abstract

The Korean government established an antimicrobial resistance (AMR) surveillance system, compatible with the Global AMR Surveillance System (GLASS): Kor-GLASS. We describe results from the first year of operation of the Kor-GLASS from May 2016 to April 2017, comprising all non-duplicated clinical isolates of major pathogens from blood, urine, faeces and urethral and cervical swabs from six sentinel hospitals. Antimicrobial susceptibility tests were carried out by disk diffusion, Etest, broth microdilution and agar dilution methods. Among 67,803 blood cultures, 3,523 target pathogens were recovered. The predominant bacterial species were Escherichia coli (n = 1,536), Klebsiella pneumoniae (n = 597) and Staphylococcus aureus (n = 584). From 57,477 urine cultures, 6,394 E. coli and 1,097 K. pneumoniae were recovered. Bloodstream infections in inpatients per 10,000 patient-days (10TPD) were highest for cefotaxime-resistant E. coli with 2.1, followed by 1.6 for meticillin-resistant Sta. aureus, 1.1 for imipenem-resistant Acinetobacter baumannii, 0.8 for cefotaxime-resistant K. pneumoniae and 0.4 for vancomycin-resistant Enterococcus faecium. Urinary tract infections in inpatients were 7.7 and 2.1 per 10TPD for cefotaxime-resistant E. coli and K. pneumoniae, respectively. Kor-GLASS generated well-curated surveillance data devoid of collection bias or isolate duplication. A bacterial bank and a database for the collections are under development.

Entities:  

Keywords:  Global Antimicrobial Resistance Surveillance System; antimicrobial resistance; bloodstream infection; gastroenteritis; multi-drug resistance; urinary tract infection

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Year:  2018        PMID: 30352640      PMCID: PMC6199864          DOI: 10.2807/1560-7917.ES.2018.23.42.1800047

Source DB:  PubMed          Journal:  Euro Surveill        ISSN: 1025-496X


Introduction

Antimicrobial resistance (AMR) is a growing burden in both clinical and socioeconomic context owing to the high morbidity and prolonged hospitalisation of patients that causes elevated medical and societal costs because of loss of productivity [1]. The World Health Organization launched the Global AMR Surveillance System (GLASS) in 2015 [2] as a core global action plan addressing this issue. The standardised GLASS manual allowed an overview of global AMR rates through international comparison. An AMR surveillance system in South Korea, the Korean AMR Monitoring System (KARMS), had been operated between 2002 and 2015 by Korean Centers for Disease Control and Prevention (KCDC) [3,4]. KARMS played an important role in notifying the high AMR rates in South Korea, urging the government to develop a national action plan. However, this system had limitations. Firstly, the antimicrobial susceptibility testing (AST) methods were not well harmonised across the participating clinical laboratories, affecting reliability. Secondly, duplicated isolates were not sufficiently filtered out, which could lead to an overestimation of the national AMR rates. Finally, the epidemiological interpretation of the study was limited because of insufficient clinical data. From KARMS, the KCDC established an improved AMR surveillance system compatible with the GLASS, named Kor-GLASS [5]. The Kor-GLASS manual was customised from that of GLASS: (i) three bacterial species from blood specimens were added, namely Enterococcus faecalis and Enterococcus faecium to monitor vancomycin resistance and Pseudomonas aeruginosa to monitor carbapenem resistance and (ii) more target antimicrobial agents for AST were included to investigate multi-drug resistance by species. We have operated the Kor-GLASS for one year since May 2016 and report here the first one-year assessment until April 2017.

Methods

Collection of isolates and clinical data from sentinel hospitals

The six sentinel hospitals collected bacterial isolates and clinical data, and all tests were performed in a central laboratory [5]. We collected all non-duplicated clinical isolates of Staphylococcus aureus, Streptococcus pneumoniae, Ent. faecalis, Ent. faecium, Acinetobacter spp., and P. aeruginosa from blood, Escherichia coli and Klebsiella pneumoniae from both blood and urine, Salmonella spp. from both blood and faeces, Shigella spp. from faeces and Neisseria gonorrhoeae from urethral and cervical swabs. Urine isolates were collected through semi-quantifying culture of urine samples following the criteria: (i) ≥104 colony-forming units (CFU)/mL single-species growth of either E. coli or K. pneumoniae and (ii) ≥105 CFU/mL of E. coli or K. pneumoniae in growth of mixed species [6]. We recorded epidemiological data including age, sex, infection origin (hospital origin (HO) or community origin (CO)) and admission types (outpatient department (OPD), general ward (GW), intensive care unit (ICU)) of all patients from whom blood, urine, stool or genital cultures were taken during study period. HO was defined when the specimen was taken from a patient hospitalised for two or more calendar days overall, including the hospitalisation days in another healthcare facility before transfer. CO was defined when the specimen was taken either from an outpatient or from a patient hospitalised for less than 2 calendar days.

Microbiological analysis in the central laboratory

Bacterial species were re-checked in the central laboratory using a Bruker Biotyper (Bruker Daltonics GmbH, Bremen, Germany) and/or by nucleotide sequence analysis of the 16S rDNA or rpoB (for Acinetobacter spp.). AST was carried out by disk diffusion, Etest, and broth microdilution and agar dilution methods following the Clinical and Laboratory Standards Institute guidelines [7]. Antimicrobial susceptibility phenotypes were categorised according to Magiorakos et al. [8] with a few modifications: • fully susceptible (DS): susceptible to all tested drugs; • drug-resistant (DR): non-susceptible to one or two drug classes; • multidrug-resistant (MDR): non-susceptible to three or more antimicrobial classes; • extensively drug-resistant (XDR): susceptible to two or fewer antimicrobial classes; • pandrug-resistant (PDR): not susceptible to any antimicrobial class. Double-blinded inter-laboratory parallel tests were conducted monthly for randomly selected isolates in order to evaluate proficiency of the results from central and the national KCDC reference laboratories.

Results

Target pathogen isolation from the collected cultures

During the 1-year period, six sentinel hospitals sampled 67,803 patients for blood culture, 57,477 for urine, 12,782 for stool and 3,111 for genital cultures (Figure 1). A total of 3,523 (5.2%) target pathogens were recovered from blood (Supplement: supplementary figure 1). The predominant bacterial species was E. coli (n = 1,536, 43.6%), followed by K. pneumoniae (n = 597, 16.9%) and Sta. aureus (n = 584, 16.6%). Acinetobacter spp. was recovered more often (n = 229, 6.5%) than P. aeruginosa (n = 127, 3.6%). The majority of Acinetobacter spp. were A. baumannii (188/229, 82.1%); the remaining 41 were non-baumannii Acinetobacter spp. (NBA), composed of A. nosocomialis (n = 23), A. pittii (n = 12), A. bereziniae (n = 2), A. soli (n = 2), A. radioresistens (n = 1) and Acinetobacter genomospecies 14TU (n = 1). Ent. faecium (n = 217, 6.2%) was recovered more often than Ent. faecalis (n = 161, 4.6%). Salmonella spp. (n = 44, 1.2%) and Str. pneumoniae (n = 28, 0.8%) were rarely recovered.
Figure 1

Number of patients sampled for bacterial culture, by specimen and age group, South Korea, May 2016–April 2017

Number of patients sampled for bacterial culture, by specimen and age group, South Korea, May 2016–April 2017 Patients are shown grouped by origin of infections. Detailed numbers can be found in Table 1 in the Supplement. Rates of bloodstream infection (BSI) occurrence among inpatients per 10,000 patient-days (10TPD) were calculated by bacterial pathogen (Figure 2). The total number of patient-days in the six sentinel hospitals during the surveillance period was 1,620,431 days, comprising 181,967 days in ICU and 1,438,464 days on a GW. The highest mean rate of BSI was found for E. coli with 5.5 (range: 1.4–12.2 by hospital), followed by 2.8 for Sta. aureus (range: 1.1–6.7), 2.5 for K. pneumoniae (range: 1.0–5.1), 1.2 for Ent. faecium (range: 0.5–1.7), 1.1 for A. baumannii (range: 0.8–1.7), 0.8 for Ent. faecalis (range: 0.3–1.8) and 0.6 for P. aeruginosa (range: 0.1–1.1). BSI occurrence was more common in ICU patients than in GW patients: the ratio of ICU:GW was highest in A. baumannii at 16.5 (6.6:0.4), followed by 6.0 (3.0:0.5) in Ent. faecalis, 4.4 (8.8:2.0) in Sta. aureus, 4.0 (3.6:0.9) in Ent. faecium, 3.4 (1.7:0.5) in P. aeruginosa, 2.7 (5.7:2.1) in K. pneumoniae, and 1.8 (9.0:5.1) in E. coli.
Figure 2

Occurrence of bloodstream and urinary tract infections per 10,000 patient-days, by target pathogen, South Korea, May 2016–April 2017 (total patient days = 1,620,431)

Occurrence of bloodstream and urinary tract infections per 10,000 patient-days, by target pathogen, South Korea, May 2016–April 2017 (total patient days = 1,620,431) GW: general ward; ICU: intensive care unit. The figure shows mean occurrence across all six hospitals, with the lowest and highest indicated by error bars. From the 57,477 urine cultures, 6,394 (11.1%) E. coli and 1,097 (1.9%) K. pneumoniae were recovered. The mean rate of E. coli urinary tract infection (UTI) occurrence among inpatients per 10TPD was 20.7 (range: 4.4–32.7 by hospital) and that caused by K. pneumoniae was 4.7 (range: 2.0–8.3). The ratio of UTI occurrence in ICU:GW was higher in K. pneumoniae (2.5, 10.0:4.0) than in E. coli (1.4, 26.9:19.9). From the 12,782 stool cultures, 77 Salmonella spp. (0.6%) were recovered. None of the 3,111 genital cultures were positive for N. gonorrhoeae.

Antimicrobial susceptibilities of major pathogens

Gram-positive pathogens

More than half (317/584, 54.3%) of Sta. aureus blood isolates were resistant to cefoxitin (Figures 3 and 4), which means that these were meticillin-resistant Sta. aureus (MRSA). By origin of infection, 69.4% (213/307) of HO Sta. aureus were MRSA, more than the 37.5% (104/277) of CO. Most of the isolates remained susceptible to linezolid, tigecycline and quinupristin-dalfopristin, and they were all susceptible to vancomycin and teicoplanin. The Sta. aureus blood isolates were categorised as DS (35.8%, n = 209), DR (9.9%, n = 58) and MDR (54.3%, n = 317), and all MDR isolates were MRSA (Supplement: supplementary figure 2).
Figure 3

Percentage of resistance to major antimicrobials by infection origin, South Korea, May 2016–April 2017 (Part I: panels A–F)

Figure 4

Percentage of resistance to major antimicrobials by infection origin, South Korea, May 2016–April 2017 (Part II: panels G–L)

Percentage of resistance to major antimicrobials by infection origin, South Korea, May 2016–April 2017 (Part I: panels A–F) Amox-Clav: amoxicillin-clavulanic acid; Amp-Sulb: ampicillin-sulbactam; CO: community origin; HO: hospital origin; Gentamicin-HL: high-level resistance to gentamicin; Pio-Tazob: piperacillin-tazobactam; Quin-Dalf: quinupristin-dalfopristin; Streptomycin-HL: high-level resistance to streptomycin; Trim-Sulf: trimethoprim-sulfamethoxazole. Detailed numbers can be found in Tables 2–7 in the Supplement. Percentage of resistance to major antimicrobials by infection origin, South Korea, May 2016–April 2017 (Part II: panels G–L) Amox-Clav: amoxicillin-clavulanic acid; Amp-Sulb: ampicillin-sulbactam; CO: community origin; HO: hospital origin; Gentamicin-HL: high-level resistance to gentamicin; Pio-Tazob: piperacillin-tazobactam; Quin-Dalf: quinupristin-dalfopristin; Streptomycin-HL: high-level resistance to streptomycin; Trim-Sulf: trimethoprim-sulfamethoxazole. Detailed numbers can be found in Tables 8–13 in the Supplement. While resistance to ampicillin in Ent. faecalis blood isolates was rare (1/161, 0.6%), the proportion of penicillin resistance was comparably high (n = 36, 22.4%) and more frequent in HO (24/90, 26.7%) than in CO (12/71, 16.9%). Resistance to glycopeptides was also rare (Figures 3 and 4). The rate of high-level resistance [7] to aminoglycosides was 38.5% (n = 62) to gentamicin and 18.0% (n = 29) to streptomycin. The majority of the Ent. faecalis blood isolates were either DR (49.1%, n = 79) or MDR (42.2%, n = 68). The proportion of multidrug resistance in penicillin-resistant isolates was three times higher (86.1%, 31/36) than that in susceptible ones (29.6%, 37/125). Among the 217 Ent. faecium blood isolates, 90.3% (n = 196) were resistant to ampicillin and 29.0% (n = 63) and 18.4% (n = 40) were resistant to vancomycin and teicoplanin, respectively. For these drugs, resistance rates in HO isolates were higher than those in CO isolates (Figures 3 and 4). Forty of the 63 vancomycin-resistant Ent. faecium (VREFM) were also resistant to teicoplanin and 14 were intermediate, while nine remained susceptible to the drug. In addition, 27.6% (n = 60) and 10.1% (n = 22) of all Ent. faecium were high-level resistant to gentamicin and streptomycin, respectively. Two thirds of the Ent. faecium blood isolates were MDR (62.7%, n = 136) and one third was DR (33.2%, n = 72). All VREFM isolates were categorised as MDR. All Str. pneumoniae blood isolates were susceptible (23/28) or intermediate (n = 5) to penicillin. The five penicillin-intermediate isolates were also non-susceptible to other drugs. All 28 isolates were susceptible to levofloxacin. Erythromycin resistance was observed in 21 of the 28 isolates.

Enterobacteriaceae

Ampicillin resistance was identified in 65.6% (1,007/1,536) of E. coli blood isolates and decreased to 24.2% (n = 372) when sulbactam was supplemented. Rates of resistance to cefotaxime, ceftazidime and cefepime were 34.7% (n = 533), 11.3% (n = 173) and 21.0% (n = 322), respectively. Carbapenem-non-susceptible isolates were rarely identified. The resistance rate to ciprofloxacin was 39.5% (n = 606) and that to amikacin was low at 0.7% (n = 11). Colistin-resistant isolates were seldom identified, with 0.2% (n = 3). Resistance rates in E. coli urine isolates were similar to those in blood isolates. One isolate was resistant to all three carbapenems and six were non-susceptible only to ertapenem. Colistin resistance was detected in 14 (0.2%) of the 6,394 E. coli urine isolates. HO isolates had higher resistance rates to most of the tested antimicrobials than CO isolates, and this difference was much greater in blood isolates than in urine isolates. The vast majority (98.8%, 2,616/2,648) of cefotaxime-non-susceptible E. coli isolates were MDR and all XDR isolates (0.2%, 15/7,930) were non-susceptible to both carbapenems and cefotaxime. One third (30.2%, 180/597) of K. pneumoniae blood isolates were piperacillin-resistant and a quarter (25.5%, n = 152) were resistant to ampicillin-sulbactam. For the extended-spectrum cephalosporins, 27.0% (n = 161) isolates were resistant to cefotaxime, 20.8% (n = 124) to ceftazidime and 20.6% (n = 123) to cefepime. Carbapenem resistance was identified more frequently in K. pneumoniae blood isolates than in E. coli (Figures 3 and 4). The resistance rate to ciprofloxacin was 20.8% (n = 124), and those to amikacin and gentamicin were 3.4% (n = 20) and 13.6% (n = 81), respectively. Colistin resistance was identified in 0.8% (n = 5) isolates. K. pneumoniae urine isolates exhibited higher rates of resistance to the antimicrobials tested than the blood isolates. Carbapenem resistance rates in the 1,097 urine isolates were 1.0% (n = 11) to imipenem, 1.0% (n = 11) to meropenem, and 1.3% (n = 14) to ertapenem. Colistin resistance was detected in 1.0% (n = 11) isolates. The proportion of antimicrobial resistance in K. pneumoniae of HO was higher than in those of CO and the difference between them was larger in blood isolates (ca. three times higher) than in urine isolates (ca. 1.5 times higher). Most of the 604 Cefotaxime-non-susceptible isolates were MDR (77.6%, n = 469) or XDR (20.9%, n = 126). Among 44 Salmonella blood isolates, one isolate was resistant to cefotaxime and intermediate to ceftazidime. All the isolates remained susceptible to imipenem. None was resistant to ciprofloxacin, however, 10 were intermediate to the drug, and colistin resistance was observed in four. Five of the 77 Salmonella stool isolates were cefotaxime-resistant, and four of those five were also resistant to ceftazidime. Similar to the blood isolates, all stool isolates were also susceptible to imipenem and 12 isolates were intermediate to ciprofloxacin. Three isolates were resistant to colistin.

Glucose non-fermenting Gram-negative bacilli

Non-susceptibility to piperacillin in P. aeruginosa blood isolates was observed in 21 of 127 (16.5%) isolates, and supplementing tazobactam had no effect on the susceptibility proportion (82.7%, n = 105) (Figures 3 and 4). The proportion of resistance to ceftazidime and cefepime was 11.8% (n = 15) and 12.6% (n = 16), respectively. Rates of carbapenem resistance were 18.1% (n = 23) for imipenem and 15.7% (n = 20) for meropenem. In addition, 6.3% (n = 8) of isolates were resistant to amikacin, 9.4% (n = 12) to gentamicin, 8.7% (n = 11) to tobramycin and 15.0% (n = 19) to ciprofloxacin. All isolates remained susceptible to colistin. Twice as many HO than CO isolates were non-susceptible to the drug. The amikacin-non-susceptible P. aeruginosa blood isolates were mostly XDR (8/9) with the exception of one MDR isolate. In contrast, 14 of 30 among the imipenem-non-susceptible isolates were XDR, four were MDR and 12 were DR. The proportion of AMR in the 188 A. baumannii blood isolates was higher than 70% for all tested drugs (Figures 3 and 4) and the AMR proportion in HO isolates was ca. twice that of CO isolates. Minocycline, tigecycline and colistin were still active in 93.1% (n = 175), 85.6% (n = 161) and 99.5% (n = 187) of isolates, respectively. Among the A. baumannii blood isolates, 76.1% (n = 143) and 13.8% (n = 26) were XDR and MDR, respectively, and all but two MDR isolates were imipenem-non-susceptible. NBA blood isolates had a markedly lower proportion of AMR than A. baumannii.

The estimated prevalence of major AMR pathogens

In general, the AMR proportion of major pathogens for ICU patients was higher than for GW and OPD patients (Supplement: supplementary figure 3). BSI occurrence by major AMR pathogen in inpatients per 10TPD (Figure 5) had the highest mean value of 2.1 for cefotaxime-resistant E. coli (CXREC), followed by 1.6 for MRSA, 1.1 for imipenem-resistant A. baumannii, 0.8 for cefotaxime-resistant K. pneumoniae (CXRKP), 0.4 for VREFM, 0.2 for penicillin-resistant Ent. faecalis (PREFA) and 0.2 for imipenem-resistant P. aeruginosa. As shown in Figure 5, the ratio of BSI occurrence of the major AMR pathogens was much higher in ICU than on GW. Mean UTI occurrence in inpatients per 10TPD was higher for CXREC at 7.7 than for CXRKP at 2.1. The ratio of UTI occurrence in ICU vs GW was higher for CXRKP at 2.4 than for CXREC at 1.5.
Figure 5

Occurrence of bloodstream and urinary tract infections per 10,000 patient-days, by major antimicrobial resistant pathogen, South Korea, May 2016–April 2017 (total patient days = 1,620,431)

Occurrence of bloodstream and urinary tract infections per 10,000 patient-days, by major antimicrobial resistant pathogen, South Korea, May 2016–April 2017 (total patient days = 1,620,431) CXREC: cefotaxime-resistant Escherichia coli; CXRKP: cefotaxime-resistant Klebsiella pneumoniae; GW: General ward; ICU: intensive care unit; IRAB: imipenem-resistant Acinetobacter baumannii; IRPA: imipenem-resistant Pseudomonas aeruginosa; MRSA: meticillin-resistant Staphylococcus aureus; PREFA: penicillin-resistant Enterococcus faecalis; VREFM: vancomycin-resistant Enterococcus faecium. The figure shows mean occurrence across all six hospitals, with the lowest and highest indicated by error bars.

Discussion

De Kraker et al. [9] described an increasing trend in the overall incidence of bacteremia caused by the top five pathogens (E. coli, Sta. aureus, Str. pneumoniae, Ent. faecalis and Ent. faecium) between 2002 and 2008, based on the European Antimicrobial Resistance Surveillance Network (EARS-Net; https://ecdc.europa.eu/en/about-us/networks/disease-networks-and-laboratory-networks/ears-net-about) database. Predominance of E. coli among pathogens causing BSIs is a common phenomenon worldwide. We assessed the relative incidence of BSIs caused by E. coli compared with other species: The relative ratio of E. coli to Sta. aureus in Kor-GLASS was moderate at 2.6, which was lower than the 3.2 observed in Norway [10], similar to the ratios of 2.4 in Taiwan [11] and 2.2 in Netherlands [12], and higher than the ratios of 1.2 in Japan [13], 1.2 in Vietnam [14], 1.0 in Greece [15] and 1.1 in Malawi [16]. The relative ratio of E. coli to K. pneumoniae in South Korea was also moderate at 2.6, lower than in Northern European countries (5.4 in the Netherlands and 5.0 in Norway), similar to 2.5 in Japan and 3.0 in Taiwan, and higher than 1.0 in Vietnam. Str. pneumoniae was frequently isolated from blood in European countries (relative ratio of E. coli to Str. pneumoniae: 3.2 in the Netherlands, 3.1 in Norway and 4.1 in Spain), but rarely identified in South Korea (ratio: 54.9) which was similar to Asian countries (ratio: 18.3 in Vietnam and 31.8 in Taiwan). The Salmonella spp. is still a major pathogen causing BSI in developing countries such as Vietnam (relative ratio of E. coli to Salmonella spp.: 1.4) and Malawi (ratio: 0.2), however, this species was seldom identified in South Korea (ratio: 34.9), similar to the ratios 28.1 in Spain and 14.3 in Taiwan. Sta. aureus was the second most common pathogen causing BSI following E. coli. BSI caused by Sta. aureus occurred in 2.8 inpatients per 10TPD in our study, which is 1.8-fold more than the 1.6 inpatients per 10TPD measured in 2011 in a previous prospective multi-center study in South Korea [17]. Since the surveillance system of that study is not compatible to Kor-GLASS, the potential increase in Sta. aureus-BSI needs to be further followed up. Similarly, we observed an increased incidence of MRSA-BSI at 1.6 inpatients per 10TPD compared with 1.2 inpatients per 10TPD in 2011. This incidence was 2.5 times higher than the 0.62 inpatients per 10TBD reported in a Canadian surveillance study in 2014 [18]. The high prevalence of MRSA in blood isolates in South Korea has decreased from 72% in 2013 to 66% in 2015 as measured by KARMS [4] and further to 54.3% in 2016 according to Kor-GLASS data. EARS-Net reported similarly that the percentage of MRSA has decreased from 18.1% in 2013 to 13.7% in 2016 [9]. In addition, MRSA occurred more frequently in ICU patients than in GW patients (5.8 vs 1.1), indicating that MRSA is a problem in ICUs. Enterococci have become a major cause of BSIs globally, owing to their intrinsic resistance to various antibiotics and their enormous ability to acquire resistance to antimicrobials. Ent. faecium and Ent. faecalis were the fourth and sixth most common pathogens causing BSI in inpatients in our study, with 1.2 and 0.8 BSI occurrences per 10TPD, respectively, and they caused over four times more BSI in ICUs than on GWs. Ent. faecium exhibited remarkably higher resistance rates than Ent. faecalis to ampicillin (90.3% vs 0.6%) and vancomycin (29.1% vs 0.6%), resulting in the identification of 1.3-fold more Ent. faecium than Ent. faecalis, similar to the 1.8-fold difference found in Spain [19]. A reversed ratio was observed in the Netherlands (0.8:1) [14], and Japan (0.7:1) [12], countries that have low rates of AMR to these drugs. The vancomycin resistance rate (29.1%) in Ent. faecium was higher than that of teicoplanin (18.4%) in South Korea, although all isolates were vanA-positive. This might be caused by the dissemination of clones with a vanA genotype–VanA phenotype along with a vanA genotype–VanD phenotype following inactivation of vanY and vanZ in the vanA operon by rearrangement of Tn1546 [20]. PREFA was also a common BSI-causative AMR pathogen, especially in ICUs. Clinical impacts of the penicillin resistance need to be further investigated. Both E. coli and K. pneumoniae exhibited higher resistance rates to cefotaxime than to ceftazidime owing to the dissemination of CTX-M-type extended-spectrum β-lactamases (ESBLs). The difference in the resistance rates to these drugs was greater in E. coli than in K. pneumoniae, which could have two possible causes: higher prevalence K. pneumoniae compared with E. coli (i) of CTX-M group 1 ESBLs, which have an expanded hydrolytic activity to ceftazidime, and (ii) of SHV-type ESBLs, which hydrolyse both cefotaxime and ceftazidime [21,22]. Identification of carbapenemase-producing Enterobacteriaceae (CPEs) in our surveillance study seemed the tip of an iceberg of the notorious AMR pathogen disseminated in clinical settings. All CPEs we identified were K. pneumoniae carbapenemase (KPC) producers. Continuous monitoring and action plans for CPEs are required because various types of carbapenemases, including KPC, New Delhi metallo-β-lactamase and OXA-48-likes, have been introduced to South Korea during the last decade [23-25]. Colistin resistance in Enterobacteriaceae was rare in our study and none contained the mobile colistin resistance (mcr) genes mcr-1 to mcr-5 [26-28], although clinical Enterobactericeae isolates carrying the mcr-1 gene have already been reported in South Korea [29]. Amikacin non-susceptibility was a better indicator for XDR P. aeruginosa than imipenem-non-susceptibility. The carbapenemase-producing P. aeruginosa strains in South Korea harboured a class 1 integron carrying several resistance gene cassettes coding not only for a carbapenemase, but also for aminoglycoside-modifying enzymes [30]. Thus, most of the amikacin-non-susceptible isolates were XDR. However, carbapenem resistance in P. aeruginosa strains was conferred not only through acquisition of a gene for carbapenemase, but also through loss or alteration of the intrinsic OprD porin or overproduction of the efflux pumps [31], which rarely confer resistance to amikacin to the bacterial hosts. BSIs caused by A. baumannii strains mostly occurred in ICUs rather than on GWs [32]. The likely reason is that the A. baumannii BSIs originated predominantly from pulmonary infections associated with ventilators. The rate of carbapenem resistance in A. baumannii strains was markedly high at 89.9% and most of these strains were XDR. This result is in line with previous reports from South Korea, and the resistance was mostly associated with OXA-23 carbapenemase production [33].

Conclusion

The Kor-GLASS, which performs strain collection and centralised analysis, was launched and operated. It provided well-curated surveillance data devoid of collection bias or isolate duplication, including patient data associated with the bacterial cultures. In addition, frequency of infection occurrence by patient-days was estimated for comparison with foreign countries. The results of this surveillance helped plan national action in response to the high rate of drug resistance. A bacterial bank and a database for the collections are under development.
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6.  National laboratory-based surveillance system for antimicrobial resistance: a successful tool to support the control of antimicrobial resistance in the Netherlands.

Authors:  Wieke Altorf-van der Kuil; Annelot F Schoffelen; Sabine C de Greeff; Steven Ft Thijsen; H Jeroen Alblas; Daan W Notermans; Anne Lm Vlek; Marianne Ab van der Sande; Tjalling Leenstra
Journal:  Euro Surveill       Date:  2017-11

7.  Bacterial bloodstream infections in a tertiary infectious diseases hospital in Northern Vietnam: aetiology, drug resistance, and treatment outcome.

Authors:  Vu Quoc Dat; Hieu Ngoc Vu; Hung Nguyen The; Hoa Thi Nguyen; Long Bao Hoang; Dung Vu Tien Viet; Chi Linh Bui; Kinh Van Nguyen; Trung Vu Nguyen; Dao Tuyet Trinh; Alessandro Torre; H Rogier van Doorn; Behzad Nadjm; Heiman F L Wertheim
Journal:  BMC Infect Dis       Date:  2017-07-12       Impact factor: 3.090

8.  Increasing Resistance to Extended-Spectrum Cephalosporins, Fluoroquinolone, and Carbapenem in Gram-Negative Bacilli and the Emergence of Carbapenem Non-Susceptibility in Klebsiella pneumoniae: Analysis of Korean Antimicrobial Resistance Monitoring System (KARMS) Data From 2013 to 2015.

Authors:  Dokyun Kim; Ji Young Ahn; Chae Hoon Lee; Sook Jin Jang; Hyukmin Lee; Dongeun Yong; Seok Hoon Jeong; Kyungwon Lee
Journal:  Ann Lab Med       Date:  2017-05       Impact factor: 3.464

9.  Burden of bloodstream infection in an area of Mid-Norway 2002-2013: a prospective population-based observational study.

Authors:  Arne Mehl; Bjørn Olav Åsvold; Stian Lydersen; Julie Paulsen; Erik Solligård; Jan Kristian Damås; Stig Harthug; Tom-Harald Edna
Journal:  BMC Infect Dis       Date:  2017-03-11       Impact factor: 3.090

10.  Trends in antimicrobial resistance in bloodstream infection isolates at a large urban hospital in Malawi (1998-2016): a surveillance study.

Authors:  Patrick Musicha; Jennifer E Cornick; Naor Bar-Zeev; Neil French; Clemens Masesa; Brigitte Denis; Neil Kennedy; Jane Mallewa; Melita A Gordon; Chisomo L Msefula; Robert S Heyderman; Dean B Everett; Nicholas A Feasey
Journal:  Lancet Infect Dis       Date:  2017-08-14       Impact factor: 25.071

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  26 in total

1.  Bloodstream Infections in the Intensive Care Unit: a Single-Center Retrospective Bacteriological Analysis Between 2007 and 2019.

Authors:  Aneta Guzek; Zbigniew Rybicki; Agnieszka Woźniak-Kosek; Dariusz Tomaszewski
Journal:  Pol J Microbiol       Date:  2022-06-19

2.  Comparison of Clinical Outcomes for Glycopeptides and Beta-Lactams in Methicillin-Susceptible Staphylococcus Aureus Bloodstream Infections.

Authors:  Yeon Ju La; Hye Rim Kim; Dong Hyun Oh; Jin Young Ahn; Yong Chan Kim
Journal:  Yonsei Med J       Date:  2022-07       Impact factor: 3.052

3.  Healthcare-associated infections and antimicrobial resistance in Canadian acute care hospitals, 2014-2018.

Authors:  Canadian Nosocomial Infection Surveillance
Journal:  Can Commun Dis Rep       Date:  2020-05-07

4.  Antimicrobial resistance trends in bloodstream infections at a large teaching hospital in China: a 20-year surveillance study (1998-2017).

Authors:  Lei Tian; Zhen Zhang; Ziyong Sun
Journal:  Antimicrob Resist Infect Control       Date:  2019-05-28       Impact factor: 4.887

5.  Prevalence and Risk Factors of Carbapenem-resistant Enterobacteriaceae Acquisition in an Emergency Intensive Care Unit in a Tertiary Hospital in Korea: a Case-Control Study.

Authors:  Jin Suk Kang; Jongyoun Yi; Mee Kyung Ko; Soon Ok Lee; Jeong Eun Lee; Kye Hyung Kim
Journal:  J Korean Med Sci       Date:  2019-05-13       Impact factor: 2.153

6.  Molecular Characterization of Fecal Extended-Spectrum β-Lactamase- and AmpC β-Lactamase-Producing Escherichia coli From Healthy Companion Animals and Cohabiting Humans in South Korea.

Authors:  Jun Sung Hong; Wonkeun Song; Hee-Myung Park; Jae-Young Oh; Jong-Chan Chae; Seri Jeong; Seok Hoon Jeong
Journal:  Front Microbiol       Date:  2020-04-15       Impact factor: 5.640

7.  Antibiotic Resistance Patterns of Enterobacteriaceae Isolated from Patients with Healthcare-Associated Infections.

Authors:  Young Kyun Choi; Eun Ju Byeon; Jin Ju Park; Jacob Lee; Yu Bin Seo
Journal:  Infect Chemother       Date:  2021-06

8.  In vitro activity of ceftazidime-avibactam and comparators against Gram-negative bacterial isolates collected in the Asia-Pacific region as part of the INFORM program (2015-2017).

Authors:  Wen-Chien Ko; Gregory G Stone
Journal:  Ann Clin Microbiol Antimicrob       Date:  2020-04-01       Impact factor: 3.944

9.  Prevalence and Risk Factors for Extended-Spectrum β-Lactamase-Producing Klebsiella pneumoniae Colonization in Intensive Care Units.

Authors:  Young Ah Kim; Yoon Soo Park; Banseok Kim; Young Hee Seo; Kyungwon Lee
Journal:  Ann Lab Med       Date:  2020-03       Impact factor: 3.464

10.  Pathogenic spectrum of blood stream infections and resistance pattern in Gram-negative bacteria from Aljouf region of Saudi Arabia.

Authors:  Altaf Bandy; Abdulrahman Hamdan Almaeen
Journal:  PLoS One       Date:  2020-06-09       Impact factor: 3.240

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