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. 2020 Aug 27;25(34):1900516. doi: 10.2807/1560-7917.ES.2020.25.34.1900516

Eight-year trends in the relative isolation frequency and antimicrobial susceptibility among bloodstream isolates from Greek hospitals: data from the Greek Electronic System for the Surveillance of Antimicrobial Resistance – WHONET-Greece, 2010 to 2017

Michalis Polemis 1, Kyriaki Tryfinopoulou 1, Panagiota Giakkoupi 2; WHONET-Greece study group3, Alkiviadis Vatopoulos 2; WHONET-Greece study group; WHONET-Greece study group, A Koteli, P Fitas, M Economou, C Konsolakis, Κ Fountoulis, E Perivolioti, H Vagiakou, G Ganteris, E Tsorlini, E Vagdatli, A Karantani, S Tsiplakou, V Papaioannou, G Maropoulos, I Deliolanis, E Lebessi, A Doudoulakakis, V Baka, A Platania, E Chinou, M Martsoukou, K Velentza, S Karabela, ES Moraitou, P Kazila, K Digalaki, O Zarkotou, M Papadogianni, K Zervaki, I Karatzoglou, E Platsouka, Z Roussou, F Markou, V Thomoglou, G Stamatopoulou, E Mournianakis, I Theodorakos, L Skoura, E Protonotariou, M Panopoulou, A Koutsidou, E Petinaki, A Vasdeki
PMCID: PMC7453683  PMID: 32856583

Abstract

Background

Antimicrobial resistance (AMR) changes over time and continuous monitoring provides insight on trends to inform both empirical treatment and public health action.

Aims

To survey trends in relative isolation frequency (RIF) and AMR among key bloodstream pathogens using data from the Greek Electronic System for the Surveillance of AMR (WHONET-Greece).

Methods

This observational study looked into routine susceptibility data of 50,488 blood culture isolates from hospitalised patients in 25 tertiary hospitals, participating in the WHONET-Greece for trends over time between January 2010 and December 2017. Only the first isolate per species from each patient was included. Hospital wards and intensive care units (ICUs) were analysed separately.

Results

During the study, the RIF of Acinetobacter baumannii increased in wards, as did the proportion of A. baumannii isolates, which were non-susceptibleto most antibiotics in both wards and ICUs. Coincidently, Klebsiella pneumoniae RIF declined while the respective rates of non-susceptible isolates to carbapenems and gentamicin increased. Pseudomonas aeruginosa RIF remained stable but decreasing proportions of non-susceptible isolates to all studied antibiotics, except imipenem were observed. Escherichia coli RIF increased as did the proportion of isolates non-susceptible to third-generation cephalosporins, carbapenems and fluoroquinolones. Concerning Staphylococcus aureus, a decline in the percentage of meticillin resistant isolates in ICUs was found, while the percentages of Enterococcus faecium isolates with non-susceptibility to vancomycin stayed stable.

Conclusions

Recognising these trends over time is important, since the epidemiology of AMR is complex, involving different ‘bug and drug’ combinations. This should be taken into consideration to control AMR.

Keywords: routine laboratory data, bloodstream infections, antimicrobial resistance, surveillance system, trend analysis, Greece

Introduction

Antimicrobial resistance (AMR), especially the appearance and dissemination of multiresistant bacteria, as well as the lack of alternative treatments, are a major threat to both clinical medicine and public health in Greece, elsewhere in Europe and globally. As stated in the recent World Health Organization (WHO) AMR action plans, an important cornerstone to control AMR is its surveillance [1].

Indeed, continuous monitoring of the emergence and evolution of resistance to key antimicrobials over time constitutes a crucial first step to estimate the burden of the problem, uncover trends, detect new resistance phenotypes, guide empirical antimicrobial treatment and measure the effect of interventions [2].

The routine results of the antimicrobial susceptibility tests performed daily in each hospital clinical laboratory are considered as a major resource for continuous, passive AMR surveillance since they are reliable and informative and can be collected on a daily basis without imposing any additional effort to the clinical microbiology laboratory.

Greece has been among the first countries with an electronic network based on routine susceptibility results since 1995. The Greek AMR surveillance system (WHONET-Greece) allows continuous monitoring at national level of bacterial antibiotic resistance in Greek hospitals based on the collection and processing of routine susceptibility data from the Laboratory Information System (LIS) of hospital laboratories using the WHONET software [3]. The data are publicly available (www.mednet.gr/whonet) and have been continuously submitted to the European Antimicrobial Resistance Surveillance System (EARSS) and subsequently to the European Antimicrobial Resistance Surveillance Network (EARS-net) (https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-andlaboratory-networks/ears-net) as the annual Greek AMR data.

In the present collaboration, we sought to describe the trends of the relative isolation frequency (RIF) and the AMR rates among key bloodstream pathogens and their evolution over time for the period 2010–2017 as captured by the national continuous monitoring system of routine laboratory data in order to provide information for action to both clinicians and public health authorities in Greece.

Methods

Study period and setting

The study covered the 8-year period from January 2010 to December 2017. Twenty-five tertiary Greek hospitals, participating in the WHONET-Greece network and consistently reporting data for the entire period (a maximum of two non-consecutive semesters of non-reporting were missing in three hospitals), contributed to the study. The participating hospitals were distributed across the country and represented all four first-level nomenclature of territorial units for statistics (NUTS-1) regions of Greece. Moreover, the participating hospitals’ bed capacity ranged from 178 to 908 beds and thus small (< 200 beds), medium (200–500 beds) and large (> 500 beds) public hospitals were represented (Figure 1).

Figure 1.

Number of hospitals participating in the study and total bed capacity per first-level nomenclature of territorial units for statistics regions of Greece, WHONET-Greece AMR network, January 2010–December 2017 (n = 25 hospitals)

AMR: antimicrobial resistance; EL: Greece; NUTS1_Greece: first level of the Nomenclature of Territorial Units for Statistics for Greece; WHONET-Greece: Greek electronic surveillance system for monitoring AMR in hospitals based on routine data.

Figure 1

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The antimicrobial susceptibility testing (AST) was performed in the hospitals’ clinical laboratories by automated systems. All participating hospital laboratories performed internal quality controls, and they took part in the annual external quality assessment provided by the United Kingdom National External Quality Assessment Service (UK-NEQAS), offered by the European Centre for Disease Prevention and Control (ECDC).

Isolate collection and relative isolation frequency

During the 8-year period, routine susceptibility data of 50,488 key Gram-negative and Gram-positive bacterial isolates from blood cultures of hospitalised patients in the participating tertiary hospitals, representing the nine most clinically important species, were gathered and studied (Table 1). From each patient, only the first isolate per species was included. The RIF of each one of the studied bacterial species was defined as its proportion among the nine bacterial species included in the study, calculated per year and ward type.

Table 1. Number of bloodstream bacterial isolates per year and species, from patients hospitalised in wards and ICUs of the 25 hospitals participating in the WHONET-Greece AMR network, 2010–2017 (n = 50,488 isolates).

Microorganism Year of isolation Total %
2010 2011 2012 2013 2014 2015 2016 2017
Number of bacteria isolated in wards
Escherichia coli 1,048 1,044 1,074 1,121 1,124 1,157 1,337 1,213 9,118 26.2
Klebsiella pneumoniae 774 708 672 728 713 756 754 772 5,877 16.9
Staphylococcus aureus 583 598 631 621 533 590 659 633 4,848 13.9
Pseudomonas aeruginosa 417 431 429 483 390 424 459 454 3,487 10.0
Acinetobacter baumannii 317 346 390 348 384 456 416 471 3,128 9.0
Enterococcus faecalis 368 365 414 379 363 377 414 430 3,110 8.9
Enterococcus faecium 248 229 236 245 222 233 275 288 1,976 5.7
Proteus mirabilis 157 181 201 188 203 237 249 206 1,622 4.7
Enterobacter spp. 224 206 202 206 184 198 190 194 1,604 4.6
Total in wards 4,136 4,108 4,249 4,319 4,116 4,428 4,753 4,661 34,770 100.0
Number of bacteria isolated in ICUs
Acinetobacter baumannii 652 685 600 499 516 509 503 440 4,404 28.0
Klebsiella pneumoniae 625 686 574 500 461 417 466 424 4,153 26.4
Pseudomonas aeruginosa 457 361 353 415 329 246 278 239 2,678 17.0
Enterococcus faecalis 188 217 196 158 142 148 197 149 1,395 8.9
Enterococcus faecium 130 114 111 99 88 95 110 96 843 5.4
Staphylococcus aureus 101 106 100 78 81 60 65 75 666 4.2
Proteus mirabilis 107 115 103 54 60 75 69 72 655 4.2
Enterobacter spp. 78 110 71 50 45 57 46 44 501 3.2
Escherichia coli 54 57 43 60 50 42 60 57 423 2.7
Total in ICUs 2,392 2,451 2,151 1,913 1,772 1,649 1,794 1,596 15,718 100.0
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AMR: antimicrobial resistance; ICUs: intensive care units; WHONET-Greece: Greek electronic surveillance system for monitoring AMR in hospitals based on routine data.

Classification of isolates in terms of antimicrobial susceptibility

The classification of isolates as susceptible, intermediate or resistant (including, for enterococci with acquired aminoglycoside resistance, high-level resistance (HLR) to aminoglycosides) was based on the Clinical and Laboratory Standards Institute (CLSI) (https://clsi.org) clinical breakpoints, a system which was used in Greece for routine AST interpretation during the study period. The version of WHONET software we used for the analysis was equipped with CLSI 2017–2018 breakpoints. The isolates with intermediate susceptibility were grouped with the resistant ones, forming the non-susceptible group.

Data analysis

We focused on annual trends of both RIF for the bacteria included in the study and antimicrobial non-susceptibility rates for the key antimicrobial classes traditionally used for the treatment of Gram-negative and Gram-positive bacteraemia, as well as for the presence of multidrug resistance according to the interim standard definitions for acquired resistance [4]. The data from intensive care units (ICUs) were analysed separately from medical and surgical wards. To assess trends in proportions of non-susceptible isolates over time, we used the Cochran–Armitage χ2 test for trend. A p value of ≤ 0.05 was considered significant. Statistical analysis was performed using R version 3.4.3 for Windows.

Ethical statement

For this observational study, since the confidentiality of the data was ensured by pseudo-anonymisation with unique codes for each included bacterial isolate, and data will not be identifiable back to the patient from whom they originated, an ethical approval was not needed.

Results

Relative isolation frequency and trend analysis over time

Concerning the RIF of the nine main pathogens among the bloodstream isolates from patients hospitalised in the wards (Figure 2a), Escherichia coli was the most prevalent in each year of the study period with an annual RIF ranging from 25.3% to 28.1% (median: 26.0%). This was followed by Klebsiella pneumoniae (range: 15.8–18.7%; median: 17.0%), Staphylococcus aureus (range: 12.9–14.9%; median: 14.0%), Pseudomonas aeruginosa (range: 9.5–11.2%; median: 9.9%), Enterococcus faecalis (range: 8.5–9.7%; median: 8.9%), Acinetobacter baumannii (range: 7.7–10.3%; median: 9.0%), Enterococcus faecium (range: 5.3–6.2%; median: 5.6%), Enterobacter spp. (range: 4.0–5.4%; median: 4.6%) and Proteus mirabilis (range: 3.8–5.4%; median: 4.6%).

Figure 2.

Relative isolation frequency trend analysis of nine key bloodstream pathogens from patients hospitalised in (a) the wards (n = 34,770) and (b) the ICUs (n = 15,718) of the 25 hospitals participating in the WHONET-Greece AMR network, 2010–2017

AMR: antimicrobial resistance; ICU: intensive care unit; WHONET-Greece: Greek electronic surveillance system for monitoring AMR in hospitals based on routine data.

‘↑’ and ‘↓’ indicate significant increasing and decreasing trends, respectively.

Figure 2

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Among the studied isolates from patients hospitalised in ICUs (Figure 2b), A. baumannii was the most prevalent bloodstream isolate in each year of the study period with an annual RIF ranging from 26.1% to 30.9% (median: 27.9%) followed by K. pneumoniae (range: 25.3–28.0%; median: 26.1%), P. aeruginosa (range: 14.7–21.7%; median: 16.0%), E. faecalis (range: 7.9–11.0%; median: 8.9%), E. faecium (range: 4.7–6.1%; median: 5.3%), S. aureus (range: 3.6–4.7%; median: 4.3%), P. mirabilis (range: 2.8–4.8%; median: 4.5%), Enterobacter spp. (range: 2.5–4.5%; median: 3.0%) and E. coli (range: 2.0–3.6%; median: 2.7%).

Overall (Figure 2, 2a,b), we observed a significant increasing trend in the RIF of E. coli (p ≤ 0.001), P. mirabilis (p = 0.004) and A. baumannii (p ≤ 0.001) from patients hospitalised in the wards while their RIF remained stable over the years in ICUs. In contrast, a significant decreasing trend was observed in the RIF of K. pneumoniae from ICUs (p = 0.028) and Enterobacter spp. (p = 0.002) from patients hospitalised in both wards and ICUs. As for P. aeruginosa, no trend was observed in its RIF irrespective of the hospitalisation unit. Concerning Gram-positive bloodstream pathogens, the RIFs of S. aureus, E. faecalis and E. faecium were stable without any trend over time in both the wards and ICUs.

Trends in antimicrobial resistance rates over time

All significant trends in AMR rates over time per microorganism and hospitalisation unit are shown in Table 2 and more specifically described below.

Table 2. Significant trends in antimicrobial resistance rates over time per microorganism and hospitalisation unit (wards or ICU), WHONET-Greece AMR network, 2010–2017 (n = 48,211).

Antibiotic Year of isolation p value Trend
2010 2011 2012 2013 2014 2015 2016 2017
NS/tested %NS NS/tested %NS NS/tested %NS NS/tested %NS NS/tested %NS NS/tested %NS NS/tested %NS NS/tested %NS
Escherichia coli
Ceftazidime non-susceptible
Wards 117/1,032 11.3 126/1,034 12.2 136/1,047 13.0 152/1,097 13.9 166/1,092 15.2 156/1,119 13.9 179/1,318 13.6 176/1,198 14.7 0.012 ↑
Meropenem non-susceptible
Wards 2/897 0.2 5/882 0.6 9/871 1.0 10/882 1.1 10/867 1.2 9/944 1.0 12/1,046 1.1 19/939 2.0 < 0.001 ↑
Ciprofloxacin non-susceptible
Wards 265/1,037 25.6 282/1,034 27.3 311/1,045 29.8 358/1,097 32.6 369/1,095 33.7 325/1,115 29.1 433/1,331 32.5 386/1,198 32.2 < 0.001 ↑
Trimethoprim/sulfamethoxazole non-susceptible
Wards 376/1,026 36.6 365/918 39.8 362/930 38.9 413/1,034 39.9 385/1,051 36.6 335/1,059 31.6 430/1,251 34.4 383/1,154 33.2 < 0.001 ↓
Enterobacter spp.
Ceftazidime non-susceptible
Wards 98/222 44.1 66/202 32.7 69/193 35.8 61/202 30.2 67/181 37.0 65/197 33.0 42/185 22.7 61/191 31.9 0.001 ↓
Imipenem non-susceptible
Wards 34/219 15.5 22/200 11.0 35/194 18.0 31/200 15.5 32/177 18.1 36/195 18.5 32/185 17.3 39/191 20.4 0.044 ↑
Meropenem non-susceptible
Wards 17/196 8.7 15/181 8.3 14/165 8.5 21/176 11.9 13/126 10.3 24/156 15.4 16/154 10.4 22/166 13.3 0.042 ↑
Ciprofloxacin non-susceptible
Wards 44/222 19.8 22/201 10.9 25/194 12.9 24/201 11.9 22/179 12.3 29/196 14.8 16/187 8.6 21/189 11.1 0.023 ↓
Tobramycin non-susceptible
Wards 70/214 32.7 33/199 16.6 38/184 20.7 31/188 16.5 36/170 21.2 38/165 23.0 26/165 15.8 22/150 14.7 0.001 ↓
Multiresistance
Wards 34/205 16.6 16/197 8.1 18/182 9.9 16/181 8.8 16/167 9.6 20/162 12.3 10/161 6.2 12/145 8.3 0.034 ↓
Klebsiella pneumoniae
Ceftazidime non-susceptible
Wards 470/761 61.8 434/698 62.2 366/635 57.6 396/689 57.5 391/682 57.3 416/726 57.3 421/743 56.7 445/761 58.5 0.027 ↓
ICU 567/612 92.6 589/652 90.3 504/556 90.6 397/455 87.3 387/442 87.6 349/403 86.6 396/453 87.4 364/411 88.6 0.001 ↓
Imipenem non-susceptible
Wards 380/761 49.9 347/696 49.9 294/630 46.7 320/685 46.7 320/681 47.0 346/726 47.7 375/743 50.5 399/761 52.4 0.021 ↑a
ICU 536/608 88.2 567/653 86.8 461/552 83.5 366/454 80.6 369/439 84.1 341/404 84.4 399/453 88.1 351/409 85.8 <0.001 ↓b
Meropenem non-susceptible
Wards 305/678 45.0 321/638 50.3 281/606 46.4 298/598 49.8 302/602 50.2 322/636 50.6 342/630 54.3 379/689 55.0 < 0.001 ↑
ICU 472/584 80.8 507/618 82.0 432/538 80.3 349/432 80.8 333/403 82.6 327/377 86.7 385/432 89.1 358/412 86.9 < 0.001 ↑
Ciprofloxacin non-susceptible
ICU 555/612 90.7 584/653 89.4 497/556 89.4 384/455 84.4 381/442 86.2 342/403 84.9 392/454 86.3 361/412 87.6 0.005 ↓
Gentamicin non-susceptible
Wards 133/763 17.4 108/697 15.5 108/635 17.0 140/685 20.4 148/683 21.7 142/726 19.6 202/743 27.2 225/763 29.5 < 0.001 ↑
ICU 166/611 27.2 188/651 28.9 234/557 42.0 201/456 44.1 171/437 39.1 180/405 44.4 223/455 49.0 206/413 49.9 < 0.001 ↑
Tobramycin non-susceptible
Wards 458/744 61.6 427/682 62.6 304/537 56.6 335/587 57.1 354/640 55.3 293/564 52.0 319/610 52.3 313/589 53.1 < 0.001 ↓
ICU 509/570 89.3 556/634 87.7 420/472 89.0 309/370 83.5 327/408 80.1 248/288 86.1 268/327 82.0 211/256 82.4 < 0.001 ↓
Cefoxitin non-susceptible
ICU 481/529 90.9 488/551 88.6 367/483 76.0 276/364 75.8 271/364 74.5 266/360 73.9 309/425 72.7 313/395 79.2 < 0.001 ↓
Multiresistance
Wards 391/738 53.0 372/680 54.7 272/536 50.7 282/587 48.0 308/639 48.2 252/564 44.7 268/610 43.9 271/588 46.1 < 0.001 ↓
ICU 498/569 87.5 540/628 86.0 405/471 86.0 296/369 80.2 318/406 78.3 234/288 81.3 254/325 78.2 208/256 81.3 < 0.001 ↓
Pseudomonas aeruginosa
Piperacillin/tazobactam non-susceptible
ICU 179/435 41.1 88/283 31.1 62/197 31.5 73/339 21.5 98/304 32.2 54/209 25.8 65/256 25.4 47/221 21.3 < 0.001 ↓
Ceftazidime non-susceptible
ICU 226/433 52.2 173/353 49.0 182/346 52.6 201/389 51.7 153/313 48.9 102/237 43.0 118/274 43.1 97/237 40.9 < 0.001 ↓
Imipenem non-susceptible
Wards 222/404 55.0 240/425 56.5 258/410 62.9 319/455 70.1 258/377 68.4 282/409 68.9 297/446 66.6 283/448 63.2 < 0.001 ↑b
ICU 315/431 73.1 252/354 71.2 255/346 73.7 290/389 74.6 250/313 79.9 192/237 81.0 214/273 78.4 179/235 76.2 0.005 ↑
Meropenem non-susceptible
Wards 157/406 38.7 162/414 39.1 167/398 42.0 208/432 48.1 117/348 33.6 162/393 41.2 160/425 37.6 168/423 39.7 0.004 ↑b
ICU 264/435 60.7 206/325 63.4 203/335 60.6 244/385 63.4 177/301 58.8 118/228 51.8 122/254 48.0 116/230 50.4 < 0.001 ↓
Ciprofloxacin non-susceptible
ICU 244/435 56.1 174/352 49.4 185/346 53.5 205/391 52.4 148/315 47.0 106/240 44.2 98/275 35.6 96/238 40.3 < 0.001 ↓
Tobramycin non-susceptible
Wards 123/391 31.5 121/411 29.4 121/354 34.2 141/399 35.3 98/357 27.5 76/286 26.6 101/357 28.3 91/338 26.9 0.039 ↓
ICU 214/395 54.2 165/340 48.5 144/289 49.8 169/331 51.1 125/276 45.3 60/159 37.7 68/205 33.2 60/163 36.8 < 0.001 ↓
Gentamicin non-susceptible
Wards 138/414 33.3 141/426 33.1 154/414 37.2 163/457 35.7 101/374 27.0 106/409 25.9 137/451 30.4 123/449 27.4 < 0.001 ↓
ICU 239/433 55.2 185/353 52.4 170/345 49.3 170/390 43.6 126/305 41.3 87/240 36.3 94/276 34.1 79/237 33.3 < 0.001 ↓
Amikacin non-susceptible
ICU 201/434 46.3 147/353 41.6 147/347 42.4 183/383 47.8 130/309 42.1 90/237 38.0 91/274 33.2 81/235 34.5 < 0.001 ↓
Multiresistance
ICU 156/429 36.4 116/342 33.9 127/337 37.7 155/376 41.2 118/305 38.7 72/235 30.6 74/271 27.3 73/235 31.1 0.018 ↓
Acinetobacter baumannii
Cefepime non-susceptible
Wards 265/299 88.6 285/335 85.1 324/369 87.8 282/316 89.2 323/347 93.1 398/442 90.0 369/401 92.0 444/459 96.7 < 0.001 ↑
ICU 607/629 96.5 562/619 90.8 526/570 92.3 460/474 97.0 491/495 99.2 485/495 98.0 481/491 98.0 425/434 97.9 < 0.001 ↑
Imipenem non-susceptible
Wards 243/303 80.2 290/337 86.1 322/363 88.7 281/319 88.1 300/331 90.6 369/415 88.9 351/389 90.2 416/445 93.5 < 0.001 ↑
ICU 555/576 96.4 610/637 95.8 552/567 97.4 449/460 97.6 483/486 99.4 472/482 97.9 470/475 98.9 419/426 98.4 < 0.001 ↑
Meropenem non-susceptible
Wards 244/306 79.7 282/324 87.0 321/362 88.7 259/300 86.3 290/319 90.9 358/404 88.6 346/380 91.1 423/448 94.4 < 0.001 ↑
ICU 605/635 95.3 552/576 95.8 528/546 96.7 420/437 96.1 422/428 98.6 405/418 96.9 441/447 98.7 419/427 98.1 < 0.001 ↑
Tobramycin non-susceptible
Wards 132/284 46.5 149/330 45.2 204/325 62.8 179/270 66.3 204/322 63.4 232/316 73.4 189/276 68.5 231/271 85.2 < 0.001 ↑
ICU 339/562 60.3 412/632 65.2 341/491 69.5 311/411 75.7 352/443 79.5 317/371 85.4 290/346 83.8 227/252 90.1 < 0.001 ↑
Amikacin non-susceptible
Wards 208/291 71.5 218/301 72.4 248/344 72.1 231/304 76.0 244/316 77.2 295/390 75.6 276/343 80.5 338/408 82.8 < 0.001 ↑
ICU 484/594 81.5 451/598 75.4 405/536 75.6 379/431 87.9 396/445 89.0 388/430 90.2 370/394 93.9 299/332 90.1 < 0.001 ↑
Gentamicin non-susceptible
Wards 199/306 65.0 261/337 77.4 303/371 81.7 267/328 81.4 270/335 80.6 340/421 80.8 330/393 84.0 395/448 88.2 < 0.001 ↑
ICU 474/610 77.7 548/658 83.3 512/585 87.5 427/466 91.6 457/491 93.1 462/488 94.7 447/480 93.1 399/426 93.7 < 0.001 ↑
Ciprofloxacin non-susceptible
Wards 264/298 88.6 308/336 91.7 338/370 91.4 298/326 91.4 315/338 93.2 381/421 90.5 360/394 91.4 426/445 95.7 0.009 ↑
Multiresistance
Wards 206/291 70.8 215/285 75.4 245/329 74.5 226/297 76.1 240/314 76.4 292/388 75.3 273/339 80.5 338/404 83.7 < 0.001 ↑
ICU 482/590 81.7 447/551 81.1 403/502 80.3 372/422 88.2 390/438 89.0 385/429 89.7 366/393 93.1 297/331 89.7 < 0.001 ↑
Staphylococcus aureus
Oxacillin non-susceptiblec
ICU 43/90 47.8 57/104 54.8 58/99 58.6 41/74 55.4 34/74 45.9 27/57 47.4 30/65 46.2 25/75 33.3 0.01 ↓
Ciprofloxacin non-susceptible
Wards 67/268 25.0 77/328 23.5 122/463 26.3 162/513 31.6 118/469 25.2 145/523 27.7 193/595 32.4 189/556 34.0 0.001 ↑
ICU 26/49 53.1 40/74 54.1 48/85 56.5 27/65 41.5 23/67 34.3 21/54 38.9 22/59 37.3 20/70 28.6 < 0.001 ↓
Gentamicin non-susceptible
Wards 52/573 9.1 33/570 5.8 36/623 5.8 38/601 6.3 26/512 5.1 26/575 4.5 33/653 5.1 31/630 4.9 0.003 ↓
ICU 26/98 26.5 28/104 26.9 29/99 29.3 19/72 26.4 6/76 7.9 8/57 14.0 4/65 6.2 5/75 6.7 < 0.001 ↓
Multiresistance
Wards 40/552 7.2 24/569 4.2 27/622 4.3 32/598 5.4 18/502 3.6 21/571 3.7 18/644 2.8 20/630 3.2 < 0.001 ↓
ICU 18/88 20.5 19/104 18.3 25/99 25.3 17/72 23.6 6/74 8.1 6/57 10.5 4/65 6.2 3/75 4.0 < 0.001 ↓
Enterococcus faecalis
Gentamicin HLR
Wards 128/341 37.5 118/342 34.5 100/403 24.8 70/360 19.4 65/326 19.9 48/348 13.8 65/379 17.2 47/417 11.3 < 0.001 ↓
ICU 85/173 49.1 60/190 31.6 52/195 26.7 33/147 22.4 25/125 20.0 16/138 11.6 29/183 15.8 17/143 11.9 < 0.001 ↓b
Streptomycin HLR
Wards 145/325 44.6 118/325 36.3 84/390 21.5 54/323 16.7 51/287 17.8 39/318 12.3 46/342 13.5 35/383 9.1 < 0.001 ↓
ICU 89/171 52.0 65/182 35.7 63/194 32.5 24/136 17.6 14/110 12.7 12/128 9.4 13/157 8.3 10/130 7.7 < 0.001 ↓d
Enterococcus faecium
Gentamicin HLR
Wards 121/240 50.4 94/214 43.9 77/235 32.8 63/236 26.7 41/204 20.1 33/215 15.3 57/255 22.4 43/279 18.9 < 0.001 ↓b
ICU 67/123 54.5 41/107 38.3 27/111 24.3 25/95 26.3 16/77 20.8 8/84 9.5 21/102 20.6 22/92 16.9 < 0.001 ↓b
Streptomycin HLR
Wards 145/226 64.2 113/205 55.1 69/224 30.8 63/220 28.6 43/183 23.5 50/201 24.9 66/238 27.7 54/268 20.1 < 0.001 ↓b
ICU 73/122 59.8 43/103 41.7 36/111 32.4 24/88 27.3 14/69 20.3 12/80 15.0 17/91 18.7 24/81 29.6 < 0.001 ↓b
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AMR: antimicrobial resistance; HLR: high-level resistance; ICU: intensive care unit; NS: non-susceptible; NS/tested: number of non-susceptible isolates for an antibiotic divided by the number of isolates tested for the respective antibiotic; WHONET-Greece: Greek electronic surveillance system for monitoring antimicrobial resistance in hospitals based on routine data.

‘↑’ and ‘↓’ indicate significant increasing and decreasing trends, respectively.

a A significant trend was only observed in the last 4 years of the study (2014–2017).

b A significant trend was only observed in the first 4 years of the study (2010–2013).

c Oxacillin non-susceptibility is used to test for meticillin resistance in S. aureus (MRSA).

d A significant non-linear trend.

Escherichia coli

During the study period, for third-generation cephalosporins, the annual proportions of E. coli isolates non susceptible for ceftazidime from patients hospitalised in wards, significantly increased from 11.3% in 2010 to 14.7% in 2017 (p = 0.012). An apparent increase was also observed for rates of cefotaxime non-susceptible isolates, from 18.9% (190/1,005) in 2010 to 21.2% (215/1,013) in 2017. Meropenem non-susceptible isolates represented 0.2% of isolates in 2010 and their proportion increased significantly over time, reaching 2.0% in 2017 (p < 0.001). Moreover, an increasing trend in rates of isolates non-susceptible to ciprofloxacin was also observed (p < 0.001) starting at 25.6% in 2010 to reach 32.2% in 2017. On the contrary, the proportions of trimethoprim/sulfamethoxazole non-susceptible isolates decreased during the study period (p < 0.001). Regarding non-susceptibility to aminoglycosides, no trend was found for both gentamicin and tobramycin from 2010 to 2017.

Proteus mirabilis

Third-generation cephalosporins non-susceptibility among P. mirabilis isolates from patients hospitalised in the wards was 25.0% (39/156) in 2010, with an apparent increase to 34.4% (67/195) in 2013 and a decrease to 17.6% (36/204) in 2017, while in ICUs the rate of non-susceptible isolates was 52.3% (56/107) in 2010 reaching 65.3% (47/72) in 2017. No trend was observed in ciprofloxacin non-susceptibility, remaining stable at approximately 45% and above 58% in P. mirabilis isolates from patients hospitalised in wards and ICUs respectively. Regarding non-susceptibility to aminoglycosides, the proportions of gentamicin non-susceptible isolates increased from 18.6% (29/156) to 25.1% (51/203) (p = 0.03) and from 30.2% (32/106) to 54.9% (39/71) (p = 0.001) from 2010 to 2017 for patients hospitalised in wards and ICUs, respectively.

Enterobacter spp.

Rates of carbapenem non-susceptibility in Enterobacter spp. isolates from hospital wards showed increasing trends from 15.5% to 20.4% for imipenem and from 8.7% to 13.3% for meropenem in 2010 and 2017 respectively (both p = 0.04). On the contrary, decreasing trends were found for the proportions of isolates non susceptible to ceftazidime (from 44.1% to 31.9%, p = 0.001), tobramycin (from 32.7% to 14.7%, p = 0.001), ciprofloxacin (from 19.8% to 11.1%, p = 0.023) and with multiresistance (from 16.6% to 8.3%, p = 0.034) (Figure 3).

Figure 3.

Significant non-susceptibility trends concerning the main pathogen-antimicrobial combinations for (a) Escherichia coli, (b) Enterobacter spp., (c) Staphylococcus aureus, (d) Enterococcus faecalis and faecium in wards and (e) Staphylococcus aureus in ICUs, for patients hospitalised in the 25 hospitals participating in the WHONET-Greece AMR network, 2010–2017

AMR: antimicrobial resistance; ICU: intensive care unit; NS: non-susceptible; WHONET-Greece: Greek electronic surveillance system for monitoring antimicrobial resistance in hospitals based on routine data.

‘↑’ and ‘↓’ indicate significant increasing and decreasing trends, respectively.

a A significant trend was found only in the first 4 years of the study (2010–2013).

b Oxacillin non-susceptibility is used to test for meticillin resistance in S. aureus (MRSA).

Figure 3

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Klebsiella pneumoniae

Rates of meropenem non-susceptibility increased with proportions of isolates ranging from 45.0% to 55.0% and from 80.8% to 86.9% in patients hospitalised in wards and ICUs respectively from 2010 to 2017 (both p < 0.001). Regarding the percentages of imipenem non-susceptible isolates, we found a significant decreasing trend in ICUs during the first 4 years (from 88.2% to 80.6%, p < 0.001) and an increasing trend during the last four ones in wards (from 47.0% to 52.4%, p = 0.021). High proportions of isolates with ceftazidime non-susceptibility were observed; however, a decreasing trend in both wards (from 61.8% to 58.5%) and ICUs (from 92.6% to 88.6%) (p = 0.027 and p = 0.001, respectively) was found from 2010 to 2017. Non-susceptibility rates to fluoroquinolones did not change significantly over time for K. pneumoniae isolates from patients hospitalised in wards while a significant decrease was observed in isolates from ICU patients (p < 0.005). Regarding aminoglycosides, an increasing trend in rates of gentamicin non-susceptibility was found among isolates from both wards and ICUs (from 17.4% to 29.5% and from 27.2% to 49.9% respectively, both p < 0.001). On the contrary, a decreasing trend in rates of tobramycin non-susceptibility was observed among isolates from both wards and ICUs (both p < 0.001). Finally, multiresistance rates, meaning simultaneous non-susceptibility to ceftazidime, tobramycin and ciprofloxacin, decreased significantly over the studied years, from 53.0% to 46.1% among isolates from wards and from 87.5% to 81.3% among those from ICUs (both p < 0.001) (Figure 4).

Figure 4.

Significant non-susceptibility trends of the three main carbapenem-resistant Gram-negative pathogens from patients hospitalised in the wards and ICUs of the 25 hospitals participating in the WHONET-Greece AMR network, 2010–2017

AMR: antimicrobial resistance; ICU: intensive care unit; NS: non-susceptible; WHONET-Greece: Greek electronic surveillance system for monitoring antimicrobial resistance in hospitals based on routine data.

‘↑’ and ‘↓’ indicate significant increasing and decreasing trends, respectively.

a A significant trend was found only in the first 4 years of the study (2010–2013).

Figure 4

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Pseudomonas aeruginosa

Decreasing trends were found in the proportions of non-susceptible P. aeruginosa isolates to almost all clinical relevant antibiotics with the exception of imipenem. In terms of carbapenems, the percentage of imipenem non-susceptible isolates significantly increased among isolates from patients hospitalised in wards (p < 0.001) and ICUs (p = 0.005), while proportions of non-susceptible meropenem isolates remained stable during the study period or even showed a decreasing trend in ICUs (from 60.7% to 50.4%, p < 0.001). The proportions of isolates with ceftazidime non-susceptibility also presented a decreasing trend in ICUs from 52.2% to 40.9% (p < 0.001).

Finally, the rates of isolates non-susceptible to fluoroquinolones and aminoglycosides were found to significantly decrease during the study period (both p < 0.001) (Figure 4).

Acinetobacter baumannii

From 2010 to 2017, the proportion of non-susceptible isolates to cefepime, imipenem, meropenem, aminoglycosides, as well as those with multiresistance increased significantly (all p < 0.001) in both wards and ICUs of the participating hospitals. Of note, the proportion of carbapenem resistant isolates was consistently very high in both wards and ICUs during the whole study period, ranging for meropenem from 79.7% and 95.3% in 2010 to 94.4% and 98.1% in 2017 in wards and ICUs respectively (Figure 4).

Staphylococcus aureus

A significant decreasing trend was observed in the proportion of meticillin-resistant S. aureus (MRSA) from ICU patients, ranging from 47.8% in 2010 to 33.3% in 2017 (p = 0.01) as well as for ciprofloxacin, ranging from 53.1% in 2010 to 28.6% in 2017 (p < 0.001) (Figure 3e). In contrast, an increasing trend was found for the rates of non-susceptibility to ciprofloxacin in S. aureus isolates from patients hospitalised in wards, ranging from 25.0% in 2010 to 34.0% in 2017 (p = 0.001). Finally, the proportions of isolates with non-susceptibility to gentamicin as well as with a combined non-susceptibility to meticillin and gentamicin were significantly decreased in both wards and ICUs (all p < 0.004), (Figure 3c,e).

Enterococcus faecalis and Enterococcus faecium

Regarding rates of isolates with HLR to gentamicin and streptomycin, decreasing trends were observed among both E. faecalis and E. faecium isolates (Figure 3d). The proportions of isolates non-susceptible to vancomycin among E. faecalis bloodstream isolates from patients in ICUs decreased from 7.3% (13/179) to 1.4% (2/148) from 2010 to 2017. The rates of isolates non-susceptible to vancomycin from 2010 to 2017 among E. faecium isolates was found at similar levels in wards (21.6% (53/245) to 28.4% (76/268)) and ICUs (22.7% (29/128) to 28.4% (31/109)), however, no linear increasing trend was found in either hospital departments.

Discussion

We analysed the RIF and the routine susceptibility data for 50,488 key bloodstream isolates recovered from patients hospitalised in wards and ICUs of 25 hospitals participating in the WHONET-Greece AMR surveillance network during an 8-year period and report several major findings regarding the observed trends over time.

E. coli was the most common cause of bloodstream infection (BSI) in patients hospitalised in wards. The high proportion of isolates with non-susceptibility to third-generation cephalosporins with an increasing trend over the years, coupled with similar trends for proportions of isolates with non-susceptibility to fluoroquinolones is a serious concern since prompt administration of an effective empirical antimicrobial treatment is essential at both patient and public health level. Moreover, over the years, an increasing trend was observed for the proportion of ward-patient E. coli isolates, which were non-susceptible to carbapenems. According to the results of the European Survey on Carbapenemase-Producing Enterobacteriaceae (EuSCAPE) published in 2017 [5] carbapenemase-producing E. coli are becoming more widespread in Europe, thus requiring close surveillance. Acquisition of carbapenemase genes by E. coli [5-12] is concerning, since E. coli spreads in the community more readily than K. pneumoniae. Moreover E. coli from the digestive tract of asymptomatic carriers are common vectors of promiscuous plasmids, which could also accelerate spread of resistance [5].

The observed significant increasing trend of non-susceptible ciprofloxacin isolates is possibly consistent with further dissemination of sequence type (ST)131 strains which Mavroidi et al. found [13] responsible for the increasing fluoroquinolone resistance during 2011 in Central Greece. E. coli ST131 is associated with human urinary tract infections and BSIs and was first described in 2008 as a major clone linked to the spread of extended-spectrum beta-lactamase CTX-M-15. It has since disseminated worldwide and strains resistant to fluoroquinolones, aminoglycosides, trimethoprim-sulfamethoxazole and carbapenems have been reported, limiting treatment options for this pathogen [13,14].

Regarding K. pneumoniae, the major finding was the increasing trend in the proportion of isolates with meropenem non-susceptibility, not only in the ICUs but also in wards of the participating hospitals. This finding may reflect the evolving molecular epidemiology of carbapenemase-producing K. pneumoniae. It is well documented that Greece has been facing high rates of carbapenem resistance among clinical K. pneumoniae since 2002. This was initially due to a multiclonal plasmid-mediated epidemic of Verona Integron-encoded Metallo-beta-lactamase (VIM)-producers during the period 2002–2007 [15]. From 2007, the introduction and rapid clonal dissemination of mainly ST258 K. pneumoniae carbapenemase (KPC)-producers occurred [16,17]. KPC has since been the predominant carbapenemase among the hospital K. pneumoniae population. However, starting 2011, K. pneumoniae ST11 producing New Delhi Metallo-beta-lactamase (NDM)-1 emerged in the country and was identified retrospectively as the cause of a prolonged outbreak of healthcare-associated infections in a University hospital at North-Western Greece [18]. Two years later, NDM-1 producers belonging to ST11 were reported in Athens [19]. Of note, soon after the introduction of NDM in the country, the EuSCAPE project conducted between November 2013 and April 2014 in 10 hospitals all over Greece found it to rank as the second most frequent carbapenemase [5]. This was also reported by a subsequent nationwide multicentre study during the period 2014–2016 [20], indicating further dissemination. Moreover, according to a report published in 2015 [21], while KPC-2 production provides Enterobacteriaceae with intermediate resistance or even decreased susceptibility to meropenem in many cases, NDM-1 production allows HLR to meropenem. Regarding Oxacillinase (OXA)-48-carbapenemase, in 2012 an outbreak of OXA-48 carbapenemase-producing K. pneumoniae ST11 was recorded for the first time in the country [22]. Nevertheless, no major epidemics of OXA-48 producing K. pneumoniae were recorded since their introduction in Greece and OXA-48 remained rare during the period 2014–2016 [20]. The ongoing carbapenem and/or colistin-resistant Enterobacteriaceae (CCRE) project as part of the European Antimicrobial Resistance Genes Surveillance Network (EURGen-Net) will provide updated and more detailed information on the distribution of carbapenemase-producing K. pneumoniae in Greece as well as in Europe.

The observed increasing trend in the proportion of K. pneumoniae isolates non susceptible to gentamicin over the study period in both wards and ICUs, reaching respectively up to 30% and 50%, is of concern, since gentamicin was found to be the most active in vitro aminoglycoside in clinical use, among the four available (amikacin, gentamicin, tobramycin and netilmicin) in a nationwide multicentre study between 2014 and 2016 of 300 carbapenem-resistant K. pneumoniae isolates from Greek hospitals [23].

For P. aeruginosa, the decreasing trends in rates of isolates with non-susceptibility for all of the studied antibiotics except imipenem, for which an increasing non-susceptibility trend was found, could reflect the decrease in isolation of VIM-producing P. aeruginosa, in the last 20 years [24,25] and the increasing role of non-enzymatic mechanisms of carbapenem resistance among this bacterial population. Specifically, the inactivation, downregulation, or even loss of OprD porin is well documented to confer resistance only to imipenem [26,27]. The possible relative decreasing proportion of VIM producers among the P. aeruginosa carbapenem-resistant population could affect also other antibiotic classes like aminoglycosides and fluoroquinolones since VIM producers commonly exhibit multidrug resistant phenotypes and thus could explain the overall decreasing trend we found for aminoglycosides and quinolones.

With respect to A. baumannii, the observed significant increasing trend in its RIF in the wards and its predominance in the ICUs of the participating hospitals, coupled with increasing trends in the proportion of isolates non-susceptible to almost all antimicrobials and especially to carbapenems is of outstanding importance. However, more concerning are reports of colistin-resistant/carbapenem-resistant A. baumannii isolates which constitute a great challenge for both clinical practice and public health [28]. Molecular epidemiology studies at the national level have revealed that since 2010, OXA-23 producing A. baumannii appeared and further disseminated in Greece replacing the former endemic OXA-58 producers and displaying higher minimum inhibitory concentrations (MIC)s to carbapenems due to their higher hydrolytic activity [29]. The latter characteristic has been considered as a comparative advantage to survive and predominate in the hospital setting [30]. A nationwide study from 2015 confirmed that carbapenem-resistant A. baumannii isolates in Greek hospitals produce almost exclusively the OXA-23 carbapenemase and they belong mainly to the international clone (IC) 2 and to a lesser extent, IC1 [29].

For S. aureus, the decline during the study period in the percentage of MRSA is in alignment with the situation in a majority of European Union (EU)/European Economic Area (EEA) countries where MRSA percentages seem to be stabilising or even decreasing [31]. The decline has been reported for an even larger time period (2000–2015) from a study of MRSA BSI cases in a big University hospital in Greece, where the authors reported a decreasing trend in the incidence of MRSA BSIs from 1.69 per 10,000 patient days in 2000 to 1.39 per 10,000 patient days in 2015 (p = 0.038) and in prevalence from 64.7% to 36.4% (p = 0.008), respectively. The observed decline in MRSA BSI rates was associated with changes in the population structure of the organism; the pandemic healthcare-acquired (HA)-MRSA clone ST239-III progressively declined, parallel to the increased isolation frequency of two clonal complexes (CCs): HA-MRSA CC5 and CA-MRSA CC80 [32].

Regarding enterococci, Greece is among the European countries with the lowest percentages in both E. faecalis and E. faecium of gentamicin HLR, at least since 2015 (https://atlas.ecdc.europa.eu). Furthermore, the observed significant decreasing trend during our study period is in accordance with that of the EU/EEA between 2014 and 2017 as well as the trend from almost one fourth of the countries that report national AMR data in EARS-net [31]. On the other hand, the observed level of E. faecium non-susceptibility to vancomycin, even without a significant trend over time, is a cause of concern and highlights the need for close monitoring. Contrary to many other bacterium–antimicrobial group combinations under surveillance by EARS-Net, no distinct geographical pattern could be seen for vancomycin-resistant E. faecium, as high resistance levels were reported from countries in southern, eastern and northern Europe [31].

As it is clearly indicated by the aforementioned data, AMR is a dynamic phenomenon with new resistance mechanisms or combination of resistance mechanisms that can emerge or be introduced and be disseminated rapidly in different bacterial species. In this respect, the Greek continuous electronic AMR surveillance system, focusing on the overall epidemiology of susceptible and resistant bacteria and assisted by an early warning system for new or important resistance phenotypes has developed into a successful, cost-effective tool for the surveillance of AMR in the country.

In more details, during the 2000s, in order to trace the emergence and spread of new resistance mechanisms and to further characterise them, each hospital laboratory had to report immediately through the early warning system certain new or important resistant phenotypes to both the Hospital Infection Control Committee and the Greek Centre for Diseases Control and Prevention and also to send the isolates for further testing in the relevant reference laboratories. It was this surveillance process that enabled Greek Public Health authorities to timely identify the emergence of carbapenem resistant Gram-negative pathogens and especially VIM-producing P. aeruginosa [25], VIM- [33] and KPC-producing K. pneumoniae [16,17] in the hospital setting. During the 2010s, through the National Action Plan for the prevention and control of nosocomial infections caused by carbapenem resistant Gram-negative pathogens in healthcare settings (the PROKROUSTIS project) and subsequently the relevant national legislation for the surveillance of healthcare-associated infections, protocols for sending important isolates to the national surveillance centres for confirmation and characterisation have been implemented. This process enabled us to timely identify the new entry of NDM and OXA-48 carbapenemases in the country [18,19,22] as well as OXA-23 in A. baumannii [28-30]. Overall, since 1995, WHONET-Greece has been providing valuable background information on the evolution of the complex epidemiology of AMR to be used in developing the strategy to combat this problem at the hospital, regional and national level.

This study has some limitations. The first may result from the potential impact of biases in sampling practices of routine clinical diagnostic data, since, in general, routine clinical data would often overestimate resistance because of the tendency to culture specimens from patients with treatment failures and/or complicated medical histories. This problem could be further enhanced by selective culturing and antimicrobial susceptibility testing due to the ongoing financial crisis in Greece. However, the biases are consistent from year to year. Moreover, the level of financial crisis, in terms of hospital budget cuts, is not as extensive as to affect critical diagnostic procedures, such as blood culturing (data not shown). Therefore one may still identify important temporal trends using routine AMR data from bacteraemias. Another possible limitation is that, while colistin has been increasingly used since 2010 in Greece as a fundamental companion drug for the treatment of the carbapenem-resistant Enterobacteriaceae P. aeruginosa and A. baumannii, we could neither study colistin non-susceptibility prevalence nor its evolution over time in the period 2010–2017. This was mainly due to technical challenges of testing colistin susceptibility with the gradient tests or semiautomatic instruments used in the hospitals’ laboratories during the study. However, based on the recently issued recommendations from CLSI and the European Committee on Antimicrobial Susceptibility Testing (EUCAST) [34], the Greek National Antibiogram Committee (NAC) now advises hospitals to use broth microdilution as the gold-standard method for colistin MIC determination, and the increasing compliance of hospital laboratories will likely enable the WHONET-Greece system to study colistin non-susceptibility trends prospectively in the forthcoming years. A third limitation is that we could not take some important data under consideration in our analysis, such as dates of hospital admission and/or discharge, details on the treatment received by patients as well as clinical outcomes. Indeed, at present, Greek hospital clinical laboratories do not have direct access to patients’ data even if basic patient demographic data are available. This limitation could be solved by linking routine microbiology data with other existing relevant datasets in the hospital, as part of the overall national strategy to upgrade health information systems.

To achieve this, as well as a comprehensive AMR surveillance system in the country, the WHONET software could be used as the basic tool for all microbiology laboratories to input their data. As all laboratories enter or transfer their reports into WHONET, the resulting files will be inter-compatible and will enable compiling to inform both national and international multicentre surveillance networks [35] without any additional microbiology staff’s dedicated time.

Monitoring AMR trends is an indiscernible means of assessing and possibly modifying the implemented national initiatives and interventions according to the recent national legislation. Moreover, timely and targeted dissemination of national surveillance data to all major stakeholders at European level should become an essential component of efforts to control the threat of AMR in European Union and European Economic Area countries and reduce its burden. In this context, we have found the use of routine hospital laboratory data from the Greek continuous electronic AMR surveillance system, to be important not only at hospital and national level but European level as well.

Acknowledgements

The authors acknowledge the work performed by the staff of the participating clinical microbiology laboratories.

WHONET-Greece study group affiliations of authors

“Agios Pavlos” General Hospital, Thessaloniki, A Koteli, P Fitas; “Asclepeion Voulas” General Hospital, Attiki, M Economou, C Konsolakis; “Evangelismos” General Hospital, Athens, Κ Fountoulis, E Perivolioti; “G Gennimatas” General Hospital, Athens, H Vagiakou, G Ganteris; “G. Papanikolaou” General Hospital, Thessaloniki, E Tsorlini; “Ippokrateio” General Hospital of Thessaloniki, Thessaloniki, E Vagdatli, A Karantani; “KAT” General Hospital, Athens, S Tsiplakou, V Papaioannou; “Laikon” General Hospital, Athens, G Maropoulos, I Deliolanis; “P & A Kyriakou” Children's Hospital, Athens, E Lebessi, A Doudoulakakis; “Red Cross” General Hospital, Athens, V Baka, A Platania; “Saint Savas” Anticancer Hospital, Athens, E Chinou; “Sismanoglion” General Hospital, Athens, M Martsoukou, K Velentza; “Sotiria” General Hospital of Chest Diseases, Athens, S Karabela, ES Moraitou; “ Theageneio” Anticancer Hospital, Thessaloniki, P Kazila; “Tzaneio” General Hospital, Piraeus, K Digalaki, O Zarkotou; General Hospital of Chania, Crete (Hania), M Papadogianni, K Zervaki; General Hospital of Kavala “Agios Silas”, Kavala, I Karatzoglou; General Hospital of N Ionia “Konstantopouleio-Patision”, Athens, E Platsouka, Z Roussou; General Hospital of Serres, Serres, F Markou; General Hospital of Veria, Veria, V Thomoglou; General Hospital of Xanthi, Xanthi, G Stamatopoulou; Naval and Veterans Hospital of Athens, Athens, E Mournianakis, I Theodorakos; University Hospital “AHEPA”, Thessaloniki, L Skoura, E Protonotariou; University Hospital of Alexandroupolis, Alexandroupoli, M Panopoulou, A Koutsidou; University Hospital of Larissa, Larissa, E Petinaki, A Vasdeki.

Conflict of interest: None declared.

Authors’ contributions: M. Polemis & K. Tryfinopoulou contributed equally in this paper.

MP managed the database, performed all data analyses and reviewed the manuscript.

KT contributed in the interpretation of the data, wrote the manuscript’s first draft and revisions.

PG reviewed the manuscript.

AV designed and coordinated the analysis, and reviewed the manuscript.

The WHONET-Greece study group provided routine susceptibility data.

All authors discussed the results and approved the final manuscript.

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