1. bookVolume 71 (2022): Issue 2 (June 2022)
Polish Journal of Microbiology's Cover Image
Polish Journal of Microbiology
Journal Details
License
Format
Journal
eISSN
2544-4646
First Published
04 Mar 1952
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4 times per year
Languages
English
Open Access

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

Aneta Guzek,
Aneta Guzek,
Zbigniew Rybicki,
Zbigniew Rybicki,
Agnieszka Woźniak-kosek and
Agnieszka Woźniak-kosek and
Dariusz Tomaszewski
Dariusz Tomaszewski
Published Online: 19 Jun 2022
Volume & Issue: Volume 71 (2022) - Issue 2 (June 2022)
Page range: 263 - 277
Received: 16 Feb 2022
Accepted: 14 May 2022
Polish Journal of Microbiology's Cover Image
Polish Journal of Microbiology
Journal Details
License
Format
Journal
eISSN
2544-4646
First Published
04 Mar 1952
Publication timeframe
4 times per year
Languages
English
Introduction

Hospital-acquired bloodstream infections (BSI) are a severe care problem worldwide, associated with significant mortality (Massart et al. 2021). According to Watson et al. (2019), hospital-acquired bloodstream infections result in a 1.3- to 4.3-fold increase in the hospitalization duration, 2.8- to 5.3-fold higher hospitalization costs and a 4.3- to 8-fold increase in the percentage of patients who died.

Observations from the last few years have shown an increased incidence of bloodstream infections (Salm et al. 2018; Tajima et al. 2021). Moreover, data from Denmark revealed a considerable increase in bacteremia between 2000 and 2014, although the all-cause 30-day mortality after first-time bacteremia decreased (Holm et al. 2021).

Over 50% of patients admitted to the intensive care unit (ICU) require central vein catheterization (CVC) (Blot et al. 2015). Central lines are necessary for multiple purposes, including drug infusion, blood sample collection, and hemodynamic monitoring. The presence of a catheter inside a central vein is associated with the risk of central line-associated bloodstream infections (CLABSI). In the USA, five million CVCs are inserted each year, leading to approximately 200,000 cases of CLABSI, and the number of deaths attributable to such infections may be as high as 25,000 (Blot et al. 2015). However, these estimates may be understated because some cases of BSI secondary to urinary, respiratory, and gastrointestinal infections may be assigned the International Classification of Disease (ICD) codes for those illnesses (Goto and Al-Hasan 2013).

The objective of this study was to analyze bloodstream infections in patients hospitalized in the intensive care unit of the Military Institute of Medicine between 2009 and 2017 and to determine the changes in the incidence of pathogens and their susceptibility/resistance to antimicrobial agents with particular attention paid to the incidence of CVC infections in the analyzed cohort.
Experimental
Materials and Methods

Study design. It was an observational cohort study. The study protocol was approved by the institutional Bio-ethical Committee (43/WIM/2020 of August 19, 2020).

Setting. Data were collected in the intensive care unit of the Military Institute of Medicine in Warsaw, Poland, between January 1, 2007, and December 31, 2019. The Military Institute of Medicine is a 1,000-bed university hospital and a regional trauma center. The number of beds in the ICU varied throughout the study period: from 8 (2007–2013), 14 (2014), to 18 beds (2015–2019).

Participants and the procedures when infection was suspected. We analyzed the data of all critically ill patients hospitalized in our ICU during the study period. No other eligibility criteria were applied.

In our center, the physicians always insert central venous catheters, either specialists or residents. Regardless of who performed the CVC insertion, the procedure was the same and was performed aseptically. Trained nurses provided routine care of inserted catheters and venous line connectors. When the infection was suspected, two blood samples were drawn: one sample of peripheral blood and a second one drawn through the CVC; both were submitted to microbiological testing. When a catheter-related bloodstream infection was suspected, the procedure was like that described above. The blood samples were taken from both the catheter and a peripheral vein. The catheter was removed according to clinical guidelines (O’Grady et al. 2011), and the tip of the catheter was microbiologically analyzed. Blood samples were collected by trained nurses under aseptic conditions, according to standard procedures in all cases. Its tip was cut off and microbiologically analyzed whenever the catheter was removed. Catheters were released by physicians, under aseptic conditions, according to standard procedures.

Microbiological analysis. Blood samples (10 ml) were collected into two BactAlert Bottles (bioMérieux, France): a BactAlert FA Plus Bottle to detect the presence of aerobes and fungi and a BactAlert FN Plus Bottle to check for anaerobes. Both blood samples were placed in a BactAlert 3D automatic analyzer (bioMérieux, France) and incubated at 37°C either until the growth of the pathogens was observed or until the end of the fifth day of incubation.

When pathogen growth was noted, the samples were inoculated on specific growth media: Columbia agar, McConkey agar, chocolate agar, and Sabouraud agar. When the growth of anaerobic pathogens was observed, the samples were inoculated in a Schaedler agar. The pathogens were incubated in the growth media for 24–48 hours at 37°C under aerobic or anaerobic conditions. After the incubation period, the Gram-stained bacteria morphology was analyzed.

When the growth of a mixed bacterial culture was observed, separating procedures were performed to obtain pure colonies, which were further identified, and antibiotic susceptibility of isolates was assayed. The microorganisms were identified by an automatic VITEK® 2 testing system (bioMérieux, France) using VITEK® ID Cards (VITEK® 2 GN ID Card for the identification of fermenting and non-fermenting Gram-negative bacilli, VITEK® 2 GP ID Cards for Gram-positive bacteria, and VITEK® YST ID Cards of yeast and yeast-like organisms, respectively) following the manufacturer’s instructions. The quality of bacterial identification was assessed with the VITEK® 2 Advanced Expert System. The results were defined as acceptable at a confidence level between 96–99% (excellent identification) or 93–95% (very good quality). Antimicrobial susceptibility testing was performed with the VITEK® 2 system according to the manufacturer’s instructions, using the software 9.02 version and the AST-N 332, AST-P644, AST-643, AST-ST03 cards for Gram-negative bacteria, staphylococci, enterococci, and streptococci, respectively. Between 2007 and 2010, the antimicrobial susceptibility of isolated pathogens was classified according to the Clinical and Laboratory Standard Institute (CLSI 2009; 2010a; 2010b), and since 2011 following the regulations of the European Committee on Antimicrobial Susceptibility Testing (EUCAST 2013; 2017) and the National Reference Centre for Susceptibility Testing in Warsaw, Poland. Control susceptibility tests included reference strains of Pseudomonas aeruginosa ATCC 27853, Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 29213, Enterococcus faecalis ATCC 29212, Klebsiella pneumoniae ATCC 700603, Klebsiella pneumoniae ATCC BAA-2814, Staphylococcus aureus NCTC 124943, and Enterococcus faecalis ATCC 51299.

The microbiological investigation of the catheters was performed using both a semiquantitative Maki et al. (1977) and a quantitative Brun-Buisson et al. (1987) techniques. A central venous line may be a source of blood infection when the growth of the same pathogen identified in a catheter-drawn sample is observed two or more hours earlier in a blood sample drawn from a peripheral vein. In a catheter tip culture, more than 15 CFU colonies of the same pathogen were isolated via the semiquantitative analysis (Maki et al. 1977). More than thousand bacterial species were isolated via the quantitative analysis (Brun-Buisson et al. 1987).

Study size. Due to the retrospective nature of this study, its size was not determined before the start of the project.

Statistical methods. Collected data were archived and analyzed using the Microsoft Excel software. Descriptive statistics were used for analysis. All figures were prepared with the DataGraph software.
Results

The study analyzed data collected between 2007 and 2019. General information regarding the number of patients hospitalized in the ICU, the reasons for their hospitalization, the number of microbiological investigations of blood samples, and the results of these examinations are shown in Tables I and II.

Descriptive statistics of the study population and their primary diagnoses according to ICD10.

Year
2007200820092010201120122013201420152016201720182019
Patientsn197182216173224178172186350422422450348
Agemedian53546059494345494343525753
minimum18181821191818151918192124
maximum84868787828782918785878588
Q1-Q342-6929-7442-7144-7537-6528-5928-6737-6227-6329-5740-6738-6937-63
Hospitalization time in ICU (days)median2226163017202314161514148
minimum1111111111111
maximum Q1-Q3136 11–47147 9-48124 7-27137 11–5848 5-27107 11-31106 10-36273 8-39126 8–31275 7-35205 5-36159 5-32238 24
Deathsn (%)71 (36%)62 (34%)68 (31%)57 (33%)83 (37%)60 (34%)56 (33%)64 (34%)135(39%)117(28%)166 (39%)160 (36%)149 (43%)
Main diagnosis according to ICD10
Year
2007200820092010201120122013201420152016201720182019
Other bacterial diseases [A30–A49]144636344811131210
Malignant [C00–C14]neoplasms 2 of lip, oral cavity, and pharynx3534434344354
Malignant neoplasms of digestive organs [C15–C26]30120000001000
Malignant organs [C30neoplasms –C39]4 of respiratory and intrathoracic0010000011000
Malignant and related neoplasms tissue [C81of -lymphoid, C96]5 hematopoietic,4344443478665
Diabetes mellitus [E10-E14]64754532465765
Obesity and other hyperalimentation [E65-E68]0010100022331
Metabolic disorders74230101130342
Inflammatory system [G00–Gdiseases 09]8 of the central nervous3120400022342
Systemic nervous system atrophies [Gprimarily 10–G14]9 affecting the central0010000000000
Episodic and paroxysmal disorders [G40–G47]102320100112122
Diseases [G70–G73of ]myoneural 11 junction and muscle0011000001000
Cerebral [G80–G83palsy ]12 and other paralytic syndromes0200000000000
Other disorders of the nervous system [G90–G99]130000000021000
Ischemic heart diseases [I20–I25]143340322246654
Pulmonary circulation heart [I26–Idisease 28]15 and diseases of pulmonary2120222367886
Other forms of heart disease [I30–I52]1636272513271716172431273428
Cerebrovascular diseases [I60–I69]1768100108881413142216
Diseases of arteries, arterioles, and capillaries [I70–I79]184220000021100
Diseases nodes [I80of –veins, I89]19 lymphatic vessels, and lymph1000000000100
Influenza and pneumonia [J09-J18]201035532256664
Chronic lower respiratory diseases [J40–J47]217791098891619182118
Lung diseases due to external agents [J60–J70]225450221113342
Other the interstitium respiratory [Jdiseases 80–J84)23 principally affecting5156643335543
Suppurative respiratory tract and necrotic [J85–J86conditions ]24 of the lower0100000002010
Other diseases of the respiratory system [J95–J99]2521101944382822192530283727
Diseases [K20–K31of ]esophagus, 26 stomach, and duodenum5442221024560
Hernia [K40–K46]270011200011002
Other diseases of the intestines [K55-K64]280012110023431
Diseases of peritoneum [K65–K67]295810111391191616141610
Diseases of the liver [K70–K77]300010010122330
Disorders [K80–K87of ]31 gallbladder, biliary tract, and pancreas13101013149891197106
Other diseases of the digestive system [K90–K93]320000001100320
Infections [L00–L08]of 33 the skin and subcutaneous tissue0000010000000
Systemic connective tissue disorders [M30 -M32]340000000001000
Osteopathies and chondropathies [M80–M94]350000000000010
Injuries to the head [S00–S09]365579981192723232416
Injuries to the neck [S10–S19]370004023020020
Injuries to the thorax [S20–S29]384332020473842
Injuries and pelvis to the [S30abdomen, –S39]39 lower back, lumbar spine,23344202101723179
Injuries to the shoulder and upper arm [S40–S49]400000010001000
Injuries to the hip and thigh [S70–S79]410000000022002
Injuries to the knee and lower leg [S80–S89]420010000002010
Injuries involving multiple body regions [T00–T07]434445532132414857101142145141134
Burns and corrosions [T20–T32]444969161011111931293526
Poisoning substances by [Tdrugs, 36–T50medicaments, ]45 and biological0211220213210
Other [T66-Tand 78]unspecified 46 effects of external causes0100100011001

Diagnoses were presented in blocks, as on the World Health Organization webpage (https://icd.who.int/browsel0/2019/en)

1 including sepsis due to other specified staphylococci (A41.1); sepsis due to anaerobes (A41.4); sepsis due to other Gram-negative organisms (A41.5); sepsis, unspecified (A41.9)

2 including malignant neoplasm of other and unspecified parts of the tongue (C02); malignant neoplasm of other and ill-defined sites of the lip, oral cavity, and pharynx (C14)

3 including malignant neoplasm of the stomach (C16); malignant neoplasm of the colon (C18)

4 including malignant neoplasm of bronchus and lung (C34)

5 including acute myeloblastic leukemia (C92.0)

6 including diabetes mellitus with coma (E.10.0), ketoacidosis (E10.1), and multiple complications (E10.7)

7 including acidosis (E87.2)

Diagnoses were presented in blocks, as on the World Health Organization webpage (https://icd.who.int/browsel0/2019/en)

8 including bacterial meningitis, not elsewhere classified (GOO); bacterial meningoencephalitis and meningomyelitis, not elsewhere classified (G04.2); encephalitis, myelitis, and encephalomyelitis in diseases classified elsewhere

9 including motor neuron disease (G12.2)

10 including epilepsy (G40); status epilepticus (G41); brain stem stroke syndrome (G46.3); cerebellar stroke syndrome (G46.4)

11 including myasthenia gravis and other myoneural disorders (G70)

12 including cerebral palsy (G80); flaccid tetraplegia (G82.3)

13 including encephalopathy, unspecified (G93.4)

14 including acute myocardial infarction (121)

15 including pulmonary embolism (I26)

16 including cardiac arrest with successful resuscitation (I46.0); other cardiac arrhythmias (I49); heart failure (I50)

17 including subarachnoid hemorrhage (I60); intracerebral hemorrhage (I61); cerebral infarction (I63); stroke (I64)

18 including abdominal aortic aneurysm, ruptured (I71.3)

19 including embolism and thrombosis of vena cava (I82.2)

20 including influenza with pneumonia, seasonal influenza virus identified (J10.0); bacterial pneumonia (J15); pneumonia due to other infectious organisms (J16); pneumonia, organism unspecified (J18)

21 including other chronic obstructive pulmonary disease (J44); status asthmaticus (J46)

Diagnoses were presented in blocks, as on the World Health Organization webpage (https://icd.who.int/browsel0/2019/en)

22 including pneumonitis due to food and vomit (J69.0)

23 including adult respiratory distress syndrome (J80); other interstitial pulmonary diseases (J84)

24 including abscess of the mediastinum (J85.3)

25 including postprocedural respiratory disorders (J95); respiratory failure (J96)

26 including perforation of the esophagus (K22.3); duodenal ulcer, acute with hemorrhage (K26.0), acute with hemorrhage and perforation (K26.2); gastrojejunal ulcer with hemorrhage (K28.0), hemorrhage and perforation (K28.2); acute hemorrhagic gastritis (K29)

27 including ventral hernia (K43)

28 including paralytic ileus and intestinal obstruction without hernia (K56)

29 including peritonitis (K65)

30 including toxic liver disease (K71); hepatic failure (K72)

31 including cholelithiasis (K80); cholecystitis (K81); obstruction of the bile duct (K83.1); acute pancreatitis (K85)

32 including gastrointestinal hemorrhage, unspecified (K92.2)

33 including other local infections of the skin and subcutaneous tissue (L08)

34 including systemic lupus erythematosus (M32)

35 including osteomyelitis (M86)

Diagnoses were presented in blocks, as on the World Health Organization webpage (https://icd.who.int/browsel0/2019/en)

36 including fracture of the skull and facial bones (S02); intracranial injury (S06); other and unspecified injuries of the head (S09)

37 including open wound of the neck (S11); fracture of the neck (S12); injury of nerves and spinal cord at neck level (S14); injury of blood vessels at neck level (S15)

38 including fracture of rib(s), sternum, and thoracic spine (S22); injury of blood vessels of the thorax (S25); injury of other and unspecified intrathoracic organs (S27); crushing injury of the thorax and traumatic amputation of part of thorax (S28)

39 including fracture of lumbar spine and pelvis (S32); injury of blood vessels at abdomen, lower back, and pelvis level (S35); injury of intra-abdominal organs (S36)

40 including traumatic amputation of shoulder and upper arm (S48)

41 including fracture of the femur (S72); crushing injury of hip and thigh (S77)

42 including crushing injury of the lower leg (S87); traumatic amputation of the lower leg (S88)

43 including fractures involving multiple body regions (T02); crushing injuries involving multiple body regions (T04); other injuries involving multiple body regions (T06); multiple unspecified injuries (T07)

44 including burn and corrosion of head and neck (T20); burn and corrosion of trunk (T21); burn and corrosion of respiratory tract (T27); burn and corrosion of other internal organs (T28); burns and corrosions of multiple body regions (T29); burns classified according to the extent of body surface involved (T31)

45 including poisoning by narcotics and psychodysleptics [hallucinogens] (T40)

46 including hypothermia (T68); drowning and nonfatal submersion (T75.1); effect of electric current (T75.8); anaphylactic shock (T78.2)

The number of microbiological analyses, with their results, performed between 2007 and 2019.

2007200820092010201120122013201420152016201720182019
Beds in ICU (n)8888888141818181818
Hospitalizations (n)179182216173224178172186350422422450348
Microbiological analyses (n)2,3612,3492,7102,4543,1232,7962,7972,8114,0935,3765,0305,0895,264
Microbiological of blood samples analyses (n)6706137856411,2451,0169448311,2191,3269881,1611,180
Blood analyses, microbiological negative results (n)5484736325341,1308898096901,0641,1408581,023994
Blood analyses, microbiological positive results (n)1071201359710499106112120154104106145
Blood microbiological analyses, contaminated samples (n)15201810112829293532263241
Microbiological of the tip of the analyses catheter (n)30232818392945537070767765
Microbiological analyses of the tip of the catheter, positive results (n)13111712211131302029312626

Study population and blood samples. Between 2007 and 2019, 3,502 patients were hospitalized in our ICU. Among these, 2,581/3,502 were men (73.7%), and 921/3,502 (26.3%) were women. Among 46,253 microbiological specimens, 12,619 (27.3%) were obtained from blood samples. One thousand five hundred nine samples (12%) were positive, and 1,557 pathogens were isolated. Among these were 770/1,557 (49.5%) Gram-negative bacteria, 733/1,557 (47.1%) Gram-positive bacteria, and 54/1,557 (3.5%) fungal species. A CVC was inserted in 3,460 of the 3,502 (98.8%) patients. The CVC was inserted into a subclavian vein in 2,588/3,460 cases (74.8%), into the internal jugular in 685/3,460 cases (19.8%), and the femoral vein in 187/3,460 cases (5.4%). A CVC was implicated in 278/1,509 (18.4%) of positive blood cultures, and the number of infected central vein catheters was 278/632 (44.6%). The pathogens isolated from positive blood cultures are shown in Table II. Among all Gram-negative bacteria, A. baumannii was isolated quite often, in 312/770 (40.5%) of cases. It represented 312/1,557 (20%) of all isolated pathogens.

Isolated pathogens. Gram-negative bacilli were the most common isolated pathogens in our materials. The most frequently isolated pathogen was A. baumannii, followed by K. pneumoniae, and P. aeruginosa. Among Gram-positive cocci, the most frequent was MRCNS, followed by E. faecalis. A. baumannii was isolated from 312 samples (20% of all isolated pathogens and 40.5% (312/770) of all Gram-negative isolates). P. aeruginosa was obtained from 111 blood samples (7.4% (111/1,509)), representing 7.1% of all isolated bacterial species and 14.4% (111/770) of Gram-negative pathogens. Only in two A. baumannii isolates with the MBL mechanism of antibiotic resistance were found. K. pneumoniae was detected in 165 blood samples (11% (165/1,509)), and represented 10.6% (165/1,557) of all isolated pathogens and 21.4% (165/770) of Gram-negative bacterial isolates. Among all K. pneumoniae strains, the following antibiotic resistance mechanisms were identified: ESBL in 67 (40.6%) isolates, NDM in five, KPC – four, and OXA-48 in one isolate. E. coli was isolated from 69 samples and comprised 4.6% (69/1,509) of all and 9% (69/770) of Gram-negative isolates. Eleven of them (15.9%) exhibited an ESBL mechanism of resistance.

Staphylococci were the most frequent (74.4% (545/ 733)) isolates among the Gram-positive bacteria. The majority (368/545, 67.5%) of all isolated staphylococci were MRCNS. More than 78% (426/545) of staphylococci were resistant to methicillin (86.4% (368/426) of them were MRCNS). Enterococci were isolated from 184/1509 (12.2%) samples; 41/184 (22.3%) strains exhibited a high-level aminoglycoside resistance (HLAR), and 11 (6%) E. faecium species were resistant to vancomycin.

The resistances of isolated pathogens to antimicrobial agents are shown in Tables III and IV. The graphical presentation of these data is shown in Fig. 1, 2, and 3. The above data include the number of Gram-positive (Table III, Fig. 2) and Gram-negative (Table III, Fig. 3) alert pathogens with their resistance mechanisms. All MRSA and MRCNS strains were susceptible to vancomycin during the analyzed period. From 2010, all MRSA strains were susceptible to gentamycin and trimethoprim/sulfamethoxazole. However, MRCNS strains were rather (mean 57%, median 61%) susceptible to sulphonamide and exhibited high resistance (up to 90% in 2019) to gentamycin. MRSA was more susceptible to the other than mentioned above antimicrobials than MRCNS. All MSSA strains were susceptible to isoxazolyl penicillins.

Fig. 1

Trends in pathogens isolated between 2007 and 2019.

Fig. 2

Gram-positive alert pathogens with mechanisms of resistance, isolated between 2009 and 2019.

Fig. 3

Gram-negative alert pathogens with mechanisms of resistance, isolated between 2009 and 2019.

The number of pathogens isolated from blood samples between 2007 and 2019.

Pathogen (mechanism of Pathogen antibiotic resistance)2007200820092010201120112012201320142015201620172018Total
Gram-negative bacilliAcinetobacter baumannii33242219382625291826201814312
Pseudomonas aeruginosa9129127576889611109
Pseudomonas aeruginosa (MBL)00000010010002
Stenotrophomonas maltophila004011224740126
Klebsiella pneumoniae68524249714681388
Klebsiella pneumoniae (ESBL)11833241107745267
Klebsiella pneumoniae (NDM)00000000002125
Klebsiella pneumoniae (KPC)04000000000004
Klebsiella pneumoniae (OXA 48)00000000000011
Escherichia coli1320334649711558
Escherichia coli (ESBL)020000000233111
Enterobacter cloacae101011332557534
Enterobacter cloacae (ESBL)00110001020207
Proteus mirabilis010002221333421
Proteus mirabilis (ESBL)43000000002009
Morganella morgani00000011112028
Serratia marcescens00000011022028
Gram-positive cocciStaphylococcus aureus1513733344491865
Staphylococcus aureus (MRSA)3715354237324058
Coagulase-Staphylococcus negative (CNS)2253226461251454
Coagulase-negative Staphylococcus (MRCNS)31253435223435233828181530368
Enterococcus faecalis581555545616261395
Enterococcus faecalis (HLAR)039030001200220
Enterococcus faecium129512104302737
Enterococcus faecium (VRE)010100110123111
Enterococcus faecium (HLAR)111612111103221
Streptococcus pneumoniae00000000001113
Neisseria meningitidis10000000000001
FungiCandida albicans534524112121334
Candida glabrata01100000001014
Candida krusei00000100000001
Candida tropicalis00000010000001
Candida parapsilosis020002113110314
Total1151251411031041031071121241591071091481,557

Resistance of Gram-negative pathogens to antimicrobial agents.

Antimicrobial agentPseudomonas aeruginosa
2007 n = 92008 n = 122009 n = 92010 n = 122011 n = 72012 n = 52013 n = 72014 n = 62015 n = 82016 n = 82017 n = 92018 n = 62019 n = 11
Ceftazidime2430001002100
Cefepime0300112003100
Piperacillin/tazobactam1150011014100
Gentamycin5451323004000
Ciprofloxacin6350222225320
Imipenem3244212025437
Meropenem3043212014437
Acinetobacter baumannii
2007 n = 332008 n = 242009 n = 222010 n = 192011 n = 382012 n = 262013 n = 252014 n = 292015 n = 182016 n = 262017 n = 202018 n = 182019 n = 14
Gentamycin302271129242225161813158
Ciprofloxacin32242119342523291825201814
Imipenem1161011312321281725191710
Meropenem66811312321281725191710
Trimethoprim-sulfamethoxazole20181619362415271625201710
Ampicillin/sulbactam121281219392016ndndndnd
Colistin––––––––00000
Stenotrophomonas maltophila
2007200820092010201120122013201420152016201720182019
n = 0n = 0n = 4n = 0n = 1n =1 n = 2n = 2n = 4n = 7n = 4n = 0n = 1
Trimethoprim-sulfamethoxazole––0–0000000–0
ESBL-negative Enterobacterales
2007200820092010201120122013201420152016201720182019
n = 8n = 12n = 8n = 2n = 8n =9 n = 15n = 22n = 15n = 34n = 25n = 29n = 31
Ceftazidime0000000000000
Cefepime0000000000000
Ciprofloxacin03301051210645
Gentamycin0200000002025
Piperacillin/tazobactam0010001100148
Trimethoprim-sulfamethoxazole3231116103424
ESBL-positive Enterobacterales
2007200820092010201120122013201420152016201720182019
n = 15n = 13n = 4n = 4n = 2n =4 n = 1n = 11n = 7n = 11n = 9n = 10n = 3
Amoxicillin/clavulanate1293424111689103
Gentamycin10934241877682
Ciprofloxacin131144241117119103
Imipenem4300000000200
Meropenem0000000000000
Trimethoprim-sulfamethoxazole139231319511983
KPC-producing Klebsiella pneumoniae
2007200820092010201120122013201420152016201720182019
n = 0n = 4n = 0n = 0n = 0n =0 n = 0n = 0n = 0n = 0n = 0n = 0n = 0
Amikacin–0–––––––––––
Gentamicin–0–––––––––––
Tigecycline–2–––––––––––
Trimethoprim-sulfamethoxazole–4–––––––––––
Colistin–0–––––––––––
NDM-producing Klebsiella pneumoniae
Antimicrobial agent2007 n = 02008 n = 02009 n = 02010 n = 02011 n = 02012 n = 02013 n = 02014 n = 02015 n = 02016 n = 02017 n = 22018 n = 12019 n = 2
Amikacin––––––––––212
Gentamicin––––––––––111
Tigecycline––––––––––210
Trimethoprim-sulfamethoxazole––––––––––111
Colistin––––––––––000
OXA48-producing Klebsiella pneumoniae
2007 n = 02008 n = 02009 n = 02010 n = 02011 n = 02012 n = 02013 n = 02014 n = 02015 n = 02016 n = 02017 n = 02018 n = 02019 n = 1
Amikacin––––––––––––0
Gentamicin––––––––––––1
Tigecycline––––––––––––1
Trimethoprim-sulfamethoxazole––––––––––––1
Colistin––––––––––––0

Amongst the enterococci, all E. faecalis isolates (21% of isolates with the HLAR mechanism of resistance) were susceptible to ampicillin, E. faecium to vancomycin and teicoplanin, and VRE to linezolid and tigecycline.

The most problematic Gram-negative alert pathogen was A. baumannii due to its high prevalence and resistance to antimicrobial agents. In such cases, colistin was virtually the only therapeutic choice. In the last two years of the period analyzed, all P. aeruginosa isolates were susceptible to ceftazidime, cefepime, and gentamycin.

The most frequently isolated species of Enterobacterales were K. pneumoniae (165 isolates) and E. coli (69 isolates). More than 40% (67/165) of K. pneumoniae strains and more than 16% of E. coli (11/69) exhibited an ESBL mechanism of resistance. Fortunately, all these pathogens were susceptible to meropenem, and only six of these isolates produced carbapenemases.

We had a broad spectrum of therapeutic options for fungal infection treatment. Candida albicans isolates were completely susceptible to fluconazole and non-albicans Candida species were susceptible to echinocandins and amphotericin.
Discussion

Bloodstream infections may lead to metastatic infections, severe sepsis, and multiorgan failure. The prevalence of bloodstream infections is estimated at 174–204/100,000 in North America and 166–189/100,000 in Europe, corresponding to 73,349–84,823 cases in the USA and 157,750–276,318 in Europe (Goto and Al-Hasan 2013). CVCs may be related to BSIs in 90% of cases (Polderman and Girbes 2002).

Possible reasons for this strong correlation include lack of asepsis upon catheter insertion and use, skin changes (e.g., burn-related), the biofilm formation on the catheter’s inner and outer surfaces, and the development of central vein thrombosis at the site of the catheter insertion. The only way to decrease the number of CLABSI cases is to ensure rigorous asepsis when the catheter is placed and used (Ling et al. 2016; Bell and O’Grady 2017; Ielapi et al. 2020).

Our work has been one of the most extensive single-center analyses performed in Poland in recent years. The study was conducted over a long period in a multibed tertiary hospital, a regional trauma center that gives credibility to the results and allows their generalization. The authors of this study believe that analyzing the microbiological situation in single centers may help make up a complete picture of both microbiological hazards and therapeutic possibilities on the national and regional levels. Our analysis was performed at a multidisciplinary ICU, with most of the cases being surgical and trauma patients. Some of them may be immunocompromised; in such patients, the transfer of pathogens from the site of infection to the lumen of the catheter via different connectors may be reasonably easy, resulting in more facile development and progression of a disease.

The data suggest that one in 20 ICU patients develop bloodstream infections. The longer the period of central vein catheterization, the higher the incidence of catheter infection (Gunst et al. 2011). We found that the incidence of positive microbiological results in blood samples was 12.8%. Those values are relatively low compared to the results of other studies which report positive results in 18.9% to 31.3% of cases (Rani et al. 2012; Musicha et al. 2017; Rani et al. 2017). This discrepancy may be due to the procedures at our center, where patient blood samples are analyzed microbiologically every time the patient’s body temperature exceeds 38°C. Some studies from ICUs in southern Poland report a lower incidence of BSI (Wałaszek et al. 2018). However, the spectrum of pathogens isolated from blood samples was similar to our results, including A. baumannii, coagulase-negative staphylococci, E. coli, P. aeruginosa, K. pneumoniae, and C. albicans (Kołpa et al. 2018; Wałaszek et al. 2018).

The etiology of bloodstream infection depends on the geographical localization of the hospital. For example, in Malawi (Africa), the most common BSI pathogens are Salmonella Typhi and Streptococcus pneumoniae (Musicha et al. 2017). The Surveillance Network data from Korea collected from 2006 to 2017 showed that the most common pathogens were E. coli and S. aureus. In Japan, E. coli, S. aureus, and K. pneumoniae are the most common isolates (Rani et al. 2017; Lee et al. 2018).

Data from the European Antimicrobial Resistance Surveillance Network study performed in 22 countries between 2000 and 2009 indicated that E. coli and S. aureus were the most common BSI pathogens (Gagliotti et al. 2011). The results of a EUROBACT study spanning 162 ICUs in 24 European countries and Turkey, Brazil, and China showed that in 53%, 32%, 7.8%, and 1.2% of cases, bacteremia was caused by Gram-negative bacteria, Gram-positive pathogens, fungi, and anaerobic bacteria, respectively. Multidrug-resistant pathogens were isolated in 47.8% of cases (Tabah et al. 2012). Our results were similar, although there were some differences in the exact numbers of isolated pathogens (49.5% Gram-negative strains, 47.1% Gram-positive strains, and 3.5% fungi).

Gram-positive pathogens were responsible for half of all bloodstream infections. Most of them were staphylococci. Their resistance to methicillin ranges from 40 to 60%. of importance is that MRCNS are a more likely etiological factor in infection than MRSA (Gunst et al. 2011; Louzi et al. 2016; Tian et al. 2019; Tomaszewski et al. 2019). Our results supported this observation. Moreover, MRCNS exhibit greater resistance to antimicrobials, except against vancomycin. We also noted the difference in resistance to gentamycin and trimethoprim/sulfamethoxazole. Such differences may result from the different proportions of branched-chain and straight-chain fatty acids in the membrane lipids of bacteria (Tiwari et al. 2020). However, susceptibility to sulphonamide is significant clinically because the drug can be administered orally, which may be necessary in patients who suffer from staphylococcal bone infections and require proper therapy for an extended time.

In many studies, Gram-negative pathogens responsible for more than half of bloodstream infections pose a greater therapeutic challenge than Gram-positive bacteria, partially due to their increasing antibiotic resistance. Enterobacterales produce ESBL and CPE mechanisms of resistance. Both Acinetobacter spp. and Pseudomonas spp. exhibit mechanisms of resistance that are multidirectional and difficult to treat.

In our study, Gram-negative bacteria were isolated in 49.5% of cases. The most frequently isolated was A. baumannii (40.5%), followed by K. pneumoniae (21.4%), P. aeruginosa (14.1%), and E. coli (9%). These results differ significantly from those found in an analysis of 9,334 strains of A. baumannii performed between 1994 and 2011 (Munoz-Price et al. 2013), during which time this pathogen was responsible for 11% of blood infections. This situation is alarming because the only effective antimicrobial against this pathogen is colistin.

Among the Gram-negative bacteria, 30.4% were K. pneumoniae or E. coli. The ESBL mechanism of resistance was found in 40.6% of K. pneumoniae and 16% of E. coli. These results are similar to those found by other researchers. According to the literature, the ESBL mechanism of resistance is present in 34–75% of K. pneumoniae and is increasingly common (Gunst et al. 2011; Louzi et al. 2016; Tian et al. 2019). Fortunately, we found this pathogen to be entirely susceptible to meropenem. Moreover, only a small number of the isolated K. pneumoniae exhibited a KPC resistance mechanism.

There are a few significant limitations to our study. The first group of constraints is related to other observational studies with routinely collected electronic data. They include missing data, potential bias, and possible misclassification or inconsistencies in medical coding. The second one is related to the indication for blood sample collection. In our center, blood samples were collected when the infection was suspected clinically. It cannot be ruled out that some patients’ pathogens were present in their bloodstream with no clinical and bacteriological signs and symptoms of infection. The third one is related to the setting of this study: our analysis is connected to only one hospital, although a large one. Finally, assessing the results with some differences in patient-level factors, such as the severity of illness, may have influenced the conclusions.

Despite the limitations mentioned earlier, we believe that our results may be informative and exciting for those interesting in the epidemiology of BSI. Our study estimated bloodstream infections in a large tertiary university hospital and trauma center for 13 years, as incidence rates and pathogens’ distribution, and their susceptibility/ resistance to antimicrobial agents. The presented data may constitute material for further analyses assessing the microbiological situation in Poland and the region to improve the quality of care and outcome in critically ill patients.
Conclusions

Our 13-year study shows that among 12,619 micro-biologically analyzed blood samples, 12% (1,509/12,619) were positive. In 278/1,509 (18.4%) of cases, a central line catheter infection was confirmed, and 1,557 pathogens were isolated.

The most frequently (770/1,557; 49.5%) isolated species were Gram-negative bacteria. Among the Gram-negative bacteria, the most frequently isolated were A. baumannii (312/770; 40.5%), K. pneumoniae (165/770 (24.1%); 67/165 (40.6%) of them produced ESBL, 5/165 (3%) – produced NDM, 4/165 (3.4%) – expressed KPC, 1/165 (0.6%) – produced OXA48), P. aeruginosa (111/770 (14.4%); 2/111 (1.8%) strains produced MBL), and E. coli (69/770 (9%); 11/69 (15.9%) strains expressed ESBL).

Gram-positive pathogens were isolated in 733/1,557 (47.1%) cases. The majority were staphylococci (545/733; 74.4%), mainly coagulase-negative (368/545; 67.5%). MRSA species represented 58/545 (10.6%) of all staphylococci. Fungi were isolated from 3.5% of samples.

Using these data to improve clinical practice, one can say that the MRSA and MRCNS species are susceptible to vancomycin, MSSA is susceptible to isoxazolyl penicillins, and VRE is susceptible to linezolid and tigecycline. However, colistin remains the only therapeutic option in some infections caused by A. baumannii and KPC-producing K. pneumoniae. P. aeruginosa is still susceptible to cefepime and ceftazidime. Echinocandins are effective therapeutics in treating fungal infections caused by C. albicans and non-albicans Candida species.

The bacteriological situation in our department, assessed by the incidence of infections, is similar to other ICUs in Poland and Eastern Europe. However, the number of A. baumannii and P. aeruginosa among the isolated pathogens is disturbing. We implemented and followed the infection control procedures. They include the decontamination of the patient environment, prevention of secondary contamination, personnel training, compliance control, hand hygiene, and clothing policy. We also follow the central catheter procedures. They emphasize full aseptic, and the additional connections are reduced to a minimum. A separate catheter lumen is reserved for parenteral nutrition, and the administration of drugs takes place after the disinfection of the connectors.

The applied infection reduction procedures follow the existing recommendations (Hryniewicz et al. 2013). In addition to the guidelines, it is essential to be aware of the infections, severity of the problem, prevention methods, and the real benefits of compliance with the recommendations that translate into a reduction in the frequency of infections in intensive care units.

Fig. 1

Trends in pathogens isolated between 2007 and 2019.
Trends in pathogens isolated between 2007 and 2019.

Fig. 2

Gram-positive alert pathogens with mechanisms of resistance, isolated between 2009 and 2019.
Gram-positive alert pathogens with mechanisms of resistance, isolated between 2009 and 2019.

Fig. 3

Gram-negative alert pathogens with mechanisms of resistance, isolated between 2009 and 2019.
Gram-negative alert pathogens with mechanisms of resistance, isolated between 2009 and 2019.

Descriptive statistics of the study population and their primary diagnoses according to ICD10.

Year
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Patients n 197 182 216 173 224 178 172 186 350 422 422 450 348
Age median 53 54 60 59 49 43 45 49 43 43 52 57 53
minimum 18 18 18 21 19 18 18 15 19 18 19 21 24
maximum 84 86 87 87 82 87 82 91 87 85 87 85 88
Q1-Q3 42-69 29-74 42-71 44-75 37-65 28-59 28-67 37-62 27-63 29-57 40-67 38-69 37-63
Hospitalization time in ICU (days) median 22 26 16 30 17 20 23 14 16 15 14 14 8
minimum 1 1 1 1 1 1 1 1 1 1 1 1 1
maximum Q1-Q3 136 11–47 147 9-48 124 7-27 137 11–58 48 5-27 107 11-31 106 10-36 273 8-39 126 8–31 275 7-35 205 5-36 159 5-32 238 24
Deaths n (%) 71 (36%) 62 (34%) 68 (31%) 57 (33%) 83 (37%) 60 (34%) 56 (33%) 64 (34%) 135(39%) 117(28%) 166 (39%) 160 (36%) 149 (43%)
Main diagnosis according to ICD10
Year
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Other bacterial diseases [A30–A49]1 4 4 6 3 6 3 4 4 8 11 13 12 10
Malignant [C00–C14]neoplasms 2 of lip, oral cavity, and pharynx 3 5 3 4 4 3 4 3 4 4 3 5 4
Malignant neoplasms of digestive organs [C15–C26]3 0 1 2 0 0 0 0 0 0 1 0 0 0
Malignant organs [C30neoplasms –C39]4 of respiratory and intrathoracic 0 0 1 0 0 0 0 0 1 1 0 0 0
Malignant and related neoplasms tissue [C81of -lymphoid, C96]5 hematopoietic, 4 3 4 4 4 4 3 4 7 8 6 6 5
Diabetes mellitus [E10-E14]6 4 7 5 4 5 3 2 4 6 5 7 6 5
Obesity and other hyperalimentation [E65-E68] 0 0 1 0 1 0 0 0 2 2 3 3 1
Metabolic disorders7 4 2 3 0 1 0 1 1 3 0 3 4 2
Inflammatory system [G00–Gdiseases 09]8 of the central nervous 3 1 2 0 4 0 0 0 2 2 3 4 2
Systemic nervous system atrophies [Gprimarily 10–G14]9 affecting the central 0 0 1 0 0 0 0 0 0 0 0 0 0
Episodic and paroxysmal disorders [G40–G47]10 2 3 2 0 1 0 0 1 1 2 1 2 2
Diseases [G70–G73of ]myoneural 11 junction and muscle 0 0 1 1 0 0 0 0 0 1 0 0 0
Cerebral [G80–G83palsy ]12 and other paralytic syndromes 0 2 0 0 0 0 0 0 0 0 0 0 0
Other disorders of the nervous system [G90–G99]13 0 0 0 0 0 0 0 0 2 1 0 0 0
Ischemic heart diseases [I20–I25]14 3 3 4 0 3 2 2 2 4 6 6 5 4
Pulmonary circulation heart [I26–Idisease 28]15 and diseases of pulmonary 2 1 2 0 2 2 2 3 6 7 8 8 6
Other forms of heart disease [I30–I52]16 36 27 25 13 27 17 16 17 24 31 27 34 28
Cerebrovascular diseases [I60–I69]17 6 8 10 0 10 8 8 8 14 13 14 22 16
Diseases of arteries, arterioles, and capillaries [I70–I79]18 4 2 2 0 0 0 0 0 2 1 1 0 0
Diseases nodes [I80of –veins, I89]19 lymphatic vessels, and lymph 1 0 0 0 0 0 0 0 0 0 1 0 0
Influenza and pneumonia [J09-J18]20 1 0 3 5 5 3 2 2 5 6 6 6 4
Chronic lower respiratory diseases [J40–J47]21 7 7 9 10 9 8 8 9 16 19 18 21 18
Lung diseases due to external agents [J60–J70]22 5 4 5 0 2 2 1 1 1 3 3 4 2
Other the interstitium respiratory [Jdiseases 80–J84)23 principally affecting 5 1 5 6 6 4 3 3 3 5 5 4 3
Suppurative respiratory tract and necrotic [J85–J86conditions ]24 of the lower 0 1 0 0 0 0 0 0 0 2 0 1 0
Other diseases of the respiratory system [J95–J99]25 21 10 19 44 38 28 22 19 25 30 28 37 27
Diseases [K20–K31of ]esophagus, 26 stomach, and duodenum 5 4 4 2 2 2 1 0 2 4 5 6 0
Hernia [K40–K46]27 0 0 1 1 2 0 0 0 1 1 0 0 2
Other diseases of the intestines [K55-K64]28 0 0 1 2 1 1 0 0 2 3 4 3 1
Diseases of peritoneum [K65–K67]29 5 8 10 11 13 9 11 9 16 16 14 16 10
Diseases of the liver [K70–K77]30 0 0 1 0 0 1 0 1 2 2 3 3 0
Disorders [K80–K87of ]31 gallbladder, biliary tract, and pancreas 13 10 10 13 14 9 8 9 11 9 7 10 6
Other diseases of the digestive system [K90–K93]32 0 0 0 0 0 0 1 1 0 0 3 2 0
Infections [L00–L08]of 33 the skin and subcutaneous tissue 0 0 0 0 0 1 0 0 0 0 0 0 0
Systemic connective tissue disorders [M30 -M32]34 0 0 0 0 0 0 0 0 0 1 0 0 0
Osteopathies and chondropathies [M80–M94]35 0 0 0 0 0 0 0 0 0 0 0 1 0
Injuries to the head [S00–S09]36 5 5 7 9 9 8 11 9 27 23 23 24 16
Injuries to the neck [S10–S19]37 0 0 0 4 0 2 3 0 2 0 0 2 0
Injuries to the thorax [S20–S29]38 4 3 3 2 0 2 0 4 7 3 8 4 2
Injuries and pelvis to the [S30abdomen, –S39]39 lower back, lumbar spine, 2 3 3 4 4 2 0 2 10 17 23 17 9
Injuries to the shoulder and upper arm [S40–S49]40 0 0 0 0 0 1 0 0 0 1 0 0 0
Injuries to the hip and thigh [S70–S79]41 0 0 0 0 0 0 0 0 2 2 0 0 2
Injuries to the knee and lower leg [S80–S89]42 0 0 1 0 0 0 0 0 0 2 0 1 0
Injuries involving multiple body regions [T00–T07]43 44 45 53 21 32 41 48 57 101 142 145 141 134
Burns and corrosions [T20–T32]44 4 9 6 9 16 10 11 11 19 31 29 35 26
Poisoning substances by [Tdrugs, 36–T50medicaments, ]45 and biological 0 2 1 1 2 2 0 2 1 3 2 1 0
Other [T66-Tand 78]unspecified 46 effects of external causes 0 1 0 0 1 0 0 0 1 1 0 0 1

The number of microbiological analyses, with their results, performed between 2007 and 2019.

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Beds in ICU (n) 8 8 8 8 8 8 8 14 18 18 18 18 18
Hospitalizations (n) 179 182 216 173 224 178 172 186 350 422 422 450 348
Microbiological analyses (n) 2,361 2,349 2,710 2,454 3,123 2,796 2,797 2,811 4,093 5,376 5,030 5,089 5,264
Microbiological of blood samples analyses (n) 670 613 785 641 1,245 1,016 944 831 1,219 1,326 988 1,161 1,180
Blood analyses, microbiological negative results (n) 548 473 632 534 1,130 889 809 690 1,064 1,140 858 1,023 994
Blood analyses, microbiological positive results (n) 107 120 135 97 104 99 106 112 120 154 104 106 145
Blood microbiological analyses, contaminated samples (n) 15 20 18 10 11 28 29 29 35 32 26 32 41
Microbiological of the tip of the analyses catheter (n) 30 23 28 18 39 29 45 53 70 70 76 77 65
Microbiological analyses of the tip of the catheter, positive results (n) 13 11 17 12 21 11 31 30 20 29 31 26 26

The number of pathogens isolated from blood samples between 2007 and 2019.

Pathogen (mechanism of Pathogen antibiotic resistance) 2007 2008 2009 2010 2011 2011 2012 2013 2014 2015 2016 2017 2018 Total
Gram-negative bacilli Acinetobacter baumannii 33 24 22 19 38 26 25 29 18 26 20 18 14 312
Pseudomonas aeruginosa 9 12 9 12 7 5 7 6 8 8 9 6 11 109
Pseudomonas aeruginosa (MBL) 0 0 0 0 0 0 1 0 0 1 0 0 0 2
Stenotrophomonas maltophila 0 0 4 0 1 1 2 2 4 7 4 0 1 26
Klebsiella pneumoniae 6 8 5 2 4 2 4 9 7 14 6 8 13 88
Klebsiella pneumoniae (ESBL) 11 8 3 3 2 4 1 10 7 7 4 5 2 67
Klebsiella pneumoniae (NDM) 0 0 0 0 0 0 0 0 0 0 2 1 2 5
Klebsiella pneumoniae (KPC) 0 4 0 0 0 0 0 0 0 0 0 0 0 4
Klebsiella pneumoniae (OXA 48) 0 0 0 0 0 0 0 0 0 0 0 0 1 1
Escherichia coli 1 3 2 0 3 3 4 6 4 9 7 11 5 58
Escherichia coli (ESBL) 0 2 0 0 0 0 0 0 0 2 3 3 1 11
Enterobacter cloacae 1 0 1 0 1 1 3 3 2 5 5 7 5 34
Enterobacter cloacae (ESBL) 0 0 1 1 0 0 0 1 0 2 0 2 0 7
Proteus mirabilis 0 1 0 0 0 2 2 2 1 3 3 3 4 21
Proteus mirabilis (ESBL) 4 3 0 0 0 0 0 0 0 0 2 0 0 9
Morganella morgani 0 0 0 0 0 0 1 1 1 1 2 0 2 8
Serratia marcescens 0 0 0 0 0 0 1 1 0 2 2 0 2 8
Gram-positive cocci Staphylococcus aureus 1 5 1 3 7 3 3 3 4 4 4 9 18 65
Staphylococcus aureus (MRSA) 3 7 15 3 5 4 2 3 7 3 2 4 0 58
Coagulase-Staphylococcus negative (CNS) 2 2 5 3 2 2 6 4 6 12 5 1 4 54
Coagulase-negative Staphylococcus (MRCNS) 31 25 34 35 22 34 35 23 38 28 18 15 30 368
Enterococcus faecalis 5 8 15 5 5 5 4 5 6 16 2 6 13 95
Enterococcus faecalis (HLAR) 0 3 9 0 3 0 0 0 1 2 0 0 2 20
Enterococcus faecium 1 2 9 5 1 2 1 0 4 3 0 2 7 37
Enterococcus faecium (VRE) 0 1 0 1 0 0 1 1 0 1 2 3 1 11
Enterococcus faecium (HLAR) 1 1 1 6 1 2 1 1 1 1 0 3 2 21
Streptococcus pneumoniae 0 0 0 0 0 0 0 0 0 0 1 1 1 3
Neisseria meningitidis 1 0 0 0 0 0 0 0 0 0 0 0 0 1
Fungi Candida albicans 5 3 4 5 2 4 1 1 2 1 2 1 3 34
Candida glabrata 0 1 1 0 0 0 0 0 0 0 1 0 1 4
Candida krusei 0 0 0 0 0 1 0 0 0 0 0 0 0 1
Candida tropicalis 0 0 0 0 0 0 1 0 0 0 0 0 0 1
Candida parapsilosis 0 2 0 0 0 2 1 1 3 1 1 0 3 14
Total 115 125 141 103 104 103 107 112 124 159 107 109 148 1,557

Resistance of Gram-negative pathogens to antimicrobial agents.

Antimicrobial agent Pseudomonas aeruginosa
2007 n = 9 2008 n = 12 2009 n = 9 2010 n = 12 2011 n = 7 2012 n = 5 2013 n = 7 2014 n = 6 2015 n = 8 2016 n = 8 2017 n = 9 2018 n = 6 2019 n = 11
Ceftazidime 2 4 3 0 0 0 1 0 0 2 1 0 0
Cefepime 0 3 0 0 1 1 2 0 0 3 1 0 0
Piperacillin/tazobactam 1 1 5 0 0 1 1 0 1 4 1 0 0
Gentamycin 5 4 5 1 3 2 3 0 0 4 0 0 0
Ciprofloxacin 6 3 5 0 2 2 2 2 2 5 3 2 0
Imipenem 3 2 4 4 2 1 2 0 2 5 4 3 7
Meropenem 3 0 4 3 2 1 2 0 1 4 4 3 7
Acinetobacter baumannii
2007 n = 33 2008 n = 24 2009 n = 22 2010 n = 19 2011 n = 38 2012 n = 26 2013 n = 25 2014 n = 29 2015 n = 18 2016 n = 26 2017 n = 20 2018 n = 18 2019 n = 14
Gentamycin 30 22 7 11 29 24 22 25 16 18 13 15 8
Ciprofloxacin 32 24 21 19 34 25 23 29 18 25 20 18 14
Imipenem 11 6 10 11 31 23 21 28 17 25 19 17 10
Meropenem 6 6 8 11 31 23 21 28 17 25 19 17 10
Trimethoprim-sulfamethoxazole 20 18 16 19 36 24 15 27 16 25 20 17 10
Ampicillin/sulbactam 12 12 8 12 19 3 9 20 16 nd nd nd nd
Colistin – – – – – – – – 0 0 0 0 0
Stenotrophomonas maltophila
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
n = 0 n = 0 n = 4 n = 0 n = 1 n = 1 n = 2 n = 2 n = 4 n = 7 n = 4 n = 0 n = 1
Trimethoprim-sulfamethoxazole – – 0 – 0 0 0 0 0 0 0 – 0
ESBL-negative Enterobacterales
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
n = 8 n = 12 n = 8 n = 2 n = 8 n = 9 n = 15 n = 22 n = 15 n = 34 n = 25 n = 29 n = 31
Ceftazidime 0 0 0 0 0 0 0 0 0 0 0 0 0
Cefepime 0 0 0 0 0 0 0 0 0 0 0 0 0
Ciprofloxacin 0 3 3 0 1 0 5 1 2 10 6 4 5
Gentamycin 0 2 0 0 0 0 0 0 0 2 0 2 5
Piperacillin/tazobactam 0 0 1 0 0 0 1 1 0 0 1 4 8
Trimethoprim-sulfamethoxazole 3 2 3 1 1 1 6 1 0 3 4 2 4
ESBL-positive Enterobacterales
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
n = 15 n = 13 n = 4 n = 4 n = 2 n = 4 n = 1 n = 11 n = 7 n = 11 n = 9 n = 10 n = 3
Amoxicillin/clavulanate 12 9 3 4 2 4 1 11 6 8 9 10 3
Gentamycin 10 9 3 4 2 4 1 8 7 7 6 8 2
Ciprofloxacin 13 11 4 4 2 4 1 11 7 11 9 10 3
Imipenem 4 3 0 0 0 0 0 0 0 0 2 0 0
Meropenem 0 0 0 0 0 0 0 0 0 0 0 0 0
Trimethoprim-sulfamethoxazole 13 9 2 3 1 3 1 9 5 11 9 8 3
KPC-producing Klebsiella pneumoniae
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
n = 0 n = 4 n = 0 n = 0 n = 0 n = 0 n = 0 n = 0 n = 0 n = 0 n = 0 n = 0 n = 0
Amikacin – 0 – – – – – – – – – – –
Gentamicin – 0 – – – – – – – – – – –
Tigecycline – 2 – – – – – – – – – – –
Trimethoprim-sulfamethoxazole – 4 – – – – – – – – – – –
Colistin – 0 – – – – – – – – – – –
NDM-producing Klebsiella pneumoniae
Antimicrobial agent 2007 n = 0 2008 n = 0 2009 n = 0 2010 n = 0 2011 n = 0 2012 n = 0 2013 n = 0 2014 n = 0 2015 n = 0 2016 n = 0 2017 n = 2 2018 n = 1 2019 n = 2
Amikacin – – – – – – – – – – 2 1 2
Gentamicin – – – – – – – – – – 1 1 1
Tigecycline – – – – – – – – – – 2 1 0
Trimethoprim-sulfamethoxazole – – – – – – – – – – 1 1 1
Colistin – – – – – – – – – – 0 0 0
OXA48-producing Klebsiella pneumoniae
2007 n = 0 2008 n = 0 2009 n = 0 2010 n = 0 2011 n = 0 2012 n = 0 2013 n = 0 2014 n = 0 2015 n = 0 2016 n = 0 2017 n = 0 2018 n = 0 2019 n = 1
Amikacin – – – – – – – – – – – – 0
Gentamicin – – – – – – – – – – – – 1
Tigecycline – – – – – – – – – – – – 1
Trimethoprim-sulfamethoxazole – – – – – – – – – – – – 1
Colistin – – – – – – – – – – – – 0

Bell T, O’Grady NP. Prevention of central line-associated bloodstream infections. Infect Dis Clin North Am. 2017 Sep;31(3):551–559. https://doi.org/10.1016/j.idc.2017.05.007Bell T O’Grady NP Prevention of central line-associated bloodstream infections Infect Dis Clin North Am 2017 Sep31 3 551 559 https://doi.org/10.1016/j.idc.2017.05.007566669628687213Open DOISearch in Google Scholar

Blot K, Vogelaers D, Blot S. Central line-associated bloodstream infections: A critical look at the role and research of quality improvement interventions and strategies. In: Vincent JL, editor. Annual update in intensive care and emergency medicine. Cham (Switzerland): Springer Cham; 2015. p. 15–24. https://doi.org/10.1007/978-3-319-13761-2_2Blot K Vogelaers D Blot S Central line-associated bloodstream infections: A critical look at the role and research of quality improvement interventions and strategies. In: Vincent JL, editor. Annual update in intensive care and emergency medicine Cham (Switzerland) Springer Cham 2015 p 15–24 https://doi.org/10.1007/978-3-319-13761-2_2Open DOISearch in Google Scholar

Brun-Buisson C, Abrouk F, Legrand P, Huet Y, Larabi S, Rapin M. Diagnosis of central venous catheter-related sepsis. Critical level of quantitative tip cultures. Arch Intern Med. 1987 May 01;147(5): 873–877. https://doi.org/10.1001/archinte.1987.00370050069012Brun-Buisson C Abrouk F Legrand P Huet Y Larabi S Rapin M Diagnosis of central venous catheter-related sepsis Critical level of quantitative tip cultures. Arch Intern Med 1987 May 01147 5 873 877 https://doi.org/10.1001/archinte.1987.00370050069012Open DOISearch in Google Scholar

CLSI. Performance standards for antimicrobial susceptibility testing. 19th ed. CLSI supplement M100-S19. Wayne (USA): Clinical and Laboratory Standards Institute; 2009.CLSI Performance standards for antimicrobial susceptibility testing. 19th ed. CLSI supplement M100-S19 Wayne (USA) Clinical and Laboratory Standards Institute 2009Search in Google Scholar

CLSI. Performance standards for antimicrobial susceptibility testing. 20th ed. CLSI supplement M100-S20. Wayne (USA): Clinical and Laboratory Standards Institute; 2010a.CLSI Performance standards for antimicrobial susceptibility testing. 20th ed. CLSI supplement M100-S20 Wayne (USA) Clinical and Laboratory Standards Institute 2010aSearch in Google Scholar

CLSI. Performance standards for antimicrobial susceptibility testing. 20th ed. (June 2010, Update). CLSI supplement M100-S20-U. Wayne (USA): Clinical and Laboratory Standards Institute; 2010b. EUCAST. EUCAST guideline for the detection of resistance mechanisms and specific resistances of clinical and/ or epidemiological importance. Version 1.0. Basel (Switzerland): The European Committee on Antimicrobial Susceptibility Testing; 2013 [cited 2022 Jan 26]. Available from https://www.eucast.org/resistance_mechanisms/CLSI Performance standards for antimicrobial susceptibility testing. 20th ed. (June 2010, Update). CLSI supplement M100-S20-U. Wayne (USA): Clinical and Laboratory Standards Institute; 2010b. EUCAST. EUCAST guideline for the detection of resistance mechanisms and specific resistances of clinical and/ or epidemiological importance. Version 1.0 Basel (Switzerland) The European Committee on Antimicrobial Susceptibility Testing; 2013 [cited 2022 Jan 26].. Available from https://www.eucast.org/resistance_mechanisms/Search in Google Scholar

EUCAST. EUCAST guideline for the detection of resistance mechanisms and specific resistances of clinical and/ or epidemiological importance. Version 2.0. Basel (Switzerland): The European Committee on Antimicrobial Susceptibility Testing; 2017 [cited 2022 Jan 26]. Available from https://www.eucast.org/resistance_mechanisms/EUCAST EUCAST guideline for the detection of resistance mechanisms and specific resistances of clinical and/ or epidemiological importance. Version 2.0 Basel (Switzerland) The European Committee on Antimicrobial Susceptibility Testing; 2017 [cited 2022 Jan 26]. Available from https://www.eucast.org/resistance_mechanisms/Search in Google Scholar

Gagliotti C, Balode A, Baquero F, Degener J, Grundmann H, Gür D, Jarlier V, Kahlmeter G, Monen J, Monnet DL, et al.; EARS-Net Participants (Disease Specific Contact Points for AMR). Escherichia coli and Staphylococcus aureus: bad news and good news from the European Antimicrobial Resistance Surveillance Network (EARS-Net, formerly EARSS), 2002 to 2009. Euro Surveill. 2011 Mar 17;16(11):19819. https://doi.org/10.2807/ese.16.11.19819-enGagliotti C Balode A Baquero F Degener J Grundmann H Gür D Jarlier V Kahlmeter G Monen J Monnet DL et al EARS-Net Participants (Disease Specific Contact Points for AMR) Escherichia coli and Staphylococcus aureus: bad news and good news from the European Antimicrobial Resistance Surveillance Network (EARS-Net, formerly EARSS) 2002 to 2009. Euro Surveill. 2011 Mar 1716 11 19819 https://doi.org/10.2807/ese.16.11.19819-en21435327Open DOISearch in Google Scholar

Goto M, Al-Hasan MN. Overall burden of bloodstream infection and nosocomial bloodstream infection in North America and Europe. Clin Microbiol Infect. 2013 Jun;19(6):501–509. https://doi.org/10.1111/1469-0691.12195Goto M Al-Hasan MN Overall burden of bloodstream infection and nosocomial bloodstream infection in North America and Europe Clin Microbiol Infect 2013 Jun19 6 501 509 https://doi.org/10.1111/1469-0691.1219523473333Open DOISearch in Google Scholar

Gunst M, Matsushima K, Vanek S, Gunst R, Shafi S, Frankel H. Peripherally inserted central catheters may lower the incidence of catheter-related blood stream infections in patients in surgical intensive care units. Surg Infect (Larchmt). 2011 Aug; 12(4):279–282. https://doi.org/10.1089/sur.2008.058Gunst M Matsushima K Vanek S Gunst R Shafi S Frankel H Peripherally inserted central catheters may lower the incidence of catheter-related blood stream infections in patients in surgical intensive care units Surg Infect (Larchmt) 2011 Aug12 4 279 282 https://doi.org/10.1089/sur.2008.05820629557Open DOISearch in Google Scholar

Holm MKA, Jansåker F, Gradel KO, Nielsen RT, Østergaard Andersen C, Jarløv JO, Schønheyder HC, Dahl Knudsen J. Decrease in all-cause 30-day mortality after bacteraemia over a 15-year period: a population-based cohort study in Denmark in 2000–2014. Int J Environ Res Public Health. 2021 Jun 2;18(11):5982. https://doi.org/10.3390/ijerph18115982Holm MKA Jansåker F Gradel KO Nielsen RT Østergaard Andersen C Jarløv JO Schønheyder HC Dahl Knudsen J Decrease in all-cause 30-day mortality after bacteraemia over a 15-year period: a population-based cohort study in Denmark in 2000–2014 Int J Environ Res Public Health 2021 Jun 218 11 5982 https://doi.org/10.3390/ijerph18115982819966334199587Open DOISearch in Google Scholar

Hryniewicz W, Kusza K, Ozorowski T, Misiewska-Kaczur A, Fleischer M, Trejnowska E, Deptuła A. [Strategia zapobiegania lekooporności w oddziałach intensywnej terapii. Rekomendacje profilaktyki zakażeńw oddziałach intensywnej terapii] (in Polish). Warsaw (Poland): National Medicines Institute; 2013.Hryniewicz W Kusza K Ozorowski T Misiewska-Kaczur A Fleischer M Trejnowska E Deptuła A [Strategia zapobiegania lekooporności w oddziałach intensywnej terapii. Rekomendacje profilaktyki zakażeńw oddziałach intensywnej terapii] (in Polish) Warsaw (Poland) National Medicines Institute; 2013Search in Google Scholar

Ielapi N, Nicoletti E, Lorè C, Guasticchi G, Avenoso T, Barbetta A, de Franciscis S, Andreucci M, Sapienza P, Serra R. The Role of biofilm in central venous catheter related bloodstream infections: Evidence-based nursing and review of the literature. Rev Recent Clin Trials. 2020;15(1):22–27. https://doi.org/10.2174/1574887114666191018144739Ielapi N Nicoletti E Lorè C Guasticchi G Avenoso T Barbetta A de Franciscis S Andreucci M Sapienza P Serra R The Role of biofilm in central venous catheter related bloodstream infections: Evidence-based nursing and review of the literature Rev Recent Clin Trials 202015 1 22 27 https://doi.org/10.2174/157488711466619101814473931656155Open DOISearch in Google Scholar

Kołpa M, Wałaszek M, Gniadek A, Wolak Z, Dobroś W. Incidence, microbiological profile and risk factors of healthcare-associated infections in intensive care units: A 10 year observation in a provincial hospital in southern Poland. Int J Environ Res Public Health. 2018 Jan 11;15(1):112. https://doi.org/10.3390/ijerph15010112Kołpa M Wałaszek M Gniadek A Wolak Z Dobroś W Incidence, microbiological profile and risk factors of healthcare-associated infections in intensive care units: A 10 year observation in a provincial hospital in southern Poland Int J Environ Res Public Health 2018 Jan 1115 1 112 https://doi.org/10.3390/ijerph15010112580021129324651Open DOISearch in Google Scholar

Lee H, Yoon EJ, Kim D, Jeong SH, Won EJ, Shin JH, Kim SH, Shin JH, Shin KS, Kim YA, et al. 2018. Antimicrobial resistance of major clinical pathogens in South Korea, May 2016 to April 2017: first one-year report from Kor-GLASS. Euro Surveill. 2018 Oct; 23(42):1800047. https://doi.org/10.2807/1560-7917.ES.2018.23.42.1800047Lee H Yoon EJ Kim D Jeong SH Won EJ Shin JH Kim SH Shin JH Shin KS Kim YA et al 2018 Antimicrobial resistance of major clinical pathogens in South Korea, May 2016 to April 2017: first one-year report from Kor-GLASS Euro Surveill 2018 Oct 23 42 1800047 https://doi.org/10.2807/1560-7917.ES.2018.23.42.1800047619986430352640Open DOISearch in Google Scholar

Ling ML, Apisarnthanarak A, Jaggi N, Harrington G, Morikane K, Thu LTA, Ching P, Villanueva V, Zong Z, Jeong JS, et al. APSIC guide for prevention of Central Line Associated Bloodstream Infections (CLABSI). Antimicrob Resist Infect Control. 2016 Dec;5(1):16. https://doi.org/10.1186/s13756-016-0116-5Ling ML Apisarnthanarak A Jaggi N Harrington G Morikane K Thu LTA Ching P Villanueva V Zong Z Jeong JS et al APSIC guide for prevention of Central Line Associated Bloodstream Infections (CLABSI) Antimicrob Resist Infect Control 2016 Dec5 1 16 https://doi.org/10.1186/s13756-016-0116-5Open DOISearch in Google Scholar

Louzi L, Doblali T, Sbiti M, L’Kassmi H. Microbiological and resistance patterns of blood cultures clinical isolates at Moulay Ismail Military Hospital of Meknes, Morocco. A four-year period retrospective study: 2011–2014. JSM Microbiol. 2016;4(1):1030.Louzi L Doblali T Sbiti M L’Kassmi H Microbiological and resistance patterns of blood cultures clinical isolates at Moulay Ismail Military Hospital of Meknes, Morocco A four-year period retrospective study: 2011–2014. JSM Microbiol 20164 1 1030Search in Google Scholar

Maki DG, Weise CE, Sarafin HW. A semiquantitative culture method for identifying intravenous-catheter-related infection. N Engl J Med. 1977 Jun 09;296(23):1305–1309. https://doi.org/10.1056/NEJM197706092962301Maki DG Weise CE Sarafin HW A semiquantitative culture method for identifying intravenous-catheter-related infection N Engl J Med 1977 Jun 09296 23 1305 1309 https://doi.org/10.1056/NEJM197706092962301Open DOISearch in Google Scholar

Massart N, Wattecamps G, Moriconi M, Fillatre P. Attributable mortality of ICU acquired bloodstream infections: a propensity-score matched analysis. Eur J Clin Microbiol Infect Dis. 2021 Aug; 40(8):1673–1680. https://doi.org/10.1007/s10096-021-04215-4Massart N Wattecamps G Moriconi M Fillatre P Attributable mortality of ICU acquired bloodstream infections: a propensity-score matched analysis Eur J Clin Microbiol Infect Dis 2021 Aug40 8 1673 1680 https://doi.org/10.1007/s10096-021-04215-4Open DOISearch in Google Scholar

Munoz-Price LS, Arheart K, Nordmann P, Boulanger AE, Cleary T, Alvarez R, Pizano L, Namias N, Kett DH, Poirel L. Eighteen years of experience with Acinetobacter baumannii in a tertiary care hospital. Crit Care Med. 2013 Dec;41(12):2733-42. https://doi.org/10.1097/CCM.0b013e318298a541Munoz-Price LS Arheart K Nordmann P Boulanger AE Cleary T Alvarez R Pizano L Namias N Kett DH Poirel L Eighteen years of experience with Acinetobacter baumannii in a tertiary care hospital Crit Care Med 2013 Dec41 12 2733 42 https://doi.org/10.1097/CCM.0b013e318298a541Open DOISearch in Google Scholar

Musicha P, Cornick JE, Bar-Zeev N, French N, Masesa C, Denis B, Kennedy N, Mallewa J, Gordon MA, Msefula CL, et al. Trends in antimicrobial resistance in bloodstream infection isolates at a large urban hospital in Malawi (1998–2016): a surveillance study. Lancet Infect Dis. 2017 Oct; 17(10):1042–1052. https://doi.org/10.1016/S1473-3099(17)30394-8Musicha P Cornick JE Bar-Zeev N French N Masesa C Denis B Kennedy N Mallewa J Gordon MA Msefula CL et al Trends in antimicrobial resistance in bloodstream infection isolates at a large urban hospital in Malawi (1998–2016): a surveillance study Lancet Infect Dis 2017 Oct17 10 1042 1052 https://doi.org/10.1016/S1473-3099(17)30394-8Open DOISearch in Google Scholar

O’Grady NP, Alexander M, Burns LA, Dellinger EP, Garland J, Heard SO, Lipsett PA, Masur H, Mermel LA, Pearson ML, et al.; Healthcare Infection Control Practices Advisory Committee (HICPAC). Guidelines for the prevention of intravascular catheter-related infections. Clin Infect Dis. 2011 May 01;52(9):e162–e193. https://doi.org/10.1093/cid/cir257O’Grady NP Alexander M Burns LA Dellinger EP Garland J Heard SO Lipsett PA Masur H Mermel LA Pearson ML et al Healthcare Infection Control Practices Advisory Committee (HICPAC) Guidelines for the prevention of intravascular catheter-related infections. Clin Infect Dis 2011 May 0152 9 e162 e193 https://doi.org/10.1093/cid/cir257310626921460264Open DOISearch in Google Scholar

Polderman K, Girbes A. Central venous catheter use. Intensive Care Med. 2002 Jan;28(1):18–28. https://doi.org/10.1007/s00134-001-1156-7Polderman K Girbes A Central venous catheter use Intensive Care Med 2002 Jan28 1 18 28 https://doi.org/10.1007/s00134-001-1156-711818995Open DOISearch in Google Scholar

Rani RD, Chaitanya SB, Rajappa SJ, Kumar BR, Prabhakar KK, Mohan KM, Nayak VK, Kumar P, Santa A, Rao S. Retrospective analysis of blood stream infections and antibiotic susceptibility pattern of gram negative bacteria in a Tertiary Care Cancer Hospital. Int J Med Res Health Sci. 2017;6(12):19–26.Rani RD Chaitanya SB Rajappa SJ Kumar BR Prabhakar KK Mohan KM Nayak VK Kumar P Santa A Rao S Retrospective analysis of blood stream infections and antibiotic susceptibility pattern of gram negative bacteria in a Tertiary Care Cancer Hospital Int J Med Res Health Sci 20176 12 19 26Search in Google Scholar

Rani VN, Gopal K, Narendra VM, Vishwakanth D, Nagesh V, Yogitha M, Sunil VM, Palani T. A retospective study on blood stream infections and antibiotic susceptibility patterns in a tertiary care teaching hospital. Int J Pharm Pharm Sci. 2012;4(1):543–548. Salm F, Schwab F, Behnke M, Brunkhorst FM, Scherag A, Geffers C, Gastmeier P. Nudge to better care – blood cultures and catheter-related bloodstream infections in Germany at two points in time (2006, 2015). Antimicrob Resist Infect Control. 2018 Dec; 7(1):141. https://doi.org/10.1186/s13756-018-0432-zRani VN Gopal K Narendra VM Vishwakanth D Nagesh V Yogitha M Sunil VM Palani T A retospective study on blood stream infections and antibiotic susceptibility patterns in a tertiary care teaching hospital Int J Pharm Pharm Sci 20124 1 543 548 Salm F, Schwab F, Behnke M, Brunkhorst FM, Scherag A, Geffers C, Gastmeier P. Nudge to better care – blood cultures and catheter-related bloodstream infections in Germany at two points in time (2006, 2015). Antimicrob Resist Infect Control. 2018 Dec; 7(1):141 https://doi.org/10.1186/s13756-018-0432-z624974230479754Open DOISearch in Google Scholar

Tabah A, Koulenti D, Laupland K, Misset B, Valles J, Bruzzi de Carvalho F, Paiva JA, Çakar N, Ma X, Eggimann P, et al. Characteristics and determinants of outcome of hospital-acquired bloodstream infections in intensive care units: the EUROBACT International Cohort Study. Intensive Care Med. 2012 Dec;38(12): 1930–1945. https://doi.org/10.1007/s00134-012-2695-9Tabah A Koulenti D Laupland K Misset B Valles J Bruzzi de Carvalho F Paiva JA Çakar N Ma X Eggimann P et al Characteristics and determinants of outcome of hospital-acquired bloodstream infections in intensive care units: the EUROBACT International Cohort Study Intensive Care Med 2012 Dec38 12 1930 1945 https://doi.org/10.1007/s00134-012-2695-923011531Open DOISearch in Google Scholar

Tajima T, Asai Y, Endo M, Suzuki T, Matsunaga N, Tsuzuki S, Hayakawa K, Ohmagari N. Rate of blood culture submissions in Japan as an indicator of bloodstream infections. J Infect Chemother. 2021 Aug;27(8):1270–1272. https://doi.org/10.1016/j.jiac.2021.04.019Tajima T Asai Y Endo M Suzuki T Matsunaga N Tsuzuki S Hayakawa K Ohmagari N Rate of blood culture submissions in Japan as an indicator of bloodstream infections J Infect Chemother 2021 Aug27 8 1270 1272 https://doi.org/10.1016/j.jiac.2021.04.01933994090Open DOISearch in Google Scholar

Tian L, Zhang Z, Sun Z. Antimicrobial resistance trends in bloodstream infections at a large teaching hospital in China: A 20-year surveillance study (1998–2017). Antimicrob Resist Infect Control. 2019 Dec;8(1):86. https://doi.org/10.1186/s13756-019-0545-zTian L Zhang Z Sun Z Antimicrobial resistance trends in bloodstream infections at a large teaching hospital in China: A 20-year surveillance study (1998–2017) Antimicrob Resist Infect Control 2019 Dec8 1 86 https://doi.org/10.1186/s13756-019-0545-z654053631161033Open DOISearch in Google Scholar

Tiwari KB, Gatto C, Wilkinson BJ. Plasticity of coagulase-negative staphylococcal membrane fatty acid composition and implications for responses to antimicrobial agents. Antibiotics (Basel). 2020 Apr 28;9(5):214. https://doi.org/10.3390/antibiotics9050214Tiwari KB Gatto C Wilkinson BJ Plasticity of coagulase-negative staphylococcal membrane fatty acid composition and implications for responses to antimicrobial agents Antibiotics (Basel) 2020 Apr 289 5 214 https://doi.org/10.3390/antibiotics9050214727770932354049Open DOISearch in Google Scholar

Tomaszewski D, Rybicki Z, Duszyńska W. The Polish Prevalence of Infection in Intensive Care (PPIC): A one-day point prevalence multicenter study. Adv Clin Exp Med. 2019 Apr 13;28(7):907–912. https://doi.org/10.17219/acem/94147Tomaszewski D Rybicki Z Duszyńska W The Polish Prevalence of Infection in Intensive Care (PPIC): A one-day point prevalence multicenter study Adv Clin Exp Med 2019 Apr 1328 7 907 912 https://doi.org/10.17219/acem/9414730986000Open DOISearch in Google Scholar

Wałaszek M, Różańska A, Bulanda M, Wojkowska-Mach J; Polish Society of Hospital Infections Team. Alarming results of nosocomial bloodstream infections surveillance in Polish intensive care units. Przegl Epidemiol. 2018;72(1):33–44.Wałaszek M Różańska A Bulanda M Wojkowska-Mach J; Polish Society of Hospital Infections Team Alarming results of nosocomial bloodstream infections surveillance in Polish intensive care units Przegl Epidemiol 201872 1 33 44Search in Google Scholar

Watson D, Spaulding AB, Dreyfus J. Risk-set matching to assess the impact of hospital-acquired bloodstream infections. Am J Epidemiol. 2019 Feb 01;188(2):461–466. https://doi.org/10.1093/aje/kwy252Watson D Spaulding AB Dreyfus J Risk-set matching to assess the impact of hospital-acquired bloodstream infections Am J Epidemiol 2019 Feb 01188 2 461 466 https://doi.org/10.1093/aje/kwy25230475949Open DOISearch in Google Scholar

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