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International Nosocomial Infection Control Consortium (INICC) national report on device-associated infection rates in 19 cities of Turkey, data summary for 2003–2012

  • Hakan Leblebicioglu1,
  • Nurettin Erben2,
  • Victor Daniel Rosenthal3Email author,
  • Begüm Atasay4,
  • Ayse Erbay5,
  • Serhat Unal6,
  • Gunes Senol7,
  • Ayse Willke8,
  • Asu Özgültekin9,
  • Nilgün Altin10,
  • Mehmet Bakir11,
  • Oral Oncul12,
  • Gülden Ersöz13,
  • Davut Ozdemir14,
  • Ata Nevzat Yalcin15,
  • Halil Özdemir16,
  • Dinçer Yıldızdaş17,
  • Iftihar Koksal18,
  • Canan Aygun19,
  • Fatma Sirmatel20,
  • Alper Sener21,
  • Nazan Tuna22,
  • Özay Arikan Akan23,
  • Huseyin Turgut24,
  • A Pekcan Demiroz25,
  • Tanil Kendirli26,
  • Emine Alp27,
  • Cengiz Uzun28,
  • Sercan Ulusoy29 and
  • Dilek Arman30
Annals of Clinical Microbiology and Antimicrobials201413:51

https://doi.org/10.1186/s12941-014-0051-3

Received: 29 April 2014

Accepted: 24 October 2014

Published: 18 November 2014

Abstract

Background

Device-associated healthcare-acquired infections (DA-HAI) pose a threat to patient safety, particularly in the intensive care unit (ICU). We report the results of the International Infection Control Consortium (INICC) study conducted in Turkey from August 2003 through October 2012.

Methods

A DA-HAI surveillance study in 63 adult, paediatric ICUs and neonatal ICUs (NICUs) from 29 hospitals, in 19 cities using the methods and definitions of the U.S. NHSN and INICC methods.

Results

We collected prospective data from 94,498 ICU patients for 647,316 bed days. Pooled DA-HAI rates for adult and paediatric ICUs were 11.1 central line-associated bloodstream infections (CLABSIs) per 1000 central line (CL)-days, 21.4 ventilator-associated pneumonias (VAPs) per 1000 mechanical ventilator (MV)-days and 7.5 catheter-associated urinary tract infections (CAUTIs) per 1000 urinary catheter-days. Pooled DA-HAI rates for NICUs were 30 CLABSIs per 1000 CL-days, and 15.8 VAPs per 1000 MV-days. Extra length of stay (LOS) in adult and paediatric ICUs was 19.4 for CLABSI, 8.7 for VAP and 10.1 for CAUTI. Extra LOS in NICUs was 13.1 for patients with CLABSI and 16.2 for patients with VAP. Extra crude mortality was 12% for CLABSI, 19.4% for VAP and 10.5% for CAUTI in ICUs, and 15.4% for CLABSI and 10.5% for VAP in NICUs. Pooled device use (DU) ratios for adult and paediatric ICUs were 0.54 for MV, 0.65 for CL and 0.88 for UC, and 0.12 for MV, and 0.09 for CL in NICUs. The CLABSI rate was 8.5 per 1,000 CL days in the Medical Surgical ICUs included in this study, which is higher than the INICC report rate of 4.9, and more than eight times higher than the NHSN rate of 0.9. Similarly, the VAP and CAUTI rates were higher compared with U.S. NHSN (22.3 vs. 1.1 for VAP; 7.9 vs. 1.2 for CAUTI) and with the INICC report (22.3 vs. 16.5 in VAP; 7.9 vs. 5.3 in CAUTI).

Conclusions

DA-HAI rates and DU ratios in our ICUs were higher than those reported in the INICC global report and in the US NHSN report.

Keywords

Hospital infectionNosocomial infectionHealthcare-associated infectionINICCInternational Nosocomial Infection ConsortiumTurkeyDevice-associated infectionAntibiotic resistanceVentilator-associated pneumoniaCatheter-associated urinary tract infectionCentral line-associated bloodstream infectionsBloodstream infectionUrinary tract infectionNetwork

Background

Increasingly in scientific literature, DA-HAIs are considered to be among the principal threat to patient safety in the ICU and are among the main causes of patient morbidity and mortality [1],[2].

The effectiveness of implementing an integrated infection control programme focused on device-associated healthcare-acquired infection (DA-HAI) surveillance was demonstrated in the many studies conducted in the U.S., whose results reported not only that the incidence of DA-HAI can be reduced by as much as 30%, but that a related reduction in healthcare costs was also feasible [3]. In the same way, it is fundamental to address the burden of antimicrobial-resistant infections that the pathogens and the susceptibility to antimicrobials of DA-HAI-associated pathogens be reported, so that informed decisions can be made to effectively prevent transmission of resistant strains and their determinants, such as strains with phenotypes with very few available treatments with chances of success [4].

For more than 30 years, the U.S. the Centers for Disease Control and Prevention (CDC)’s National Healthcare Safety Network (NHSN) [5] has provided benchmarking U.S. ICU data on DA-HAIs, which have proven invaluable for researchers [5], and served as an inspiration to the INICC [6]. The INICC is an international non-profit, open, multi-centre, collaborative healthcare-associated infection control programme with a surveillance system based on that of the CDC’s NHSN [5]. Founded in Argentina in 1998, INICC is the first multinational research network established to measure, control and reduce DA-HAI in ICUs and surgical site infections (SSIs) hospital wide through the analysis of data collected on a voluntary basis by a pool of hospitals worldwide [6],[7]. The INICC has the following goals: To create a dynamic global network of hospitals worldwide and conduct surveillance of DA-HAIs and SSIs using standardized definitions and established methodologies, to promote the implementation of evidence-based infection control practices, and to carry out applied infection control research; to provide training and surveillance tools to individual hospitals which can allow them to conduct outcome and process surveillance of DA-HAIs and SSIs, to measure their consequences, and assess the impact of infection control practices; to improve the safety and quality of healthcare world-wide through the implementation of systematized programmes to reduce rates of DA-HAIs and SSIs, their associated mortality, excess lengths of stay (LOS), excess costs, antibiotic usage, and bacterial resistance [8].

This report is a summary of data on DA-HAIs collected in 63 intensive care units (ICUs) in 29 Turkish hospitals from 19 cities participating in the International Nosocomial Infection Control Consortium (INICC) between August 2003 and October 2012 [6],[7].

Methods

Setting and study design

This prospective cohort surveillance study was conducted in 63 adult, paediatric ICUs and neonatal ICUs (NICUs) from 29 hospitals in 19 cities. Hospitals were stratified by bed numbers (<200, 201–500, 501–1000, and >1000).

The ICUs were stratified according to the patient features: adult, paediatric or NICUs. The types of ICU participating in this study were the following: Cardiothoracic, Medical, Medical Cardiac, Medical/Surgical, Neurologic, Neurosurgical, Neonatal, Paediatric, Respiratory and Surgical.

According to the level of complexity of care, the NICUs included the following levels:

Level IIIA: It provides care to neonatal patients born at ≥28 weeks, who weigh ≥1,000 grams. The provide mechanical ventilation and minor surgical procedures, such as umbilical vessel catheterization.

Level IIIB: It provides care to neonatal patients born at any viable gestational age. Mechanical ventilation and high-frequency mechanical ventilation are provided. There are paediatric surgical centres on site or nearby to complete major surgical procedures.

Level IIIC: It provides the highest level of NICU care. In addition to the capabilities of Level IIIA and B, it provides extra corporeal membrane oxygenation and complicated surgical procedures requiring cardiopulmonary bypass are performed as well.

INICC methodology

The INICC is focused on the surveillance and prevention of DA-HAI in adult, paediatric ICUs and neonatal ICUs (NICUs), and of SSIs in surgical procedures hospital wide [6],[7]. The INICC has both outcome surveillance and process surveillance components. The modules of the components may be used singly or simultaneously, but, once selected; they must be used for a minimum of 1 calendar month. All DA-HAIs and SSIs of the Outcome Surveillance Component are categorized using standard NHSN definitions that include laboratory tests, radiology tests, and clinical criteria [9]. Laboratory-confirmed BSIs are recorded and reported [9].

The Outcome Surveillance Component related to DA-HAI classifies surveillance data into specific module protocols that include excess LOS, evaluation of DA-HAI costs, crude excess length of stay, crude excess mortality, microbiological profile, bacterial resistance, and antimicrobial-use data. Data on DA-HAI costs were not included in this report. Data from the INICC Process Surveillance Module, which includes monitoring of hand hygiene, vascular catheter care, urinary catheter care, and mechanical ventilator care compliance, were not included in this report.

Training, validation, and reporting

The INICC Chairman trained the principal and secondary investigators at hospitals. Investigators were also provided with a manual and training tool that described in detail how to perform surveillance and complete surveillance forms. In addition, investigators had continuous e-mail and telephone access to a support team at the INICC Central Office in Buenos Aires, Argentina.

Each month, participating hospitals submitted the completed surveillance forms to the INICC Central Office, where the validity of each case was checked and the recorded signs and symptoms of infection and the results of laboratory studies, radiographic studies, and cultures were scrutinized to assure that the U.S. NHSN criteria for DA-HAI had been met. The forms used for surveillance of each ICU patient permit both internal and external validation, because they include every clinical and microbiological criterion for each type of DA-HAI [6],[8]. Therefore, the investigator who reviewed the data forms filled in at the participating hospital verified that adequate criteria for infection had been fulfilled in each case; and the original patient data form was further validated at the INICC Central Office before data on the reported infection are entered into the INICC’s database.

Data collection

Using standardized INICC detailed forms and following the INICC protocol and U.S. NHSN’s definitions [9], infection control professionals (ICPs), trained and with previous experience conducting surveillance of DA-HAIs, collected data on central line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs) and ventilator-associated pneumonias (VAPs) in the ICUs.

In the NICUs, ICPs collected data on CLABSIs and umbilical catheter-associated primary bloodstream infections or VAPs for each of 5 birth-weight categories (<750 g, 750–1000 g, 1001 – 1500 g, 1501 – 2500 g, >2500 g), Corresponding denominator data, patient-days and specific device-days were also collected by the ICPs.

Detailed and aggregated data were used to calculate DA-HAI rates per 1000 device-days. Only prospective data using INICC patient detailed forms were used to calculate mortality and LOS.

In accordance with the INICC’s Charter, the identity of all INICC hospitals and cities is kept confidential.

Data analysis

Data for adult combined medical/surgical ICUs were not stratified by type or size of hospital. Data for NICUs were stratified by weight categories: central line-days, urinary catheter-days, or ventilator days.

Device-days consisted of the total number of central line (CL)-days, urinary catheter (UC)-days, or mechanical ventilator (MV)-days. For NICUs, device-days consisted of the total number of CL-days, UC-days, and MV-days.

Crude excess mortality of DA-HAI equals crude mortality of ICU patients with DA-HAI minus crude mortality of patients without DA-HAI.

Crude excess LOS of DA-HAI equals crude LOS of ICU patients with DA-HAI minus crude LOS of patients without DA-HAI.

Comparisons of the percentile distribution were made if there were at least 7 locations contributing to the strata.

EpiInfo® version 6.04b (CDC, Atlanta, GA) and SPSS 16.0 (SPSS Inc. an IBM company, Chicago, Illinois) were used to conduct data analysis. Relative risk (RR) ratios, 95% confidence intervals (CIs) and P-values were determined for primary and secondary outcomes.

Results

The characteristics of 63 ICUs from 29 hospitals in 19 cities from Turkey currently participating in INICC that contributed data for this report are shown in Table 1. The length of hospital’s participation in the INICC Programme is as follows: mean length of participation ± SD, 28.7 ± 25.7 months, range 3 to 85 months.
Table 1

Characteristics of the participating intensive care units

 

<200 beds hospitals

201-500 bed hospitals

501-1000 bed hospitals

>1000 bed hospitals

Overall

No. of hospitals

3 (10%)

8 (28%)

10 (34%)

8 (28%)

29 (100%)

No. of ICUs

4 (6%)

20 (32%)

29 (46%)

10 (16%)

63 (100%)

Medical Cardiac

1 (25%)

2 (50%)

1 (25%)

0 (0%)

4 (100%)

Cardiothoracic

0 (0%)

1 (33%)

1 (33%)

1 (33%)

3 (100%)

Medical

0 (0%)

4 (44%)

3 (33%)

2 (22%)

9 (100%)

Medical/Surgical

1 (5%)

5 (26%)

9 (47%)

4 (21%)

19 (100%)

Neonatal

1 (17%)

2 (33%)

2 (33%)

1 (17%)

6 (100%)

Neurologic

0 (0%)

0 (0%)

2 (100%)

0 (0%)

2 (100%)

Neurosurgical

0 (0%)

1 (33%)

2 (67%)

0 (0%)

3 (100%)

Paediatric

1 (14%)

1 (14%)

4 (57%)

1 (14%)

7 (100%)

Respiratory

0 (0%)

1 (50%)

1 (50%)

0 (0%)

2 (100%)

Surgical

0 (0%)

3 (38%)

4 (50%)

1 (13%)

8 (100%)

ICU, intensive care unit.

For the Outcome Surveillance Component, DA-HAI rates, device utilization (DU) ratios, crude excess mortality by specific type of DA-HAI, microorganism profile and bacterial resistance from August 2003 through October 2012 are summarized (Tables 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 and 13).
Table 2

Pooled means of central line-associated bloodstream infection rates, urinary catheter-associated urinary tract infection rates, and ventilator-associated pneumonia by hospital size

Hospital size, beds, n

ICUs, n

Patients, n

Bed days, n

CL days, n

CLABSI, n

CLABSI rate (95% CI)

MV days, n

VAP, n

VAP, Rate (95% CI)

UC days, n

CAUTI, n

CAUTI, rate (95% CI)

<200

3

713

14 706

9,459

41

4.3 (31 – 5.9)

7,536

40

5.3 (3.8 - 7.2)

10 621

43

4.0 (2.9 - 5.5)

201-500

18

23 896

167 058

88 917

382

4.3 (3.9 – 4.7)

84 714

2193

25.9 (24.8 - 26.9)

142 965

652

4.6 (4.2 - 4.9)

501-1000

27

61 350

382 283

189 728

1,939

10.2 (9.8 – 10.7)

142 735

3152

22.1 (21.3 - 22.8)

314 847

2957

9.4 (9.0 - 9.7)

>1000

9

5,109

4,914

31 432

329

10.5 (9.4 – 11.7)

37 310

431

11.6 (10.4 - 12.7)

42 106

180

4.3 (3.7 - 4.9)

Pooled

57

91 068

613,191

319 536

2,691

8.4 (8.1 – 8.7)

272 295

5,816

21.4 (20.8 - 21.9)

510 539

3,832

7.5 (7.3 - 7.7)

Adult and Paediatric Patients. DA module, 2003-2012

ICU, intensive care units; CL, central line; CLABSI, central line-associated bloodstream infection; CI, confidence interval; MV, mechanical ventilator; VAP, ventilator-associated pneumonia; UC, urinary catheter; CAUTI, catheter-associated urinary tract infection.

Table 3

Pooled means of central line-associated bloodstream infection rates, and ventilator-associated pneumonia by hospital size

Hospital size, beds, n

ICUs, n

Patients, n

Bed days, n

CL days

CLABSI, N

CLABSI rate (95% CI)

MV days, n

VAP, n

VAP, rate (95% CI)

<200

1

440

4,457

269

29

107.8 (72.2 – 154.8)

273

11

40.3 (20.2 - 70.9)

201-500

2

383

4,834

1706

6

3.5 (1.3 – 7.7)

1,206

19

15.8 (9.0 - 24.5)

501-1000

2

1,442

16 826

2206

51

23.1 (17.2 – 30.4)

3,046

28

9.2 (6.1 - 13.2)

>1000

1

1,165

8,008

1049

24

22.9 (14.7 – 34.0)

985

29

29.4 (19.8 - 42.0)

Pooled

6

3,430

34 125

5,230

110

21.0 (17.3 – 25.3)

5,510

87

15.8 (12.6 - 19.5)

Neonatal Patients. DA module, 2003–2012.

ICU, intensive care units; CL, central line; CLABSI, central line-associated bloodstream infection; CI, confidence interval; MV, mechanical ventilator; VAP, ventilator-associated pneumonia.

Table 4

Pooled means and key percentiles of the distribution of central line-associated bloodstream infection rates, by type of location, adult and paediatric patients

Type of ICU

ICU, n

Patients

Bed days

CL days

CLABSI, n

CLABSI rate

95% CI

Percentiles*

10

25

50

75

90

Medical Cardiac

4

5,380

22 743

10 838

46

4.2

3.1 – 5.7

-

-

-

-

-

Cardiothoracic

3

7,800

21 796

15 165

22

1.5

0.9 – 2.2

-

-

-

-

-

Medical

9

21 854

170 042

79 343

525

6.6

6.1 – 7.2

2.5

3.8

7.3

11.1

-

Medical/Surgical

19

19 410

175 470

113 597

969

8.5

8.0 – 9.1

0.0

4.2

11.7

15.1

18.3

Neurologic

2

3,784

30 966

8,690

91

10.5

8.4 – 12.9

-

-

-

-

-

Neurosurgical

3

5,691

39 719

18 579

103

5.5

4.5 – 6.7

-

-

-

-

-

Paediatric

7

4,235

32 148

12 880

122

9.5

7.9 – 11.3

0.0

2.7

10.6

13.6

-

Respiratory

2

1,754

14 054

4,950

59

11.9

9.1 – 15.4

-

-

-

-

-

Surgical

8

21 160

106 253

55 494

754

13.6

12.6 – 14.6

1.6

3.5

9.8

17.2

-

Pooled

57

91 068

613 191

319 536

2,691

8.4

8.1 – 8.7

1.0

3.9

8.6

13.8

18.2

DA module, 2003–2012.

ICU, intensive care unit; CL, central line; CLABSI, central line-associated bloodstream infection; CI, confidence interval.

*Comparisons of the percentile distribution were made if there were at least 7 locations contributing to the strata.

Table 5

Pooled means of the distribution of central line-associated bloodstream infection rates for level III NICUs, stratified by birth-weight category

Birth-weight category

ICU, n

Patients

Bed days

CL days

CLABSI, n

CLABSI rate

95% CI

<750 grams

4

98

617

250

9

36.0

16.5 – 68.3

751-1000 grams

6

297

4,197

1,639

30

18.3

12.3 – 26.1

1001-1500 grams

6

649

10 652

1,465

48

32.8

24.2 – 43.4

1501-2500 grams

6

1,202

10 998

1,024

8

7.8

3.4 – 15.4

>2500 grams

6

1,184

7,661

852

15

17.6

9.9 – 29.0

Pooled

6

3,430

34 125

5,230

110

21.0

17.3 – 25.3

DA module, 2003–2012.

ICU, intensive care unit; CL, central line; CLABSI, central line-associated bloodstream infection; CI, confidence interval.

Table 6

Pooled means and key percentiles of the distribution of ventilator-associated pneumonia rates, by type of location, adult and paediatric patients

Type of ICU

ICUs, n

Patients

Bed days

MV days

VAP, n

VAP rate

95% CI

Percentiles*

10

25

50

75

90

Medical Cardiac

4

5, 380

22 743

5,820

58

10.0

7.6 –12.9

-

-

-

-

-

Cardiothoracic

3

7,800

21 796

9,993

123

12.3

10.2 – 14.7

-

-

-

-

-

Medical

9

21 854

170 042

82 378

1836

22.3

21.3 – 23.3

8.3

12.6

22.1

32.7

-

Medical/Surgical

19

19 410

175 470

95 021

2116

22.3

21.3 – 23.2

9.6

12.8

16.5

28.6

42.9

Neurologic

2

3,784

30 966

7,405

176

23.8

20.4 – 27.6

-

-

-

-

-

Neurosurgical

3

5,691

39 719

8,859

252

28.4

25.0 – 32.2

-

-

-

-

-

Paediatric

7

4,235

32 148

17 068

200

11.7

10.2 – 13.5

2.9

6.2

10.6

14.1

-

Respiratory

2

1,754

14 054

8,156

204

25.0

21.7 – 28.7

-

-

-

-

-

Surgical

8

21 160

106 253

37 595

851

22.6

21.1 – 24.2

12.6

18.5

21.9

26.7

-

Pooled

57

91 068

613 191

272 295

5,816

21.4

20.8 – 21.9

7.2

11.2

20.5

27.7

35.4

DA module, 2003–2012.

ICU, intensive care unit; MV, mechanical ventilator; VAP, ventilator-associated pneumonia; CI, confidence interval.

*Comparisons of the percentile distribution were made if there were at least 7 locations contributing to the strata.

Table 7

Pooled means of the distribution of ventilator-associated pneumonia rates for level III NICUs, stratified by Birth-weight category

Birth-weight category

ICUs, n

Patients

Bed days

MV days

VAP, n

VAP rate

95% CI

<750 grams

4

98

617

236

4

16.9

4.6 – 43.4

751-1000 grams

6

297

4197

1,407

25

17.8

11.5 – 26.2

1001-1500 grams

6

649

10 652

1,307

19

14.5

8.8 – 22.7

1501-2500 grams

6

1,202

10 998

1,318

19

14.4

8.7 – 22.5

>2500 grams

6

1,184

7,661

1,242

20

16.1

9.8 – 24.9

Pooled

6

3,430

34 125

5,510

87

15.8

12.6 – 19.5

DA module, 2003-2012.

ICU, intensive care unit; MV, mechanical ventilator; VAP, ventilator-associated pneumonia; CI, confidence interval.

Table 8

Pooled means and key percentiles of the distribution of urinary catheter-associated urinary tract infection rates, by type of location, adult and paediatric patients

Type of ICU

ICU, n

Patients

Bed days

UC days

CAUTI, n

CAUTI, rate

95% CI

Percentiles*

10

25

50

75

90

Medical Cardiac

4

5,380

22 743

14 907

49

3.3

2.4 - 4.3

-

-

-

-

-

Cardiothoracic

3

7,800

21 796

18 744

68

3.6

2.8 - 4.6

-

-

-

-

-

Medical

9

21 854

170 042

143 455

739

5.2

4.8 - 5.5

2.1

2.8

4.0

8.9

-

Medical/Surgical

19

19 410

175 470

154 422

1,220

7.9

7.5 - 8.4

2.1

2.8

5.8

9.1

13.7

Neurologic

2

3,784

30 966

29 856

596

20.0

18.4 - 21.6

-

-

-

-

-

Neurosurgical

3

5,691

39 719

36 688

347

9.5

8.5 - 10.5

-

-

-

-

-

Paediatric

7

4,235

32 148

10 981

73

6.6

5.2 - 8.4

1.1

1.8

3.9

10.7

-

Respiratory

2

1,754

14 054

12 833

50

3.9

2.9 - 5.1

-

-

-

-

-

Surgical

8

21 160

106 253

88 653

690

7.8

7.2 - 8.4

1.7

2.8

5.5

8.9

-

Pooled

57

91 068

613 191

510 539

3,832

7.5

7.3 - 7.7

1.7

2.6

4.9

8.5

14.2

DA module, 2003–2012.

ICU, intensive care unit; UC, urinary catheter; CAUTI, catheter-associated urinary tract infection; CI, confidence interval.

*Comparisons of the percentile distribution were made if there were at least 7 locations contributing to the strata.

Table 9

Pooled means of the distribution of central line utilization ratios, urinary catheter utilization ratios, and ventilator utilization ratios, by type of location, adult and paediatric patients

ICU type

ICU, n

Bed days

CL days

DUR, central line (95% CI)

MV days

DUR, MV (95% CI)

UC days

DUR, UC (95% CI)

Medical Cardiac

4

22 743

10 838

0.48 (0.47 – 0.48)

5,820

0.26 (0.25 – 0.26)

14 907

0.66 (0.65 – 0.66)

Cardiothoracic

3

21 796

15 165

0.70 (0.69 – 0.70)

9,993

0.46 (0.45 – 0.47)

18 744

0.86 (0.86 – 0.86)

Medical

9

170 042

79 343

0.47 (0.46 – 0.47)

82 378

0.48 (0.48 – 0.49)

143 455

0.84 (0.84 – 0.85)

Medical/Surgical

19

175 470

113 597

0.65 (0.65 – 0.65)

95 021

0.54 (0.54 – 0.54)

154 422

0.88 (0.88 – 0.88)

Neurologic

2

30 966

8,690

0.28 (0.28 – 0.29)

7,405

0.24 (0.23 – 0.24)

29 856

0.96 (0.96 – 0.97)

Neurosurgical

3

39 719

18 579

0.47 (0.46 – 0.47)

8,859

0.22 (0.22 – 0.23)

36 688

0.92 (0.92 – 0.93)

Paediatric

7

32 148

12 880

0.40 (0.40 – 0.41)

17 068

0.53 (0.53 – 0.54)

10 981

0.34 (0.34 – 0.35)

Respiratory

2

14 054

4,950

0.35 (0.34 – 0.36)

8,156

0.58 (0.57 – 0.59)

12 833

0.91 (0.91 – 0.92)

Surgical

8

106 253

55 494

0.52 (0.52 – 0.53)

37 595

0.35 (0.35 – 0.36)

88 653

0.83 (0.83 – 0.84)

Pooled

57

613 191

319 536

0.52 (0.52 – 0.52)

272 295

0.44 (0.44 – 0.45)

510 539

0.83 (0.83 – 0.83)

DA module, 2003–2012.

ICU, intensive care unit; CL, central line; MV, mechanical ventilator; UC, urinary catheter; DUR, device use ratio; CI, confidence interval.

Table 10

Pooled means of the distribution of central line utilization ratios and ventilator utilization ratios, by type of location, for level III NICUs

Birth-weight category

ICU, n

Bed days

CL days

DUR, central line (95% CI)

MV days

DUR, MV (95% CI)

<750 grams

4

617

250

0.41 (0.37 – 0.45)

236

0.38 (0.34 – 0.42)

751-1000 grams

6

4197

1639

0.39 (0.38 – 0.41)

1407

0.34 (0.32 – 0.35)

1001-1500 grams

6

10652

1465

0.14 (0.13 – 0.14)

1307

0.12 (0.12 – 0.13)

1501-2500 grams

6

10998

1024

0.09 (0.09 – 0.10)

1318

0.12 (0.11 – 0.13)

>2500 grams

6

7661

852

0.11 (0.10 – 0.12)

1242

0.16 (0.15 – 0.17)

<750 grams

6

34125

5230

0.15 (0.15 – 0.16)

5510

0.16 (0.16 – 0.17)

DA module, 2003–2012.

ICU, intensive care unit; CL, central line, MV, mechanical ventilator; DUR, device use ratio; CI, confidence interval.

Table 11

Pooled means of the distribution of crude mortality and crude excess mortality of adult and paediatric intensive care unit patients with and without device-associated healthcare-acquired infection

Adult and paediatric ICUs combined

No. of deaths

No. of patients

Pooled crude mortality, % (95% CI)

RR (95% CI)

Crude mortality of patients without DA-HAI

1,616

6,408

25.2 (24.1- 26.3)

1.0

Crude mortality of patients with CLABSI

133

357

37.3 (32.2- 42.4)

1.5 (1.2 – 1.8)

Crude excess mortality of patients with CLABSI

133

357

12.0 (8.1- 16.1)

-

Crude mortality of patients with CAUTI

55

154

35.7 (28.1- 43.8)

1.4 (1.1 – 1.9)

Crude excess mortality of patients with CAUTI

55

154

10.5 (4.0- 17.5)

-

Crude mortality of patients with VAP

253

567

44.6 (40.4- 48.8)

1.8 (1.6 – 2.0)

Crude excess mortality of patients with VAP

253

567

19.4 (16.3- 22.5)

-

Neonatal ICUs combined

No. of deaths

No. of patients

Pooled crude mortality, % (95% CI)

 

Crude mortality of patients without DA-HAI

68

1,964

3.5 (2.7- 4.4)

1.0

Crude mortality of patients with CLABSI

10

53

18.9 (9.4- 32.7)

5.5 (2.8 – 10.6)

Crude excess mortality of patients with CLABSI

10

53

15.4 (6.7- 28.3)

-

Crude mortality of patients with VAP

6

43

14.0 (5.3- 27.9)

4.0 (1.8 – 9.3)

Crude excess mortality of patients with VAP

6

43

10.5 (2.6- 23.5)

-

ICU, intensive care units; CI, confidence interval; DA-HAI, device-associated healthcare-acquired infection; CLABSI, central line-associated bloodstream infection; VAP, ventilator-associated pneumonia; CAUTI, catheter-associated urinary tract infection; RR, relative risk.

Table 12

Pooled means of the distribution of the length of stay and crude excess length of stay of intensive care unit patients with and without device-associated healthcare-acquired infection

Adult and paediatric ICUs combined

LOS, total days

No. of patients

Pooled average. LOS, days (95% CI)

RR (95% CI)

LOS of patients without DA-HAI

50 716

6,408

7.9 (7.8-7.9)

 

LOS of patients with CLABSI

6,920

357

19.4 (17.5-21.6)

2.4 (2.4 – 2.5)

Extra LOS of patients with CLABSI

6,920

357

11.5 (9.7-13.7)

 

LOS of patients with CAUTI

2,769

154

18.0 (15.4-21.2)

2.3 (2.2 – 2.3)

Extra LOS of patients with CAUTI

2,769

154

10.1 (7.6-13.3)

 

LOS of patients with VAP

9,426

567

16.6 (15.3-18.1)

2.1 (2.0 – 2.1)

Extra LOS of patients with VAP

9,426

567

8.7 (7.5-10.2)

 

Neonatal ICUs combined

LOS, total days

No. of patients

Pooled average LOS, days

 

LOS of patients without DA-HAI

17,547

1,964

8.9 (8.5-9.3)

 

LOS of patients with CLABSI

1,169

53

22.1 (16.9-29.5)

2.6 (2.3 – 2.6)

Extra LOS of patients with CLABSI

1,169

53

13.1 (16.9-9.5)

 

LOS of patients with VAP

1,081

43

25.1 (18.7-35.7)

2.8 (2.6 – 3.0)

Extra LOS of patients with VAP

1,081

43

16.2 (18.7-35.7)

 

LOS, length of stay; DA-HAI, device-associated healthcare-acquired infection; CLABSI, central line-associated bloodstream infection; VAP, ventilator-associated pneumonia; CAUTI, catheter-associated urinary tract infection.

Table 13

Antimicrobial resistance rates in the participating intensive care units

 

Pathogenic isolated tested, pooled, n

Resistance, %

Pathogenic isolated tested, pooled, n

Resistance, %

Pathogenic isolated tested, pooled, n

Resistance, %

Pathogen, antimicrobial

(CLABSI)

(CLABSI)

(VAP)

(VAP)

(CAUTI)

(CAUTI)

Staphylococcus aureus

      

Oxacilin

478

92.7%

482

83.2%

22

81.8%

Coagulase- negative staphylococci

      

Oxacilin

516

90.3%

69

81.2%

14

71.4%

Enterococcus faecalis

      

Vancomycin

80

5.0%

10

0.0%

36

0.0%

Pseudomonas aeruginosa

      

Ciprofloxacine

201

35.3%

719

40.6%

89

36.0%

Piperacillin or piperacillin-tazobactam

279

27.6%

1,009

33.8%

124

31.5%

Amikacin

185

18.9%

671

18.3%

81

16.0%

Imipenem or meropenem

251

37.1%

989

41.0%

122

33.6%

Klebsiella pneumoniae

      

Ceftriaxone or ceftazidime

140

55.7%

160

46.3%

28

50.0%

Imipenem or meropenem

189

6.3%

224

4.5%

73

1.4%

Acinetobacter baumanii

      

Imipenem or meropenem

469

56.1%

844

62.8%

73

57.5%

Escherichia Coli

      

Ceftriaxone or ceftazidime

67

55.2%

77

44.2%

78

51.3%

Imipenem or meropenem

68

4.4%

141

3.5%

132

2.3%

Ciprofloxacine

65

66.2%

110

50.0%

104

33.7%

CLABSI, central line-associated bloodstream infection; VAP, ventilator-associated pneumonia; CAUTI, catheter-associated urinary tract infection.

Table 2 shows DA-HAI rates by infection type (CLABSI, CAUTI, VAP) in adult and paediatric ICUs stratified by hospital size and Table 3 shows the same information regarding NICUs. In adult and paediatric patients, we found higher rates of CLABSI in the largest hospitals (>500 beds), however, VAP and CAUTI rates were higher in middle-sized hospitals (201–1000 beds). In NICU patients the rates of CLABSI and VAP were higher in the smallest hospitals (<200 beds).

Tables 4, 5, 6, 7 and 8 show DA-HAI rates in all the participating ICUs, and in those cases that include NICU patients (Tables 5 and 7), the information is divided by weight category. We found that in adult and paediatric patients the highest CLABSI rate was found in the Surgical ICUs, the highest VAP rate in Neurosurgical ICU, and the highest CAUTI rate in Neurologic ICUs. Regarding NICU patients, the highest CLABSI rate was found in patients within the 1000–1500 grams weight category, and the highest VAP rate was found in patients in the 751–1000 grams weight category.

Tables 9 and 10 provide data on device use ratios (DURs) for CL, UC and MV and their respective confidence intervals. Central line DUR was higher in the cardiothoracic ICUs, the mechanical ventilator DUR was higher in respiratory ICUs, and the urinary catheter DUR was higher in neurologic ICUs. In the NICU patients the highest DUR for central line and mechanical ventilator were found in <750 grams birth weight category.

Table 11 provides data on crude ICU mortality in patients hospitalized in each type of unit during the surveillance period, with and without DA-HAI, and crude excess mortality of adult and paediatric patients with CLABSI, CAUTI, and VAP, and infants in NICUs with CLABSI or VAP. The DA-HAI associated with a higher mortality was VAP in adult and paediatric patients and CLABSI in NICU patients.

Table 12 provides data on crude LOS of patients hospitalized in each ICU during the surveillance period with and without DA-HAI and crude excess LOS of adult and paediatric patients with CLABSI, CAUTI, and VAP and infants in NICUs with CLABSI or VAP. The DA-HAI associated with a longer LOS was CLABSI in adult and paediatric patients and VAP in NICU patients.

Table 13 provides data on bacterial resistance of pathogens isolated from patients with DA-HAI in adult and paediatric ICUs and NICUs. We found a high resistance of Staphylococci aureus and Coagulase-negative staphylococci to oxacilin in CLABSIs, VAP and CAUTIs.

Tables 14 and 15 compare the results of this report from Turkey with the INICC international report for the period 2007–2012 and with NHSN report of 2011 [5],[10]. Overall, we found higher DA-HAI rates in this study than in INICC and NHSN data, as shown in Table 14. DUR was higher in most cases as well, but the central line DUR was lower in paediatric ICUs and NICUs compared to NHSN. Table 15 compares the antimicrobial resistance rates of this report from Turkey with the INICC international report for the period 2007–2012 and with NHSN report of 2010–2012. In most cases, we found higher resistance rates than those found in the NHSN report.
Table 14

Benchmarking of device-associated healthcare-acquired infection rates in this report against the report of the International Nosocomial Infection Control Consortium (2007–20012) and the report of the US National Healthcare Safety Network Data (2011)

 

This report

INICC report (2007–2012) [ [10]]

U.S. NHSN report (2011) [ [5]]

Medical surgical ICU

   

CL, DUR

0.65 (0.65 – 0.65)

0.54 (0.54 – 0.54)

0.35 (0.35 – 0.35)

CLABSI rate

8.5 (8.0 – 9.1)

4.9 (4.8 – 5.1)

0.9 (0.8 - 0.9)

MV, DUR

0.54 (0.54 – 0.54)

0.36 (0.36 – 0.36)

0.24 (0.24 – 0.24)

VAP rate

22.3 (21.3 - 23.2)

16.5 (16.1 – 16.8)

1.1 (9.8 - 1.2)

UC, DUR

0.88 (0.88 – 0.88)

0.62 (0.62 – 0.62)

0.54 (0.54 – 0.54)

CAUTI rate

7.9 (7.5 - 8.4)

5.3 (5.2 – 5.8)

1.2 (1.1 - 1.3)

Paediatric ICU

   

CL, DUR

0.40 (0.40 – 0.41)

0.50 (0.50 – 0.50)

0.47 (0.46 – 0.47)

CLABSI rate

9.5 (7.9 – 11.3)

6.1 (5.7 – 6.5)

1.8 (1.6 - 1.9)

MV, DUR

0.53 (0.53 – 0.54)

0.53 (0.53 – 0.53)

0.40 (0.40 – 0.40)

VAP rate

11.7 (10.2 - 13.5)

7.9 (7.4 – 8.4)

1.1 (9.0 - 1.2)

UC, DUR

0.34 (0.34 – 0.35)

0.31 (0.31 – 0.32)

0.23 (0.22 – 0.23)

CAUTI rate

6.6 (5.2 - 8.4)

5.6 (5.1 – 6.1)

3.1 (2.7 - 3.5)

Neonatal ICU (weight 1501 to 2500 grams)

   

CL, DUR

0.09 (0.09 – 0.10)

0.21 (0.20 – 0.21)

0.18 (0.18 – 0.19)

CLABSI rate

7.8 (3.4 – 15.4)

4.8 (3.7 – 6.1)

0.7 (0.6 - 0.9)

MV, DUR

0.12 (0.11 – 0.13)

0.10 (0.10 – 0.11)

0.07 (0.07 – 0.07)

VAP rate

14.4 (8.7 - 22.5)

10.7 (8.4 – 13.4)

0.5 (0.2 - 0.9)

ICU, intensive care unit; CLABSI, central line-associated bloodstream infection; VAP, ventilator-associated pneumonia; CAUTI, catheter-associated urinary tract infection; DUR, device use ratio; INICC, International Nosocomial Infection Control Consortium; U.S. NSHN, National Healthcare Safety Network of the United States of America.

Table 15

Benchmarking of antimicrobial resistance rates in this report against the report of the International Nosocomial Infection Control Consortium (2007–20012) and the report of the US National Healthcare Safety Network Data (2009–2010)

 

This report resistance %

INICC 2007–2012 resistance %

NHSN 2009–2010 resistance, %

Pathogen, antimicrobial

(CLABSI)

(CLABSI)

(CLABSI)

Staphylococcus aureus

   

Oxacillin

92.7%

61.2%

54.6%

Enterococcus faecalis

   

Vancomycin

5.0%

12.2%

9.5%

Pseudomonas aeruginosa

   

Ciprofloxacine

35.3%

37.5%

30.5%

Piperacillin or piperacillin-tazobactam

27.6%

33.5%

17.4%

Amikacin

18.9%

42.8%

10.0%

Imipenem or meropenem

37.1%

42.4%

26.1%

Klebsiella pneumoniae

   

Ceftriaxone or ceftazidime

55.7%

71.2%

28.8%

Imipenem or meropenem

6.3%

19.6%

12.8%

Acinetobacter baumanii

   

Imipenem or meropenem

56.1%

66.3%

62.6%

Escherichia Coli

   

Ceftriaxone or ceftazidime

55.2%

65.9%

19.0%

Imipenem or meropenem

4.4%

8.5%

1.9%

Ciprofloxacine

66.2%

69.3%

41.8%

CLABSI, central line-associated bloodstream infection.

Discussion

Within the scientific literature addressing the burden of DA-HAIs in Turkey’s ICUs, in a recent study it was shown that the DA-HAI rates found in their setting were higher than the rates reported by the U.S. NHSN and INICC [11]. The CLABSI rate of our study was similar to the rate found in another study conducted in Turkey showing 11.8 CLABSIs per 1000 CL days [11]. Likewise, our CAUTI rate was similar to the findings of another study from ICUs in Turkey, showing 8.3 CAUTIs per 1000 UC days [12]. The VAP rate in our study was 21.4 per 1000 MV-days in adult and paediatric ICUs. Similarly, in 2008, Erdem et al. found a rate of 22.6 VAPs per 1000 MV-days [13], and Leblebicioglu et al. found a global VAP rate of 26.5 VAPs per 1000 MV-days in a multi-site study carried out in 12 hospitals in 2007 [12].

In our Turkish ICUs, DA-HAI rates and pooled DU ratios were higher than the Global INICC Report and U.S. NHSN’s data [5],[6]. Likewise, the antimicrobial resistance rates found in our ICUs were higher than U.S. NHSN [4] and INICC [6] report rates for Staphyloccocus aureus as resistant to oxacillin, and for Escherichia Coli as resistant for imipenem. The resistance of Escherichia Coli to ciprofloxacin also higher than than U.S. NHSN [4], but similar to INICC report. [6] On the other hand, the resistance rates for Pseudomonas aeruginosa were higher in this study than U.S. NHSN report [4], but lower than the INICC reported resistance rates [6], as resistant to ciprofloxacin, piperacillin-tazobactam, amikacin and imipenem or meropenem; for Escherichia Coli as resistant to ceftriaxone and ceftazidime; and for Klebsiella pneumonia as resistant to ceftriaxone or ceftazidime. By contrast, the resistance rates for Klebsiella pneumonia and Acinetobacter baumanii as resistant to imipenem and meropenem, and Enterococcus faecalis as resistant to vancomycin, were lower in this study than in INICC and U.S. NHSN reports [4],[6].

These high DA-HAI rates may reflect the typical ICU situation in hospitals in Turkey [14], and several reasons have been exposed to explain this fact [11],[15]. Among the primary plausible causes, it can be mentioned that, in Turkey there are still no legally enforceable rules or regulations concerning the implementation of infection control programs, such as national infection control guidelines; yet, in the few cases in which there is a legal framework, adherence to the bundles is most irregular and hospital accreditation is not mandatory [16]. This situation is further emphasized by the fact that administrative and financial support is insufficient to fund infection control programmes, and invariably results in extremely low nurse-to-patient staffing ratios–which have proved to be highly connected to high DA-HAI rates in ICUs—, hospital over-crowding, lack of medical supplies, out-dated medical supplies and in an insufficient number of experienced nurses or trained healthcare workers [14].

In order to reduce the hospitalized patients’ risk of infection, DA-HAI surveillance is primary and essential, because it effectively describes and addresses the importance and characteristics of the threatening situation created by DA-HAIs. This must be followed by the implementation of practices aimed at DA-HAI prevention and control. Additionally, participation in INICC has played a fundamental role, not only in increasing the awareness of DA-HAI risks in the ICU, but also providing an exemplary basis for the institution of infection control practices. Finally, it is of utmost importance to restrict the administration of anti-infective in order to effectively control of antibiotic resistance.

The INICC programme is focused on surveillance of DA-HAIs in the ICU and surveillance of SSIs hospital wide; that is, healthcare settings (ICUs) and procedures (Surgical Procedures) with the highest healthcare-acquired rates, in which patients’ safety is most seriously threatened, due to their critical condition and exposure to invasive devices and surgical procedures [16]. Through the last 12 years, INICC has undertaken a global effort in America, Asia, Africa, Middle East, and Europe to respond to the burden of DA-HAIs, and has achieved extremely successful results, by increasing HH compliance, improving compliance with other infection control bundles and interventions as described in several INICC publications, and consequently reducing the rates of DA-HAI and mortality [6],[17]-[21].

To compare a hospital's DA-HAI rates with the rates identified in this report, it is required that the hospital concerned start by collecting their data by applying the methods and methodology described for U.S. NHSN and INICC, and then calculate infection rates and DU ratios for the DA-HAI Module.

The particular and primary application of these data is to serve as a guide for the implementation of prevention strategies and other quality improvement efforts locally for the reduction of DA-HAI rates to the minimum possible level.

Study limitations

The findings in this report are subject to at least two limitations. First, we did not consider the difference in time periods for the different data sources in the comparisons made with INICC and U.S. NHSN. Second, it is unfortunate that the study did not include data on possible changes in DA-HAIs in Turkey throughout the study period.

Conclusions

In conclusion, the data presented in this report fortify the fact that DA-HAIs in Turkey pose a grave and many times concealed risk to patient safety, as compared to the developed world. It is INICC’s main goal to enhance infection control practices, by facilitating elemental, feasible and inexpensive tools and resources to tackle this problem effectively and systematically, leading to greater and stricter adherence to infection control programs and guidelines, and to the correlated reduction in DA-HAI and its adverse effects, in the hospitals participating in INICC, as well as at any other healthcare facility worldwide.

Declarations

Acknowledgments

The authors thank the many healthcare professionals at each member hospital who assisted with the conduct of surveillance in their hospital; Mariano Vilar and Débora López Burgardt, who work at INICC headquarters in Buenos Aires; the INICC Country Coordinators and Secretaries (Altaf Ahmed, Carlos A. Álvarez-Moreno, Anucha Apisarnthanarak, Luis E. Cuéllar, Bijie Hu, Namita Jaggi, Hakan Leblebicioglu, Montri Luxsuwong, Eduardo A. Medeiros, Yatin Mehta, Ziad Memish, Toshihiro Mitsuda, and Lul Raka,); and the INICC Advisory Board (Carla J. Alvarado, Nicholas Graves, William R. Jarvis, Patricia Lynch, Dennis Maki, Gerald McDonnell, Toshihiro Mitsuda, Cat Murphy, Russell N. Olmsted, Didier Pittet, William Rutala, Syed Sattar, and Wing Hong Seto), who have so generously supported this unique international infection control network.

List of the remaining co-authors

Ilhan Ozgunes, Gaye Usluer (Eskisehir Osmangazi University, Eskisehir); Atila Kiliç,Saadet Arsan (Ankara University School of Medicine, Faculty of Pediatrics, Department of Newborn Medicine, Ankara); Hatice Cabadak, Suha Sen (Turkiye Yuksek Ihtisas Education and Research Hospital, Ankara ) Yasemin Gelebek, Humeyra Zengin, Arzu Topeli , Yusuf Alper (Hacettepe University School of Medicine, Ankara); Meliha Meric, Emel Azak, (Kocaeli University Faculty of Medicine, Kocaeli); Asuman İnan, Güldem Turan (Haydarpaşa Numune Training and Research Hospital, Istanbul); Tuncer Haznedaroglu, Levent Gorenek, Ali Acar (Gulhane Military Medical Academy, Haydarpasa Training Hospital, Istanbul); Salih Cesur (Etlik İhtisas Training and Education Hospital, Ankara); Aynur Engin (Cumhuriyet University School of Medicine, Sivas); Ali Kaya, Necdet Kuyucu, (Mersin University, Faculty of Medicine, Mersin); Mehmet Faruk Geyik, Özlem Çetinkaya Aydın, Nurse Selvi Erdogan (Duzce University Medical School Infectious Diseases and Clinical Microbiology, Duzce); Ozge Turhan, Nurgul Gunay RN, Eylul Gumus RN Chief, Oguz Dursun (Akdeniz University, Antalya); Saban Esen, Fatma Ulger, Ahmet Dilek, Hava Yilmaz, Mustafa Sunbul (Ondokuz Mayis University Medical School, Samsun); Zeynel Gökmen, Sonay İncesoy Özdemir (Konya Training and Research Hospital, Konya); Ozden Ozgur Horoz (Çukurova University Balcali Hospital, Adana); Gürdal Yýlmaz, Selçuk Kaya, Hülya Ulusoy (Karadeniz Technical University School of Medicine, Trabzon); Sukru Küçüködük (Ondokuz Mayis University Medical School (Neo), Sansun); Cemal Ustun (Abant Izzet Baysal University Hospital, Infectious Diseases & Clinical Microbiology, Bolu); Metin Otkun (Onsekiz Mart University Canakkale, Canakkale); Melek Tulunay, Mehmet Oral, Necmettin Ünal (Ankara University School of Medicine Ibni-Sina Hospital, Ankara); Mustafa Cengiz, Leyla Yilmaz (Harran University, Faculty of Medicine, Sanliurfa); Suzan Sacar, Hülya Sungurtekin, Doğaç Uğurcan (Pamukkale University, Denizli); M. Arzu Yetkin, Cemal Bulut, F. Sebnem Erdinc, Cigdem Ataman Hatipoglu (Ankara Training and Research Hospital, Ankara); Erdal İnce, Ergin Çiftçi, Çağlar Ödek, Ayhan Yaman, Adem Karbuz, Bilge Aldemir (Ankara University School of Medicine, Department of Paediatric Critical Care Medicine, Ankara); Aysegul Ulu Kılıc (Erciyes University, Faculty of Medicine, Kayseri); Bilgin Arda, Feza Bacakoglu (Ege University Medical Faculty, Izmir); Kenan Hizel (Gazi University Medical School, Ankara).

Funding

The funding for the activities carried out at INICC head quarters were provided by the corresponding author, Victor D. Rosenthal, and Foundation to Fight against Nosocomial Infections.

Authors’ Affiliations

(1)
Ondokuz Mayis University Medical School, Samsun, Turkey
(2)
Eskisehir Osmangazi University, Eskisehir, Turkey
(3)
International Nosocomial Infection Control Consortium, Corrientes, Argentina
(4)
Department of Newborn Medicine, Ankara University School of Medicine, Faculty of Paediatrics, Ankara, Turkey
(5)
Turkiye Yuksek Ihtisas Education and Research Hospital, Ankara, Turkey
(6)
Hacettepe University School of Medicine, Ankara, Turkey
(7)
Suat Seren Chest Diseases and Chest Surgery Training Hospital, Izmir, Turkey
(8)
Kocaeli University Faculty of Medicine, Kocaeli, Turkey
(9)
Haydarpaşa Numune Training and Research Hospital, Istanbul, Turkey
(10)
Etlik İhtisas Training and Education Hospital, Ankara, Turkey
(11)
Cumhuriyet University School of Medicine, Sivas, Turkey
(12)
Gulhane Military Medical Academy, Haydarpasa Training Hospital, Istanbul, Turkey
(13)
Mersin University, Faculty of Medicine, Mersin, Turkey
(14)
Duzce University Medical School Infectious Diseases and Clinical Microbiology, Duzce, Turkey
(15)
Akdeniz University, Antalya, Turkey
(16)
Konya Training and Research Hospital, Konya, Turkey
(17)
Çukurova University Balcali Hospital, Adana, Turkey
(18)
Karadeniz Technical University School of Medicine, Trabzon, Turkey
(19)
Ondokuz Mayis University Medical School (Neonatal Unit), Samsun, Turkey
(20)
Abant Izzet Baysal University, Bolu, Turkey
(21)
Onsekiz Mart University Canakkale, Canakkale, Turkey
(22)
Sakarya Universty, Faculty of Medicine, Sakarya, Turkey
(23)
Ankara University School of Medicine Ibni-Sina Hospital, Ankara, Turkey
(24)
Pamukkale University, Denizli, Turkey
(25)
Ankara Training and Research Hospital, Ankara, Turkey
(26)
Department of Paediatric Critical Care Medicine, Ankara University School of Medicine, Ankara, Turkey
(27)
Erciyes University, Faculty of Medicine, Kayseri, Turkey
(28)
German Hospital, Istanbul, Turkey
(29)
Ege University Medical Faculty, Izmir, Turkey
(30)
Gazi University Medical School, Ankara, Turkey

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© Leblebicioglu et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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