Original article


Temporal trends of healthcare associated infections and antimicrobial use in 2011-2013, observed

with annual point prevalence surveys in Ferrara University Hospital, Italy

P. ANTONIOLI1, M.C. MANZALINI2, A. STEFANATI3, B. BONATO4, A. VERZOLA5 , A. FORMAGLIO4, G. GABUTTI3 1Department of Hospital Hygiene & Healthcare Associated Infection Risk Management, Hospital Health Medical Management,

Ferrara University Hospital, Ferrara, Italy; 2Department of Hospital Hygiene & Healthcare Associated Infection Risk Management, Ferrara University Hospital, Ferrara, Italy; 3Section of Public Health Medicine, Department of Medical Sciences, University of Ferrara, Ferrara, Italy; 4Postgraduate School of Hygiene and Preventive Medicine, Section of Public Health Medicine, Department of Medical Sciences, University of Ferrara, Ferrara, Italy; 5 Planning and Control Management, Ferrara University Hospital, Ferrara, Italy


Keywords

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Healthcare-associated infections • Antimicrobial use • Point prevalence surveys


Summary

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Introduction. Healthcare associated infections (HAIs) and mis- use of antimicrobials (AMs) represent a growing public health problem. The Point Prevalence Surveys (PPSs) find available information to be used for specific targeted interventions and evaluate their effects. The objective of this study was to estimate the prevalence of HAIs and AM use, to describe types of infec- tions, causative pathogens and to compare data collected through three PPSs in Ferrara University Hospital (FUH), repeated in 3 different years (2011-2013). The population-based sample con- sists of all patients admitted to every acute care and rehabilitation Department in a single day.

Methods. ECDC Protocol and Form for PPS of HAI and AM use, Version 4.2, July 2011. Risk factor analysis was performed using logistic regression.

Results. 1,239 patients were observed. Overall, HAI prevalence was 9.6%; prevalence was higher in Intensive Care Units; uri- nary tract infections were the most common HAIs in all 3 surveys; E.coli was the most common pathogen; AM use prevalence was 51.1%; AMs most frequently administered were fluoroquinolones, combinations of penicillins and third-generation cephalosporins. According to the regression model, urinary catheter (OR: 2.5) and invasive respiratory device (OR: 2.3) are significantly associated risk factors for HAIs (p < 0.05).

Conclusions. PPSs are a sensitive and effective method of anal- ysis. Yearly repetition is a useful way to maintain focus on the topic of HAIs and AM use, highlighting how changes in practices impact on the outcome of care and providing useful information to implement intervention programs targeted on specific issues.


Introduction


Healthcare associated infections (HAIs) represent a growing public health problem in terms of patient safety and economic burden [1-3]. The Center for Disease Con- trol (CDC) estimates the increased mean length of hos- pital stay for each HAI to be 7 extra days, ranging from 1-4 days for urinary tract infections (UTIs) to 7-30 days for pneumonia (PN). In Europe, HAIs cause 16 million additional days of hospitalization per year, 37,000 re- lated deaths and 7 billion euros of additional costs (di- rect costs only) [4]. The Italian National Health Institute estimates 450,000-700,000 HAIs per year in Italian hos- pitals, 30% of which could be prevented; HAIs could be directly responsible for 1,350-2,100 avoidable deaths per year [5]. Misuse of antimicrobials (AMs) is a grow- ing public health problem worldwide, associated with an increase in drug resistant microorganisms and adverse drug reactions that generate huge economic costs [6, 7].

The implementation of surveillance systems for both HAI and AM use is a relevant topic in modern public health [8, 9]. Although continuous surveillance still represents the gold standard for infection control, it re- quires a huge amount of human and economic resources but has rarely been used in multicenter studies. Instead, Point Prevalence Surveys (PPS), despite their inherent limitations in terms of accuracy of results and possibility of bias, are a highly feasible alternative, easier to per- form even on large scale multicenter studies, less expen- sive and less time consuming. PPSs offer many benefits, including easy repeatability and the ability to provide meaningful information to be used for specific targeted interventions. The introduction of standardized proto- cols such as the European Center for Disease Control (ECDC) Protocol for PPS of HAI and AM use in acute care hospitals, version 4.2 2011-2012 [10], guarantees consistency of results and easy repeatability. Results of local surveys may also be used for yearly intra-hospital

comparison or benchmarking at regional, national or in- ternational level. In Ferrara University Hospital (FUH), infection and AM stewardship by PPS began in 1992, with a local Protocol and data entry form, updated over the years in agreement with the literature references [11]. This Protocol was used until 2011, when FUH partici- pated in the first full scale ECDC PPS, October 2011.

The survey was repeated in 2012 and 2013. Objectives of these studies were: to estimate the overall burden of HAIs and use of AMs in the FUH; to describe HAIs and AM use by type of functionally homogeneous wards; to allow a comparison of data collected during three sur- veys and with Italian and European data.


Methods


The surveys took place in October 2011, November 2012 and November 2013 in the FUH, a tertiary care hospi- tal with 857 beds in 2011 and, after moving to a new hospital in 2012, with 711 beds. The materials and tools developed for the ECDC PPS of HAI and AM use in acute care hospitals were used for these surveys: the PPS protocol and codebook v4.2, including the case defini- tions of HAI, PPS data entry forms in an editable format for translation purposes, PPS hospital software HELIC- SWin.net, User manual – PPS hospital software HELIC- SWin.net [10]. All acute wards were included, except for Day-surgery and Day-Hospital departments. The study included all patients admitted to the ward before or at 8

a.m. and not discharged from the ward at the time of the survey, including neonates, if born before/at 8 a.m. For each ward, data had to be collected in a single day. Data collection for each survey was completed in two weeks. The surveys were carried out by trained medical doctors of the Postgraduate School of Hygiene and Preventive Medicine of Ferrara University, supported by doctors and nurses of the Hospital Network for Infection Control of each ward. The ECDC standard “Patient data form” was used, structured according to the following sections: demographic data, admission data, clinical data, AM use and HAI data [10].

Demographic, admission and clinical data, useful for identifying patient-based denominator data and risk fac- tors, included: ward name, survey date, patient counter, age, sex, date of admission, surgery since admission, McCabe score [12], invasive devices in place on survey date (central vascular catheter-CVC, peripheral vascu- lar catheter-PVC, urinary catheter, intubation). Only any active HAI on the survey date was recorded on the form [10].

Data collected for HAI included: presence of a relevant invasive device before onset (intubation for PN, central vascular catheter / peripheral vascular catheter for blood- stream infection-BSI and urinary catheter for UTI) [13], HAI present at admission, date of onset, origin of infec- tion (if bloodstream infection, source) and microorgan- isms data.

AM data (including generic or brand name, route, in- dication, diagnosis/site of infection, reason) were col-

lected when a patient was receiving an AM on the day of survey (or in the 24 hours before the day of the survey for surgical prophylaxis). Registered drugs were classi- fied according to the Anatomical Therapeutic Chemical (ATC) classification [14]. AMs included in the survey were Anatomical Therapeutic Chemical classes J01 (an- tibacterials), J02 (antifungals) and J04 (antimycobacte- rials). Indication for use of systemic AMs was recorded according to the following classification: community- acquired infection, infection acquired in long-term care facility (e.g. nursing home) or chronic-care hospital, acute hospital acquired infection, surgical prophylax- is (single dose, one day, more than one day), medical prophylaxis, other indications, unknown indication/ reason, unknown/missing information on indication not verified during survey [10]. Data were collected using the standard ECDC software HELICSWin.net v. 1.3. Statistical analysis was performed using Stata v.13. Dif- ference in the distribution of nominal variables was as- sessed using Pearson’s chi-square test with significance level set at 0.05. Continuous variables were tested for normality of distribution both graphically and by means of Shapiro-Wilkinson test, difference in distribution was then tested using Kruskal-Wallis test. Prevalence rate of HAI was calculated as the percentage of infected pa- tients over the total number of patients observed during each survey. AM use prevalence was calculated as the percentage of the number of patients receiving at least one AM over the total number of patients observed. Risk factors analysis were performed by means of logistic re- gression in relation to two outcomes: presence of at least one HAI and receipt of at least one AM.

Continuous variables were recoded into categories in order to maintain consistency with ECDC PPS [15] and to address the influence of outliers. The final mod- els for both outcomes were developed by adding those risk factors which resulted to be significant (P < 0.2) in univariate analysis in a forward stepwise manner [16]. Significance level for inclusion in final model was set at p < 0.05. The presence of a central vascular catheter or peripheral vascular catheter was excluded from both models because of the correlation with the parenteral administration of AMs. Presence of relevant invasive de- vices was considered before the onset of an HAI for the HAI regression model. Length of stay in the HAI model was considered until the date of HAI onset if an HAI oc- curred during current hospital stay. Goodness-of-fit was assessed on eight smaller random sub-samples of the data using the Hosmer–Lemeshow chi square test. The discriminatory accuracy of the multiple logistic regres- sion models was assessed using receiver operating char- acteristic (ROC) analysis. Standardized prevalence rates were calculated by using a 2-step method which takes into consideration predicted probabilities of the outcome according to the regression model and indirect standard- ization. The predicted probabilities were used to deter- mine the mean predicted risk of HAI or AM use for each survey. Risk index ratios were calculated by dividing the observed (unadjusted) prevalence rates by the mean pre- dicted risk of each survey, and adjusted prevalence rates

were determined by multiplying standardized ratios by the observed prevalence rates in the entire study sample.


Results


Overall, 1,239 patients were observed in the three sur- veys; the mean age was 62.6 years and 47.3% were male. Mean length of stay was 9.4 days (median 6 days). At the time of survey, a central vascular catheter was present in 20.2% of observed patients; a peripheral vas- cular catheter in 56.0%; a urinary catheter in 35.9% and the percentage of mechanically ventilated / intubated pa- tients was 3.8%. Differences among data collected dur- ing the three surveys proved to be statistically significant (p < 0.05) for: presence of peripheral line, presence of central line, McCabe score and surgery since admission. The overall prevalence of HAI was 9.6%, with a total number of 49 HAIs in 2011, 37 in 2012, and 54 in 2013

(HAIs to patients ratio: 1.1 in 2011, 1.1 in 2012, 1.3 in 2013). Case-mix corrected prevalence rates were: 10.1% for 2011, 8.9% for 2012 and 9.6% for 2013. UTIs were the most common HAI in all three surveys, followed by PN (in 2011 and 2012) and bloodstream infections in 2013 (Tab. I). A total of 82.8% HAIs originated in the current hospital. Regression analysis of risk factors asso- ciated with the onset of at least one HAI shows statistical significance for: length of stay at risk 4-7 days (OR: 1.9, 95%CI 1.1-3.4; p = 0.030), length of stay at risk 8-14 days (OR: 2.3, 95%CI 1.2-4.3; p = 0.010) and length of stay at risk > 3 weeks (OR: 3.8, 95%CI 2.1-7.1; p < 0.001); McCabe score “Rapidly fatal disease” (OR: 2.4, 95%CI 1.5-3.8; p < 0.001); use of urinary catheter (OR: 2.5, 95%CI 1.6-3.7; p < 0.001); mechanical ventilation (OR: 2.3, 95%CI 1.1-4.5; p = 0.023). The prevalence of HAI was higher in Intensive Care Units in all three sur- veys.

At the time of the surveys, results for microbiological investigation were available for 120 HAIs (85.0%). Escherichia coli was the most common pathogen,

followed by Klebsiella pneumoniae and Enterococ- cus faecalis (Tab. II). Escherichia coli was the most prevalent pathogen even when stratifying by survey and also the most frequent causative pathogen for UTI. During the 3-year study period, isolated strains of Escherichia coli were frequently third-generation cephalosporin resistant (range 10%-20%), but only in 2011 were they also carbapenem resistant. In 2011, 33.3% of Klebsiella pneumoniae strains were third- generation cephalosporin resistant and 16.7% were carbapenem resistant. Overall, the AM use preva- lence was 51.1% (at least one AM). A total of 858 AMs were administered (Tab. III). Parenteral ad- ministration was the most prevalent route (69.0% in 2011, 74.0% in 2012 and 79.3% in 2013). AMs

were mainly administered for treatment of an infec- tion (relative frequency 61.0% in 2011, 56.2% in 2012 and 70.7% in 2013) and among these mainly for treatment of community acquired infections (57.6% in 2011, in 2012 59.1%, in 2013 60.1%). Surgical prophylaxis was mostly prescribed for more than one day (relative frequency: 65.4% in 2011, 72.0%

in 2012 and 88.9% in 2013). Single dose prophylaxis

was prescribed in 23.1% in 2011, 20.0% in 2012 and 11.1% in 2013 (relative frequency). One-day surgi- cal prophylaxis was the least frequently prescribed. Prescription for medical prophylaxis was 19.8% in 2011, 24.9% in 2012, 15.0% in 2013. Considering all three surveys, antibacterials for systemic use (ATC group J01) accounted for 93.7% of all prescriptions. AMs most frequently administered were: J01MA fluoroquinolones (21.7% in 2011, 23.0% in 2012, 21.8% in 2013), J01CR combinations of penicillins including beta-lactamase inhibitors (20.4% in 2011,

19.2% in 2012, 21.8% in 2013), J01DD third-gen-

eration cephalosporins (22.7% in 2011, 16.6% in

2012, 16.8% in 2013). Fluoroquinolones were the most commonly used AMs in symptomatic lower UTI (total 28.8%) and PN (total 24.5%), including both community acquired infections and HAI. Risk



Tab. I. Characters of healthcare associated infections (hAIs).


HAI data

Year of survey

2011 (N = 450a)

2012

(N = 379)

2013

(N = 407)

hAI prevalence (at least one hAI) %

10.0

8.7

10.1

Total number of hAIs

49

37

54

Infection Site - No. (%) of hAI by year of survey:

Urinary tract infections

18 (36.7)

9 (24.3)

22 (40.7)

pneumonia

7 (14.3)

9 (24.3)

6 (11.1)

Bloodstream infections (BSI)

5 (10.2)

2 (5.4)

10 (18.5)

Surgical site infections

4 (8.2)

4 (10.8)

3 (5.6)

gastro-intestinal system infections

5 (10.2)

2 (5.4)

2 (3.7)

Other lower respiratory tract infections

2 (4.1)

1 (2.7)

2 (3.7)

Catheter-related infections w/o BSI

2 (5.4)

Other

8 (16.3)

8 (21.6)

9 (16.7)

a 3 missing records excluded

Tab. II. Top five microorganisms isolated in healthcare-associated infections and percentage of antimicrobial resistance markers.


Microorganisms

No. of isolated microorganisms by year of survey

2011

(N = 74)

2012

(N = 28)

2013

(N = 73)

Escherichia coli

(%C3G-R) (%Car-R)

24

(16.7) (16.7)

10

(20.0) (0.0)

20

(10.0) (0.0)

Klebsiella pneumoniae

(%C3G-R) (%Car-R)

6

(33.3) (16.7)

4

(0.0) (0.0)

6

(0.0) (0.0)

Enterococcus faecalis

2

5

5

Candida albicans

5

6

Staphylococcus epidermidis

1

1

6

C3G-R, Third-generation cephalosporin resistance Car-R, Carbapenem-resistant


Tab. III. Characters of Antimicrobials (AMs).


AM use data

Year of survey

2011 (N = 450a)

2012

(N = 379)

2013

(N = 407)

AM use prevalence (at least one AM) %

54.4

50.1

48.4

Total number of AM

313

265

280

Top ten antimicrobials agents (ATC codes) - No. (%) of AM by year of survey:

J01MA Fluoroquinolones

68 (21.7)

61 (23.0)

61 (21.8)

J01CR Combinations of penicillins, incl. beta-lactamase inhibitors

64 (20.4)

51 (19.2)

61 (21.8)

J01DD Third-generation cephalosporins

71 (22.7)

44 (16.6)

47 (16.8)

J01GB Aminoglycosides

13 (4.2)

17 (6.4)

17 (6.1)

A07AA Intestinal anti-infectives antibiotics

7 (2.2)

3 (1.1)

2 (0.7)

J01DB First-generation cephalosporins

23 (7.3)

11 (4.2)

6 (2.1)

J01DH Carbapenems

9 (2.9)

11 (4.2)

20 (7.1)

J01XA Glycopeptide antibacterials

11 (3.5)

16 (6.0)

13 (4.6)

J01XD Imidazole derivatives

7 (2.2)

8 (3.0)

13 (4.6)

J02AC Triazole derivatives

9 (2.9)

10 (3.8)

7 (2.5)

J01FA Macrolides

12 (3.8)

9 (3.4)

4 (1.4)

a 3 missing records excluded

ATC, Anatomical Therapeutic Chemical


factors associated with administration of at least one AM showing statistical significance in the regression model were: patient located in surgical ward (OR: 1.7, 95%CI 1.1-2.7; p = 0.010) and Intensive Care Unit (OR: 2.7, 95%CI 1.2-6.0; p = 0.015); length of stay 4-7 days (OR: 1.4, 95%CI 1.1-1.9; p = 0.016);

length of stay 8-14 days (OR: 1.6, 95%CI 1.1-2.2; p

= 0.010); patient underwent non-NHSN/minimal sur- gery during current hospitalization (OR: 1.5, 95%CI 1.1-2.2; p = 0.013); use of urinary catheter at the time of survey (OR: 1.9, 95%CI 1.4-2.4; p < 0.001); me-

chanical ventilation at the time of survey (OR: 2.6, 95%CI 1.1-6.0; p = 0.030). Case-mix corrected AM use prevalence rates were: 54.2% in 2011, 50.5% in

2012 and 47.9% in 2013.

Discussion


The described prevalence rate of nosocomial infections was higher than the values reported in other studies [17- 21] including the ECDC’s 2011 report [15], which esti- mates a prevalence rate of 6.0% (country range 2.3%– 10.8%) in European acute-care hospitals (6.1% in Italy). This difference in the reported values is due in part to the different characteristics of the hospitals included in the European survey which collects results from pri- mary, secondary, tertiary care and specialized hospitals in different countries. However, the prevalence rate of HAI in FUH remains higher even when comparing re- sults from tertiary care hospitals only (7.2%). One pos- sible reason may be the fact that the surveys were carried out by independent auditors, to avoid conflicts of interest and to ensure the integrity of the auditing process. As con-

firmed by existing literature, Intensive Care Units were the most affected wards [15, 17-21]. UTIs were the most common HAI in all three surveys in FUH, unlike what is reported in other studies where PN and surgi- cal site infections were more prevalent [15, 17, 18]. Use of urinary catheter, a well known risk factor for UTIs [22-24], was higher than what is reported in the literature [15, 19, 21]. Prevalence of surgical site infec- tions was found to be lower than what is reported by other similar surveys [15, 17-21]. Appropriate urinary catheter indication is certainly an area which requires further analysis to assess possible overuse and guide practical interventions [25]. Year by year comparison of nosocomial infections and risk factors in the three surveys delivers substantially constant results even when corrected for case-mix by means of logistic re- gression. Risk factor analysis is consistent with data in the literature [15, 19, 21]. Statistically significant risk for HAI occurrence is independently associated with increased length of stay, McCabe Score “Rapidly fatal disease”, use of urinary catheter and mechanical venti- lation. Mechanical ventilation associated risk suggests a need for more effective preventive measures against ventilator-associated infections [26]. At the time of the surveys, results for microbiological investigation were available for 120 HAIs (85.0%). Escherichia coli was the most frequent microorganism isolated in all three surveys and the most frequent causative pathogen for UTI, followed by Klebsiella pneumoniae, Enterococ- cus faecalis and Candida albicans. These results show a higher prevalence of Enterobacteriaceae when com- pared with the ECDC’s report data [15] which can be explained by the higher frequency of UTIs in FUH. AM use rates were higher than those reported in the literature [15, 19], while the average number of AMs to treated patients ratio is consistent with the value re- ported by ECDC [15], showing no evidence of a higher rate of multidrug protocol prescriptions in FUH. Fluo- roquinolones, third-generation cephalosporins and combinations of penicillins (including beta-lactam inhibitors) were the most frequent AM prescribed in all three surveys, a similar result to other literature reports which further underline a widespread use of broad spectrum antibiotics combined in multidrug protocols that is often necessary to counteract the in- creasing prevalence of AM resistance [15, 17-19, 27]. On the other hand, the excessive and inappropriate use of antibiotics is the prime mover of the rapidly increasing prevalence of antibiotic-resistant microor- ganisms [28, 29]. AMs were mainly prescribed to treat an infection (mainly community acquired). Medical prophylaxis was the second most frequent indication in all three surveys. These results are similar to those re- ported by the ECDC’s 2011 point prevalence survey for Italy [15]. Surgical prophylaxis was mostly prescribed for more than one day, while one-day surgical prophy- laxis was the least frequently prescribed. These results are substantially similar to those reported by ECDC for Italy in 2011 and other similar studies [15, 18, 19], underlining that antibiotics are used for longer than

what is suggested by the international consensus [30], further stressing the need for specific stewardship pro- grams [31, 32]. Year by year analysis shows a decreas- ing, although not statistically significant, prevalence of AM prescription in FUH, dropping from 54.4% in 2011 to 48.4% in 2013, a result confirmed by standardization through logistic regression model. AM stewardship is a critical area of intervention in FUH, aimed at changing prescribing practices, leading to a better control of drug resistant microorganisms, improved appropriateness of antibiotic use and decreased costs.


Conclusions


FUH has a long history of activities aimed at risk management and infection control, based on a multi- modal and multidimensional approach [11]. Moreover, the hospital’s infection control policy includes: audit and feed-back to improve compliance of the health- care workforce to good practices; retraining courses and educational programs; drafting reminders to sup- port good practices for workers, patients and caregiv- ers; continuous surveillance of surgical site infections; active support for the WHO Campaign “Save lives: clean your hands” since 2006, with the participa- tion as an international site in the experimentation of WHO Guidelines on Hand Hygiene in Health Care (Advanced Draft) [33, 34]. Despite their limitations, PPS are not expensive, take little time to carry out and need few human resources. PPS are easy repeatable and provide meaningful information to use for specific targeted interventions. The yearly repetition will be a useful means of keeping interest alive on the subject of HAI and AM use [35] and highlighting how changes in healthcare practices affect outcome variables.


Acknowledgements


Giovanni Gabutti received grants from GlaxoSmithKline Biologicals SA, Sanofi Pasteur MSD, Novartis, Crucell/ Janssen, Pfizer and Sequirus for taking part in advisory board, expert meetings, being a speaker or an organizer of congresses/conferences, and acting as investigator in clinical trials; the other Authors have no conflicts to dis- close.


Authors’ contributions


PA, GG, AS, MCM was responsable for the research coordination and contributed to the protocol definition, data collection, data analysis, manuscript drafting and critical revision of the manuscript. BB, AV, AF contrib- uted to the data collection, data analysis and critical re- vision of the manuscript. All authors read and approved the final manuscript.

References


[1] Lanini S, Jarris WR, Nicastri E, Privitera G, Gesu G, Marchetti F, Giuliani L, Piselli P, Puro V, Nisii C, Ippolito G; INF-NOS Study Group (Gruppo Italiano per lo Studio delle Infezioni Noscomiali). Healthcare-associated infection in Italy: annual point-prevalence surveys, 2002-2004. Infect Control Hosp Epi- demiol. 2009;30(7):659-65. doi: 10.1086/597596.

[2] Gastmeier P, Behnke M, Breier AC, Piening B, Schwab F, Det- tenkofer M, Geffers C. Healthcare-associated infection rates: measuring and comparing. Experiences from the German Na- tional Nosocomial Infection Surveillance System (KISS) and from other surveillance systems. Bundesgesundheitsblatt Ge- sundheitsforschung Gesundheitsschutz. 2012;55:1363-9. doi: 10.1007/s00103-012-1551-y.

[3] Geffers C, Gastmeier P. Nosocomial infections and multidrug- resistant organisms in Germany: epidemiological data from KISS (the Hospital Infection Surveillance System). Dtsch Ar- ztebl Int. 2011;108:87-93. doi: 10.3238/arztebl.2011.0087.

[4] World Health Organization. Report on the burden of endemic health care-associated infection worldwide. Geneva: WHO Document Production Services; 2011. Available at: http://apps. who.int/iris/bitstream/10665/80135/1/9789241501507_eng. pdf?ua=1. Accessed on 27/06/2016.

[5] Centro Nazionale di Epidemiologia, Sorveglianza e Promozi- one della Salute. Infezioni correlate all’assistenza, aspetti epi- demiologici. Available at: http://www.epicentro.iss.it/problemi/ infezioni_correlate/epid.asp. Accessed on 27/06/2016.

[6] Brusaferro S, Regattin L, Faruzzo A, Grasso A, Basile M, Cal- ligaris L, Scudeller L, Viale P. Surveillance of hospital-acquired infections: a model for settings with resource constraints. Am J Infect Control. 2006;34:362-6. doi: 10.1016/j.ajic.2006.03.002.

[7] Carlet J, Jarlier V, Harbarth S, Voss A, Goossens H, Pittet D; the Participants of the 3rd World Healthcare-Associated Infections Forum. Ready for a world without antibiotics? The Pensières Antibiotic Resistance Call to Action. Antimicrob Resist Infect Control. 2012;1:11. doi: 10.1186/2047-2994-1-11.

[8] Horan TC, Andrus M, Dudeck MA. CDC/NHSN Surveillance definition of healthcare-associated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control. 2008;36:309-32. doi: 10.1016/j.ajic.2008.03.002.

[9] Kuijper EJ, Coignard B, Tüll P, ESCMID Study Group for Clostridium difficile, EU Member States, European Centre for Disease Prevention and Control. Emergence of Clostrid- ium difficile-associated disease in North America and Eu- rope. Clin Microbiol Infect. 2006;12:2-18. doi:10.1111/j.1469- 0691.2006.01580.x.

[10] European Centre for Disease Prevention and Control. Point prevalence survey of healthcare-associated infections and an- timicrobial use in European acute care hospitals. Protocol ver- sion 4.2. Full-scale survey. Stockholm: ECDC; 2011. Available at: http://ecdc.europa.eu/en/activities/surveillance/hai/about_ hai-net/pages/pps.aspx. Accessed on 27/08/2014.

[11] Antonioli PM, Migliori M, Armani A, Capuzzo M, Fabbri P, Lorenzin A, Mandrioli G, Masiero A, Matarazzo MT, Mazzotti F, Pampolini M, Pantaleoni M, Sandri M, Sarti G, Sortini A. Uti- lizzo di studi di prevalenza periodici per valutare l’andamento delle infezioni nosocomiali. Giornale Italiano delle Infezioni Ospedaliere. 1996;3:91-6.

[12] McCabe WR, Jackson GG. Gram-negative bacteremia, I: etiology and ecology. Arch Intern Med. 1962;110:847-55. doi:10.1001/archinte.1962.03620240029006.

[13] Horan TC, Emori TG. Definitions of key terms used in the NNIS system. Am J Infect Control. 1997;25(2):112-6. doi: 10.1016/ S0196-6553(97)90037-7.

[14] Hansen S, Sohr D, Geffers C, Astagneau P, Blacky A, Koller W, Morales I, Moro ML, Palomar M, Szilagyi E, Suetens C, Gastmeier P. Concordance between European and US case definitions of healthcare-associated infections. Antimicrob

Resist Infect Control 2012;1:28. doi: 10.1186/2047-2994- 1-28.

[15] European Centre for Disease Prevention and Control. Point prevalence survey of healthcare-associated infections and an- timicrobial use in European acute care hospitals. Stockholm: ECDC; 2013. Available at: http://ecdc.europa.eu/en/publica- tions/Publications/healthcare-associated-infections-antimicro- bial-use-PPS.pdf. Accessed on 27/06/2016.

[16] Hosmer DW, Lemeshow S. Applied Logistic Regression. 2nd ed. New York: Wiley 2000.

[17] Lyytikäinen O, Kanerva M, Agthe N, Möttönen T, Ruutu P; Finnish Prevalence Survey Study Group. Healthcare-associated infections in Finnish acute care hospitals: a national prevalence survey, 2005. J Hosp Infect 2008;69:288-94. doi: 10.1016/j. jhin.2008.03.005.

[18] Behnke M, Hansen S, Leistner R, Diaz LA, Gropmann A, Sohr D, Gastmeier P, Piening B. Nosocomial infection and antibio- tic use: a second national prevalence study in Germany. Dtsch Arztebl Int. 2013;110:627-33. doi: 10.3238/arztebl.2013.0627.

[19] Sinatra I, Carubia L, Marchese V, Aprea L, D’Alessandro N, Mammina C, Torregrossa MV. Prevalence survey of healthcare- associated infections and antimicrobial use at the University Hospital “Paolo Giaccone”, Palermo, Italy. J Prev Med Hyg 2013;54:200-4.

[20] Weinstein JW, Mazon D, Pantelick E, Reagan-Cirincione P, Dembry LM, Hierholzer WJ. A decade of prevalence surveys in a tertiary-care center: trends in nosocomial infection rates, device utilization, and patient acuity. Infect Control Hosp Epi- demiol. 1999;20:543-8. doi: 10.1086/501675.

[21] Kritsotakis EI, Dimitriadis I, Roumbelaki M, Vounou E, Kontou M, Papakyriakou P, Koliou-Mazeri M, Varthalitis I, Vrouchos G, Troulakis G, Gikas A. Case-mix adjustment approach to benchmarking prevalence rates of nosocomial infection in hos- pitals in Cyprus and Greece. Infect Control Hosp Epidemiol 2008;29:685-92. doi: 10.1086/588704.

[22] Saint S, Chenowith CE. Biofilms and catheter-associated uri- nary tract infections. Infect Dis Clin North Am 2003;17:411-32.

[23] Tambyah PA, Maki DG. Catheter-associated urinary tract infection is rarely symptomatic: a prospective study of 1,497 catheterized patients. Arch Intern Med 2000;160:678-82. doi: 10.1001/archinte.160.5.678.

[24] Saint S, Kaufman SR, Rogers MA, Baker PD, Boyko EJ, Lipsky BA. Risk factors for nosocomial urinary tract-related bactere- mia: a case-control study. Am J Infect Control 2006;34:401-7. doi: 10.1016/j.ajic.2006.03.001.

[25] Harbarth S, Sax H, Gastmeier P. The preventable proportion of nosocomial infections: an overview of published reports. J Hosp Infect 2003;54:258-66. doi: 10.1016/S0195-6701(03)00150-6.

[26] Dodek P, Keenan S, Cook D, Heyland D, Jacka M, Hand L, Muscedere J, Foster D, Mehta N, Hall R, Brun-Buisson C; Ca- nadian Critical Care Trials Group; Canadian Critical Care So- ciety. Evidence-based clinical practice guide-line for the pre- vention of ventilator-associated pneumonia. Ann Intern Med 2004;141:305-13. doi: 10.7326/0003-4819-141-4-200408170-

00011.

[27] Mazzeo F, Capuano A, Motola G, Russo F, Berrino L, Filippelli A, Rossi F. Antibiotic use in an Italian University Hospital. J Chemother 2002;14:332-5. doi: 10.1179/joc.2002.14.4.332.

[28] Zarb P, Coignard B, Griskeviciene J, Muller A, Vankerckhoven V, Weist K, Goossens M, Vaerenberg S, Hopkins S, Catry B, Monnet D, Goossens H, Suetens C; National Contact Points for the ECDC pilot point prevalence survey; Hospital Contact Points for the ECDC pilot point prevalence survey. The Euro- pean Centre for Disease Prevention and Control (ECDC) pilot point prevalence survey of healthcare-associated infections and antimicrobial use. Euro Surveill 2012;17.

[29] Malta R, Di Rosa S, D’Alessandro N. Aspetti etici e controllo di gestione dei farmaci antibiotici antibatterici. Italian Journal of Medicine 2010;4:137-44.

[30] Vaccheri A, Silvani MC, Bersaglia L, Motola D, Strahinja P, Vargiu A, Poluzzi E, Montanaro N. A 3 year survey on the use of antibacterial agents in five italian hospitals. J Antimicrob Chemother 2008;61:953-8. doi: 10.1093/jac/dkn010.

[31] Schön T, Sandelin LL, Bonnedahl J, Hedebäck F, Wistedt A, Bru- din L, Jarnheimer PÅ. A comparative study of three methods to evaluate an intervention to improve empirical antibiotic therapy for acute bacterial infections in hospitalized patients. Scand J Infect Dis 2011;43:251-7. doi: 10.3109/00365548.2010.544326.

[32] Muller-Pebody B, Muscat M, Pelle B, Klein BM, Brandt CT, Monnet DL. Increase and change in pattern of hospital anti- microbial use, Denmark, 1997-2001. J Antimicrob Chemother 2004;54:1122-6. doi: 10.1093/jac/dkh494.

[33] Pittet D, Donaldson L. Clean care is safer care: a world- wide priority. Lancet. 2005;366:1246-7. doi: 10.1016/S0140- 6736(05)67506-X.

[34] World Health Organization. WHO Guidelines on Hand Hy- giene in Healthcare (Advanced Draft). Geneva: World Health Organization; 2006. Available at: http://www.who. int/patientsafety/information_centre/Last_April_versionHH_ Guidelines%5b3%5d.pdf?ua=1. Accessed on 27/06/2016.

[35] Haley RW, Culver DH, White JW, Morgan WM, Emori TG, Munn VP, Hooton TM. The efficacy of infection surveillance and control programs in preventing nosocomial infections in US hospitals. Am J Epidemiol. 1985;121:182-205.


n Received on May 29, 2016. Accepted on July 21, 2016.


n Correspondence: Giovanni Gabutti, Section of Public Health Medicine, Department of Medical Sciences, University of Ferrara, via Fossato di Mortara 64/b, 44121 Ferrara, Italy - Tel. +39 0532 455568 - Fax +39 0532 205066 - E-mail: giovanni.gabutti@unife. it