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e242 | www.pidj.com The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013
AntimicrobiAl reviews
Background: The neonatal and pediatric antimicrobial point prevalence
survey (PPS) of the Antibiotic Resistance and Prescribing in European Chil-
dren project (http://www.arpecproject.eu/) aims to standardize a method for
surveillance of antimicrobial use in children and neonates admitted to the
hospital within Europe. This article describes the audit criteria used and
reports overall country-specific proportions of antimicrobial use. An ana-
lytical review presents methodologies on antimicrobial use.
Methods: A 1-day PPS on antimicrobial use in hospitalized children was organ-
ized in September 2011, using a previously validated and standardized method.
The survey included all inpatient pediatric and neonatal beds and identified all
children receiving an antimicrobial treatment on the day of survey. Mandatory
data were age, gender, (birth) weight, underlying diagnosis, antimicrobial agent,
dose and indication for treatment. Data were entered through a web-based sys-
tem for data-entry and reporting, based on the WebPPS program developed for
the European Surveillance of Antimicrobial Consumption project.
Results: There were 2760 and 1565 pediatric versus 1154 and 589 neona-
tal inpatients reported among 50 European (n = 14 countries) and 23 non-
European hospitals (n = 9 countries), respectively. Overall, antibiotic pediat-
ric and neonatal use was significantly higher in non-European (43.8%; 95%
confidence interval [CI]: 41.3–46.3% and 39.4%; 95% CI: 35.5–43.4%)
compared with that in European hospitals (35.4; 95% CI: 33.6–37.2% and
21.8%; 95% CI: 19.4–24.2%). Proportions of antibiotic use were highest in
hematology/oncology wards (61.3%; 95% CI: 56.2–66.4%) and pediatric
intensive care units (55.8%; 95% CI: 50.3–61.3%).
Conclusions: An Antibiotic Resistance and Prescribing in European Chil-
dren standardized web-based method for a 1-day PPS was successfully
developed and conducted in 73 hospitals worldwide. It offers a simple, fea-
sible and sustainable way of data collection that can be used globally.
Key Words: hospitalized children, point prevalence survey, antimicrobial
use, antibiotic use, surveillance
(Pediatr Infect Dis J 2013;32: e242–e253)
Inappropriate and excessive use of antibiotics among hospitalized
children has been linked to the emergence of antibiotic-resistant
bacteria that may spread and persist in hospitals and the commu-
nity.1–4 There is a critical need for antimicrobial stewardship and
changing prescribing practices for neonates and children, but we
lack knowledge about the determinants influencing antibiotic pre-
scribing.4,5
Cross-sectional point prevalence surveys (PPS) have pro-
vided useful data on patterns of hospital antimicrobial prescribing
in adults, providing insight on the factors that influence the vari-
ation in antimicrobial use. The European Surveillance of Antimi-
crobial Consumption (ESAC) project has carried out 3 successful
PPS on hospital antimicrobial use in 2006, 2008 and 2009.6–8 These
well-established surveillance methodologies developed by ESAC
focused mainly on adults and also provided preliminary data on
antimicrobial prescribing patterns among hospitalized children.5
However, the methodology used was not specifically designed for
neonates and children.9
With the overall aim of optimizing antimicrobial prescrib-
ing among children, the “Antibiotic Resistance and Prescribing in
European Children” (ARPEC) project has been cofunded by the
European Commission Directorate General for Health and Con-
sumers (DG SANCO) through the Executive Agency for Health and
Consumers.10 Based on the established ESAC PPS,6–8 we developed
within this project a novel neonatal and pediatric cross-sectional
survey method. The PPS was conducted during the last 2 weeks
of September 2011. The current article describes the methodology
used. Existing methodologies analyzing antimicrobial use have been
reviewed and compared with the ARPEC methodology. Country-
specific proportions of antimicrobial use worldwide are presented
for the ARPEC PPS which was conducted during the last 2 weeks
of September 2011.
METHODS
Promotion of the study was important to enable data col-
lection from a wide variety of hospitals, wards and patients.
Pediatricians belonging to the well-established networks from
ESAC,11 European Society of Paediatric Infectious Diseases12
and Global Research in Paediatrics13 were invited to participate.
Any interested hospital-based physician caring for neonates or
children could indicate his/her interest in the project by con-
tacting arpec@ua.ac.be. The study encouraged the creation of a
multidisciplinary team of health professionals, including pedi-
atric infectious disease specialists, neonatologists, infection
control teams, clinical microbiologists and clinical pharma-
cists. They received a detailed standardized protocol to ensure
uniformity of data collection. Although the project focused on
Europe, centers outside Europe that were keen to take part were
also included.
Copyright © 2013 by Lippincott Williams & Wilkins
ISSN: 0891-3668/13/3206-e242
DOI: 10.1097/INF.0b013e318286c612
The Antibiotic Resistance and Prescribing in European
Children Project
A Neonatal and Pediatric Antimicrobial Web-based Point Prevalence Survey in
73 Hospitals Worldwide
Ann Versporten, MPH, MEHS,* Mike Sharland, FRCPH,† Julia Bielicki, MD, MPH,† Nico Drapier, BAI,*
Vanessa Vankerckhoven, PhD,* and Herman Goossens, MD, PhD,* for the ARPEC Project Group Members
Accepted for publication January 08, 2013.
From the *Laboratory of Medical Microbiology, Vaccine & Infectious Disease
Institute, University of Antwerp, Antwerp, Belgium; and †Infection and
Immunity, Division of Clinical Sciences, St. Georges University of London,
London, United Kindgom.
The ARPEC project was cofunded by the European Commission Directorate
General for Health and Consumers (DG SANCO) through the Executive
Agency for Health and Consumers (http://ec.europa.eu/eahc/). The authors
have no other funding or conflicts of interest to disclose.
Address for correspondence: Ann Versporten, MPH, MEHS, Laboratory of
Medical Microbiology, Vaccine & Infectious Disease Institute (VAXINFEC-
TIO), Faculty of Medicine and Health Science, University of Antwerp—
CDE, Universiteitsplein 1, Room S6.23, B-2610 Antwerp, Belgium. E-mail:
ann.versporten@ua.ac.be.
Supplemental digital content is available for this article. Direct URL citations
appear in the printed text and are provided in the HTML and PDF versions of
this article on the journal’s website (www.pidj.com).
The Pediatric Infectious Disease Journal
32
6
Copyright © 2013 by Lippincott Williams & Wilkins
0891-3668
INF
203137
ARPEC Antimicrobial Survey
Versporten et al
2013
June
00
00
10.1097/INF.0b013e318286c612
2013
Pediatr Infect Dis J
Lippincott Williams & Wilkins
Hagerstown, MD
Divya J
XXX
The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013 ARPEC Antimicrobial Survey
© 2013 Lippincott Williams & Wilkins www.pidj.com | e243
Participants were asked to conduct a 1-day cross-sectional
hospital-based PPS during which all pediatric and neonatal wards
had to be audited once between September 19–30, 2011. Each
participant needed to register his/her hospital providing the name,
geographic location and type of hospital (primary, secondary, ter-
tiary level and specialized hospital and teaching vs. nonteaching
hospital).14,15 Seven major pediatric ward types (general pediatric
medicine, 4 types of specialized pediatric medicine wards, pedi-
atric surgery and pediatric intensive care unit) and 4 major neo-
natal wards were defined (3 levels of neonatal intensive care units
[NICUs] and a general neonatal medical ward) (Appendices, Sup-
plemental Digital Content 1 and 2, http://links.lww.com/INF/B548
and http://links.lww.com/INF/B549). Pediatric surgical wards were
not audited on a Monday to capture information about prophylaxis
in the previous 24 hours. Pediatric medical wards could be audited
on any weekday. Surveys were not allowed to take place on week-
end days, bank holidays or school holidays.
All neonates and pediatric inpatients younger than 18 years,
present in the ward at 8 AM at least since midnight, were included
in the denominator for the survey. Detailed data were recorded only
for patients with active antimicrobial prescriptions at 8 AM on the
day of survey. Prescriptions that became active after 8 AM on the day
of the survey were excluded. Day surgery, day hospital admissions,
emergency admissions after midnight, patients on psychiatric wards
and children younger than 18 years admitted on an adult ward were
excluded. Also adults older than 18 years admitted on a pediatric
ward together with their child were excluded from the survey.
The surveillance included antibacterials for systemic use
(Anatomical Therapeutic Chemical code J01), antimycotics (J02),
antifungals (D01BA) and antivirals for systemic use (J05), antibiot-
ics used as drugs for treatment of tuberculosis (J04A), antibiotics
used as intestinal anti-infectives (A07AA) and the nitroimidazole
derivatives (P01AB). They were aggregated at the level of active
substance in accordance with the Anatomical Therapeutic Chemi-
cal classification system of medicines (World Health Organization,
version 2011).16 Antimicrobials for topical use applied on skin were
not surveyed.
Two denominators were defined: the total number of eligible
neonatal or pediatric inpatients younger than 18 years, present at 8
AM of the ward surveyed; and the total number of eligible neonatal
or pediatric beds, attributed to inpatients younger than 18 years, at
8 AM of the ward surveyed. Participants needed to provide informa-
tion of the “actual real situation” on the day of the PPS.
Data collection was performed using paper data collection
forms: a department (denominator data), a pediatric and a neonatal
patient form. Essential data to collect were the patients’ age, gender,
current weight, ventilation status, underlying diagnosis, antimicro-
bial agent, single unit dose and number of prescribed doses per 24
hours, route of administration, anatomical site of infection accord-
ing to the reason for treatment, type of treatment (community- or
hospital-acquired infection) and details of prophylaxis for surgical
patients (duration of prophylaxis was 1 dose, 1 day or >1 day). To
facilitate data collection on underlying diagnosis and reason for
treatment, a predefined list of grouped “underlying conditions” and
“acute diagnosis” was used. This was originally developed by our
group as part of a pilot study looking at methodologic issues rel-
evant to the evaluation of antimicrobial consumption in hospitalized
children17 and was refined for this study with consultation among
project participants to ensure it was simple to use and also captured
clinically relevant groups. Similar diagnostic categories have been
used in the recent European Centre for Disease Prevention and Con-
trol hospital-acquired infection and antibiotic use PPS that does not
specifically target children.15 For neonates, additional information
on birth weight and gestational age had to be completed (Appen-
dices, Supplemental Digital Content 1 and 2, http://links.lww.com/
INF/B548 and http://links.lww.com/INF/B549).
After data collection on the wards, participants used the
ARPEC-webPPS program, a web-based application for data-
entry and reporting as designed by the Laboratory of Medical
Microbiology, University of Antwerp, Belgium (http://app.esac.
ua.ac.be/arpec_webpps/). A defined stepwise manner of data-
entry was followed as described in the available online training
sessions (http://www.arpecstudy.eu/training/vids/videos). Sev-
eral online checks prevented entering wrong data. Data entry
had to be validated using the online validation procedure which
discovered errors in the survey or provided warnings (eg, depart-
ments without patient data, duplicated antimicrobial treatments).
Supplementary data cleaning (eg, unexpected high/low [birth]
weight) led to direct contact with the participant concerned to
verify and if needed modify the data online. Hospitals could, at
any time, extract their data for verification or analysis (Excel for-
mat). After online validation, a feedback report in power point
slide format could be downloaded. It provided specific hospital
prevalence rates plotted against European and overall national
rates if at least 3 hospitals per country had participated. It also
provided information on targets for quality improvement in anti-
microbial prescribing.
The helpdesk was based at the University of Antwerp, Bel-
gium. They provided support for data collection, entry and vali-
dation by e-mail or phone. A Frequently Asked Question list was
made available online providing detailed answers on content and
IT-related questions. Finally, participants were given timely infor-
mation and feedback on the process of data collection through peri-
odic e-mails.
Countries were individually responsible for ascertaining the
need for local ethical approval as legal requirements vary across
Europe and worldwide. All data collected was completely anon-
ymous. Data privacy was guaranteed. A sequence number was
assigned to each hospital after registration to the ARPEC-webPPS.
Every patient record was given an automatically generated unique
not identifiable survey number. All participants were assured that
individual hospital names would not be revealed in any internal or
external report, or in a publication. For this publication, we wanted
to acknowledge participation and asked permission to publish the
contact details of the participants.
The feasibility of the developed method was first tested
in 11 European hospitals of 9 countries (Belgium, Estonia, Ger-
many, Lithuania, Italy, Slovenia, Spain, Switzerland and the
United Kingdom) during a 2-week period between March 28
and April 8, 2011. Unlike the method described above, a 2-day
data collection was performed, 1 day in each participating
week. This was done to determine the variation in PPS results.
This method was not retained during the global PPS as the pilot
data demonstrated limited additional benefit (double counting
of patients). Instead, the number of participating hospitals was
expanded to capture information on a larger number of patients
and settings.
For this article, we analyzed country-specific proportions of
antimicrobial and antibiotic use separately for pediatric and neonatal
patients, and for European versus non-European participating
countries. Countries are classified using the United Nations
Standard Country and Area Codes.18 For Iran, the area coding of
the United Nations Programme on Global Geospatial Information
Management has been followed.19 The proportions of antimicrobial
and antibiotic use represent prevalence rates accompanied by
their 95% confidence intervals (CIs) for percentages and counts
Versporten et al The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013
e244 | www.pidj.com © 2013 Lippincott Williams & Wilkins
TABLE 1. Overall Degree of Participation Among European Countries and Country-specific Proportions of Patients Treated With At Least 1
Antimicrobial vs. At Least 1 Antibiotic
N Hospitals Global PPS Patient Overview Global PPS Pediatric Antimicrobial and Antibiotic (J01)
Proportions
Neonatal Antimicrobial and Antibiotic (J01)
Proportions
N Countries Teaching Non-
teaching Total N Beds N
Patients
Bed
Utilization
(%)
Treated
Patients All
Antimicrobials N
Patients
Admitted
Treated N
Patients
Admitted
Treated
N % (95% CI) N All N J01 % All
(95% CI)
% J01
(95% CI) N All N J01 % All
(95% CI)
% J01
(95% CI)
Northern Europe
Estonia 1 1 111 67 60.4 17 25.4
(15.0–35.8)
44 13 12 29.5
(16.0–42.9)
27.3
(14.1–40.5)
23 4 4 17.4
(1.9–32.9)
17.4
(1.9–32.9)
Latvia 2 2 562 410 73.0 123 30.0
(25.6–34.4)
354 107 107 30.2
(25.4–35.0)
30.2
(25.4–35.0)
56 16 16 28.6
(16.8–40.4)
28.6
(16.8–40.4)
Lithuania 1 1 450 319 70.9 84 26.3
(21.5–31.1)
274 68 68 24.8
(19.7–29.9)
24.8
(19.7–29.9)
45 16 15 35.6
(21.6–49.6)
33.3
(19.5–47.1)
United King-
dom
4 15 19 1060 691 65.2 211 30.5
(27.1–33.9)
441 149 147 33.8
(29.4–38.2)
33.3
(28.9–37.7)
250 62 60 24.8
(19.5–30.2)
24.0
(18.7–29.3)
Subtotal 8 15 23 2183 1487 68.1 435 29.3
(27.0–31.6)
1113 337 334 30.3
(27.6–33.0)
30.0
(27.3–32.7)
374 98 95 26.2
(21.7–30.7)
25.4
(21.0–29.8)
Western Europe
Belgium 4 4 460 309 67.9 98 31.7
(26.5–36.9)
184 70 62 38.0
(31.0–45.0)
33.7
(26.9–40.5)
125 28 27 22.4
(15.1–29.7)
21.6
(14.4–28.8)
France 4 4 701 548 78.2 175 31.9
(28.0–35.8)
369 137 134 37.1
(32.2–42.0)
36.3
(31.4–41.2)
179 38 31 21.2
(15.2–27.2)
17.3
(11.8–22.8)
Germany 1 1 119 97 81.5 36 37.1
(27.5–46.7)
76 30 30 39.5
(28.5–50.5)
39.5
(28.5–50.5)
21 6 6 28.6
(9.3–47.9)
28.6
(9.3–47.9)
Luxembourg 1 1 55 45 81.8 16 35.6
(21.6–49.6)
28 13 13 46.4
(27.9–64.9)
46.4
(27.9–64.9)
17 3 2 17.6
(0.0–35.7)
11.8
(0.0–35.7)
Switzerland 2 2 208 129 62.0 34 26.4
(18.8–34.0)
96 30 30 31.3
(22.0–40.6)
31.3
(22.0–40.6)
33 4 4 12.1
(1.0–23.2)
12.1
(1.0–23.2)
Subtotal 12 0 12 1543 1128 73.3 359 31.8
(29.1–34.5)
753 280 269 37.2
(33.8–40.7)
35.7
(32.3–39.1)
375 79 70 21.1
(17.0–25.2)
18.7
(14.8–22.7)
Southern Europe
Greece 1 1 2 525 332 63.2 132 39.8
(34.5–45.1)
236 89 79 37.7
(31.5–43.9)
29.7
(23.9–35.5)
96 43 43 44.8
(34.9–54.8)
44.8
(34.9–54.8)
Italy 3 1 4 419 306 73.0 116 37.9
(32.5–43.3)
171 88 88 51.5
(44.0–59.0)
51.5
(44.0–59.0)
135 28 23 20.7
(13.9–27.5)
17.0
(10.7–23.3)
Portugal 2 2 213 144 67.6 41 28.5
(21.1–35.9)
115 40 38 34.8
(26.1–43.5)
33.0
(24.4–41.6)
29 1 1 3.4
(0.0–10.0)
3.4
(0.0–10.0)
Slovenia* (1) (1) 271 146 53.9 38 26.0
(18.8–33.4)
116 34 33 29.3
(21.0–37.6)
28.4
(20.2–36.6)
30 4 3 13.3
(1.5–25.5)
10.0
(0.0–20.7)
Spain 4 1 5 368 289 78.5 109 37.7
(32.1–43.3)
175 79 77 45.1
(37.7–52.5)
44.0
(36.7–51.4)
114 30 28 26.3
(18.2–34.4)
24.6
(16.7–32.5)
Subtotal 10 3 13 1796 1217 67.8 436 35.8
(33.1–38.5)
813 330 315 40.6
(37.2–44.0)
37.9
(34.6–41.2)
404 104 98 25.7
(21.4–30.0)
24.3
(20.1–28.5)
Eastern Europe
Romania 1 1 2 92 81 88.0 58 71.6
(61.8–81.4)
81 58 58 71.6
(61.8–81.4)
71.6
(61.8–81.4)
/ / / / /
Subtotal
Europe
31 19 50 5614 3913 69.8 1288 32.9
(31.4–34.4)
2760 1005 976 36.4
(34.6–38.2)
35.4
(33.6–37.2)
1153 281 263 24.4
(21.9–26.9)
22.8
(20.4–25.2)
Antimicrobial use = all patients treated with at least 1 antibiotic and/or antimycotic and/or antiviral and/or antibiotic for the treatment of tuberculosis and/or an intestinal anti-infective.
Antibiotics = all patients treated with at least 1 antibacterial for systemic use (Anatomical Therapeutic Chemical code = J01).
*Slovenia: data collected during feasibility PPS (2nd day of data collection, April 2011). No neonatal wards reported to this PPS.
The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013 ARPEC Antimicrobial Survey
© 2013 Lippincott Williams & Wilkins www.pidj.com | e245
TABLE 2. Overall Degree of Participation Among non-European Countries and Country-specific Proportions of Patients Treated with At Least 1
Antimicrobial vs. At Least 1 Antibiotic
N Hospitals Global PPS Patient Overview Global PPS Pediatric Antimicrobial and Antibiotic (J01)
Proportions
Neonatal Antimicrobial and Antibiotic (J01)
Proportions
N Countries Teaching Non-
teaching Total N Beds N
Patients
Bed
Utilization
(%)
Treated Patients All
Antimicrobials N
Patients
Admitted
Treated N
Patients
Admitted
Treated
N %
(95% CI) N All N J01 % All
(95% CI)
% J01
(95% CI) N All N J01 % All
(95% CI)
% J01
(95% CI)
Australia and
New Zealand
Australia 2 2 436 416 95.4 170 40.9
(36.2–45.6)
335 137 133 40.9
(35.6–46.2)
39.7
(34.5–44.9)
81 33 24 40.7
(30.0–51.4)
29.6
(19.7–39.5)
Eastern Africa
Malawi 1 1 339 339 100.0 136 40.1
(34.9–45.3)
270 109 108 40.4
(34.6–46.3)
40.0
(34.2–45.8)
69 27 27 39.1
(27.6–50.6)
39.1
(27.6–50.6)
Western Africa
Ghana 1 1 299 292 97.7 111 38.0
(32.4–43.6)
178 77 77 43.3
(36.0–50.6)
43.3
(36.0–50.6)
114* 34 34 29.8
(21.4–38.2)
29.8
(21.4–38.2)
Gambia 1 1 2 146 102 69.9 37 36.3
(27.0–45.6)
90 31 29 34.4
(24.6–44.2)
32.2
(22.6–41.9)
12* 6 6 50.0
(21.7–78.3)
50.0
(21.7–78.3)
Southern Africa
South Africa 1 1 112 78 69.6 33 42.3
(31.3–53.3)
/ / / / / 78 33 22 42.3
(31.3–53.3)
28.2
(18.2–38.2)
Southern Asia
Iran 3 3 445 364 81.8 222 61.0
(56.0–66.0)
258 151 149 58.5
(52.5–64.5)
57.8
(51.8–63.8)
106 71 71 67.0
(58.1–75.9)
67.0
(58.1–75.9)
Western Asia
Saudi Arabia 1 1 210 137 65.2 61 44.5
(36.2–52.8)
102 50 47 49.0
(39.3–58.7)
46.1
(36.4–55.8)
35 11 11 31.4
(16.0–46.8)
31.4
(16.0–46.8)
Georgia 11 11 454 186 41.0 113 60.8
(53.8–67.8)
149 97 97 65.1
(57.5–72.8)
65.1
(57.5–72.8)
37* 16 16 43.2
(27.2–59.2)
43.2
(27.2–59.2)
Northern America
United States 1 1 303 240 79.2 100 41.7
(35.5–47.9)
183 78 75 42.6
(35.4–49.8)
41.0
(33.9–48.1)
57 22 21 38.6
(26.0–51.2)
36.8
(24.3–49.3)
Subtotal
non-
Europe
11 12 23 2744 2154 78.5 983 45.6
(43.5–47.7)
1565 730 715 46.6
(44.1–49.1)
43.8
(41.3–46.3)
589 253 232 43.0
(39.0–47.0)
39.4
(35.5–43.4)
Grand total 42 31 73 5358 6067 72.6 2271 37.4
(36.2–38.6)
4325 1735 1691 40.1
(38.6–41.6)
38.3
(36.9–39.8)
1742 534 495 30.7
(28.5–32.9)
28.4
(26.3–30.5)
Antimicrobial use = all patients treated with at least 1 antibiotic and/or antimycotic and/or antiviral and/or antibiotic for the treatment of tuberculosis and/or an intestinal anti-infective.
Antibiotics = all patients treated with at least 1 antibacterial for systemic use (Anatomical Therapeutic Chemical code = J01).
*Data for general neonatal medical wards are provided (no NICU data available). /: No pediatric wards reported to this PPS.
Versporten et al The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013
e246 | www.pidj.com © 2013 Lippincott Williams & Wilkins
algorithms.20 An analytic review was conducted and compared
existing methods on quantifying pediatric hospital antimicrobial
use with the ARPEC methodology.
RESULTS
Tables 1 and 2 present the overall degree of participation and
country-specific proportions of antimicrobial and antibiotic use for
European and non-European participating hospitals. Overall, 50
hospitals of 14 European countries and 23 hospitals of 9 non-Euro-
pean countries (columns N hospitals global PPS) participated in this
first PPS. All hospitals, except 13 United Kingdom, 1 Spanish and
1 South African hospital conducted the survey between September
19 and 30, 2011. Detailed information was returned for all hospitals
because all fields had to be completed during online data-entry.
Overall, 60% were teaching hospitals. Eight were district- or
first-level hospitals (primary level; 2.3% and 1.7% of total beds
and patients), 18 were provincial or general hospitals (secondary
level; 12.0% and 9.3% of total beds and patients), 36 were tertiary
referral hospitals (69.4% and 71.2% of total beds and patients)
and 11 were specialized hospitals (infectious diseases, pediatrics;
16.4% and 17.8% of total beds and patients).
Sixty-three participants (83%) surveyed all eligible wards
within the hospital and 10 participants (17%) surveyed only
neonatal wards or specialized pediatric medicine wards. A wide
range of 8 to 450 beds at the hospital level was observed. The 73
participating hospital and Slovenia accounted for 6141 pediatric
and 2217 neonatal beds (Table 1). Mean and median beds were
higher in non-European compared with European beds (mean, 119
vs. 107 beds; median, 85 vs. 68 beds, respectively).
A pediatric intensive care unit was present in 25 European
(50%) and 13 non-European (57%) hospitals; a hematology–
oncology unit in 18 European (36%) and 7 non-European hospi-
tals (30%) and one or more pediatric surgery units in 22 European
(44%) and 13 non-European hospitals (57%). Thirty-eight Euro-
pean (76%) versus 9 non-European hospitals (39%) had one or
more NICUs, among which 27 (71%) versus 7 (78%) had a large
referral NICU level 3, respectively. The data set contains a high
TABLE 3. Bed Utilization and Proportional Antimicrobial and Antibiotic Use by Department Type
Department Type N Patients N Beds
N Patients
Treated
With an
Antimicrobial*
Bed
Utilization (%)
Proportion
Antimicrobial Use %
(95% CI)
N Patients
Treated With an
Antibiotic†
Proportion
Antibiotic Use %
(95% CI)
Pediatric wards
Hematology–oncology SPMW 351 483 223 72.7 63.5 (58.5–68.5) 215 61.3 (56.2–66.4)
Pediatric intensive care unit 312 443 179 70.4 57.4 (51.9–62.9) 174 55.8 (50.3–61.3)
Transplant (BMT-solid)‡ SPMW 37 45 16 82.2 43.2 (27.2–59.2) 16 43.2 (27.2–59.2)
General pediatric medical ward 1472 2255 574 65.3 39.0 (36.5–41.5) 562 38.2 (35.7–40.7)
All other SPMW 836 1063 319 78.6 38.2 (34.9–41.5) 317 37.9 (34.6–41.2)
Pediatric surgery 1023 1439 338 71.1 33.0 (30.1–35.9) 338 33.0 (30.1–35.9)
Cardiology SPMW 178 212 52 84.0 29.2 (22.5–35.9) 49 27.5 (20.9–34.1)
Subtotal 4209 5940 1701 70.9 40.4 (38.9–41.9) 1671 39.7 (38.2–41.2)
Neonatal wards
Tertiary referral NICU level 3 678 812 282 83.5 41.6 (37.9–45.3) 265 39.1 (35.4–42.8)
Special NICU level 1 183 220 64 83.2 35.0 (28.1–41.9) 62 33.9 (27.0–40.8)
Medium NICU level 2 218 291 59 74.9 27.1 (21.2–33.0) 48 22.0 (16.5–27.5)
General neonatal medical ward 633 819 127 77.3 20.1 (17.0–23.2) 126 19.9 (16.8–23.0)
Subtotal 1712 2142 532 79.9 31.1 (28.9–33.3) 501 29.3 (27.1–31.5)
Grand total 5921 8082 2233 73.3 37.7 (36.5–38.9) 2172 36.7 (35.5–37.9)
*Antimicrobial use = all patients treated with at least 1 antibiotic and/or antimycotic and/or antiviral and/or antibiotic for the treatment of tuberculosis and/or an intestinal
anti-infective.
†Antibiotic use = all patients treated with at least 1 antibacterial for systemic use (Anatomical Therapeutic Chemical code = J01).
‡Bone Marrow Transplantation and Solid Organ Transplantation. Slovenian data are not included.
SPMW indicates specialist pediatric medical ward.
FIGURE 1. Number of reported children admitted on a pediatric ward and receiving at least 1 antimicrobial treatment, by age.
The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013 ARPEC Antimicrobial Survey
© 2013 Lippincott Williams & Wilkins www.pidj.com | e247
sample of patients admitted on NICU-3 (Table, Supplemental Digi-
tal Content 3, http://links.lww.com/INF/B550). The high number of
patients admitted on a general neonatal medical ward represented
mainly the African countries and Georgia.
On the day of the survey, there were 4325 pediatric and 1742
neonatal inpatients reported. Bed utilization was higher among
non-European (78.5%, Table 1) compared with European hospitals
(69.8%, Table 2). Bed utilization was higher for neonatal wards
(79.9%) compared with pediatric wards (70.9%) (Table 3).
Of the treated patients admitted on a pediatric ward, 56.0%
(n = 543) and 53.8% (n = 150) were male in European and non-
European hospitals, respectively. With respect to neonatal wards,
52.9% (n = 387) and 63.2% (n = 160) were male in European and
non-European hospitals, respectively. The 2.7% (n = 27) miss-
ing gender specifications for the non-European hospitals originate
mainly from African countries and 40.4% (n = 903) of patients
admitted on a pediatric ward were younger than 1 year. The high-
est number of treated patients admitted on a neonatal ward was
≤7 days old (42.2%, n = 227); 3.5% of the treated patients was
≥3 months old (n = 19), 5 among them were over 6 months of age
(Figs. 1 and 2).
The highest antibiotic prevalence rates (number of patients
treated with at least 1 antibiotic/100 patients) were observed among
non-European pediatric (43.8%, range 32.2–65.1%) and neonatal
wards (39.4%, range 28.2–67.0%) (Table 2). Overall, children
admitted to non-European hospitals were significantly more likely
to receive one or more antibiotics (43.8%; 95% CI: 41.3–46.3%)
(Table 2) compared with European hospitals (35.4%; 95% CI:
33.6–37.2%) (Table 1). A North-South gradient was observed
for European pediatric wards, with significantly lower antibiotic
prevalence rates seen in the Northern European region (30.0%,
95% CI: 27.3–32.7%) and highest in South Europe (37.9%, 95%
CI: 34.6–41.2%), apart from the Romanian pediatric hospitals
(71.6%; 95% CI: 61.8–81.4%) (Table 1).
We observed significantly higher antibiotic prevalence rates
in hematology–oncology pediatric medical wards (61.3%; 95% CI:
56.2–66.4%) and the pediatric intensive care units (55.8%; 95%
CI: 50.3–61.3%) when compared with the other wards. Lowest
antibiotic use was observed for the general neonatal medical ward
(19.9%; 95% CI: 16.8–23.0%) (Fig. 3 and Table 3). At ward level,
a wide variation of treated patients on the day of the survey was
observed (range 0–100%).
DISCUSSION
The organization and process of data collection, as
described above, resulted in an active participation involving Euro-
pean and non-European hospitals. This cross-sectional survey on
FIGURE 2. Number of reported babies admitted on a neonatal ward and receiving at least 1 antimicrobial treatment, by age.
FIGURE 3. Variation in overall proportions of antibiotic use (J01) by ward type (N = 2172 children treated with at least 1 anti-
biotic, N = 50 European and 23 non-European hospitals). SPMW indicates specialist pediatric medical ward ; BMT-solid, Bone
Marrow Transplantation and Solid Organ Transplantation.
Versporten et al The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013
e248 | www.pidj.com © 2013 Lippincott Williams & Wilkins
antimicrobial use provided for the first time detailed directly com-
parable data about the frequency and characteristics of antimicro-
bial prescribing for hospitalized neonates and children in Europe
and worldwide.
Antibiotic use and bed utilization rates varied considerable
by region. The higher bed utilization rates observed among non-
European countries are partially explained by the inclusion of
African hospitals admitting more patients than beds available. A
bed utilization of 100% means that we do not know how many
beds were available for the number of patients admitted. September
was still the winter period within Australia, involving higher bed
use due to respiratory infections. Worldwide differences in season
subsequently may have influenced antibiotic prescribing rates at
country level. We observed a European North-South gradient of
pediatric antibiotic use. Significantly lower pediatric antibiotic
prescribing rates were found for the Northern compared with the
Southern European countries. This is consistent with the findings
of ESAC on outpatient antibiotic use; the Northern European
countries are well known for their low prescribing practice.21 Next,
significantly higher proportions of overall antibiotic use were
observed for non-European countries compared with the European
sample. This seems in line with previous published studies from
Turkey22 (54.6%), Nepal23,24 (range 70–93%) and Israel25 (range
35–72%).
With respect to neonatal wards, overall observed antibiotic
use was highest in tertiary referral NICUs. Similar rates were found
in an Israeli study25 (35 ± 12%), whereas much higher rates were
observed in Turkey22 (73.3%). NICUs admit a vulnerable popula-
tion of low-birth-weight babies with high rates of sepsis. Subse-
quently, there is a risk of high antibiotic pressure, which has led
to the emergence of antibiotic-resistant bacteria.26 Finally, sig-
nificantly higher proportions of antibiotic use were observed for a
hematology/oncology ward or a pediatrics intensive care unit when
compared with the overall prevalence in pediatric wards, which is
also in line with previously published studies.22,27,28
The observed variation in antibiotic use within Europe and
worldwide could be determined by cultural influences, national
guidelines, local or regional policy, local resistance patterns,
knowledge on appropriate antibiotic prescribing and availability of
drugs on the market. The observed country-specific proportions of
antibiotic use cannot be generalized; neither its appropriateness of
use can be discussed because relevant determinants of antibiotic use
such as hospital type, bed occupancy rates, high severity of disease
and relevant patients’ characteristics were not controlled for in this
analysis. In Romania for example, high proportions of antibiotic
use were to be expected as 1 of the 2 participating hospitals was an
infectious disease hospital.
Previous epidemiologic studies on antibiotic use have
been conducted using a wide range of methods and with different
numerator and denominators, which makes comparison with
the current study difficult (Table 4). Different approaches for
data collection; analysis and reporting of antibiotic use among
hospitalized children have been used and/or suggested. A
standardized approach to uniformly report and compare data on
pediatric and neonatal antibiotic prescribing within Europe and
worldwide is lacking. Most studies report proportions (%) of patients
on antibiotics (prevalence rates) using a 1-day PPS design,5,22,27,29,30
a retrospective,23,24 mixed retroprospective28 or prospective25,31–34
design with different time periods or intervals of data collection
within a single hospital23,24,27–30,32or between hospitals.5,22,34–38 Billing
data have also been used to compare proportions of antibiotic use.39
Besides proportions, antibiotic volumes have been expressed in
number of daily defined doses (DDD) using, for example, purchase
records of pharmacies for the whole pediatric hospital36,38,40 or
for particular wards of interest (eg, NICU).35 Yet, interpretation
and certainly comparison of results between studies using this
measurement unit have been profoundly hampered by the lack of
standard international pediatric DDDs. Many medicinal products
used in children are not approved for certain indications and very
limited formal dosing recommendations, based on well-powered
pharmacokinetic and pharmacodynamic studies, are available.16
We have recently proposed a new method for measuring antibiotic
consumption using pediatric DDDs by grouping neonates and
children into 4 age-related bands,37 but this has not yet been
prospectively evaluated.
The 2 main methods of presenting antibiotic volumes of
use (proportions vs. number of DDD) imply the adoption of sev-
eral existing numerators (patients receiving antibiotics, packages,
prescriptions, days of therapy, number of prescribed daily doses,
number of defined daily doses) and denominators (admissions,
all inpatients, occupied bed-days, all prescriptions, number of full
courses), depending on the nature of the data available (1-day PPS
vs. longitudinal data vs. pharmacy sales data). In addition to the
different methods of data collection, with respect to eligibility of
patient populations and wards, there is relevant variability in patient
case-mix, institutional characteristics, seasonality of data collec-
tion and other determinants which need to be taken into account to
correctly interpret observed variations in antimicrobial use among
patient populations, institutions and regions.
Possible intervention studies need to be based on robust sur-
veillance data. The first step in improving the quality of antibiotic
use is to establish the extent of (in) appropriate use of antibiotics. To
interpret results of an epidemiological study on antibiotic use, we
need to compare the results with data from other studies. Yet, meth-
odological differences between the studies may be greater than any
statistically significant difference in the results. Meaningful com-
parisons between antibiotic use patterns can only be made between
studies using similar study designs, definitions and data collection
methods. The ARPEC PPS cross-sectional design responds to this
critical need as it assesses similarities between groups, in terms
of a current health status (indication for treatment, the underlying
disease) and exposure (prevalence) to antibiotics.
The strength of our method is the uniformity of data collec-
tion. The quality assurance approach (data validation process) guar-
anteed a standardized, solid database for cross-sectional analyses
and further longitudinal studies. It will allow investigation of the
key determinants of antibiotic use prescribed for children and neo-
nates admitted to the hospital. The simplicity of the protocol made
the survey feasible and achievable. As such, we offered simple case
definitions to aid auditing of antibiotic use, without recourse to
complicated algorithms (eg, diagnostic criteria). We only collected
detailed data on patients with an active antimicrobial prescription
(not all admitted children). At hospital level, the conduct of a PPS
itself brought together a multidisciplinary team of professional’s
willing to work toward appropriate antimicrobial prescribing. The
survey results were shared with participating centers in the hope
that they will contribute to “sustained” awareness, and further will
serve as an evaluation tool of hospital-based interventions (eg,
the development of a local antimicrobial stewardship program).
Finally, the online tool of data-entry and reporting offered the
opportunity to add other questions. For example, participants were
also invited and encouraged to complete a questionnaire on their
current empiric antibiotic guidelines.
There are limitations to the current study. The generalizabil-
ity of the findings is limited by the methodological approach. A
1-day PPS captures only small numbers of children with individual
conditions (eg, pneumonia) in each hospital. Pediatric hospitals are
smaller in general than adult hospitals and care must be taken to
The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013 ARPEC Antimicrobial Survey
© 2013 Lippincott Williams & Wilkins www.pidj.com | e249
TABLE 4. Previous Studies Reporting Variation in Antibiotic Prescribing in Children and Neonates Admitted to Hospital Worldwide
Study
Region/Year
Investigation/
Sample Setting
Type Population Main Aim Design Nominator/
Denominator
Overall Antimicrobial
Use Estimates (Preva-
lence Rates)
Antimicrobial
Classification
Ang L., J. Hosp.
Infect., 200832
United Kingdom
(England)/2006/240-
bed secondary 1
tertiary care center
All pediatric inpa-
tients, large propor-
tion of specialist
patients
Determine preva-
lence antimicrobial
prescribing and
community-
acquired infections
Survey on 2 consecu-
tive weeks
All patients receiving
antimicrobials / 359
inpatients for 2 sur-
vey dates, patients
on both dates
included twice
49.3% Not specified
Amadeo B., JAC,
20105
21 European coun-
tries/2008/32 hospitals
admitting children
All children Describe pediatric
antimicrobial
prescribing / identify
targets quality
improvement
1-day PPS Children receiving an
antibiotic
PDD / all children
present 24 hr before
survey
32% (range 17–100%) ATC/DDD
method
Berild D.,
Int.J.Antimicr.
Agents, 200829
Russia/2002-’04/600 bed
pediatric hospital
All children of 2 wards
for gastro intestinal
infections(0–18 yr)
and respiratory tract
infections(1–14 yr)
Improve antibiotic use
and evaluate its
persistence
Controlled interven-
tion study (1-day
PPS): implementa-
tion guidelines in
1 ward vs. control
ward
N patients receiving
antibiotics / all
patients
Calculation of risk
difference for the 2
wards
Not specified
Ceyhan M., IJID,
201022
Turkey/2007/12 (referral)
children hospitals
Patients 0–16 yr Determine prevalence
of inappropriate
antimicrobial use
1-day PPS All patients receiving
antimicrobials / all
patients = 1302
54.6% Not specified
Ciofi degli Atti
ML., Euro sur-
veill., 200830
Italy (2 sites)/2007/607
children hospital
All children Describe prevalence of
antibiotic use
1-day PPS Prescriptions / all
patients hospital-
ized >48 hr (n = 412
children)
43.9% Not specified
Gerber JS., Pediat-
rics, 201039
USA/2008/40 freestand-
ing children hospitals
All children and
neonates
Quantify and type
antibiotic prescrib-
ing across US child-
rens hospitals
Retrospective cohort
study. Hospital
billing data on
antibiotic use
from Pediatric
Health Information
System.
-Patients receiving any
antibiotic
-Days of therapy / all
discharged patients
between January 1
and December 31,
2008
60% (range 38–72%)
Days of therapy
= 468/1000
inpatient-days
Own clas-
sification /
definition
broad
spectrum
antibiotic
Hajdu A., J.Hosp.
Infec., 200727
North West Russia/
2006/500-bed public
pediatric hospital
All inpatients ≤18 yr Estimate prevalence of
Health care associ-
ated infections and
antimicrobial use
1-day PPS All patients receiving
antimicrobials/ all
patients = 472
39% Not specified
Palikhe N., KUMJ.,
200423
Nepal/2003/ Major child
hospital Kathmandu
valley
Selection odd numbers
of children 1 mo to
12 yr admitted in 1
general ward
Study prescribing
practice of antibiot-
ics
Retrospective study of
1.5 mo
N prescriptions/121
patients
93% Not specified
Porta A., JAC,
201237
United Kingdom, Greece,
Italy/2009/4 childrens
hospitals
Children and neonates Develop a standard-
ized way to compare
antimicrobial
prescribing
14-day period preva-
lence survey
1) N Prescriptions / N
admissions
2) N patients on antibi-
otics on any 1 day/N
patients
3) DDD and PDD / N
occupied bed-days
Pediatrics: 43.5%–
55.9% (0.97–1.06
DDD/100bed-days)
Neonates: 30.1%–
39.2% (1.39–2.38
PDD/100 bed-days)
ATC/DDD
method
Potocki M., Infec-
tion, 200331
Switzerland,
Zurich/2001/ tertiary
care centre
All inpatients 1–16
yr of 1 randomly
chosen medical and
surgical ward
Examine use of
antibiotics, identify
targets to improve
use
Prospective study—6-
week consecutive
period
All patients
receiving
antibiotics / all
admitted patients
-Medical ward = 42%
-Surgical ward = 32%
-Justified antibiotic
prescribing = 85%
Not specified
Raveh D. QJM.,
200125
Israel/1998/528-bed uni-
versity institution
All patients receiving
antimicrobial agents
Generate information
on antimicrobial use
by ward
Prospective compara-
tive longitudinal
approach (3–4 mo
follow-up)
All patients receiv-
ing antibiotics /
N courses (3-day
interval) by ward
Pediatrics = 72% ±
12%
Neonatology = 35%
± 14%
Not specified
(Continued)
Versporten et al The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013
e250 | www.pidj.com © 2013 Lippincott Williams & Wilkins
TABLE 4. Continued
Study
Region/Year
Investigation/
Sample Setting
Type Population Main Aim Design Nominator/
Denominator
Overall Antimicro-
bial Use Estimates
(Prevalence Rates)
Antimicro-
bial Clas-
sification
Salas AA., Acta
paediatrica
200733
Bolivia/2006/160-bed
public pediatric
hospital
Inpatients with
suspected bacterial
infection receiving
antibiotics during
first 24 hr admission
Determine antibiotic
prescribing in
patients receiving
empirical therapy
Cohort study over
4-wk period
67 patients (excluding
admissions to pedi-
atrics intensive care
unit) / 338 admis-
sions to surgery and
medical wards
24% Not specified
Shankar PR.,
Singapore Med
J., 200624
Nepal /2003-’04/ Teach-
ing tertiary care
hospital
All children 0–14 yr
discharged from
pediatric ward
Obtain information on
prescribing patterns
of drugs
Retrospectively
collected informa-
tion during a 4-mo
period
All patients receiv-
ing antibiotics / N
admissions
N prescriptions
69.9% WHO model
list of
essential
medicines
13th rev.
Ufer M., Pharm-
coepid. Drug
Saf., 200534
Germany and Croatia/
2003/ pediatric units
(±80 beds) of 2 univer-
sity hospitals
Children ≤8 yr Compare systemic
antimicrobial use
among 2 hospitals
Prospective obser-
vational study of
hospital records
First course of antibi-
otic (incident) use
(J01)/ N admissions
(300 for each set-
ting)
N treatment courses
Germany = 10.0%
Croatia = 24.7%
ATC/DDD
method
Van Houten M.A.,
Int.J.Antimicr.
Agents, 199828
The Netherlands/
1994-’96/105-bed ter-
tiary referral pediatric
university hospital
All patients Analyze antibiotic use
over 3 consecutive
years
Retroprospective
study—3 times in a
8-wk period
All patients receiving
antibiotics / admis-
sions
1994: 33.3%
1995: 40.5 %
1996: 33.7%
Not specified
Antibiotic volume
expressed in N
DDD/100 bed-days
(or admissions)
Bassetti M.,
Int.J.Antimicr.
Agents, 199940
Italy/1993-’95/ pediatric
hospital
All children Study antimicrobial
drug use
Data from purchase
records of phar-
macy service
-N DDDs
-Expenditure (US$)/
not specified
Comparison (differ-
ence) of N DDD by
antibiotic drug and
class and cost over
time
ATC/DDD
method
Liem TB., JAC,
201035
The Netherlands/
2005/10 tertiary
NICUs
All patients admitted
to NICU
Characterize type and
volume of antibiotic
use; DU90%
Use of dispensing
antibiotics from
hospital pharma-
cies to NICUs
N DDD at substance
level / N admissions
per NICU
130 to 360 DDD / 100
admissions
ATC/DDD
method
Palcevski G.,
Pharmcoepid.
Drug Saf., 200436
Croatia vs. Russia/
2000/2 pediatric clinics
Patients 0–15 yr Describe antibiotic use
between 2 countries;
DU90%
Use of dispensing
antibiotics from
hospital pharma-
cies (J01)
N DDD at substance
level / bed-days
Rijeka = 29.0
DDD/100 BD
Smolensk = 8.3
DDD/100 BD
ATC/DDD
method
Zhang W., Pharma-
coepi.Drug Saf.,
200838
China/2002-’06/5 chil-
dren hospitals
All children 0–>12 yr
(4%)
Investigate if antibiotic
guidelines have
impact on use
Retrieval of N pack-
ages and doses
from each hospital
database for com-
plete years
N packages
N doses/-N inpatients/
year
-Duration of stay
2002: 68.2 DDD/100
BD
2006: 49.9 DDD /100
BD
ATC/DDD
method
PDD indicates prescribed daily dose; ATC, Anatomical Therapeutic Chemical.
The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013 ARPEC Antimicrobial Survey
© 2013 Lippincott Williams & Wilkins www.pidj.com | e251
not misinterpret the data. Ten institutions (17%) did not include all
targeted wards in the survey. Those hospitals mainly submitted data
for the high intensity care wards, admitting children more likely
to have received more antibiotics. Information on the other wards
is missing. We therefore did not report analyses by institution.
Benchmarking was not an aim of this first PPS, even for fully sur-
veyed hospitals. Nevertheless, antimicrobial use prevalence rates
obtained through repetitive PPS conducted among inpatient adults
seem to remain stable over time.6 Next, we had to develop our own
classifications for the clinical indication for prescribing and under-
lying diseases as no specific formal way of grouping pediatric and
neonatal International Statistical Classification of Diseases and
related health problems—10th Revision (ICD10 codes) suitable for
a simplified PPS exists. Furthermore, we did not collect informa-
tion about the clinical justification and duration of antibiotic ther-
apy, whether a suitable culture was obtained, whether the treatment
was appropriate for the infection to be treated or whether the surgi-
cal prophylaxis and its duration were justified. Finally, we noticed
insufficient knowledge of the protocol among some participants.
Data collection was done on an entirely voluntary basis, involving
motivated, but busy clinicians. The online validation procedure, a
requisite to download the personalized feedback, proved to be very
useful as it enforced verification, correction and validation of data
by participants.
Despite the excellent degree of participation, small numbers
at hospital and/or country level were included. During a follow-up
PPS study, we aim to increase the number of participating hospitals
(minimum 3 hospitals per country) in a wide variety of settings
globally in high and low income countries and to identify country-
specific trends (geographical variation), hospital-specific outcomes
(hospital type, ward-specific variations) and patient-related vari-
ability of antibiotic use. Repeated surveys in the same institutions
could identify antibiotic prescribing trends over time and further
will assess the key importance of seasonal variation in pediatrics.
The method may allow a self-sustainable long-term routine data
collection, but core long-term funding remains a problem. The
incorporated automated feedback system, which will be further
refined, should enhance local discussions. We strive for the identi-
fication of clear targets for quality improvement at hospital and/or
national level, offering baseline data for the development of feasi-
ble antibiotic stewardship programs.
ACKNOWLEDGMENTS
ARPEC project group members are as follows:
Celia Cooper, MD, PhD, Lai-Yang Lee, Microbiology and
Infectious Disease Directorate, SA Pathology, South Australia.
Joseph Whitehouse, PharmD, Department of Pharmacy,
Women’s and Children’s Hospital, South Australia.
Penelope A. Bryant, BM, BCh, PhD, Gabrielle Haeusler,
MBBS, Nigel Curtis, MBBS, PhD, Mike Starr, MBBS, Infectious
Diseases Unit, Department of General Medicine, The Royal Chil-
dren’s Hospital, Melbourne, Australia.
Anne Vergison, MD, MPH, Véronique Léon, Michèle Dele-
strait, Claudia Huza, MD, Philippe Lepage, MD, PhD, Paediatric
Infectious Diseases Unit, Infection control and Epidemiology Unit,
ULB-HUDERF, Brussels, Belgium.
Ludo Mahieu, MD, PhD, Tine Boiy, MD, Hilde Jansens, MD,
University Hospital Antwerp, Antwerp, Belgium.
Dimitri Van der Linden, MD, Pediatric Infectious and Tropi-
cal Diseases, Pediatric Department, Clinique Universitaires Saint-
Luc, Brussels, Belgium.
Caroline Briquet, PharmD, Centre for Clinical Pharmacy,
Cliniques Universitaires Saint-Luc, Brussels, Belgium.
Karel Allegaert, MD, PhD, Anne Smits, MD, neonatal inten-
sive care unit, University Hospitals Leuven, Belgium.
Irja Lutsar, MD, PhD, University of Tartu, Tartu, Estonia.
Eda Tamm, MD, Anneli Larionova, MD, University Clinics
of Tartu, Tartu, Estonia.
Daniel Orbach, MD, Pediatric Oncology Department, Insti-
tut Curie, Paris, France.
Mathie Lorrot, MD, PhD, François Angoulvant, MD, Cath-
erine Doit, PharmD, PhD, Sonia Prot-Labarthe, PharmD, PhD,
Université Paris Diderot, Sorbonne Paris Cité, Hôpital Universi-
taire Robert Debré, Paris, France.
Francois Dubos, MD, PhD, Marion Lagree, MD, Peadiatric
Emergency Unit and Infectious Diseases, Université Lille Nord-de-
France, UDSL, CHRU Lille, Lille, France.
Sandra Biscardi, MD, Fabrice Decobert, MD, Isabelle Hau,
MD, Fouad Madhi, MD, Xavier Durrmeyer, MD, Centre Hospital-
ier Intercommunal de Créteil, Créteil, France.
Kalifa Bojang, MD, PhD, Ismaela Abubakr, MD, Uduak
Okomo, MD, Rohey Awe, MD, Medical Research Council Unit,
Banjul, The Gambia.
Suzanne Anderson, MD, PhD, Ireneh Akwara, MD, Readon
C. Ideh, MBBS, FWACP, Clinical Services Department, Medical
Research Council Unit, The Gambia.
Karaman Pagava, MD, PhD, DSc, Tbilisi State Medical Uni-
versity, Tbilisi, Georgia.
Markus Hufnagel, MD, PhD, Division of Pediatric Infec-
tious Diseases and Rheumatology, Center of Pediatrics and Ado-
lescent Medicine, University Medical Center Freiburg, Germany.
Katharina Schuster, MD, Center of Pediatrics and Adoles-
cent Medicine, University Medical Center Freiburg, Germany.
Philipp Henneke, MD, PhD, Division of Pediatric Infectious
Diseases and Rheumatology, Center of Pediatrics and Adolescent
Medicine, and Center of Chronic Immunodeficiency, University
Medical Center Freiburg, Germany.
Anthony Enimil, MD, Alex Osei-Akoto, MD, Samuel Blay
Nguah, MD, Daniel Ansong, MD, Komfo Anokye Teaching Hospital
Kumasi, Ghana.
Elias Iosifidis, MD, MSc, Emmanuel Roilides, MD, PhD, 3rd
Department of Pediatrics, Aristotle University School of Medicine,
Hippokration Hospital, Thessaloniki, Greece.
Nikos Spyridis, MD, PhD, Garyfallia Syridou, MD, PhD,
Second Department of Paediatrics, National and Kapodistrian
University of Athens School of Medicine, Athens, Greece.
Jafar Soltani, MD, Naseh Soleimani, MD, Soheila Nahedi,
MD, Fatima Khosravi, MSN, Kurdistan University of Medical Sci-
ences, Sanandaj, Iran.
Gholamreza Pouladfar, MD, Zahra Jafarpour, MD, Professor
Alborzi Clinical Microbiology Research Center, Shiraz University
of Medical Sciences, Shiraz, Iran.
Carlo Giacquinto, MD, PhD, Germana Longo, MD, Dan-
iele Donà, MD, Teresa Mion, MD, Department of Pediatrics “Salus
pueri”, Padua, Italy.
Patrizia D’Argenio, MD, Marta Luisa Ciofi Degli Atti, MD,
Maia De Luca, MD, Gaetano Ciliento, RN, Bambino Gesù Children
Hospital IRCCS, Rome, Italy.
Susanna Esposito, MD, PhD, Elena Danieli, MBiol, Valen-
tina Montinaro, MBiol, Rossana Tenconi, MD, Pediatric Clinic 1,
Department of Pathophysiology and Transplantation, Fondazione
IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy.
Chiara Centenari, MD, hospital of Trento, Trento, Italy.
Giangiacomo Nicolini, MD, PENTA coordinator, ARPEC
educational group, San Martino Hospital, Belluno-Italy.
Dzintars Mozgis, PhD, Riga Stradins University, Public
Health and Epidemiology Department, Riga, Latvia.
Versporten et al The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013
e252 | www.pidj.com © 2013 Lippincott Williams & Wilkins
Inese Sviestina, MD, University Children’s Hospital (Gailez-
ers), Riga, Latvia.
Jana Pavare, MD, PhD, Kristine Rasnaca, MD, Dace Gar-
dovska, MD, PhD, Ilze Grope, MD, PhD, University Children’s
Hospital, Riga, Latvia.
Vytautas Usonis, MD, PhD, Vilnius University Clinic of
Children Diseases, Vilnius, Lithuania and Children’s Hospital,
Affiliate of Vilnius University Hospital Santariskiu Klinikos, Vil-
nius, Lithuania.
Vilija Gurksniene, MD, Audrone Eidukaite, MD, PhD, Chil-
dren’s Hospital, Affiliate of Vilnius University Hospital Santariskiu
Klinikos, Vilnius, Lithuania.
Armand Biver, MD, Clinique Pédiatrique, Centre Hospital-
ier Luxembourg, Luxembourg.
Aisleen Bennett, MD, Bernadette O’Hare, MD, Department
of Paediatrics, Queen Elizabeth Central Hospital, Blantyre, Malawi.
Neil Kennedy, MB ChB, MRCPCH, Queen Elizabeth Cen-
tral Hospital, Blantyre, Malawi and Department of Paediatrics,
College of Medicine, Malawi.
Ana Brett, MD, Fernanda Rodrigues, MD, Infectious Dis-
eases Unit and Emergency Service, Hospital Pediátrico de Coimbra,
Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.
Isabel Esteves, MD, Pediatrics Department, Pediatric Infec-
tious Diseases Unit, Santa Maria Hospital, Lisbon, Portugal.
Simona Claudia Cambrea, MD, PhD, Clinic of Infectious
Diseases, Faculty of Medicine, “Ovidius” University, Constanta,
Romania.
Mihai Craiu, MD, PhD, Emil Tomescu, MD, Pediatrics
Department, Life Memorial Hospital, Bucharest, Romania.
Mohammed A. Al Shehri, MD, Dayel Al Shahrani, MD, King
Fahad Medical City, Riyadh, Saudi Arabia.
Milan Čižman, MD, PhD, Janez Babnik, MD, PhD, Rajko
Kenda, MD, PhD, Ivan Vidmar, MD, University Medical Centre,
Ljubljana, Slovenia.
Heather Finlayson, MBChB, FCPaed (SA), Cert ID (Paed),
DCH, Helena Rabie, MBChB, MMed (Paed), FCPaed(SA), Dip
Infect Dis, MSc ID, Mark Cotton, FCPaed (SA), M.Med (Paed),
PhD, DCH (SA), DTM&H, Tygerberg Children’s Hospital, Division
of Paediatric Infectious Diseases, Stellenbosch University, Cape
Town, South Africa. Angela Dramowski, MBChB, FC Paed(SA),
MMed (Paed), Cert ID(Paed), DCH, Academic Unit for Infection
Prevention and Control, Tygerberg Hospital and Division of Com-
munity Health, Stellenbosch University, Cape Town, South Africa.
Carlos Rodrigo, MD, PhD, Maria Mendez, MD, Paediatric
Infectious Disease Unit, Germans Trias i Pujol University Hospi-
tal, Badalona, Barcelona, and Universitat Autònoma de Barcelona,
Spain.
Pablo Rojo, MD, PhD, Elisa López-Varela, MD, MPH, Noe-
lia Ureta, MD, Rocío Mosqueda, MD, Department of Paediatrics
(Division of Paediatric Infectious Disease) and Neonatology Unit,
Hospital Universitario 12 de Octubre, Madrid, Spain.
Andrés Pérez-López, MD, Lourdes Orta, MD, Department of
Paediatrics, Hospital de Manacor, Majorca, Balearic Islands, Spain.
M. Santos, MD, M. Navarro, MD, PhD, B. Santiago, MD, T.
Hernández-Sampelayo, MD, PhD, Jesus Saavedra, MD, PhD, Pedi-
atric Infectious Diseases Division, Gregorio Marañón Hospital,
Madrid, Spain.
Amaya Bustinza, MD, Pediatric Intensive Care, Hospital
General Universitario Gregorio Marañón, Madrid, Spain.
Javier Gil, MD, Adolf Valls, MD, PhD, Elena Santesteban,
PharmD, PhD, Hospital Universitario Cruces, Barakaldo, Spain.
Philipp Baumann, MD, Division of Neonatology, University
Hospital Zurich, Zurich, Switzerland.
Christoph Berger, MD, University Children’s Hospital
Zurich, Zürich, Switzerland.
Alison Gifford, MD, Ninewells Hospital, Dundee, United
Kingdom.
Esse Menson, MD, Alina Botgros, MD, Department of General
Paediatrics, Evelina Children’s Hospital, London, United Kingdom.
Sara Arenas-Lopez, MSc, MRPharmS, Paul Wade, MD,
Department of Pharmacy, Evelina Children’s Hospital, London,
United Kingdom.
Katja Doerholt, MD, Paediatric Infectious Diseases Unit, St
George’s Hospital, London, United Kingdom.
Simon B Drysdale, MRCPCH, St Helier Hospital, London,
United Kingdom.
James C. McElnay, MD, PhD, Clinical and Practice
Research Group, School of Pharmacy, Queen’s University Belfast,
Belfast, Northern Ireland, United Kingdom.
Mary P. Kearney, MB, BCH, BAO, FRCPath, Michael G.
Scott, PhD, Fidelma A. Magee, BSc, Northern Health and Social
Care Trust, Ballymena, Northern Ireland, United Kingdom.Mamoon
Aldeyab, PhD, Clinical and Practice Research Group, School of
Pharmacy, Queen’s University Belfast, Belfast, Northern Ireland,
United Kingdom and Northern Health and Social Care Trust, Bal-
lymena, Northern Ireland, United Kingdom.
Maggie Heginbothom, PhD, ARPEC PPS coordinator,
Antimicrobial Resistance Programme - Surveillance Unit, Public
Health Wales, Cardiff, United Kingdom.
Jason G Newland, MD, MEd, Erin B Hedican, MD, Hirak
Shah, MD, Leslie Stach, MD, Diane Yu, MD, Children’s Mercy
Hospital and Clinics, Section of Infectious Diseases, Kansas City,
issouri, USA.
REFERENCES
1. de Man P, Verhoeven BA, Verbrugh HA, et al. An antibiotic policy to prevent
emergence of resistant bacilli. Lancet. 2000;355:973–978.
2. Asensio A, Oliver A, González-Diego P, et al. Outbreak of a multiresistant
Klebsiella pneumoniae strain in an intensive care unit: antibiotic use as risk
factor for colonization and infection. Clin Infect Dis. 2000;30:55–60.
3. Nourse C, Murphy H, Byrne C, et al. Control of a nosocomial outbreak of
vancomycin resistant Enterococcus faecium in a paediatric oncology unit:
risk factors for colonisation. Eur J Pediatr. 1998;157:20–27.
4. Iosifidis E, Antachopoulos C, Tsivitanidou M, et al. Differential correlation
between rates of antimicrobial drug consumption and prevalence of antimi-
crobial resistance in a tertiary care hospital in Greece. Infect Control Hosp
Epidemiol. 2008;29:615–622.
5. Amadeo B, Zarb P, Muller A, et al.; ESAC III Hospital Care Subproject
Group. European Surveillance of Antibiotic Consumption (ESAC) point
prevalence survey 2008: paediatric antimicrobial prescribing in 32 hospitals
of 21 European countries. J Antimicrob Chemother. 2010;65:2247–2252.
6. Ansari F, Erntell M, Goossens H, et al. The European surveillance of anti-
microbial consumption (ESAC) point-prevalence survey of antibacterial use
in 20 European hospitals in 2006. Clin Infect Dis. 2009;49:1496–1504.
7. Zarb P, Amadeo B, Muller A, et al. Identification of targets for quality
improvement in antimicrobial prescribing: the web-based ESAC Point
Prevalence Survey 2009. J Antimicrob Chemother. 2011;66:443–449.
8. Zarb P, Goossens H. European Surveillance of Antimicrobial Consumption
(ESAC): value of a point-prevalence survey of antimicrobial use across
Europe. Drugs. 2011;71:745–755.
9. Spyridis N, Sharland M. The European Union Antibiotic Awareness Day:
the paediatric perspective. Arch Dis Child. 2008;93:909–910.
10. Antibiotic Resistance and Prescribing in European Children. Available at:
http://www.arpecproject.eu/. Accessed December 1, 2012.
11. European Surveillance of Antimicrobial Consumption. Available at: http://
www.esac.ua.ac.be/. Accessed August 23, 2012.
12. European Society of Paediatric Infectious Diseases. Available at: http://
www.espid.org/. Accessed August 23, 2012.
13. Global Research in Paediatrics. Available at: http://grip-network.org/.
Accessed August 23, 2012.
The Pediatric Infectious Disease Journal • Volume 32, Number 6, June 2013 ARPEC Antimicrobial Survey
© 2013 Lippincott Williams & Wilkins www.pidj.com | e253
14. Mosby’s Medical Dictionary. 8th ed. St Louis,. MO: osby/Elsevier, 2009.
15. European Centre for Disease Prevention and Control. ECDC point preva-
lence survey of healthcare-associated infections and antimicrobial use in
acute care hospitals. (see protocol) Available at http://www.ecdc.europa.eu/
en/activities/surveillance/hai/about_hai-net/pages/pps.aspx. Accessed July
6, 2012.
16. WHO Collaborating Centre for Drug Statistics Methodology. Anatomical
Therapeutic Chemical (ATC) classification system: Guidelines for ATC
classification and DDD assignment. Oslo, 2011. Available at: http://www.
whocc.no/. Accessed August 23, 2012.
17. Porta A, Esposito S, Menson E, et al. Off-label antibiotic use in children in
three European countries. Eur J Clin Pharmacol. 2010;66:919–927.
18. United Nations Statistics Division. United Nations Statistic Division -
Standard Country and Area Codes Classification. Composition of macro
geographical (continental) regions, geographical sub-regions, and selected
economic and other groupings. Available at: http://unstats.un.org/unsd/
methods/m49/m49.htm. Accessed July 29, 2012.
19. United Nations Group of Exper ts on Geographical Names. The UN Programme
on Global Geospatial Information Management. Available at: http://www.
un.org/Depts/Cartographic/english/htmain.htm. Accessed July 29, 2012.
20. Brown LD, DasGupta A. Interval estimation for a binomial proportion.
Statistical Science. 2001;16:101–133.
21. Adriaenssens N, Coenen S, Verspor ten A, et al. European Surveillance of
Antimicrobial Consumption (ESAC): outpatient antibiotic use in Europe
(1997–2009). J Antimicrob Chemother. 2011;66(suppl 6):vi3–vi12.
22. Ceyhan M, Yildirim I, Ecevit C, et al. Inappropriate antimicrobial use in
Turkish pediatric hospitals: a multicenter point prevalence survey. Int J
Infect Dis. 2010;14:e55–e61.
23. Palikhe N. Prescribing pattern of antibiotics in paediatric hospital of
Kathmandu valley. Kathmandu Univ Med J (KUMJ). 2004;2:6–12.
24. Shankar PR, Upadhyay DK, Subish P, et al. Prescribing patterns among pae-
diatric inpatients in a teaching hospital in western Nepal. Singapore Med J.
2006;47:261–265.
25. Raveh D, Levy Y, Schlesinger Y, et al. Longitudinal surveillance of antibi-
otic use in the hospital. QJM. 2001;94:141–152.
26. Stoll BJ, Hansen N, Fanaroff AA, et al. Changes in pathogens caus-
ing early-onset sepsis in very-low-birth-weight infants. N Engl J Med.
2002;347:240–247.
27. Hajdu A, Samodova OV, Carlsson TR, et al. A point prevalence survey of
hospital-acquired infections and antimicrobial use in a paediatric hospital in
north-western Russia. J Hosp Infect. 2007;66:378–384.
28. van Houten MA, Luinge K, Laseur M, et al. Antibiotic utilisation for hospi-
talised paediatric patients. Int J Antimicrob Agents. 1998;10:161–164.
29. Berild D, Abrahamsen TG, Andresen S, et al. A controlled intervention study
to improve antibiotic use in a Russian paediatric hospital. Int J Antimicrob
Agents. 2008;31:478–483.
30. Ciofi Degli Atti ML, Raponi M, Tozzi AE, et al. Point prevalence
study of antibiotic use in a paediatric hospital in Italy. Euro Surveill.
2008;13:19003.
31. Potocki M, Goette J, Szucs TD, et al. Prospective survey of antibiotic utiliza-
tion in pediatric hospitalized patients to identify targets for improvement of
prescription. Infection. 2003;31:398–403.
32. Ang L, Laskar R, Gray JW. A point prevalence study of infection and anti-
microbial use at a UK children’s hospital. J Hosp Infect. 2008;68:372–374.
33. Salas AA, Aranda E. Antibiotic prescribing patterns as empirical therapy
among hospitalized patients in a Bolivian paediatric teaching hospital. Acta
Paediatr. 2007;96:1533–1535.
34. Ufer M, Radosević N, Vogt A, et al. Antimicrobial drug use in hospital-
ised paediatric patients: a cross-national comparison between Germany and
Croatia. Pharmacoepidemiol Drug Saf. 2005;14:735–739.
35. Liem TB, Krediet TG, Fleer A, et al. Variation in antibiotic use in neo-
natal intensive care units in the Netherlands. J Antimicrob Chemother.
2010;65:1270–1275.
36. Palcevski G, Ahel V, Vlahović-Palcevski V, et al. Antibiotic use profile at
paediatric clinics in two transitional countries. Pharmacoepidemiol Drug
Saf. 2004;13:181–185.
37. Porta A, Hsia Y, Doerholt K, et al. Comparing neonatal and paediatric anti-
biotic prescribing between hospitals: a new algorithm to help international
benchmarking. J Antimicrob Chemother. 2012;67:1278–1286.
38. Zhang W, Shen X, Wang Y, et al. Antibiotic use in five children’s hospitals
during 2002-2006: the impact of antibiotic guidelines issued by the Chinese
Ministry of Health. Pharmacoepidemiol Drug Saf. 2008;17:306–311.
39. Gerber JS, Newland JG, Coffin SE, et al. Variability in antibiotic use at
children’s hospitals. Pediatrics. 2010;126:1067–1073.
40. Bassetti M, Collidà A, Rossi R, et al. Use of antibiotics in an Italian chil-
dren’s hospital, 1993-1995; clinical and economic considerations. Int J
Antimicrob Agents. 2000;14:33–37.
