J Antimicrob Chemother 2016; 71: 2273 – 2279
doi:10.1093/jac/dkw119 Advance Access publication 26 April 2016
Risk factors for the acquisition of OXA-48-producing Enterobacteriaceae
in a hospital outbreak setting: a matched case–control study
M. J. D. Dautzenberg1–3*, J. M. Ossewaarde3, S. C. de Greeff4, A. Troelstra1 and M. J. M. Bonten1,2
1
Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands; 2Julius Center for Health Sciences and
Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; 3Department of Medical Microbiology, Maasstad Ziekenhuis,
Rotterdam, The Netherlands; 4Center for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM),
Bilthoven, The Netherlands
*Corresponding author. Tel: (+31)-(0)88-75-686-33; E-mail: [email protected]
Received 4 January 2016; returned 29 January 2016; revised 4 March 2016; accepted 9 March 2016
Objectives: In the context of a large outbreak of OXA-48-producing Enterobacteriaceae (OXA-E) in a Dutch
hospital we determined risk factors for acquisition of OXA-E.
Patients and methods: A matched case–control study was performed in which cases (culture positive for OXA-E)
were matched 1:3 to controls (culture negative for OXA-E) based on hospital ward, index date (+1 week) and
time exposed in the hospital (best match). Stratified analyses were performed for patients with OXA-E producing
and not producing ESBL. Potential risk factors included age, gender, surgery and ICU admission within 30 days
preceding the index date, presence of comorbidities and in-hospital antibiotic treatment within 30 days preceding the index date. Data analysis was performed using multivariable conditional logistic regression with
Firth correction.
Results: In total, 73 cases were matched to 211 controls. In the multivariable conditional logistic regression
model, male gender (OR 2.63, 95% CI 1.25 – 5.53), age (per year increase, OR 1.03, 95% CI 1.00 – 1.05) and
use of fluoroquinolones within 30 days preceding the index date (OR 2.98, 95% CI 1.06– 8.41) were risk factors
for acquisition of OXA-E. In the stratified multivariable conditional logistic regression model, quinolone use was
a risk factor for the acquisition of ESBL-producing OXA-E and surgery was a risk factor for the acquisition of
non-ESBL-producing OXA-E.
Conclusions: During a large, hospital-wide OXA-E outbreak, male gender, age and previous use of fluoroquinolones were risk factors for acquisition of OXA-E. These findings may help in optimizing screening and isolation
strategies in future OXA-E outbreaks.
Introduction
The spread of carbapenemase producers in Enterobacteriaceae
has been identified worldwide. OXA-48 belongs to class D carbapenemases, consisting of OXA-type b-lactamases, and was first
identified in a Klebsiella pneumoniae isolate from Istanbul,
Turkey, in 2001.1 OXA-48 carbapenemases are plasmid mediated
and frequently detected in K. pneumoniae, but also in other
Enterobacteriaceae, including Escherichia coli, Enterobacter
cloacae and Citrobacter freundii. OXA-48 hydrolyses penicillins
and carbapenems, but spares cephalosporins. OXA-48-producing Enterobacteriaceae (OXA-E) pose major challenges in
patient management as resistance is not consistently phenotypically expressed, especially in isolates not coproducing ESBL,
hampering identification by routine microbiological laboratory
methods.2,3
OXA-48-type carbapenemases have been identified mostly in
eastern and southern Mediterranean countries and are widely disseminated throughout Europe.4 Hospital outbreaks in western
European countries and in the northern part of Africa have been
linked to transfer of patients from endemic regions, including
Turkey and Morocco.5
During hospital outbreaks, identification of patients at
the highest risk of acquisition will optimize screening and isolation strategies. However, risk factors for acquisition of OXA-E
have not been identified, so far. The reported risk factors for
other carbapenemase-producing and/or carbapenem-resistant
Enterobacteriaceae include illness severity,6 comorbidities such
as pulmonary disease,7,8 presence of invasive devices,9 previous
hospitalization or ICU stay,7,8 and prior antibiotic use,8,10 including
carbapenems,7,11 b-lactam/b-lactamase inhibitors,7 cephalosporins6,12 and fluoroquinolones.6
# The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved.
For Permissions, please e-mail: [email protected]
2273
Dautzenberg et al.
In the Netherlands OXA-48 is only sporadically detected in hospitalized patients and the community. Between 2009 and 2011
an outbreak of OXA-E occurred in a Dutch hospital, in which at
least 118 patients were involved, and most likely with interspecies spread of the OXA-48 plasmid.13 In the context of this
OXA-E outbreak we determined risk factors for acquisition of
OXA-E (colonization or infection) using a matched case – control
study design.
Patients and methods
Setting
During an outbreak of OXA-E (July 2009 to July 2011), 72 147 patients
were classified into risk groups based on assumed risk of acquisition
of OXA-E and screened accordingly, as described in Dautzenberg et al.13
In short, screening swabs were collected from the rectum, throat and possible infection sites on three consecutive days, inoculated in ertapenem
broth and screened for OXA-48 using high-throughput PCR methods. In
total, 7527 patients were screened during hospitalization (hospital screening), after hospital discharge at home (post-discharge screening) or when
readmitted. The presence of OXA-48 was also determined retrospectively
in stored isolates (retrospective screening).
Selection of cases and controls
All patients eligible for the current study had been hospitalized in the
Maasstad Hospital, Rotterdam, the Netherlands, during the OXA-E outbreak period (from 1 January 2009 to 18 July 2011) and had been
screened for OXA-E carriage. Cases had documented OXA-E carriage and
controls had documented absence of OXA-E carriage based on at least one
screening culture.
Cross-transmission of bacteria or plasmids is the main driving factor
for OXA-E acquisition during a hospital outbreak, especially in a setting
of low prevalence of OXA-E in a hospital and the community. Therefore,
differences in colonization pressure should be taken into account when
determining risk factors.14,15 As the number of colonized patients per
day could not be quantified, a proxy was used to distinguish differences
in colonization pressure, which includes location in the hospital and
assumed exposure duration. For patients screened during hospitalization,
the day of obtaining the first culture yielding OXA-E (for cases) and the
days of obtaining cultures that did not yield OXA-E (for potential controls)
were used as index dates. For patients screened in post-discharge screening, the last day of hospitalization during the outbreak period was used as
the index date. Controls were matched to cases based on: (i) the index
date (+1 week); (ii) the ward of admission at the index date (exact
match); and (iii) the logarithm of length of stay in the hospital during
the outbreak period, before the index date (best match) (Figure 1). For controls an index date could be selected based on all available negative culture results, including negative cultures preceding a first positive culture
result of case patients.
For each case patient three control patients were selected. Case
patients for which, based on the above-mentioned criteria, no suitable
controls were available, were excluded from analysis. For efficiency reasons, controls could only be selected once. When individual control
patients were eligible for matching to multiple case patients (i.e. multiple
OXA-E carriers in a single ward in a short time period), selection of control
patients was performed in successive steps, each time selecting the bestmatching control for each consecutive case patient.
Data collection
Potential risk factors and matching variables were collected retrospectively from the hospital information system and included age, gender, hospital admission and discharge dates, ward of admission, in-hospital
antibiotic treatment, Charlson comorbidity index (CCI) and comorbidities
(diabetes, peptic ulcer, respiratory illness, kidney disease, transplant and
cancer). These comorbidities were selected based upon their inclusion in
the Chronic Disease Score – Infectious Disease (CDS-ID).16
Data analysis
Data analysis was performed using multivariable conditional logistic
regression that took matching of cases and controls into account,17 with
acquisition of OXA-E as a dependent variable and potential risk factors as
independent variables. All potential risk factors were included in the multivariable analysis. Because of differences in resistance profiles, additionally
a stratified analysis was performed for carriers of OXA-E with and without
ESBL. For stratification, only isolates from the first culture were considered.
Patients cultured in hospital screening
Admission
Culture
Index date
Start of
outbreak
End of
outbreak
3.
1.&2.
Patients cultured in post-discharge screening
Last admission during
outbreak period
Culture
End of
outbreak
Start of
outbreak
3.
1.&2.
Figure 1. Matching of cases and controls. Matching was performed on: (1) index date (+1 week); (2) ward (exact match); and (3) log(exposure time)
(best match).
2274
JAC
Risk factors for the acquisition of OXA-E
For this analysis, only variables with P,0.20 in univariable analysis were
included in the multivariable model.
Analyses were performed with Firth correction because of low patient
numbers and a relatively large number of independent variables.18 Results
are given as ORs with 95% CIs and P, 0.05 was considered statistically
significant. Analyses were performed using the package ‘coxphf’ in
R version 3.0.3.
Ethics
The Medical Ethics Review Committee of the Maasstad Ziekenhuis determined that this study was exempted from evaluation with regard to the
Dutch Medical Research Involving Subjects Act (reference number 13.153).
Results
In all, 73 OXA-E carriers were identified during hospital and postdischarge screening, of which 2 were excluded (no suitable controls
available), and for 1 patient only 1 suitable control could be included,
yielding 71 cases matched to 211 controls for analysis. There were
no missing data. Baseline characteristics are shown in Table 1. All
patients had documented carriage of OXA-E and five of them an
infection with OXA-E. The most widely used antibiotics in these
patients were amoxicillin with clavulanic acid (n ¼ 37 cases and
53 controls), ciprofloxacin (n ¼ 22 cases and 26 controls) and
cefazolin (n¼6 cases and 24 controls). Meropenem was the only
carbapenem used (n ¼ 4 controls). Other antibiotics included,
amongst others, trimethoprim/sulfamethoxazole and metronidazole (Table S1, available as Supplementary data at JAC Online). As
there was no carbapenem use or organ transplant in cases
(Table 1), these variables could not be included in the multivariable
conditional logistic regression model.
Multiple OXA-48-producing microorganisms were detected in 39
of 71 patients (54.9%). In 53 cases OXA-48-producing K. pneumoniae were detected and in 44 cases OXA-48-producing E. coli were
detected (Table 2). OXA-E isolates that also produced ESBL were
more frequently resistant to cephalosporins, ciprofloxacin, trimethoprim/sulfamethoxazole, gentamicin and amikacin than non-ESBLproducing isolates (Table 3).
In the multivariable conditional logistic regression model, male
gender, increasing age and quinolone use during the 30 days preceding the index date were identified as risk factors for the acquisition of OXA-E (Table 4). In the stratified multivariable conditional
logistic regression model, quinolone use was associated with
acquisition of ESBL-producing OXA-E and surgery was associated
with acquisition of non-ESBL-producing OXA-E (Table 4). Results of
analyses with and without Firth correction are provided in Tables
S2, S3 and S4.
Because of the observed difference in exposure time of cases and
controls, a sensitivity analysis was performed, using only controls
with a maximum of 7–14 days difference in exposure time compared with their corresponding case patients, yielding similar results,
with, as expected, no association with exposure time (Table S5).
Table 1. Baseline characteristics
All OXA-E
ESBL-producing OXA-E
Non-ESBL-producing OXA-E
cases (n¼71)
controls (n ¼211)
cases (n¼22)
controls (n¼66)
cases (n¼50)
controls (n ¼148)
Exposure time (days), median (IQR)
19 (6–39)
11 (5–26)
16 (5– 23)
11 (4–20)
21 (7– 43)
13 (5–29)
Male gender
43 (60.6)
93 (44.1)
16 (72.7)
31 (47.0)
27 (54.0)
61 (41.2)
Age (years), median (IQR)
70 (61 –78)
66 (48– 79)
71 (53 –78)
62 (46– 77)
69 (61 –78)
67 (49– 80)
CCI, median (IQR)
peptic ulcer
diabetes mellitus
chronic pulmonary disease
malignancy
transplant
mild to severe renal disease
2 (1–3)
4 (5.6)
12 (16.9)
17 (23.9)
18 (25.4)
0 (0.0)
4 (5.6)
1 (0–2)
8 (3.8)
31 (14.7)
48 (22.7)
29 (13.7)
2 (0.9)
12 (5.7)
1.5 (1– 3)
0 (0.0)
6 (27.3)
6 (27.3)
4 (18.2)
0 (0.0)
1 (4.5)
1 (0–2.8)
1 (1.5)
10 (15.2)
14 (21.2)
13 (19.7)
1 (1.5)
3 (4.5)
2 (1– 2.8)
4 (8.0)
8 (16.0)
11 (22.0)
14 (28.0)
0 (0.0)
3 (6.0)
1 (0–2)
2 (4.7)
21 (14.2)
34 (23.0)
17 (11.5)
1 (0.7)
10 (6.8)
Use of antibioticsa
penicillins (+inhibitor)
cephalosporins
carbapenems
quinolones
aminoglycosides
macrolides/lincosamides
other
38 (53.5)
7 (9.9)
0 (0.0)
23 (32.4)
8 (11.3)
13 (18.3)
14 (19.7)
62 (29.4)
31 (14.7)
4 (1.9)
27 (12.8)
4 (1.9)
12 (5.7)
42 (19.9)
9 (40.9)
0 (0.0)
0 (0.0)
9 (40.9)
0 (0.0)
3 (13.6)
4 (18.2)
17 (25.8)
10 (15.2)
1 (1.5)
5 (7.6)
1 (1.5)
2 (3.0)
12 (18.2)
26 (52.0)
6 (12.0)
0 (0.0)
13 (26.0)
8 (16.0)
10 (20.0)
10 (20.0)
46 (31.1)
21 (14.2)
3 (2.0)
21 (14.2)
3 (2.0)
10 (6.8)
31 (20.9)
Surgerya
35 (49.3)
84 (39.8)
10 (45.5)
32 (48.5)
27 (54.0)
55 (37.2)
10 (14.1)
18 (8.5)
0 (0.0)
5 (7.6)
10 (20.0)
14 (9.5)
Variable
a
Admission to ICU
Values are given as n (%) unless otherwise specified.
Within 30 days before the index date.
a
2275
Dautzenberg et al.
Discussion
The results of this study demonstrate that, during an outbreak of
OXA-E, fluoroquinolone use was the only modifiable risk factor for
acquisition of OXA-E that could be identified, which underscores
the relevance of selective antibiotic pressure during nosocomial
outbreaks of bacteria resistant to multiple antibiotics. Our findings
also demonstrate that this outbreak occurred in the almost complete absence of selective pressure induced by carbapenems.
Most OXA-48-producing isolates involved in this outbreak did
not harbour ESBL genes and were susceptible to fluoroquinolones,
cephalosporins and carbapenems. In the stratified analysis,
acquisition of these isolates was associated with surgery. For
this analysis stratification was based on the presence or absence
of ESBL genes in the first positive culture, as follow-up cultures
with OXA-48 in a different species or with a different resistance
profile can be the result of new acquisition, but also of horizontal
gene transfer within the patient. In our study risk factors for
ESBL-coproducing Enterobacteriaceae appeared similar to risk
factors previously reported for only ESBL producers (quinolones,
diabetes mellitus), suggesting that OXA-48 might have been a
mere bystander for ESBL production.
The statistically significant effect of exposure time in the
regression model resulted from imperfect matching. Especially
Table 2. OXA-48-producing microorganisms detected in cases
Organism
Number of patients
Only K. pneumoniae
K. pneumoniae and E. coli
K. pneumoniae and other
K. pneumoniae and E. coli and other
Only E. coli
E. coli and other
Only other
19
17
5
12
10
5
3
for case patients with long exposure time, it was difficult to identify controls with comparable exposure times. Despite the use of
the logarithm of exposure time for matching, because of the rightskewed distribution of exposure time, case patients had longer
average exposure times than controls. The sensitivity analysis,
using only controls with a maximum of 7 – 14 days difference in
exposure time compared with their corresponding case patients
yielded similar results, with, as expected, no association with
exposure time.
Strengths of this study include the large number of cases
(in comparison with previous studies19 – 22) and the use of an
adequate control group, with correction for colonization pressure,
which was not performed in other risk factor analyses for acquisition of resistant bacteria.23,24
Often, control groups consisting of patients carrying the susceptible variant of the bacteria are used. However, as de novo
emergence of OXA-48 in Enterobacteriaceae is highly unlikely,
patients colonized with susceptible Enterobacteriaceae are not
representative of the source population. Using such controls
could therefore lead to an inflated (biased) estimate of the effect
of antibiotic exposure, as receiving certain antibiotics might inhibit
the recovery of susceptible organisms.24,25 A case –control design
using patients uncolonized with OXA-48 as controls does select
controls representative of the source population. With this design,
risk factors for the acquisition of OXA-E in general are identified,
not risk factors for acquiring a resistant strain compared with
acquiring susceptible strains, as would be the case when using
controls colonized with susceptible variants.23 This design, however, also has some limitations. It cannot be elucidated whether
the risk factors are associated with acquisition of the organisms in
general (Enterobacteriaceae with or without OXA-48) or with the
resistant phenotype (OXA-48 producers).25 Also, there is a risk of
misclassification bias if undetected cases without a clinical culture taken are included as controls.26 To avoid this, we included
only patients that were screened as possible controls. Sensitivity
of screening for OXA-E is very high,27 so there is a high likelihood
that controls were not colonized with OXA-E at the moment
of screening. Yet the possibility of misclassification due to
Table 3. Antibiotic resistance among OXA-48-producing K. pneumoniae and E. coli isolates
OXA-48-producing K. pneumoniae
Antibiotic
Meropenem
Ertapenema
Ciprofloxacin
Trimethoprim/sulfamethoxazole
Amikacin
Gentamicin
Cefotaxime or ceftriaxone
Cefepime
OXA-48-producing E. coli
Susceptibility
breakpoint (mg/L)
ESBL
producing (n¼60)
non-ESBL
producing (n¼36)
ESBL producing
(n¼3)
non-ESBL producing
(n¼26)
≤2
≤0.5
≤0.5
≤2
≤8
≤2
≤1
≤1
25
100
100
100
12
100
100
100
8
94
72
78
0
17
11
0
0
33
67
100
33
0
100
33
0
57
8
12
0
4
8
0
Numbers are percentages of isolates with intermediate susceptibility or resistance to the given antibiotics, as determined by Vitek 2 (EUCAST 2012
breakpoints).
a
Ertapenem susceptibility testing was performed on 56 K. pneumoniae ESBL-positive isolates, 35 K. pneumoniae ESBL-negative isolates, 3 E. coli
ESBL-positive isolates and 23 E. coli ESBL-negative isolates.
2276
JAC
Risk factors for the acquisition of OXA-E
Table 4. Multivariable conditional logistic regression risk factor analysis for acquisition of OXA-E
All, 71 cases and 211 controls
Variable
Exposure time, per day
Male gender
Age, per year
Peptic ulcer
Diabetes mellitus
Chronic pulmonary disease
Malignancy
Mild to severe renal disease
Penicillins (+inhibitor)a
Cephalosporinsa
Quinolonesa
Aminoglycosidesa
Macrolides/lincosamidesa
Other antibioticsa
Surgerya
Admission to ICUa
ESBL-producing OXA-E,
22 cases and 66 controls
Non-ESBL-producing OXA-E,
50 cases and 148 controls
OR (95% CI)
P
OR (95% CI)
P
OR (95% CI)
P
1.08 (1.03–1.13)
2.63 (1.25–5.53)
1.03 (1.00–1.05)
1.41 (0.52–3.78)
0.66 (0.28–1.57)
1.12 (0.41–3.06)
2.16 (0.37–12.72)
1.45 (0.38–5.48)
1.82 (0.73–4.54)
0.92 (0.30–2.85)
2.98 (1.06–8.41)
6.16 (0.75–50.86)
1.62 (0.41–6.41)
0.88 (0.30–2.56)
2.35 (0.84–6.56)
0.60 (0.17–2.09)
0.001
0.011
0.041
0.498
0.348
0.818
0.395
0.583
0.201
0.884
0.039
0.091
0.491
0.808
0.102
0.425
1.11 (0.98–1.26)
2.34 (0.58–9.36)
1.03 (0.98–1.08)
0.105
0.230
0.266
1.06 (1.01–1.11)
1.80 (0.74–4.33)
0.012
0.193
6.12 (0.97–38.55)
0.054
2.19 (0.62–7.75)
0.225
1.00 (0.22–4.45)
0.997
2.46 (0.80–7.54)
0.115
13.76 (1.88–101.00)
0.010
1.01 (0.08–13.11)
0.992
1.21 (0.31–4.75)
6.02 (0.82–44.23)
2.29 (0.42–12.40)
0.787
0.078
0.338
4.52 (1.20–16.98)
0.78 (0.19–3.27)
0.025
0.738
For the ESBL-producing OXA-E and non-ESBL-producing OXA-E groups only variables with P, 0.20 in the univariable analysis were included in the
multivariable model.
a
Within 30 days before the index date.
decolonization remained, which may occur especially after hospital
discharge, when antibiotic pressure declines. However, as the prevalence of OXA-E carriage in the hospital population was low (even in
the high-risk group only 1% of patients tested positive), the likelihood
of misclassification bias among controls is also very low and, if any
bias exists, estimates would be biased towards the null effect.
Another proposed study design in risk factor analysis for resistant bacteria is the case –case – control study design.25 However,
as we investigated acquisition of colonization, it would be very difficult to define a timepoint at which carriage with susceptible
Enterobacteriaceae was acquired.
Colonization pressure is a main driving factor for acquisition
during hospital outbreaks and is typically related to the physical
location of the patient within the hospital. We therefore matched
on ward, precluding spurious effects of admission speciality being
detected.
Patients detected in retrospective screening were not included
in this analysis. They were identified based on stored clinical cultures and the date of acquisition could not be determined. Also, as
patients cannot be considered OXA-E negative based on clinical
cultures only, it was not possible to select a proper control
group for these patients.
This study has some potential limitations. It is a single-hospital
outbreak study, which hampers generalizability. Although the
outbreak was one of the largest reported OXA-48 outbreaks as
of today, the number of patients involved is still relatively low
compared with the number of variables tested. We aimed to identify risk factors without a priori hypotheses relative to particular
variables. Although we incorporated a Firth correction in order
to reduce bias (Tables S2, S3 and S4), identification of spurious
associations is not excluded. In fact, the finding of male gender
as a risk factor for OXA-E acquisition may well indicate the presence of residual confounding. We investigated the effect of
surgery and ICU admission. In general, however, the true risk factors might have been, e.g. wound treatment after surgery or
mechanical ventilation on the ICU. Data on antibiotic use was
only available for in-hospital antibiotic use. Prescriptions before
hospital admission could not be traced.
Although the use of matching in the study had advantages, it
may also have posed some limitations. Because of the matching,
the effect of exposure time or colonization pressure cannot be
quantified. Also, matching on admission ward and length of
stay prior to the culture might have caused additional matching
on, e.g. comorbidities (patients admitted to the same ward are
more likely to have similar comorbidities than patients admitted
to different wards) and disease severity (patients with a higher
disease severity are more likely to stay longer in the hospital).
Formal risk-factor analyses for the acquisition of OXA-E have not
been performed previously; however, case reports or patient
cohorts have been described with respect to possible risk factors.
In different populations of patients colonized or infected with
OXA-E, the reported median age ranges from 59 to 74 years and
the percentage of males ranges from 50 to 57.5, with high prevalence of comorbidities (malignancy), previous healthcare contacts
or nosocomial acquisition, use of antibiotics (carbapenem use),
presence of invasive devices and ICU stay.19,20,22,28 An outbreak
of OXA-48-producing K. pneumoniae has been linked to the use
of a possibly contaminated duodenoscope for endoscopic retrograde cholangiopancreatography.21 Also, two patients were
infected with OXA-48-producing K. pneumoniae through a solid
2277
Dautzenberg et al.
organ transplant (liver and kidney) from the same donor.29 As
these studies do not have control groups, associations could not
be quantified.
Prior fluoroquinolone use is known to be associated with acquisition of quinolone-resistant E. coli and K. pneumoniae,30,31 and
also with Enterobacteriaceae resistant to non-fluoroquinolones,
including carbapenemase-producing Enterobacteriaceae.6,10,32
Our finding of prior fluoroquinolone use as a risk factor of OXA-E
acquisition is in line with these findings. Explanations for this
include suppression of intestinal flora susceptible to fluoroquinolones, as well as (plasmid-mediated) co-resistance of OXA-E to
fluoroquinolones.33,34
Conclusions
This hypothesis-generating study suggests that recent use
of fluoroquinolones and increasing age were risk factors for
the acquisition of OXA-E during a large hospital outbreak of
OXA-E. These findings may be used to identify high-risk patients
for screening and isolation in other OXA-E outbreak settings, but
should—preferably—be validated in future studies.
Acknowledgements
Preliminary results of this research were presented at the Twenty-fifth
European Congress of Clinical Microbiology and Infectious Diseases,
Copenhagen, Denmark, 2015 (Oral Presentation O125).
We would like to thank W. C. Rottier and C. H. van Werkhoven for their
advice on study design and analysis.
Funding
This study was supported by internal funding.
Transparency declarations
None to declare.
5 Poirel L, Ros A, Carrër A et al. Cross-border transmission of OXA-48producing Enterobacter cloacae from Morocco to France. J Antimicrob
Chemother 2011; 66: 1181– 2.
6 Gasink LB, Edelstein PH, Lautenbach E et al. Risk factors and clinical impact
of Klebsiella pneumoniae carbapenemase-producing K. pneumoniae. Infect
Control Hosp Epidemiol 2009; 30: 1180–5.
7 Papadimitriou-Olivgeris M, Marangos M, Fligou F et al. Risk factors for
KPC-producing Klebsiella pneumoniae enteric colonization upon ICU
admission. J Antimicrob Chemother 2012; 67: 2976 –81.
8 Swaminathan M, Sharma S, Poliansky Blash S et al. Prevalence and risk
factors for acquisition of carbapenem-resistant Enterobacteriaceae
in the setting of endemicity. Infect Control Hosp Epidemiol 2013; 34:
809 – 17.
9 Marchaim D, Navon-Venezia S, Schwaber MJ et al. Isolation
of imipenem-resistant Enterobacter species: emergence of KPC-2 carbapenemase, molecular characterization, epidemiology, and outcomes.
Antimicrob Agents Chemother 2008; 52: 1413– 8.
10 Patel N, Harrington S, Dihmess A et al. Clinical epidemiology of
carbapenem-intermediate or -resistant Enterobacteriaceae. J Antimicrob
Chemother 2011; 66: 1600– 8.
11 Gagliotti C, Giordani S, Ciccarese V et al. Risk factors for colonization
with carbapenemase-producing Klebsiella pneumoniae in hospital: a
matched case–control study. Am J Infect Control 2014; 42: 1006 –8.
12 Patel G, Huprikar S, Factor SH et al. Outcomes of carbapenemresistant Klebsiella pneumoniae infection and the impact of antimicrobial
and adjunctive therapies. Infect Control Hosp Epidemiol 2008; 29:
1099 – 106.
13 Dautzenberg MJ, Ossewaarde JM, de Kraker ME et al. Successful control
of a hospital-wide outbreak of OXA-48 producing Enterobacteriaceae in
the Netherlands, 2009 to 2011. Euro Surveill 2014; 19: pii¼20723.
14 Bonten MJ. Colonization pressure: a critical parameter in the epidemiology of antibiotic-resistant bacteria. Crit Care 2012; 16: 142.
15 D’Agata EMC. Methodologic issues of case– control studies: a review
of established and newly recognized limitations. Infect Control Hosp
Epidemiol 2005; 26: 338–41.
16 McGregor JC, Perencevich EN, Furuno JP et al. Comorbidity
risk-adjustment measures were developed and validated for studies of
antibiotic-resistant infections. J Clin Epidemiol 2006; 59: 1266 –73.
17 Breslow NE, Day NE. Statistical methods in cancer research. Volume I—
The analysis of case– control studies. IARC Sci Publ 1980; 32: 5 –338.
Supplementary data
Tables S1 to S5 are available as Supplementary data at JAC Online (http://
jac.oxfordjournals.org/).
18 Heinze G, Puhr R. Bias-reduced and separation-proof conditional
logistic regression with small or sparse data sets. Stat Med 2010; 29:
770 – 7.
References
19 Balkan II, Aygün G, Aydin S et al. Blood stream infections due to
OXA-48-like carbapenemase-producing Enterobacteriaceae: treatment
and survival. Int J Infect Dis 2014; 26: 51–6.
1 Poirel L, Héritier C, Tolün V, Nordmann P. Emergence of oxacillinasemediated resistance to imipenem in Klebsiella pneumoniae. Antimicrob
Agents Chemother 2004; 48: 15– 22.
20 Thomas CP, Moore LSP, Elamin N et al. Early (2008– 2010) hospital outbreak of Klebsiella pneumoniae producing OXA-48 carbapenemase in the
UK. Int. J Antimicrob Agents 2013; 42: 531– 6.
2 Gupta N, Limbago BM, Patel JB, Kallen AJ. Carbapenem-resistant
Enterobacteriaceae: epidemiology and prevention. Clin Infect Dis
2011; 53: 60– 7.
21 Kola A, Piening B, Pape U-F et al. An outbreak of carbapenem-resistant
OXA-48-producing Klebsiella pneumonia associated to duodenoscopy.
Antimicrob Resist Infect Control 2015; 4: 8.
3 Nordmann P, Gniadkowski M, Giske CG et al. Identification and screening
of carbapenemase-producing Enterobacteriaceae. Clin Microbiol Infect
2012; 18: 432–8.
22 Navarro-San Francisco C, Mora-Rillo M, Romero-Gómez MP et al.
Bacteraemia due to OXA-48-carbapenemase-producing Enterobacteriaceae:
a major clinical challenge. Clin Microbiol Infect 2013; 19: E72–9.
4 Nordmann P, Poirel L. The difficult-to-control spread of carbapenemase
producers among Enterobacteriaceae worldwide. Clin Microbiol Infect
2014; 20: 821–30.
23 Schechner V, Temkin E, Harbarth S et al. Epidemiological interpretation
of studies examining the effect of antibiotic usage on resistance.
Clin Microbiol Rev 2013; 26: 289–307.
2278
Risk factors for the acquisition of OXA-E
24 Harris AD, Karchmer TB, Carmeli Y et al. Methodological principles of
case – control studies that analyzed risk factors for antibiotic resistance:
a systematic review. Clin Infect Dis 2001; 32: 1055– 61.
25 Kaye KS, Harris AD, Samore M et al. The case – case – control study
design: addressing the limitations of risk factor studies for antimicrobial
resistance. Infect Control Hosp Epidemiol 2005; 26: 346–51.
26 Harris AD, Carmeli Y, Samore MH et al. Impact of severity of illness bias and
control group misclassification bias in case–control studies of antimicrobialresistant organisms. Infect Control Hosp Epidemiol 2005; 26: 342–5.
JAC
30 Lautenbach E, Strom BL, Bilker WB et al. Epidemiological investigation
of fluoroquinolone resistance in infections due to extended-spectrum
b-lactamase-producing Escherichia coli and Klebsiella pneumoniae. Clin
Infect Dis 2001; 33: 1288– 94.
31 Lautenbach E, Metlay JP, Weiner MG et al. Gastrointestinal tract colonization with fluoroquinolone-resistant Escherichia coli in hospitalized
patients: changes over time in risk factors for resistance. Infect Control
Hosp Epidemiol 2009; 30: 18 –24.
27 Van der Zee A, Roorda L, Bosman G et al. Multi-centre evaluation of
real-time multiplex PCR for detection of carbapenemase genes OXA-48,
VIM, IMP, NDM and KPC. BMC Infect Dis 2014; 14: 27.
32 Schwaber MJ, Klarfeld-Lidji S, Navon-Venezia S et al. Predictors of
carbapenem-resistant Klebsiella pneumoniae acquisition among hospitalized adults and effect of acquisition on mortality. Antimicrob Agents
Chemother 2008; 52: 1028– 33.
28 Pano-Pardo JR, Ruiz-Carrascoso G, Navarro-San Francisco C et al.
Infections caused by OXA-48-producing Klebsiella pneumoniae in a
tertiary hospital in Spain in the setting of a prolonged, hospital-wide outbreak. J Antimicrob Chemother 2012; 68: 89– 96.
33 Barguigua A, Zerouali K, Katfy K et al. Occurrence of OXA-48 and
NDM-1 carbapenemase-producing Klebsiella pneumoniae in a Moroccan
university hospital in Casablanca, Morocco. Infect Genet Evol 2015; 31:
142–8.
29 Giani T, Conte V, Mandalà S et al. Cross-infection of solid organ transplant recipients by a multidrug-resistant Klebsiella pneumoniae isolate
producing the OXA-48 carbapenemase, likely derived from a multiorgan
donor. J Clin Microbiol 2014; 52: 2702– 5.
34 Rodrı́guez Martı́nez JM, Dı́az-de Alba P, Lopez-Cerero et al. Presence
of quinolone resistance to qnrB1 genes and blaOXA-48 carbapenemase
in clinical isolates of Klebsiella pneumoniae in Spain. Enferm Infecc
Microbiol Clin 2014; 32: 441– 2.
2279