Risk Factors for Intra-Abdominal Infections Caused by Carbapenemase-Producing Enterobacteriaceae in a Surgical Setting

Abstract

Background:

The aim of this study was to identify risk factors for acquisition of intra-abdominal infections (IAI) caused by carbapenemase-producing Enterobacteriaceae (CPE) in surgical patients.

Methods:

A matched case-control study was performed. We included all cases with CPE-related IAI acquired during admission to a general surgery department from January 2013 to December 2018, and they were matched with control subjects with IAI caused by non-resistant bacteria (ratio 1:3). Independent risk factors were obtained by logistic regression.

Results:

Forty patients with IAI-CPE were matched with 120 control subjects. Independent risk factors for acquisition of IAI-CPE were previous hospitalization (odds ratio [OR] 2.56; 95% confidence interval [CI] l 1.01–6.49; p = 0.047), digestive endoscopy (OR 4.11; 95% CI 1.40–12.07; p = 0.010), carbapenem therapy (OR 9.54; 95% CI 3.33–27.30; p < 0.001), and aminoglycoside use (OR 45.41; 95% CI 7.90–261.06; p < 0.001).

Conclusions:

Four clinical factors can identify patients at high-risk of IAI-CPE.

Infections caused by carbapenemase-producing Enterobacteriaceae (CPE) are considered a priority and a public health problem, with limited therapeutic options available [1 –3]. These multi-drug-resistant (MDR) bacterial infections imply a significant rate of complications and mortality in hospitalized patients, with increased length of stay (LOS) and higher costs of hospitalization [4 –6].

Risk factors for acquisition of CPE-related infections have been detailed in numerous publications. Prior administration of antibiotic therapy is a key factor, with other relevant variables such as recent hospitalizations, need for periodic medical care/medical devices, or several co-morbidities [7,8]. Although specific studies analyzing intra-abdominal infections (IAI) and CPE are scarce, IAI is an important cause of complications and death, especially in surgical patients and those having abdominal operations [9 –11]. The possibility of identifying those patients with IAI admitted to surgical wards who are at high risk of acquiring IAI-CPE could be a useful tool to improve strategies for prevention and control of CPE. Previous studies have described several independent risk factors including some predictive models of acquisition of these infections in other populations at risk [12 –14].

The aim of this study was to identify risk factors for acquisition of IAI-CPE in hospitalized surgical patients with IAI.

Patients and Methods

Study design and population

The study was performed at a tertiary-care teaching hospital (600 beds). Cases and control subjects were obtained from patients admitted to our General Surgery Department (GSD) from January 2013 to December 2018. This study was reviewed and approved by the hospital's Research Ethics Committee.

A matched case-control study was designed to reach our objective. A patient was defined as a case with the following inclusion criteria: Adults aged >18 years and at least one positive culture for CPE from an intra-abdominal source 48 hours after admission and associated clinical data of IAI. Exclusion criteria were patients not admitted to the GSD, those with incomplete microbiologic information about CPE, those with CPE isolation from other sources than the abdomen, CPE isolation in units other than the GSD, and asymptomatic carriers of CPE. Asymptomatic carriers were not systematically studied in our unit previously, therefore this group was excluded. Consecutive patients with nosocomial IAI-CPE acquired while admitted to the GSD from January 2013 to December 2018 were included. We selected matched control subjects (ratio 1:3) defined as patients with IAI with no CPE-positive culture 48 hours after admission to the GSD.

Patients with IAI were included without using the traditional terminology based on anatomic location of the infection because of the difficult applicability in clinical practice (it does not assess the severity of IAI or the clinical situation of the patient), and we collected patient factors [15,16]. Matching involved date of hospitalization (year and month of admission), ward (GSD), and intra-abdominal location of underlying disease (colorectal, stomach, small bowel, liver, biliary tree, pancreas, abdominal wall).

Patient data were provided in a database and reviewed from admission to hospital discharge or death. Only clinically relevant isolates were included, and all patients were included only once.

Clinical and microbiologic characteristics and treatment and complications were retrieved from the medical records. Demographic data and co-morbidities including malignant diseases and Charlson Comorbidity Index were included. Risk factors recorded were hospitalization in the previous 12 months and antibiotic use and type >48 hours, surgical operations, dialysis, and invasive endoscopic procedures performed in the last 30 days. Procedures and interventions performed during the current hospitalization (before the positive culture) also were recorded: Dialysis, blood transfusion, intubation or mechanical ventilation, tracheostomy, central venous catheter placement, indwelling gastric tube insertion, indwelling urethral catheter establishment, abdominal drain placement, parenteral nutrition administration, ICU admission (stay >48 hours), and endoscopic procedures. Data related to the surgical procedures were collected: American Society of Anesthesiologists (ASA) status [17], specific location of the pathology (liver, biliary, pancreas, stomach, colon, rectum, etc.), elective/emergency operation, approach (open, minimally invasive), U.S. Centers for Disease Control and Prevention (CDC) classification of surgical contamination (clean, clean–contaminated, contaminated, and dirty), re-operations, and complications including 30-day mortality rate (registered according to the Clavien-Dindo classification [18]). Microbiological data and infection-related variables were septic shock, species of CPE isolated and carbapenemase classification [19], microbiologic susceptibility patterns for CPE, and isolation of other concomitant MDR bacteria (extended-spectrum β-lactamases (ESBL)). Appropriate empirical antimicrobial regimens and definitive therapy (including use of combination therapy) used were also registered. Median LOS and readmissions were also collected for each patient.

Definitions

The following terms were specified prior to database analysis: 1.

Nosocomial infection was defined as an infection that occurred 48 hours after the current hospital admission or an infection that already existed within the previous two weeks related with another hospital admission [20].

Septic shock was catalogued as sepsis associated with hemodynamic failure and persistent hypotension despite adequate volume replacement, including systolic blood pressure <90 mm Hg, mean blood pressure <60 mm Hg, or reduction in systolic blood pressure >40 mm Hg from the arterial baseline pressure [21].

The probable infectious source was defined for each patient according to microbiologic results and the analysis of clinical findings by two physicians in accordance with CDC definitions [20,22].

An appropriate empirical antimicrobial regimen referred to as administration of in vitro active antimicrobial drugs against the CPE isolate within the first 24 hours from the infection onset.

Appropriate definitive treatment was determined if it showed in vitro activity against the studied isolate and was administered for at least 48 hours [23].

Treatment regimens were defined as monotherapy or combination therapy on the basis of the number of active antimicrobials included.

Microbiologic methods

Patient samples were collected and incubated based on standard recommendations. Cultures were processed using standard methodology according to the Clinical and Laboratory Standards Institute guidelines [24]. MicroScan System “Walk away” ^® (Beckman Coulter, Spain) was used for microbiologic identification and to determine susceptibility patterns, according to manufacturer recommendations. All the strains with minimum inhibitory concentrations (MIC) >0.125 mg/L for ertapenem and meropenem, and MIC >1 mg/L for imipenem following European Committee Antimicrobial Susceptibility Testing (EUCAST) recommendations [25], were included. In the strains isolated in 2013 and 2014, phenotypic detection of carbapenemase was performed using the CARBA NP colorimetric method [26] and were studied genotypically at the National Center of Microbiology (Carlos III Health Institute). In those obtained from 2015 onward, phenotypic study was performed by immunochromatography using OXA-48 Card Letitest (Coris BioConcept, Belgium) [27], and polymerase chain reaction (PCR) Xpert Carba-R (Cepheid Sunnyvale, CA) was performed in those with negative results with the phenotypic method [28].

Statistical analysis

The results were expressed as counts and proportions for categorical variables and means with standard deviations (SD) or median with interquartile range (IQR) for continuous variables. The normality of distributions was determined using the Kolmogorov-Smirnov test. The χ² test or the two-tailed Fisher exact test were used for comparison of categorical variables. Continuous variables were compared by the Student t-test and the Mann-Whitney U test, according to normally and non-normally distributed variables, as required. The differences were considered using two-tailed tests, and p values <0.05 were considered statistically significant.

Statistically significant variables were selected from univariate analyses and included in a multivariable binary logistic regression (stepwise regression method). The logistic regression model included a maximum number of variables taking into account the existence of at least 10 cases per variable (number of events per variable), following the recommendations of Peduzzi et al. [29]. The validity of the model was evaluated using the Hosmer-Lemeshow (test for goodness of fit) to determine calibration using area under the receiver operating characteristic (ROC) curve (AUC) to determine accuracy.

All statistical analyses were performed using SPSS^® v. 25.0 for Windows (SPSS Inc., Chicago, Illinois, USA).

Results

Cohort characteristics of IAI-CPE

During the study period, 40 patients were found to have a CPE-related IAI while they were hospitalized in the GSD. Table 1 shows the characteristics of the case cohort and the control subjects. Surgery was performed previous to the IAI-CPE diagnosis in 34 patients (85%), and the re-operation rate was 30%. The median LOS until CPE isolation was 18 (IQR 8–22) days, and the median global LOS for IAI-CPE was 43 (IQR 27–64) days. The 30-day mortality rate for IAI-CPE was 17.5%.

Table 1.

Univariable Analysis of Risk Factors for IAI-CPE Acquisition

Characteristic	Total (n = 160)	IAI-CPE (n = 40)	Control subjects (n = 120)	p	n
Patient-related
Male	100 (62.5)	25 (62.5)	75 (62.5)	1	NA
Age (y) (mean ± SD)	64.7 ± 12.9	66.3 ± 11.4	64.7 ± 12.9	0.378	NA
Cardiovascular disease	26 (16.3)	10 (25)	16 (13.3)	0.083	2.17 (0.89–5.27)
Cerebrovascular disease or dementia	7 (4.4)	0	7 (5.8)	0.194	NA
COPD	18 (11.3)	1 (2.5)	17 (14.2)	0.051	0.15 (0.02–1.21)
Solid tumor	76 (47.5)	21 (52.5)	55 (45.8)	0.715	1.14 (0.56–2.34)
Metastatic disease	26 (16.3)	6 (15)	20 (16.7)	0.805	0.88 (0.33–2.38)
Hematologic malignancy	4 (2.5)	0	4 (3.3)	0.573	NA
Anemia	25 (15.6)	8 (20)	17 (14.2)	0.379	1.51 (0.60–3.84)
Immunodeficiency	63 (39.4)	14 (35)	49 (40.8)	0.304	0.67 (0.32–1.43)
Diabetes	34 (21.3)	12 (30)	22 (18.3)	0.118	1.91 (0.84–4.33)
Liver disease	13 (8.1)	7 (17.5)	6 (5)	0.019	4.03 (1.23–12.82)
Chronic renal failure/dialysis	12 (7.5)	6 (15)	6 (5)	0.075	3.35 (1.01–11.07)
Charlson Comorbidity Index (median [IQR])	4 (2–6)	5 (3–6)	4 (2–6)	0.522	NA
Pre-infection intervention
Hospitalization^a	84 (52.5)	27 (67.5)	56 (46.7)	0.022	2.37 (1.12–5.04)
Surgery^b	116 (72.5)	34 (85)	95 (79.2)	0.419	1.49 (0.56–3.95)
Dialysis^b	17 (10.6)	6 (15)	11 (9.2)	0.373	1.75 (0.60–5.08)
ICU^c	62 (38.8)	18 (45)	44 (36.7)	0.349	1.41 (0.68–2.92)
Intubation or mechanical ventilation^b	24 (15)	8 (20)	16 (13.3)	0.306	1.62 (0.64–4.15)
Digestive endoscopy^b	32 (19.4)	11 (27.5)	20 (16.7)	0.047	1.90 (1.21–4.41)
ERCP^b	22 (13.8)	12 (30)	10 (8.3)	0.001	4.71 (1.85–12.02)
Central venous catheter^b	93 (58.1)	26 (65)	67 (55.8)	0.309	1.47 (0.70–3.09)
Nasogastric tube^b	62 (38.8)	17 (42.5)	45 (37.5)	0.574	1.23 (0.59–2.55)
Parenteral nutrition^b	81 (50.6)	23 (57.5)	58 (48.3)	0.315	1.45 (0.70–2.98)
Blood transfusion^b	71 (44.4)	21 (52.5)	50 (41.7)	0.232	1.55 (0.75–3.17)
Re-operation^b	56 (35)	12 (30)	44 (36.7)	0.444	0.74 (0.34–1.60)
Hemorrhage^b	24 (15)	11 (27.5)	13 (10.8)	0.011	3.12 (1.27–7.69)
Recent treatment
Antibiotic therapy^d	120 (75)	40 (100)	80 (66.7)	<0.001	NA
Carbapenems^d	72 (45)	29 (72.5)	43 (35.8)	<0.001	4.72 (2.15–10.38)
Aminoglycosides^d	14 (8.8)	12 (30)	2 (1.7)	<0.001	25.29 (5.35–119.44)
Fluoroquinolones^d	19 (11.9)	10 (25)	9 (7.5)	0.008	4.11 (1.53–11.03)
Piperacillin-tazobactam^d	65 (40.6)	22 (55)	43 (35.8)	0.033	2.12 (1.06–4.52)
Cephalosporins^d	5 (3.1)	3 (7.5)	2 (1.7)	0.100	4.78 (0.77–29.73)

Data are expressed as n (%), unless otherwise stated. Statistically significant figures are in boldface type.

During 12 mos preceding infection onset.

During 30 d preceding infection onset.

ICU (intensive care unit) admission includes only stay >48 h.

Antibiotic use >48 h during 30 days preceding infection onset.

ASA = American Society of Anesthesiologists; COPD = chronic obstructive pulmonary disease; CPE = carbapenemase-producing Enterobacteriaceae; ERCP = endoscopic retrograde cholangiopancreatography; ESBL = extended-spectrum β-lactamases; IQR = interquartile range; NA = non-applicable; OR = odds ratio; SD = standard deviation.

Regarding microbiologic data, OXA-48-producing Klebsiella pneumoniae was the most common CPE, with 34 cases (85%). Enterobacter cloacae was isolated in 3 patients (7.5%) (OXA-48 2 patients and VIM 1 patient), OXA-48-producing Escherichia coli was present in 2 patients (5%), and OXA-48-producing Morganella morganii in 1 patient (2.5%). Co-infection with ESBL-producing bacteria was identified in 10 patients (25%). Classification of CPE patients according to the frequency of intra-abdominal locations of underlying disease was colorectal 32.5%, pancreas 25%, biliary 20%, abdominal wall 7.5%, liver 5%, stomach 5%, and small bowel 5%.

Risk factors associated with IAI-CPE acquisition

Risk factors for IAI-CPE acquisition were analyzed in 160 patients (40 cases and 120 matched control subjects). Significant variables identified from the univariable analysis (Table 1) were included in a logistic regression analysis. The logistic regression model finally identified four independent risk factors (Table 2): Previous hospitalization, digestive endoscopy, carbapenem therapy and aminoglycosides. The model's accuracy was tested through ROC analysis and returned an AUC of 0.844 (95% CI 0.766–0.922; SE = 0.040; p < 0.001) (Fig. 1).

FIG. 1.

Area under the receiver operating characteristic curve.

Table 2.

Logistic Regression Analysis of Risk Factors for IAI-CPE Acquisition

Variable	Coefficient	p	Odds ratio (95% confidence interval)
Hospitalization^a	0.941	0.047	2.56 (1.01–6.49)
Digestive endoscopy^b	1.413	0.010	4.11 (1.40–12.07)
Carbapenems^c	2.256	< 0.001	9.54 (3.33–27.30)
Aminoglycosides^c	3.816	< 0.001	45.41 (7.90–261.06)
Constant	-3.655	< 0.001	0.026

During 12 mos preceding infection onset.

During 30 d preceding infection onset.

Antibiotic use >48 h during 30 d preceding infection onset.

Discussion

To the best of our knowledge, this is the first study to identify risk factors for acquisition of IAI-CPE specifically, including an analysis from a surgical population. Previous literature included a small percentage of studies of surgical patients [9,30,31], with IAI-CPE being a minor subgroup of larger cohorts in some studies [14,32].

Our study identified four independent risk factors for IAI-CPE: Previous hospitalization, digestive endoscopy, and use of carbapenems or aminoglycosides. Hospitalization within the 12 months preceding infection is a variable associated with acquisition of CPE in carriers in multiple studies, being less commonly described as a risk factor for CPE-related infection [7,8,33]. This variable is not exclusive for IAI, and it has been detailed previously in some studies including a high number of cases [14,34,35]. Tumbarello et al. examined the variable two or more hospitalizations within 12 months as an independent risk factor for both colonization and infection [14]. Also, in surgical patients, previous hospitalization was associated with CPE-related surgical site infection in a study about emergency surgery (61% having abdominal surgery) [36].

Endoscopic procedures, and more specifically digestive endoscopy, have been suggested as factors in the transmission of CPE [37]. Specifically, outbreaks have been reported in relation to certain endoscopes and inadequate hygiene, this has been analyzed in specific medical units and consensus groups of endoscopists to improve preventive measures [38,39]. Previous endoscopy has already been described as an independent risk factor for CPE in patients undergoing abdominal surgery [31], and in our experience, this factor was present in almost double the number of IAI-CPE cases compared with control subjects. Considering the underlying diseases of patients susceptible to acquiring IAI (especially colorectal and biliopancreatic conditions), in addition to a high rate of cases with abdominal surgery, recent digestive endoscopy could be considered a specific variable in patients with this clinical profile.

Previous antibiotic use, and specifically of carbapenems, is a crucial risk factor in the development of these infections [5], being the antibiotic group with the greatest potential for the selection of CPE strains. In a recent meta-analysis, it was estimated that the likelihood of acquiring CPE in relation to previous administration of carbapenems increases the risk 4.7 times [8]. In our series, the use of carbapenems increased the risk in as many as 72% of IAI-CPE cases compared with 35% in IAI control subjects. Previous use of aminoglycosides also was identified as a risk factor in some studies that reviewed patients with serious infections and CPE admitted to ICU [40 –42]. The identification of these antibiotics as an important factor can be explained through clinical and microbiologic considerations. Some aminoglycosides are used frequently in the empiric treatment of infections, especially in patients with severe ICU conditions (such as those presenting with sepsis) [43,44], and increasing resistance rates are documented in the literature [45,46]. Thus, in our series, a previous aminoglycoside prescription was detected in 30% cases compared with only 1% of control subjects. Finally, combination therapy can lead to antimicrobial resistance. The acquisition of cross-resistance by plasmid transmission, in particular, is common among CPE [7,47]. Therefore, the use of aminoglycosides, even in the absence of carbapenems, can facilitate the selection of carbapenem-resistant strains [48].

Identification of these risk factors in patients with IAI could be useful in settings with a high prevalence of CPE, where nosocomial infections caused by CPE are associated with high LOS and costs [49]. Therefore, these factors may be kept in mind to identify those individuals at high-risk of acquiring IAI-CPE in relation to IAI patients in a surgical ward. The active detection of CPE (active screening through rectal swab samples) could be applied, and preventive isolation could be established earlier in patients with positive results, allowing reduction of the probability of transmission to other patients. In such a way, Tumbarello et al. proposed the implementation of preventive measures and active detection of CPE selectively in patients at high risk of CPE infection according to a clinical predictive model [14]. The knowledge and identification of some risk factors in clinical practice could help us select better which patients should be screened. Currently, the active screening of CPE is performed mainly in ICU patients (mostly in combination with other MDR bacteria), and the protocol for other units remains unclear, with more heterogeneous criteria. According to the European Centre for Disease Prevention and Control (ECDC), preventive measures and active screening are recommended for “at-risk” patients [50].

Our study has some limitations that must be remembered. As a single-center study with IAI in general surgery patients, outcomes described may not be extrapolated to other populations or centers with different characteristics or microbiologic profiles. Moreover, we acknowledge the limited sample size, although this was improved through the case-control analysis. Regarding the characteristics of the IAI control group, it is possible that the inclusion of asymptomatic carriers (study exclusion criteria) could have been performed unintentionally, because active screening of all patients is not systematically performed in our GSD. Finally, the present investigation represents an observational study and not a clinical trial; therefore, our outcomes and conclusions must be considered accordingly.

In conclusion, our results can be useful for identifying surgical patients at risk of acquisition of IAI-CPE by recognizing some risk factors.

Funding Information

This study received no financial support.

Footnotes

Author Diclosure Statement

All the authors contributed to the conception and design of the study or the acquisition, analysis, or interpretation of data and drafting of the article or revising it for critically important intellectual content. Final approval of the version to be published was given by all the authors, who are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work have been appropriately investigated and resolved.

The authors report no conflicts of interest.

Ethical approval was received from the Clinical Research Ethics Committee of our centre at July 8, 2018.

This article is original and has not been submitted to another journal.

References

Brolund

, Lagerqvist

, Byfors

, et al. Worsening epidemiological situation of carbapenemase-producing Enterobacteriaceae in Europe: Assessment by national experts from 37 countries, July 2018. Eur Surveill, 2019; 24:1900123.

Grundmann

, Glasner

, Albiger

, et al. Occurrence of carbapenemase-producing Klebsiella pneumoniae and Escherichia coli in the European survey of carbapenemase-producing Enterobacteriaceae (EuSCAPE): A prospective, multinational study. Lancet Infect Dis, 2017; 17:153–163.

Tacconelli

, Carrara

, Savoldi

, et al. Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis. Lancet Infect Dis, 2018; 18:318–327.

Bartsch

, McKinnell

, Mueller

, et al. Potential economic burden of carbapenem-resistant Enterobacteriaceae (CRE) in the United States. Clin Microbiol Infect, 2017;23:48 e9–e16.

Martin

, Fahrbach

, Zhao

, Lodise

. Association between carbapenem resistance and mortality among adult, hospitalized patients with serious infections due to Enterobacteriaceae: Results of a systematic literature review and meta-analysis. Open Forum Infect Dis, 2018; 5:ofy150.

Otter

, Burgess

, Davies

, et al. Counting the cost of an outbreak of carbapenemase-producing Enterobacteriaceae: An economic evaluation from a hospital perspective. Clin Microbiol Infect, 2017; 23:188–196.

Pano Pardo

, Serrano Villar

, Ramos Ramos

, Pintado

. Infections caused by carbapenemase-producing Enterobacteriaceae: Risk factors, clinical features and prognosis. Enferm Infecc Microbiol Clin, 2014; 32(Suppl 4):41–48.

van Loon

, Voor In 't Holt

, Vos

. A systematic review and meta-analyses of the clinical epidemiology of carbapenem-resistant Enterobacteriaceae. Antimicrob Agents Chemother. 2018; 62:e01730-17.

Di Carlo

, Gulotta

, Casuccio

, et al. KPC-3 Klebsiella pneumoniae ST258 clone infection in postoperative abdominal surgery patients in an intensive care setting: Analysis of a case series of 30 patients. BMC Anesthesiol, 2013; 13:13.

10.

Di Carlo

, Pantuso

, Cusimano

, et al. Two cases of monomicrobial intraabdominal abscesses due to KPC–3 Klebsiella pneumoniae ST258 clone. BMC Gastroenterol, 2011; 11:103.

11.

Di Carlo

, Vitale

, O'Suilleabhain

, Casuccio

. Management of intra-abdominal infections due to carbapenemase-producing organisms. Curr Infect Dis Rep, 2014; 16:428.

12.

Giannella

, Trecarichi

, De Rosa

, et al. Risk factors for carbapenem-resistant Klebsiella pneumoniae bloodstream infection among rectal carriers: A prospective observational multicentre study. Clin Microbiol Infect, 2014; 20:1357–1362.

13.

, Shen

, Zhu

, Yu

. Carbapenem-resistant Klebsiella pneumoniae Infections among ICU admission patients in central China: Prevalence and prediction model. Biomed Res Int, 2019; 2019:9767313.

14.

Tumbarello

, Trecarichi

, Tumietto

, et al. Predictive models for identification of hospitalized patients harboring KPC-producing Klebsiella pneumoniae. Antimicrob Agents Chemother, 2014; 58:3514–3520.

15.

Mazuski

, Tessier

, May

, Sawyer

. Response to “re-thinking the definition of complicated intra-abdominal infection.”. Surg Infect, 2017; 18:375–376.

16.

Mazuski

, Tessier

, May

, et al. The Surgical Infection Society Revised Guidelines on the Management of Intra-Abdominal Infection. Surg Infect, 2017; 18:1–76.

17.

Dripps

. New classification of physical status. Anesthesiology, 1963; 24:111.

18.

Dindo

, Demartines

, Clavien

. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg, 2004; 240:205–213.

19.

Queenan

, Bush

. Carbapenemases: the versatile beta-lactamases. Clin Microbiol Rev, 2007; 20:440–458.

20.

Garner

, Jarvis

, Emori

, et al. CDC definitions for nosocomial infections, 1988. Am J Infect Control, 1988; 16:128–140.

21.

Levy

, Fink

, Marshall

, et al. 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Crit Care Med, 2003; 31:1250–1256.

22.

Horan

, Andrus

, Dudeck

. CDC/NHSN surveillance definition of health care-associated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control, 2008; 36:309–332.

23.

Zarkotou

, Pournaras

, Tselioti

, et al. Predictors of mortality in patients with bloodstream infections caused by KPC-producing Klebsiella pneumoniae and impact of appropriate antimicrobial treatment. Clin Microbiol Infect, 2011; 17:17981–17983.

24.

Clinical and Laboratory Standards Institute. Performance Standards for Antimicrobial Susceptibility Testing; Twenty-Fifth Informational Supplement. M100-S25. Wayne, PA: The Institute, 2015.

25.

EUCAST guidelines for detection of resistance mechanisms and specific resistances of clinical and/or epidemiological importance. Version 1.0, December 2013. http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Resistance_mechanisms/EUCAST_detection_of_resistance_mechanisms_v1.0_20131211.pdf

26.

Nordmann

, Poirel

, Dortet

. Rapid detection of carbapenemase-producing Enterobacteriaceae. Emerg Infect Dis, 2012; 18:1503–1507.

27.

Mediavilla-Gradolph

, Sainz-Rodriguez

, Valverde-Troya

, et al. [Evaluation of an immunochromatographic test for the detection of OXA-48 carbapenemase] (Spa). Rev Esp Quimioter, 2017; 30:45–49.

28.

Tato

, Ruiz-Garbajosa

, Traczewski

, et al. Multisite evaluation of Cepheid Xpert Carba-R Assay for detection of carbapenemase-producing organisms in rectal swabs. J Clin Microbiol, 2016; 54:1814–1819.

29.

Peduzzi

, Concato

, Kemper

, et al. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol, 1996; 49:1373–1379.

30.

Giannella

, Bartoletti

, Morelli

, et al. Risk factors for infection with carbapenem-resistant Klebsiella pneumoniae after liver transplantation: The importance of pre- and posttransplant colonization. Am J Transplant, 2015; 15:1708–1715.

31.

Maseda

, Salgado

, Anillo

, et al. Risk factors for colonization by carbapenemase-producing enterobacteria at admission to a surgical ICU: A retrospective study. Enferm Infecc Microbiol Clin, 2017; 35:333–337.

32.

Tumbarello

, Trecarichi

, De Rosa

, et al. Infections caused by KPC-producing Klebsiella pneumoniae: Differences in therapy and mortality in a multicentre study. J Antimicrob Chemother, 2015; 70:2133–2143.

33.

Giannella

, Pascale

, Gutierrez-Gutierrez

, et al. The use of predictive scores in the management of patients with carbapenem-resistant Klebsiella pneumoniae infection. Expert Rev Anti Infect Ther, 2019; 17:265–273.

34.

Tartof

, Kuntz

, Chen

, et al. Development and assessment of risk scores for carbapenem and extensive beta-lactam resistance among adult hospitalized patients with Pseudomonas aeruginosa nfection. JAMA Netw Open, 2018; 1:e183927.

35.

Giacobbe

, Del Bono

, Trecarichi

, et al. Risk factors for bloodstream infections due to colistin-resistant KPC-producing Klebsiella pneumoniae: Results from a multicenter case-control-control study. Clin Microbiol Infect 2015;21:1106 e1–e8.

36.

El-Kholy

, Elanany

, Sherif

, Gad

. High prevalence of VIM, KPC, and NDM expression among surgical site infection pathogens in patients having emergency surgery. Surg Infect, 2018; 19:629–633.

37.

O'Horo

, Farrell

, Sohail

, Safdar

. Carbapenem-resistant Enterobacteriaceae and endoscopy: An evolving threat. Am J Infect Control, 2016; 44:1032–1036.

38.

Devereaux

, Athan

, Brown

, et al. Australian infection control in endoscopy consensus statements on carbapenemase-producing Enterobacteriaceae. J Gastroenterol Hepatol, 2019; 34:650–658.

39.

Rutala

, Weber

. Outbreaks of carbapenem-resistant Enterobacteriaceae infections associated with duodenoscopes: What can we do to prevent infections?. Am J Infect Control, 2016; 44(5 Suppl):e47–e51.

40.

Papadimitriou-Olivgeris

, Marangos

, Christofidou

, et al. Risk factors for infection and predictors of mortality among patients with KPC-producing Klebsiella pneumoniae bloodstream infections in the intensive care unit. Scand J Infect Dis, 2014; 46:642–648.

41.

Soubirou

, Gault

, Alfaiate

, et al. Ventilator-associated pneumonia due to carbapenem-resistant gram-negative bacilli in an intensive care unit without carbapenemase-producing Enterobacteriaceae or epidemic Acinetobacter baumannii. Scand J Infect Dis, 2014; 46:215–220.

42.

Zheng

, Cao

, Xu

, et al. Risk factors, outcomes and genotypes of carbapenem-nonsusceptible Klebsiella pneumoniae bloodstream infection: A three-year retrospective study in a large tertiary hospital in Northern China. Infect Dis, 2018; 50:443–451.

43.

Kumar

, Safdar

, Kethireddy

, Chateau

. A survival benefit of combination antibiotic therapy for serious infections associated with sepsis and septic shock is contingent only on the risk of death: A meta-analytic/meta-regression study. Crit Care Med, 2010; 38:1651–1664.

44.

Buckman

, Turnbull

, Mazuski

. Empiric antibiotics for sepsis. Surg Infect, 2018; 19:147–154.

45.

Bassetti

, Giacobbe

, Giamarellou

, et al. Management of KPC-producing Klebsiella pneumoniae infections. Clin Microbiol Infect, 2018; 24:133–144.

46.

Trecarichi

, Tumbarello

. Therapeutic options for carbapenem-resistant Enterobacteriaceae infections. Virulence, 2017; 8:470–484.

47.

Iredell

, Brown

, Tagg

. Antibiotic resistance in Enterobacteriaceae: Mechanisms and clinical implications. BMJ, 2016; 352:h6420.

48.

Mittal

, Gaind

, Kumar

, et al. Risk factors for fecal carriage of carbapenemase producing Enterobacteriaceae among intensive care unit patients from a tertiary care center in India. BMC Microbiol, 2016; 16:138.

49.

Mora-Guzman

, Rubio-Perez

, Maqueda Gonzalez

, et al. Surgical site infection by carbapenemase-producing Enterobacteriaceae. A challenge for today's surgeons. Cir Esp, 2020; 98:342–349.

50.

Magiorakos

, Burns

, Rodriguez Bano

, et al. Infection prevention and control measures and tools for the prevention of entry of carbapenem-resistant Enterobacteriaceae into healthcare settings: guidance from the European Centre for Disease Prevention and Control. Antimicrob Resist Infect Control, 2017; 6:113.