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/lp/springer-journals/risk-factors-for-carbapenem-resistant-klebsiella-pneumoniae-infection-810LjEHn0k
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- Springer Journals
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- Copyright © The Author(s). 2020
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- 2047-2994
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- 10.1186/s13756-020-0686-0
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Abstract
Background: Studies on risk factors for carbapenem-resistant Klebsiella pneumoniae (CRKP) infection have provided inconsistent results, partly due to the choice of the control group. We conducted a systematic review and meta- analysis to assess the risk factors for CRKP infection by comparing CRKP-infected patients with two types of controls: patients infected with carbapenem-susceptible Klebsiella pneumoniae (comparison 1) or patients not infected with CRKP (comparison 2). Methods: Data on potentially relevant risk factors for CRKP infection were extracted from studies indexed in PubMed, EMBASE, Web of Science or EBSCO databases from January 1996 to April 2019, and meta-analyzed based on the outcomes for each type of comparison. Results: The meta-analysis included 18 studies for comparison 1 and 14 studies for comparison 2. The following eight risk factors were common to both comparisons: admission to intensive care unit (ICU; odds ratio, OR = comparison 1 3.20, OR = 4.44), central venous catheter use (2.62, 3.85), mechanical ventilation (2.70, 4.78), tracheostomy comparison 2 (2.11, 8.48), urinary catheter use (1.99, 0.27), prior use of antibiotic (6.07, 1.61), exposure to carbapenems (4.16, 3.84) and exposure to aminoglycosides (1.85, 1.80). Another 10 risk factors were unique to comparison 1: longer length of hospital stay (OR = 15.28); prior hospitalization (within the previous 6 months) (OR = 1.91); renal dysfunction (OR = 2.17); neurological disorders (OR = 1.52); nasogastric tube use (OR = 2.62); dialysis (OR = 3.56); and exposure to quinolones (OR = 2.11), fluoroquinolones (OR = 2.03), glycopeptides (OR = 3.70) and vancomycin (OR = 2.82). Conclusions: Eighteen factors may increase the risk of carbapenem resistance in K. pneumoniae infection; eight factors may be associated with both K. pneumoniae infections in general and CRKP in particular. The eight shared factors are likely to be ‘true’ risk factors for CRKP infection. Evaluation of risk factors in different situations may be helpful for empirical treatment and prevention of CRKP infections. Keywords: Klebsiella pneumoniae, Carbapenem-resistance, Infection, Risk factor, Systematic review, Meta-analysis * Correspondence: lixiangdaren@163.com Department of Hospital Infection Control, The First Affiliated Hospital of Chongqing Medical University, No. 1 You Yi Road, Yuan Jia Gang, Yuzhong District, Chongqing 400016, China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 2 of 13 Background Methods Carbapenem-resistant Gram-negative bacteria, mainly This meta-analysis was conducted according to the Klebsiella pneumoniae, are an emerging cause of Preferred Reporting Items for Systematic Reviews and healthcare-associated infections that pose a significant Meta-Analyses (PRISMA) guidelines [13]. threat to public health [1]. The percentage of K. pneu- moniae infections resistant to carbapenems continues Search strategy to rise [2, 3], with proportions exceeding 50% in parts Two authors (H.Y.Z. and Z.Y.) searched for relevant of the Eastern Mediterranean and Europe [1, 2]. K. studies in PubMed, EMBASE, Web of Science and pneumoniae carbapenemase originated in the northeastern EBSCO databases that were published from January 1996 to USA in the early 2000s, but rapidly disseminated to other April 2019. The search terms included “Klebsiella pneumo- regions worldwide [4]. niae” AND (“carbapenem-resistant” OR “imipenem-resist- Carbapenem-resistant K. pneumoniae (CRKP) infection ant” OR “meropenem-resistant” OR “ertapenem-resistant” is difficult to treat since carbapenems are often considered OR “carbapenemase-producing” OR “Klebsiella pneumoniae last-resort antibiotics for severe K. pneumoniae infections. carbapenemase”)AND (“risk factors” OR “risk” OR “fac- The most important genes that can confer carbapenem re- tors”). Only studies published in English were considered. sistance (via carbapenemases) are present in K. pneumo- Reference lists in selected articles and relevant review arti- niae, rendering almost all available treatment options cles were manually searched to identify additional studies. ineffective [2]. Mortality rates reach 33–50% among CRKP-infected patients in different regions of the world Inclusion and exclusion criteria [5], significantly higher than mortality caused by infection Studies were included if they met the following criteria: with carbapenem-susceptible K. pneumoniae (CSKP) [1]. (1) case-control or cohort study design, whether prospect- Preventing CRKP infection is therefore important not only ive or retrospective; (2) the risk factors for CRKP infection to avoid poor prognosis and even death, but also to pre- were reported; (3) either comparison 1 or comparison 2 vent widespread transmission of carbapenem resistance was made; (4) CRKP and CSKP were classified based on through mobile genetic elements [6, 7]. K. pneumoniae isolate identification and tests for resist- Numerous studies have assessed risk factors for CRKP ance to carbapenem (imipenem, meropenem, or ertape- infection with different and sometimes even contradictory nem) involving well-defined microbiological methods; and conclusions. A previous meta-analysis attempted to ad- (5) infection was explicitly defined. The inclusion criterion dress this inconsistency [8] but did not take into consider- (3) led us to exclude studies comparing patients infected ation that different studies often use different control with carbapenemase-producing K. pneumoniae (CPKP) (reference) groups. The appropriate selection of the con- with controls without such infection, since such controls trol group in the analysis of risk factors for antibiotic- may have been infected with carbapenem-resistant, non- resistant pathogen infections depends on the specific re- carbapenemase-producing K. pneumoniae. Studies were search question [9–12]. In studies analyzing risk factors also excluded if they had the format of a report, review, for CRKP infection, two control groups are most often se- comment, meeting abstract or letter to the editor; or if lected: patients infected with CSKP or patients without they reported insufficient data to assess outcomes. CRKP infection. The comparison of CRKP-infected with CSKP-infected patients may allow the identification of risk Data extraction factors for carbapenem-resistant infections, although the Two authors (H.Y.Z. and W.M.Z.) independently evalu- results may be overestimated. In contrast, the comparison ated and extracted data from the included studies using of CRKP-infected individuals with patients without CRKP a predefined, standardized protocol. The extracted data infection may help to identify risk factors associated with on general characteristics of studies included the first both K. pneumoniae infections in general and CRKP author’s name, year of publication, journal of publica- in particular. Risk factors that are significant in both tion, country, study period, study design and setting, comparisons can be considered ‘true’ risk factors for type of inter-group comparison, sample size, average CRKP infection [11, 12]. age, and sex distribution. Potential risk factors were in- Thus, we performed a systematic review and meta- cluded in the meta-analysis only if at least three studies analysis to clarify risk factors for CRKP infection relative examined them and those studies reported the numbers to infection with CSKP (comparison 1) or to the absence of individuals in each comparison group. Disagreements of CRKP infection (comparison 2). This design, similar about extracted data were resolved through discussion. to a case-control-control study, aimed to compare the results of the two analyses and their different implica- Quality assessment tions for the clinical practice, allowing the identification Two authors (W.M.Z. and Z.Y.) independently evaluated of the likely true risk factors for CRKP infection. the quality of each study using the Newcastle-Ottawa Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 3 of 13 Scale (NOS), a scale for assessing the quality of pub- case-control (12), retrospective cohort (3), case-case- lished non-randomized studies in meta-analyses [14]. control (1), nested case-control (1), and prospective The scale contains eight items, categorized into three cohort (1). The comparison and reference groups were dimensions: selection, comparability, and outcome (co- matched in 11 studies. All but three studies enrolled pa- hort studies) or exposure (case-control studies) [14]. We tients from a single center, and six studies enrolled only developed a NOS-based scale ranging from 0 to 9 points: patients in the intensive care unit (ICU). studies scoring 0–4 points were defined as low quality, The main characteristics of the 14 studies included in while those scoring 5–9 points were defined as high comparison 2 are presented in Table 2. These studies quality. Differences were resolved by consensus. were published from 2012 to 2019, and involved 893 patients with CRKP infection and 3073 without CRKP Statistical analysis infection from six countries: Italy (6), USA (2), Greece The meta-analysis was performed using RevMan 5.2 (2), Turkey (2), Israel (1), and China (1). The designs of software provided by The Cochrane Collaboration the studies were case-control (6), retrospective cohort (Copenhagen: The Nordic Cochrane Centre, 2014). (4), prospective cohort (2), case-case-control (1), and Pooled odds ratios (ORs) and 95% confidence intervals case-cohort (1). In six of these studies the comparison (CIs) were calculated for all outcomes. The Z-test was and reference groups were matched. All but one study used to determine the significance of the pooled OR, enrolled patients from a single center and three studies and the results were considered statistically significant involved only patients in the ICU. when P < 0.05. Statistical heterogeneity among studies was assessed using a chi-squared test in which P < 0.10 Quality assessment was taken as the threshold for significant heterogeneity, All studies in the review were judged to be of high quality 2 2 or by calculating I value, with I > 50% considered evi- based on NOS assessment. The 18 studies in comparison dence of heterogeneity [15]. Depending on the assessed 1scoredanaverage of7 (range 5–8) (Table 1). The 14 heterogeneity, the Mantel-Haenszel fixed- or random- studies in comparison 2 scored an average of 6 (range 5– effect methods were used to meta-analyze the outcomes. 8) (Table 2). Publication bias was quantitatively analyzed using Egger’s test in STATA software version 12.0 (College Risk factors for CRKP infection based on CRKP-CSKP Station, TX: StataCorp LP) [16], and the results were comparison (comparison 1) considered statistically significant when P < 0.05. Sensi- Table 3 shows the risk factors for CRKP infection for tivity analyses were conducted by omitting studies one this comparison, as well as the heterogeneity in the by one, and the P values of pooled ORs were compared. meta-analysis. All 43 risk factors were dichotomous vari- The results were considered robust when the P values ables except for the following continuous variables: were not substantially different. length of hospital stay (LOS), length of ICU stay, and Acute Physiology and Chronic Health Evaluation (APA- Results CHE) II score on ICU admission. Of the 43 factors, the Study selection following 18 were statistically significant: longer LOS, A total of 428 unique records were retrieved from elec- prior hospitalization (within the previous 6 months), ad- tronic databases, and 203 duplicate records were re- mission to ICU, renal dysfunction, neurological disor- moved. After screening of titles and abstracts, 171 ders, tracheostomy, mechanical ventilation, central records were excluded. The remaining 54 studies were venous catheter (CVC) use, urinary catheter use, naso- read in full to determine the eligibility. In the end, 18 gastric tube use, implementation of dialysis, prior use of studies performing comparison 1 [17–34] and 14 for any antibiotic, and specific use of carbapenems, amino- comparison 2 [35–48] were included in the systematic glycosides, quinolones, fluoroquinolones, glycopeptides, review, while subsets of these studies were included in or vancomycin. the meta-analyses of the various risk factors (Fig. 1). Risk factors for CRKP infection compared with absence of Study characteristics CRKP infection (comparison 2) The main characteristics of the 18 studies included in Table 4 shows the risk factors for CRKP infection for this comparison 1 are presented in Table 1. The studies were comparison, as well as the heterogeneity in the meta- published from 2007 to 2019, and involved 1010 patients analysis. All 20 risk factors were dichotomous variables, with CRKP infection and 1190 with CSKP infection from and the following eight were statistically significant: ad- nine countries: China (6 studies), Greece (3), Israel (2), mission to ICU, tracheostomy, mechanical ventilation, USA (2), Italy (1), Colombia (1), Turkey (1), Brazil (1), CVC use, urinary catheter use, prior antibiotic use, and and Georgia (1). The designs of the 18 studies were specific use of carbapenems or aminoglycosides. Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 4 of 13 Fig. 1 Flow diagram of study selection for meta-analysis. Abbreviations: CRKP, carbapenem-resistant Klebsiella pneumoniae; CSKP, carbapenem- susceptible Klebsiella pneumoniae Publication bias alter the results. We noted two exceptions: in comparison Egger’s test showed no obvious asymmetry in the risk 1, omitting the study by Mouloudi et al. from 2010 [30] factors, suggesting low risk of publication bias (Tables 3 made the factor “β-lactam + β-lactamase inhibitor” signifi- and 4). cant (OR 2.42, 95% CI 1.08 to 5.44); in comparison 2, re- moving the study by Mouloudi et al. in 2014 [37]madethe Sensitivity analyses factor “diabetes” significant (OR 1.39, 95% CI 1.01 to 1.90). The sensitivity analysis was performed by repeating the meta-analysis after omitting each study one by one and Discussion examining whether the results changed substantially. For CRKP is one of the most serious life-threating nosoco- most risk factors, no single study seemed to substantially mial pathogens worldwide, and CRKP infections are Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 5 of 13 Table 1 Characteristics of studies included in the meta-analysis of the type 1 comparison Study Study design Matching Matched factors Enrollment period Country Setting Sample size, Average age(SD Sex (male), NOS ratio CRKP infection/ or range),CRKP CRKP infection/ points CSKP infection infection/CSKP CSKP infection infection Gómez, 2014 [7] Case-case-control 1:1:2 Length of stay in ICU and January 2008–January 2011 Colombia Single center 61/61 42.2 ± 28.4/40.5 ± 28.2 30/44 8 date of bacterial isolation Wu, 2011 [8] Case-control 1:2 Site of infection and the July 2006–July 2008 China Single center 39/78 64.0 ± 16.0/56.9 ± 17.6 28/60 7 date of hospital admission (± within 5 days) Falagas, 2007 [9] Case-control 1:1 Site of infection, age ± October 2000–May 2006 Greece Multicenter 53/53 61.5 ± 18.8/61.9 ± 17.2 23/54 6 5 years and length of (2 hospitals) hospital stay up to isolation of CRKP ±3 days and year of hospital admission Patel, 2008 [20] Case-control 1:1 Anatomic site of infection, July 2004–June 2006 USA Single center 99/99 60.67 ± 14.95/59.39 ± 13.34 58/58 7 age and date of isolation of K. pneumoniae Simkins, 2014 [21] Case-control NA NA January 2006–December 2010 USA Single center 13/39 53 ± 18/55 ± 16 7/14 5 Hu, 2016 [22] Case-control 1:1 Year of ICU admission and January 2011–June 2013 China Single center, 65/65 64.12 ± 13.69/59.06 ± 14.61 45/50 6 site of infection a 67-bed ICU Candevir, 2015 [23] Retrospective cohort NA NA January 2012–December 2012 Turkey Single center, 47/51 38 (0–83)/8 (0–86) 31/30 7 ICUs Vardakas, 2015 [24] Retrospective cohort NA NA January 2006–October 2009 Greece Single center, 73/18 66.3 ± 14.4/60.9 ± 15.6 36/7 7 an 8-bed ICU Correa, 2013 [25] Case-control 1:2 Infection date, anatomic January 2006–August 2008 Brazil Single center 20/40 59.6/64.9 13/21 7 site of infection, and the unit where infection was acquired X. Zheng, 2017 [26] Case-control NA NA January 2013–December 2014 China Single center, 31/17 57.61 ± 14.78/62.71 ± 16.34 27/11 5 30-bed medical ICU Zheng, 2017 [27] Case-control 1:1 In the same ward during January 2013–July 2015 China Single center 51/51 69.84 ± 18.0/67.25 ± 20.1 39/35 8 the same period (within 30 days) and ages within 5 years of each other Shilo, 2013 [28] Case-control 1:1 Hospitalized during the January 2006–April 2009 Israel Single center 135/127 77 ± 14/80 ± 13 62/53 7 same year Wang, 2018 [29] Case-control 1:1 Admitted to the same January 2010–December 2014 China Single center 48/48 67.7 ± 19.5/63.1 ± 17.8 35/34 6 department during the same time period Mouloudi, 2010 [30] Nested case-control NA NA January 2007–December 2008 Greece Single center, 37/22 NA 28/17 6 8-bed polyvalent ICU Hussein, 2013 [31] Case-control NA NA January 2006–December 2008 Israel Single center 103/214 61.4 ± 17/63.2 ± 18 73/133 7 Pan, 2019 [32] Retrospective cohort 1:2 Age, sex, and specimen 2014 China Single center 66/132 58.8 ± 15.9/57.4 ± 14.7 45/90 8 source Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 6 of 13 Table 1 Characteristics of studies included in the meta-analysis of the type 1 comparison (Continued) Study Study design Matching Matched factors Enrollment period Country Setting Sample size, Average age(SD Sex (male), NOS ratio CRKP infection/ or range),CRKP CRKP infection/ points CSKP infection infection/CSKP CSKP infection infection Tsereteli, 2018 [33] Case-control NA NA January 2017–February 2018 Georgia Multicenter 20/26 52.3 ± 19.153/54.46 ± 18.591 18/16 6 (2 hospitals), ICUs Hoxha, 2016 [34] Prospective cohort 1:1 Age (10 years), hospital, November 2012–July 2013 Italy Multicenter 49/49 72/74 32/32 8 and type of specimen (10 Italian (blood/bronchoscopy hospitals) specimen) Abbreviations: CRKP carbapenem-resistant Klebsiella pneumoniae, CSKP Carbapenem-susceptible Klebsiella pneumoniae, SD Standard deviation, NOS Newcastle-Ottawa Scale, ICU Intensive care unit, NA Not available Age, median (range), years Age, mean, years Age, median, years Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 7 of 13 Table 2 Characteristics of studies included in the meta-analysis of the type 2 comparison Study Study design Matching ratio Matched factors Period Country Setting Sample size, Average age Sex (male), NOS CRKP infection/ (SD or range), CRKP infection/ points without CRKP CRKP infection/ without CRKP infection without CRKP infection infection Mouloudi, 2014 [37] Prospective cohort 1:2 During the same period January 2008–December 2011 Greece Single center, 17/34 54 (44–66)/55 (26–66) 10/19 5 8-bed polyvalent ICU Giannella, 2015 [38] Prospective cohort NA NA June 2010–December 2013 Italy Single center 20/217 63 ± 2.8/55 ± 14 15/143 7 Akgul, 2016 [39] Case-control NA At least 72 h in the same January 2010–September 2014 Turkey Single center 95/100 66 (19–94)/58 (21–87) 63/62 6 wards and period with the cases Giannella, 2014 [36] Case–control 1:4 The time of the primary January 2012–December 2013 Italy Multicenter 143/572 65 (52–75)/70 (58–81) 84/307 6 positive CRKP rectal swab (5 large (within the same month) tertiary-care and the time atrisk of teachinghospitals) having a subsequent infection Borer, 2012 [35] Case-control 1:2 Age within 5 years, same May 2007–January 2010 Israel Single center 42/84 72 (19–91)/72.5 (21–95) NA 6 sex, time of admission ± 5 days, and similar length of time at risk ±2 days Yang, 2016 [40] Case-control 1:2 Month of admission, ward, January 2012–December 2013 China Single center 370/740 85 (80–87)/74 (59–84) 321/434 7 as well as interval days (interval from admission to confirmation of the index culture) Micozzi, 2017 [41] Retrospective cohort NA NA 24 February 2012–31 May 2013 Italy Single center 11/8 NA 5/8 5 Mazza, 2017 [42] Retrospective cohort NA NA January 2012–December 2015 Italy Single center 8/302 NA NA 6 Varotti, 2017 [43] Case-control 1:2 The patient transplanted January 2010–June 2015 Italy Single center 26/52 59 ± 13/53 ± 14 21/43 8 chronologically before and the patient transplanted chronologically after the study patient Salsano, 2016 [44] Retrospective cohort NA NA January 2104–December 2014 Italy Single center 32/521 74 (67–77)/71 (63–77) 17/362 6 Kontopoulou, 2019 [45] Case-cohort NA NA June 2011–August 2014 Greece Single center, 48/178 60/63 NA 6 8-bed medical and surgical ICU Gallagher, 2014 [46] Case-case-control 1:1 Location (hospital unit) June 2005–October 2010 USA Single center 43/43 56/58 26/26 6 and time (within 30 days) Kalpoe, 2012 [47] Retrospectivecohort NA NA 1 January 2005–1 October 2006 USA Single center 14/161 57 (52–71)/55 (23–78) 9/133 6 Akturk, 2016 [48] Case-control NA NA January 2010–December2014 Turkey Single center, 24/61 53 ± 14.7/23.5 ± 5.8 NA 6 pediatric and neonatal ICUs Abbreviations: CRKP Carbapenem-resistant Klebsiella pneumoniae, SD Standard deviation, NOS Newcastle-Ottawa Scale, ICU Intensive care unit, NA Not available Age, median (range), years Age, mean, years Age, median, years Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 8 of 13 Table 3 Meta-analysis of risk factors for CRKP infection in the type 1 comparison Number of Sample size, Heterogeneity Effects OR or MD [95% CI] ZP Egger’s included studies CRKP infection/ 2 2 model test, P >|t| χ PI CSKP infection LOS 3 191/230 10.02 0.007 80% Random 15.28 [1.11, 29.46] 2.11 0.03* 0.329 Prior hospitalization 4 230/172 5.67 0.13 47% Fixed 1.91 [1.23, 2.97] 2.89 0.004* 0.480 (within the previous 6 months) Admission to ICU 10 684/874 31.80 0.0002 72% Random 3.20 [1.97, 5.18] 4.72 <0.00001* 0.796 Length of ICU stay 3 259/196 4.84 0.09 59% Random −1.78 [−9.25, 5.68] 0.47 0.64 0.909 APACHE II score on 5 253/157 10.95 0.03 63% Random 0.91 [−1.28, 3.10] 0.82 0.41 0.692 ICU admission Hypertension 3 148/200 0.08 0.96 0% Fixed 0.97 [0.61, 1.55] 0.12 0.91 0.271 Diabetes 13 757/800 10.80 0.55 0% Fixed 1.12 [0.88, 1.43] 0.94 0.35 0.874 Respiratory disease 3 149/118 0.77 0.68 0% Fixed 1.34 [0.71, 2.55] 0.91 0.37 0.294 Heart disorders 5 305/290 3.79 0.44 0% Fixed 1.25 [0.87, 1.78] 1.20 0.23 0.594 Acute renal failure 3 261/198 0.95 0.62 0% Fixed 1.12 [0.68, 1.85] 0.46 0.65 0.156 Chronic renal failure 6 460/494 7.24 0.20 31% Fixed 1.25 [0.89, 1.73] 1.30 0.19 0.580 Renal dysfunction 3 213/279 2.26 0.32 11% Fixed 2.17 [1.32, 3.56] 3.07 0.002* 0.072 Liver disease 5 313/243 2.17 0.70 0% Fixed 1.40 [0.88, 2.23] 1.43 0.15 0.665 Neurological disorders 5 289/235 1.51 0.83 0% Fixed 1.52 [1.04, 2.24] 2.15 0.03* 0.081 Hematological disorders 3 177/122 0.78 0.68 0% Fixed 2.83 [0.82, 9.72] 1.65 0.10 0.772 Malignancy 5 343/374 5.50 0.24 27% Fixed 0.84 [0.55, 1.28] 0.82 0.41 0.306 Trauma 3 168/219 0.82 0.66 0% Fixed 0.58 [0.30, 1.12] 1.63 0.10 0.324 Immunosuppression 3 135/124 2.25 0.32 11% Fixed 1.49 [0.71, 3.13] 1.04 0.30 0.106 Steroid therapy 3 174/174 1.09 0.58 0% Fixed 1.44 [0.85, 2.44] 1.34 0.18 0.108 Chemotherapy 3 148/187 0.16 0.92 0% Fixed 1.03 [0.47, 2.26] 0.07 0.95 0.169 Prior surgery 11 616/628 22.47 0.01 55% Random 1.31 [0.88, 1.94] 1.33 0.18 0.723 Tracheostomy 6 385/468 18.30 0.003 73% Random 2.11 [1.03, 4.32] 2.05 0.04* 0.769 Mechanical ventilation 12 764/947 41.95 <0.0001 74% Random 2.70 [1.68, 4.33] 4.12 <0.0001* 0.901 CVC 9 642/706 30.00 0.0002 73% Random 2.62 [1.44, 4.76] 3.16 0.002* 0.871 Urinary catheter 10 532/606 22.30 0.008 60% Random 1.99 [1.28, 3.09] 3.04 0.002* 0.626 Nasogastric tube 6 250/246 17.20 0.004 71% Random 2.62 [1.20, 5.68] 2.43 0.02* 0.623 Dialysis 7 378/527 3.01 0.81 0% Fixed 3.56 [2.39, 5.31] 6.25 <0.00001* 0.592 Parenteral nutrition 4 231/178 6.64 0.08 55% Random 1.59 [0.72, 3.49] 1.15 0.25 0.448 Enteral feeding 3 178/130 2.02 0.36 1% Fixed 1.35 [0.78, 2.35] 1.08 0.28 0.843 Prior antibiotic use 6 352/507 20.64 0.0009 76% Random 6.07 [2.03, 18.18] 3.22 0.001* 0.133 Penicillin 3 185/282 7.07 0.03 72% Random 2.18 [0.75, 6.35] 1.42 0.15 0.408 Cephalosporins 7 468/513 31.51 <0.0001 81% Random 1.45 [0.70, 2.99] 1.00 0.32 0.148 Second-generation 3 149/135 0.13 0.94 0% Fixed 1.62 [0.75, 3.47] 1.23 0.22 0.357 cephalosporins Third-generation 3 112/157 4.61 0.10 57% Random 2.05 [0.83, 5.06] 1.56 0.12 0.756 cephalosporins Carbapenems 12 658/774 25.57 0.008 57% Random 4.16 [2.75, 6.29] 6.76 <0.00001* 0.954 β-lactam+β-lactamase 5 262/273 13.21 0.01 70% Random 2.06 [1.01, 4.20] 2.00 0.05 0.276 inhibitor Aminoglycosides 12 669/765 10.47 0.49 0% Fixed 1.85 [1.32, 2.60] 3.54 0.0004* 0.770 Quinolones 8 420/531 20.85 0.004 66% Random 2.11 [1.15, 3.87] 2.42 0.02* 0.324 Fluoroquinolones 4 249/234 0.57 0.90 0% Fixed 2.03 [1.28, 3.24] 2.98 0.003* 0.184 Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 9 of 13 Table 3 Meta-analysis of risk factors for CRKP infection in the type 1 comparison (Continued) Number of Sample size, Heterogeneity Effects OR or MD [95% CI] ZP Egger’s included studies CRKP infection/ 2 2 model test, P >|t| χ PI CSKP infection Glycopeptides 4 191/230 0.69 0.88 0% Fixed 3.70 [2.31, 5.94] 5.43 <0.00001* 0.677 Vancomycin 3 195/292 3.64 0.16 45% Fixed 2.82 [1.86, 4.28] 4.87 <0.00001* 0.930 Macrolides 4 254/404 10.12 0.02 70% Random 2.46 [0.44, 13.87] 1.02 0.31 0.571 Metronidazole 4 201/240 0.52 0.92 0% Fixed 0.85 [0.50, 1.43] 0.62 0.54 0.491 Abbreviations: CRKP Carbapenem-resistant Klebsiella pneumoniae, CSKP Carbapenem-susceptible Klebsiella pneumoniae, OR Odds ratio, MD Mean difference, CI Confidence interval, LOS Length of hospital stay, ICU Intensive care unit, APACHE Acute Physiology and Chronic Health Evaluation, CVC Central venous catheter Mean difference * Statistically significant differences between groups (α = 0.05) highly prevalent in most of the countries where the stud- steeply in the USA from 0.6% in 2004 to 10.8% in 2007 ies included in our review were performed (such as Italy, [50]. The most severely affected European countries are China, Greece, USA, Turkey and Israel). The proportion Greece and Italy, where 64.7 and 29.7% of K. pneumo- K. pneumoniae infections involving meropenem resist- niae infections in 2017 showed carbapenem resistance ance in China increased from 14.1% in 2013 to 28.6% in [3]. The proportion of CRKP infections in Turkey in- 2018, with four provinces showing CRKP proportions > creased from 3.2% in 2010 to 66.9% in 2014 [39]. Israel 10% in 2013 (the highest was Zhejiang province with faced a nationwide CRKP outbreak in 2006 that, by mid- 37.40%) and 13 in 2017 (the highest was Henan province 2007, had infected 1275 patients in 27 hospitals [51]. with 53.01%) [49]. The proportion of K. pneumoniae in- The identification of risk factors of CRKP is the first step fections involving meropenem resistance has grown to discover high-risk patients and high-risk wards in Table 4 Meta-analysis of risk factors for CRKP infection in the type 2 comparison Number of Sample size Heterogeneity Effects OR [95% CI] ZP Egger’s included (CRKP infection/ 2 2 model test χ PI studies Without CRKP P >|t| infection) Admission to ICU 4 576/1572 41.44 <0.00001 93% Random 4.44 [1.32, 14.95] 2.40 0.02* 0.313 Diabetes 6 523/1718 6.59 0.25 24% Fixed 1.36 [0.99, 1.86] 1.92 0.05 0.199 Hypertension 3 94/860 3.83 0.15 48% Fixed 1.06 [0.65, 1.72] 0.23 0.82 0.127 HBV 3 39/497 1.41 0.49 0% Fixed 0.79 [0.31, 2.02] 0.50 0.62 0.116 HCV 4 86/613 3.88 0.27 23% Fixed 1.41 [0.85, 2.34] 1.33 0.19 0.083 HCC 4 86/613 7.78 0.05 61% Random 1.14 [0.43, 3.02] 0.26 0.80 0.488 Alcoholic liver disease 3 78/311 0.23 0.89 0% Fixed 1.13 [0.65, 1.97] 0.44 0.66 0.555 Retransplantation 3 54/571 7.39 0.02 73% Random 3.70 [0.74, 18.58] 1.59 0.11 0.590 Tracheostomy 3 161/245 0.17 0.92 0% Fixed 8.48 [4.43, 16.22] 6.46 <0.00001* 0.375 Mechanical ventilation 5 693/1539 67.27 <0.00001 94% Random 4.78 [1.78, 12.82] 3.10 0.002* 0.652 CVC 4 632/1473 34.74 <0.00001 91% Random 3.85 [1.56, 9.52] 2.92 0.004* 0.996 Urinary catheter 5 693/1539 108.70 <0.00001 96% Random 0.27 [0.02, 0.51] 2.13 0.03* 0.748 Dialysis 3 164/195 0.48 0.79 0% Fixed 1.54 [0.86, 2.75] 1.47 0.14 0.158 Parenteral nutrition 3 262/733 7.89 0.02 75% Random 1.73 [0.80, 3.74] 1.39 0.16 0.966 Prior antibiotic use 4 253/1051 3.95 0.27 24% Fixed 1.61 [1.05, 2.48] 2.19 0.03* 0.265 Carbapenems 5 627/1635 22.29 0.0002 82% Random 3.84 [2.02, 7.28] 4.12 <0.0001* 0.222 β-lactam+β-lactamase 3 537/1373 58.55 <0.00001 97% Random 1.89 [0.48, 7.48] 0.91 0.37 0.538 inhibitor Aminoglycosides 4 585/1551 3.50 0.32 14% Fixed 1.80 [1.28, 2.55] 3.34 0.0008* 0.415 Fluoroquinolones 3 533/1529 14.90 0.0006 87% Random 1.71 [0.77, 3.77] 1.33 0.18 0.904 Glycopeptides 3 215/811 1.66 0.44 0% Fixed 1.44 [0.96, 2.14] 1.78 0.07 0.812 Abbreviations: CRKP Carbapenem-resistant Klebsiella pneumoniae, OR Odds ratio, CI Confidence interval, ICU Intensive care unit, HBV Hepatitis B virus, HCV Hepatitis C virus, HCC Hepatocellular carcinoma, CVC Central venous catheter * Statistically significant differences between groups (α = 0.05) Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 10 of 13 order to channel limited resources most effectively into ventilation,CVC,urinary catheter),prior useofany anti- prevention and treatment. biotic, and exposure to carbapenems or aminoglycosides. Unfortunately, although many studies have investi- Importantly, these risk factors were also statistically signifi- gated risk factors for CRKP infection, they have come to cant in comparison 1, which means that they are probably diverging, often conflicting, conclusions. For example, true risk factors for acquiring CRKP infection among hospi- some studies have reported that exposure to carbapen- talized patients. ems increased the risk of CRKP infection [17–22, 27, 29, In contrast, dialysis and exposure to fluoroquinolones 31, 33], but others did not find the same effect [24, 30]. or glycopeptides were risk factors only for the first com- These discrepancies may reflect differences in sample size parison. These factors may therefore increase primarily and overall lack of statistical power, which prompted us to the risk of carbapenem resistance in K. pneumoniae. In- perform a systematic review in order to assess the associa- deed, fluoroquinolone exposure can generate resistance tions as reliably and comprehensively as possible. not only to fluoroquinolones but also to carbapenems, We based our review on the idea that the choice of the as fluoroquinolones lead to upregulation of the multi- control group for risk assessment can provide different re- drug efflux pump MexEF-OprN and downregulation of sults, as suggested in several previous studies [9–12]. We the porin OprD, which is involved in carbapenem resist- meta-analyzed 32 studies in nine countries involving sev- ance [51, 52]. In addition, a quinolone resistance gene eral thousands of patients. Consistent with our initial idea, that causes low-level fluoroquinolone resistance is the profiles of risk factors differed between comparisons 1 located on K. pneumoniae plasmids carrying carbapene- and 2, with immediate implications for clinical practice. mase genes [52]. Long-term administration of the glyco- Comparison 1 assessed risk factors for carbapenem- peptide vancomycin may disrupt the balance of microflora resistant infections, which are relevant for the situation in the body, promoting the propagation of Gram-negative when the patient is known to be infected with K. pneumo- bacteria and increasing the rate of mutation and spread of niae but tests of antibiotic susceptibility are pending. In carbapenemases, which may augment the risk of CRKP this case, the clinician estimates the probability of resist- [18]. These considerations imply that restricting the use of ance to carbapenem based on risk factors, adopting an fluoroquinolones and glycopeptides, whenever possible, empirical approach that prioritizes interventions to pre- may decrease the transmission of carbapenem resistance. vent transmission of carbapenem resistance at this early Our sensitivity analysis confirmed that meta-analysis re- stage. In this type of comparison, our analysis identified sults were robust, with the possible exceptions of exposure the following risk factors: prior hospitalization (within the to β-lactam + β-lactamase inhibitor (comparison 1) and previous 6 months), longer length of stay, admission to diabetes (comparision 2). The status of these variables as the ICU, concomitant diseases (renal dysfunction, neuro- risk factors changed depending on the inclusion of two logical disorders), certain invasive procedures (tracheos- small studies [30, 37]. The heterogeneity surrounding tomy, mechanical ventilation, CVC, urinary catheter, these variables suggests the need for further studies to nasogastric tube and dialysis), prior use of any antibiotic, confirm their relationship with risk of CRKP infection. and specific exposure to vancomycin or other five classes Compared to a previous meta-analysis with a similar of antimicrobial agents (carbapenems, aminoglycosides, goal [8], the present work included 12 additional studies quinolones, fluoroquinolones, glycopeptides). These risk involving 2981 patients published after September 2016. factors are more likely to be present in patients with more In addition, we excluded studies comparing patients in- severe illness and greater susceptibility to infection, and fected with CPKP with controls without CPKP infection, who are therefore exposed to greater antibiotic selection and our results for separate two comparisons contrast pressure, which may ultimately increase the likelihood of with a previous meta-analysis that aggregated both types infection with multidrug-resistant pathogens [20]. of comparison. Consistent with our initial hypothesis, we Comparison 2 is more relevant for the situation when identified several differences in the risk factors that were hospitals need to identify patients at increased risk of suf- significant in each comparison, and we were able to de- fering K. pneumoniae infection in general and CRKP in par- rive a set of likely true risk factors of CRKP infection as ticular. The impact of risk factors on CRKP infection those factors significant in both comparisons. The previ- reflects an integrated effect of K. pneumoniae characteris- ous work identified the following significant risk factors: tics and carbapenem resistance. This may allow clinicians exposure to glycopeptides, parenteral nutrition, length of and hospital epidemiologists to take timely action to pre- ICU stay and steroid therapy [8]. In our analysis, how- vent CRKP transmission, even when no pathogen is de- ever, exposure to glycopeptides was significant only in tected in patient specimens, which may be due to their use comparison 1, while length of ICU stay and steroid ther- of medications. In this type of comparison, our analysis apy were not significant in comparison 1, and parenteral identified the following risk factors: admission to ICU, nutrition was not significant in either type of compari- certain invasive procedures (tracheostomy, mechanical son, suggesting that these four factors may not be Zhu et al. Antimicrobial Resistance and Infection Control (2020) 9:23 Page 11 of 13 considered true risk factors. Furthermore, we found NA: Not available; NOS: Newcastle-Ottawa Scale; OR: Odds ratio; PRISMA: Preferred Reporting Items for Systematic Reviews and Meta- urinary catheter use to be a significant risk factor in both Analyses; SD: Standard deviation types of comparison, contrary to the previous meta- analysis. Acknowledgements We thank the authors of the studies included in our meta-analysis for sharing Like the previously published meta-analysis on risk their data. factors of CRKP infection [8], our exclusion criteria did not include that the source or base population of both Authors’ contributions case and control groups were identified with CRKP WmZ, ZY and HyZ designed the study. WmZ and HyZ searched the literature and extracted data, which HyZ analyzed. WmZ, ZY and HyZ drafted the colonization based on rectal culture. With the exception manuscript, which all authors revised. All authors read and approved the of two studies [35, 36], the studies included in our meta- final version of the manuscript. analysis did not perform rectal screening for CRKP, and thus potential CRKP rectal colonization was not identi- Funding This work was supported by the Humanities and Social Sciences Research fied. In these cases, it was difficult to judge whether the Project of the Chongqing Education Commission, China [grant number risk factors associated with the process of CRKP 17SKG019]. colonization developing into infection or acquiring Availability of data and materials CRKP and having it cause infection. Moreover, the rela- The datasets supporting the conclusions of this article are included with in tive timing of CRKP colonization and onset of risk fac- the article (Tables 1, 2, 3 and 4). tors is often difficult to determine [36]. Further studies are needed in which risk factors associated with CRKP Ethics approval and consent to participate Not applicable. colonization developing into infection, which would then allow meta-analysis to identify the risk factors for CRKP Consent for publication infection among patients with CRKP colonization. Not applicable. The findings of our meta-analysis should be interpreted Competing interests with caution given that some potential risk factors were The authors declare that they have no competing interests. analyzed based on data from a small number of studies. Indeed, data for some factors showed significant hetero- Author details Division of Infectious Diseases, The First Affiliated Hospital of Chongqing geneity across studies, especially in comparison 2, prob- Medical University, No. 1 You Yi Road, Yuan Jia Gang, Yuzhong District, ably because control patients included those without any Chongqing 400016, China. Department of Hospital Infection Control, The infection as well as those infected with nosocomial patho- First Affiliated Hospital of Chongqing Medical University, No. 1 You Yi Road, Yuan Jia Gang, Yuzhong District, Chongqing 400016, China. gens other than CRKP. 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