Abstract
Carbapenem-resistant Klebsiella pneumoniae (CRKP) infection is a major public health threat in the world. To inform the prevention and control of CRKP infection in hospitals, this study analyzed the factors associated with CRKP infection and resistance to carbapenems in K. pneumoniae. This case-case-control study was carried out in a large general hospital in China from January 2016 to December 2018, comprising 494 hospitalized patients infected with CRKP (case group 1) and 2429 hospitalized patients infected with carbapenem-susceptible K. pneumoniae (CSKP, case group 2). We selected control groups from hospitalized patients without K. pneumoniae infections for the two case groups separately, with a 1:3 case-control ratio, to analyze the risk factors of the two case groups using the conditional logistic regression. Multivariate analysis showed that the risk factors of CRKP infection were intensive care unit (ICU) admission (odds ratio [OR], 6.85; 95% confidence interval [CI], 4.90–9.58; P < 0.001), respiratory failure (OR, 1.93; 95% CI, 1.34–2.77; P < 0.001), age-adjusted Charlson comorbidity index (aCCI; OR, 1.08; 95% CI, 1.02–1.15; P = 0.007), admission from the Emergency (OR, 1.37; 95% CI, 1.02–1.85; P = 0.036), and imipenem use (OR, 1.80; 95% CI, 1.30–2.49; P < 0.001). Among the aforementioned five risk factors, aCCI (OR, 1.09; 95% CI, 1.06–1.13; P < 0.001) was also identified as a risk factor of CSKP infections in multivariate analysis. The risk factors for resistance to carbapenems in K. pneumoniae were ICU admission, respiratory failure, admission from the Emergency, and imipenem use.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10096-023-04578-w.
Keywords: Carbapenem-resistant Klebsiella pneumoniae, Risk factors, Healthcare-associated infection, Case-case-control study
Introduction
Carbapenem, a class of antimicrobial agents, such as imipenem, meropenem, and ertapenem, are the mainstream choice to treat severe infections due to Klebsiella pneumoniae, a notorious opportunistic pathogen. However, carbapenem-resistant K. pneumoniae (CRKP) have already emerged as a severe threat of human health. In 2018, the World Health Organization (WHO) categorized CRKP as Priority 1 (critical priority) in the global priority list of antimicrobial-resistant bacteria [1]. In 2019, the Centers for Disease Control and Prevention (CDC) classified 18 common multidrug-resistant bacteria into three categories, urgent, serious, and concerning threat, based on the levels of health concern in humans, among which CRKP was classified as an urgent threat to human health [2]. In China, data from the China Antimicrobial Surveillance Network (CHINET) have shown that the carbapenem resistance rate of K. pneumoniae has been continuously increasing from 3% in 2015 to 9.2% in 2010 then to 24.4% in 2021 [3].
Identification of risk factors of CRKP infection is critical for informing the prevention and control of CRKP in hospitals. There are many studies addressing risk factors of CRKP infection in literature. However, many of these studies have used a case-control design with directly comparing CRKP cases to carbapenem-susceptible K. pneumoniae (CSKP) ones. Such a case-control design has an intrinsic flaw as it implies the “replacement scenario” assumption, in which each patient is assumed to be infected either by the antimicrobial-resistant organisms or by their antimicrobial-susceptible counterparts but the patient could be infected by other pathogens or had no infection at all [4–6]. Therefore, more studies with improved design are needed to further elucidate the risk factors of CRKP infection. We then performed a study with a case-case-control design to identify associated with carbapenem resistance in K. pneumoniae to generate useful information for the targeted prevention and control of CRKP infection.
Materials and methods
Study design
This study was conducted in West China Hospital, Sichuan University, Chengdu, China. This hospital has 4300 beds and is a tertiary general hospital with an average annual admission of approximately 270,000 patients. The study design was case-case-control. This project was approved by the Ethics Committee of West China Hospital with informed consent being waived.
Subjects
This study was carried out retrospectively between January 2016 and December 2018 and comprised two case-control comparisons, in which inpatients with CRKP infection and those with CSKP infection were compared to their corresponding matched inpatient controls, respectively. The matched controls for those with CRKP or CSKP infection were inpatients with no infection due to K. pneumoniae.
Data sources
Patients with CRKP or CSKP and without K. pneumoniae were screened in the laboratory information system (LIS) and patient data were retrieved from their electronic medical records in the hospital information system (HIS). In the clinical microbiology laboratory, species identification for K. pneumoniae from clinical samples were performed using the automated VITEK 2 system (bioMérieux; Marcy l'Etoile, France). In vitro antimicrobial susceptibility testing was also determined by Vitek II and breakpoints defined by the Clinical and Laboratory Standards Institute (CLSI) [7] were applied.
Inclusion and exclusion criteria
For the case groups, inpatients with CRKP or CSKP recovered from a clinical specimen were included. Inpatients who met one of the following were excluded: (1) those were infected with CRKP and/or CSKP before or within 2 days of admission to the hospital; (2) those had both CRKP and CSKP; (3) those were not discharged at the time of data collection; and (4) those had CRKP only from screening rectal and/or oral swabs but no CRKP from any clinical specimens. For patients with multiple admissions during the study period, only the first admission of CRKP or CSKP infection was included, and the subsequent admissions were excluded.
The selection of control needs to represent the source patient population of the hospital and therefore we selected the control from inpatients. The control group of CRKP was inpatients without CRKP detected, and the control group of CSKP was inpatients without CRKP/CSKP detected. Therefore, the control group may have no infection or may be infected with other microorganisms. Inpatients who met one of the following were excluded: (1) those admitted with hospitalization time less than 2 days; (2) those lacked an International Statistical Classification of Diseases and Related Health Problems (ICD) diagnosis.
Patient matching and grouping
Data of patients who met the inclusion but not exclusion criteria were retrieved as described above. There were two, CRKP and CSKP, case study groups. Each of the patients infected with CRKP or CSKP was matched with inpatient controls at a ratio of 1:3 according to the matching conditions as follows: risk-time matching [6, 8], hospitalization difference no more than 1 month, and same initial diagnosis using first three digits of the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) code [9]. Three controls were randomly selected for each patient infected with CRKP or CSKP if multiple controls met the matching conditions. If ≤ 3 controls were found matching a patient, all of these controls were included. Data from the medical order of the physicians and information about the emergency admission collected from the matched study subjects were combined allowing manual queries for separately analyzing the impact of each factor on the CRKP and CSKP infections. The results of two case-control studies were then combined for further analysis to investigate risk factors for carbapenem resistance.
Definitions
CRKP was defined as K. pneumoniae that is resistant or intermediate to any of the following carbapenem antibiotics: meropenem, imipenem, or ertapenem (doripenem is not available in China). CSKP was K. pneumoniae that is susceptible to all of meropenem, imipenem, and ertapenem. Healthcare-associated CRKP/CSKP infection in this study referred to the first detection of CRKP/CSKP in any clinical specimens, such as blood, sputum, urine, drainage, bile, and ascites, collected 2 days after admission. Risk-time matching referred to that the length of hospital stays of the control was not less than the length of hospital stays of a patient infected with CRKP/CSKP before the collection date of the first CRKP/CSKP-positive clinical specimen. Respiratory failure was defined as PaO2 < 60 mmHg while breathing air, or a PaCO2 > 50 mmHg.
The explanatory variables
Factors before the risk time of the patient were collected as explanatory variables/independent variables. For the case groups, the explanatory variables existed before the collection date of the first CRKP/CSKP-positive clinical specimen. For the control group, the explanatory variables existed during the entire hospital stay of the patients. The explanatory variables collected in this study comprised those of the following six categories, i.e., patient’s factors, underlying diseases, antimicrobial agents, other drugs, invasive procedures, and other examinations/operations (mainly noninvasive procedures).
Data analysis
Microsoft Excel 2016 was used for compiling a Visual Basic for Applications programming language to match inpatients infected with CRKP or CSKP infections and those for control. In the univariate analysis, the non-normally distributed quantitative data were subjected to a descriptive analysis using the median (P25–P75) and statistical analysis using the Friedman’s rank-sum test, while the qualitative data were presented as frequency (%) and the statistical analysis was performed using the Cochran’s Q test [10]. The statistically significant variables in the univariate analysis (P < 0.05) were included in the multivariate analysis. Conditional logistic regression was used to analyze the risk factors of the CRKP-case and the CSKP-case groups [11]. The backward stepwise regression was mainly used to select the variable in a multivariate model. The least important variables (with the largest P value) to the model were sequentially removed until all variables retained in the model were statistically significant. The correlation coefficient matrix was used to evaluate the collinearity of variables. Some variables were removed in combination with professional consideration when a strong collinearity was found. The SPSS 21.0 software package (IBM, Armonk, NY) was used for the statistical analysis. P values were 2-tailed, and P < 0.05 was considered statistically significant.
Results
The case-case-control groups
The flowchart of this study is shown in Fig. 1. There were 537 patients in the CRKP group and 2594 patients in the CSKP group during the study period. The most common infection type due to CRKP was pneumonia, accounting for 50.09% (269/537), followed by bacteremia (14.53%) and urinary tract infection (11.73%). And the most common type of CSKP was pneumonia, accounting for 64.38% (1670/2594), followed by urinary tract infection (12.68%) and bacteremia (7.13%).
Fig. 1.
The flowchart of this study
Controls of this study were matched from 602,212 inpatients without K. pneumoniae with a ratio of 1:3 (one inpatient with CRKP or CSKP infection corresponded to three inpatient controls). A total of 1357 and 6953 controls were successfully matched for 494 (91.99%, 494/537) inpatients infected with CRKP and 2429 infected with CSKP (93.64%, 2429/2594), respectively.
Case-control study for CRKP infection
Univariate analysis identified 43 variables including sex, aCCI, and ICU admission that were statistically different (P < 0.05) between the CRKP case and the control groups (Table 1) as possible risk factors for CRKP infection. Spearman’s correlation analysis of these 43 variables exhibited that the correlation coefficient of mechanical ventilation versus chest radiography, nasogastric tube feeding, and bathing was 0.71, 0.70, and 0.72, respectively, while that of nasogastric tube feeding versus bathing and enteral nutrition was 0.69 and 0.63, respectively. This suggests that the above variables may have collinearity and could interfere with the analysis. Therefore, three factors (chest radiography, nasogastric tube feeding, and bathing) were removed based on clinical experience. To test the independent effects of imipenem and meropenem (no ertapenem was used in the study period), the introduction of carbapenems into the model was divided into two variables (imipenem and meropenem). Using a backward stepwise approach [12], the remaining statistically significant variables were included into multivariate and conditional logistic regression analyses. The Hosmer-Lemeshow test [12] for examining the goodness of fit for the logistic regression model showed χ2 = 2.35 and P = 0.968, suggesting that the model fit well (Table 2).
Table 1.
Univariate analysis of possible risk factors for CRKP infection
| Characteristics | Cases (n = 494) | Controls (n = 1357) | Wald χ2 | P | OR (95% CI) |
|---|---|---|---|---|---|
| Patient's factors | |||||
| Female | 341 (69.03%) | 859 (63.3%) | 5.43 | 0.020 | 0.76 (0.6–0.96) |
| Age, years (median, IQR) | 55 (44–68) | 54 (41–68) | 2.84 | 0.416 | / |
| Han nationality | 452 (91.5%) | 1259 (92.78%) | 0.62 | 0.432 | 0.86 (0.58–1.26) |
| aCCI (median, IQR) | 3 (1–5) | 3 (2–5) | 22.17 | < 0.001 | / |
| ICU admission | 297 (60.12%) | 353 (26.01%) | 169.53 | < 0.001 | 8.05 (5.88–11.01) |
| Admission from the Emergency | 292 (59.11%) | 668 (49.23%) | 20.07 | < 0.001 | 1.77 (1.38–2.27) |
| Underlying diseases | |||||
| Hypertension | 137 (27.73%) | 422 (31.1%) | 1.60 | 0.206 | 0.85 (0.65–1.1) |
| Tuberculosis | 10 (2.02%) | 43 (3.17%) | 3.31 | 0.069 | 0.37 (0.12–1.08) |
| Respiratory failure | 129 (26.11%) | 160 (11.79%) | 56.11 | < 0.001 | 3.2 (2.36–4.34) |
| Heart failure | 76 (15.38%) | 141 (10.39%) | 9.81 | 0.002 | 1.78 (1.24–2.56) |
| Malignant tumors | 82 (16.6%) | 241 (17.76%) | 1.76 | 0.185 | 0.71 (0.43–1.18) |
| Hematological diseases | 15 (3.04%) | 51 (3.76%) | 2.30 | 0.130 | 0.4 (0.12–1.31) |
| Pancreatitis | 85 (17.21%) | 241 (17.76%) | 0.04 | 0.838 | 0.9 (0.34–2.4) |
| Diabetes | 85 (17.21%) | 237 (17.46%) | 0.04 | 0.834 | 1.03 (0.77–1.38) |
| Antimicrobial administration | |||||
| Pyrroles | 116 (23.48%) | 220 (16.21%) | 12.48 | < 0.001 | 1.69 (1.26–2.25) |
| Amphotericin B | 14 (2.83%) | 23 (1.69%) | 1.38 | 0.240 | 1.53 (0.75–3.14) |
| Caspofungin | 64 (12.96%) | 66 (4.86%) | 31.89 | < 0.001 | 3.02 (2.06–4.43) |
| Nitroimidazole | 16 (3.24%) | 57 (4.2%) | 0.87 | 0.350 | 0.76 (0.43–1.35) |
| Penicillin | 2 (0.4%) | 19 (1.4%) | 2.50 | 0.114 | 0.31 (0.07–1.33) |
| Aztreonam | 3 (0.61%) | 20 (1.47%) | 2.59 | 0.107 | 0.37 (0.11–1.24) |
| Macrolides | 5 (1.01%) | 4 (0.29%) | 2.95 | 0.086 | 3.21 (0.85–12.18) |
| Linezolid | 51 (10.32%) | 59 (4.35%) | 19.54 | < 0.001 | 2.55 (1.68–3.86) |
| Quinolones | 123 (24.9%) | 436 (32.13%) | 13.96 | < 0.001 | 0.61 (0.48–0.79) |
| β-lactam/β-lactamase inhibitors | 303 (61.34%) | 731 (53.87%) | 6.81 | 0.009 | 1.36 (1.08–1.72) |
| Carbapenems | 263 (53.24%) | 440 (32.42%) | 67.61 | < 0.001 | 2.76 (2.17–3.52) |
| Imipenem | 173 (35.02%) | 288 (21.22%) | 37.73 | < 0.001 | 2.33 (1.78–3.04) |
| Meropenem | 110 (22.27%) | 137 (10.10%) | 42.95 | < 0.001 | 2.77 (2.04–3.75) |
| Clindamycin | 47 (9.51%) | 117 (8.62%) | 0.16 | 0.685 | 1.08 (0.73–1.61) |
| First- and second-generation cephalosporins | 60 (12.15%) | 283 (20.85%) | 26.35 | <0.001 | 0.39(0.27–0.56) |
| Third-generation cephalosporins | 40 (8.1%) | 122 (8.99%) | 0.78 | 0.377 | 0.84 (0.56–1.24) |
| Cephamycins | 62 (12.55%) | 269 (19.82%) | 16.03 | < 0.001 | 0.51 (0.36–0.71) |
| Tigecycline | 99 (20.04%) | 88 (6.48%) | 62.33 | < 0.001 | 4.21 (2.95–6.02) |
| Vancomycin | 136 (27.53%) | 192 (14.15%) | 33.66 | < 0.001 | 2.22 (1.69–2.9) |
| Aminoglycosides | 36 (7.29%) | 77 (5.67%) | 0.17 | 0.678 | 1.1 (0.71–1.7) |
| Other drugs | |||||
| Steroids | 270 (54.66%) | 631 (46.5%) | 7.87 | 0.005 | 1.38 (1.1–1.73) |
| Parenteral nutrition | 308 (62.35%) | 788 (58.07%) | 2.96 | 0.085 | 1.25 (0.97–1.61) |
| Enteral nutrition | 275 (55.67%) | 523 (38.54%) | 41.33 | < 0.001 | 2.17 (1.71–2.74) |
| Histamine type-2 (H2) receptor antagonists | 8 (1.62%) | 65 (4.79%) | 9.72 | 0.002 | 0.3 (0.14–0.64) |
| Proton pump inhibitors | 352 (71.26%) | 1006 (74.13%) | 2.16 | 0.142 | 0.82 (0.64–1.07) |
| Gastric mucosal protective agents | 38 (7.69%) | 151 (11.13%) | 6.05 | 0.014 | 0.62 (0.42–0.91) |
| Immunosuppressants | 32 (6.48%) | 55 (4.05%) | 5.85 | 0.016 | 1.89 (1.13–3.15) |
| Invasive procedures | |||||
| Mechanical ventilation | 308 (62.35%) | 489 (36.04%) | 104.04 | < 0.001 | 3.97 (3.05–5.18) |
| Central venous catheterization | 261 (52.83%) | 372 (27.41%) | 96.42 | < 0.001 | 3.38 (2.65–4.31) |
| Peripherally inserted central catheter | 56 (11.34%) | 128 (9.43%) | 0.51 | 0.474 | 1.14 (0.8–1.64) |
| Urinary catheterization | 172 (34.82%) | 385 (28.37%) | 13.47 | < 0.001 | 1.81 (1.32–2.48) |
| Blood purification | 68 (13.77%) | 55 (4.05%) | 46.74 | < 0.001 | 4.19 (2.78–6.32) |
| Surgery | 375 (75.91%) | 935 (68.9%) | 8.97 | 0.003 | 1.49 (1.15–1.94) |
| Organ transplantation | 19 (3.85%) | 26 (1.92%) | 5.97 | 0.015 | 2.27 (1.18–4.37) |
| Tracheotomy | 85 (17.21%) | 149 (10.98%) | 13.87 | < 0.001 | 1.95 (1.37–2.76) |
| Cardiopulmonary bypass | 15 (3.04%) | 30 (2.21%) | 1.22 | 0.269 | 1.64 (0.68–3.98) |
| Other examinations/operations | |||||
| Nasogastric tube feeding | 298 (60.32%) | 421 (31.02%) | 129.07 | <0.001 | 4.65 (3.57–6.07) |
| Fiberoptic bronchoscopy | 192 (38.87%) | 272 (20.04%) | 67.39 | <0.001 | 3 (2.31–3.9) |
| ERCP | 11 (2.23%) | 35 (2.58%) | 0.12 | 0.727 | 0.88 (0.44–1.78) |
| Nebulization and inhalation | 264 (53.44%) | 613 (45.17%) | 9.73 | 0.002 | 1.46 (1.15–1.85) |
| Mechanically assisted expectoration of sputum | 103 (20.85%) | 173 (12.75%) | 16.23 | < 0.001 | 1.87 (1.38–2.53) |
| Sputum suctioning | 0 (0%) | 1 (0.07%) | 0.12 | 0.725 | 0.03 (0–7359780.74) |
| Bladder irrigation | 20 (4.05%) | 67 (4.94%) | 1.26 | 0.262 | 0.73 (0.41–1.27) |
| Gastroscopy and duodenoscope | 49 (9.92%) | 140 (10.32%) | 0.35 | 0.552 | 0.89 (0.61–1.3) |
| Colonoscopy | 3 (0.61%) | 45 (3.32%) | 8.98 | 0.003 | 0.16 (0.05–0.53) |
| Negative pressure suction | 105 (21.26%) | 115 (8.47%) | 53.88 | < 0.001 | 3.59 (2.55–5.05) |
| Drainage | 101 (20.45%) | 159 (11.72%) | 27.98 | < 0.001 | 2.5 (1.78–3.52) |
| Chest radiography | 265 (53.64%) | 426 (31.39%) | 72.25 | <0.001 | 2.87 (2.25–3.65) |
| Electrocardiogram | 191 (38.66%) | 736 (54.24%) | 40.95 | < 0.001 | 0.47 (0.38–0.6) |
| Bedside ultrasonography | 256 (51.82%) | 361 (26.6%) | 101.15 | < 0.001 | 3.68 (2.86–4.75) |
| Gastrointestinal decompression | 289 (58.5%) | 463 (34.12%) | 92.58 | < 0.001 | 3.46 (2.69–4.46) |
| Enema | 116 (23.48%) | 150 (11.05%) | 42.86 | < 0.001 | 2.81 (2.06–3.82) |
| Bathing | 253 (51.21%) | 300 (22.11%) | 133.82 | < 0.001 | 4.97 (3.79–6.52) |
aCCI age-adjusted Charlson Comorbidity Index, ERCP endoscopic retrograde cholangiopancreatography
Table 2.
Multivariate analysis of influencing factors for CRKP infection
| Characteristics | β | SE | Wald χ2 | P | OR(95% CI) |
|---|---|---|---|---|---|
| ICU admission | 1.92 | 0.17 | 126.86 | < 0.001 | 6.85(4.9–9.58) |
| Quinolones | − 0.59 | 0.15 | 14.44 | < 0.001 | 0.56(0.41–0.75) |
| First- and second-generation cephalosporins | − 0.98 | 0.21 | 22.62 | < 0.001 | 0.38(0.25–0.56) |
| Cephamycins | − 0.82 | 0.20 | 17.45 | < 0.001 | 0.44(0.3–0.65) |
| Gastric mucosal protective agents | − 0.63 | 0.23 | 7.58 | 0.006 | 0.53(0.34–0.83) |
| Respiratory failure | 0.66 | 0.18 | 12.74 | < 0.001 | 1.93(1.34–2.77) |
| aCCI | 0.08 | 0.03 | 7.32 | 0.007 | 1.08(1.02–1.15) |
| admission from the Emergency | 0.32 | 0.15 | 4.39 | 0.036 | 1.37(1.02–1.85) |
| Imipenem | 0.59 | 0.17 | 12.68 | < 0.001 | 1.8(1.3–2.49) |
The independent risk factors of CRKP infection included ICU admission (OR: 6.85, 95% CI: 4.90–9.58; P < 0.001), respiratory failure (OR: 1.93, 95% CI: 1.34–2.77; P < 0.001), aCCI (OR: 1.08, 95% CI: 1.02–1.15; P = 0.007), admission from the Emergency (OR: 1.37, 95% CI: 1.02–1.85; P = 0.036), and imipenem use (OR: 1.80, 95% CI: 1.30–2.49; P < 0.001). The preventive factors of CRKP infection included quinolone use (OR: 0.56, 95% CI: 0.41–0.75; P < 0.001), first- and second-generation cephalosporin (OR: 0.38, 95% CI: 0.25–0.56; P < 0.001), Cephamycins (OR: 0.44, 95% CI: 0.30–0.65; P < 0.001), and sucralfate (OR: 0.53, 95% CI: 0.34–0.83; P = 0.006).
Case-control study for CSKP infection
Univariate analysis of the risk factors for CSKP infection showed that 50 variables, including sex, age, and aCCI, were statistically different between the CSKP-case and the corresponding control groups (P < 0.05, see Table 3 for details). The statistically significant variables in the univariate analysis were combined in multivariate and conditional logistic regression analyses using a backward stepwise approach. The Hosmer-Lemeshow test for goodness of fit for the regression model showed χ2 = 12.39, P = 0.135, indicating that the model fit well (Table 4). Spearman’s correlation analysis of these 50 variables exhibited that the correlation coefficient of mechanical ventilation versus ICU admission and sputum suctioning was 0.74 and 0.78, respectively. This suggests that the above variables may have collinearity and could interfere with the analysis. Therefore, ICU admission and sputum suctioning were removed based on clinical experience.
Table 3.
Bivariate analysis of influencing factors associated with CSKP infection
| Characteristic | Cases (n = 2429) | Controls (n = 6953) | Wald χ2 | P | OR (95%CI) |
|---|---|---|---|---|---|
| Patient’s factors | |||||
| Female | 1627 (66.98%) | 4049 (58.23%) | 59.04 | < 0.001 | 0.67 (0.61–0.74) |
| Age, years (median, IQR) | 60 (47–71) | 54 (43–67) | 90.35 | < 0.001 | / |
| Han nationality | 2285 (94.07%) | 6530 (93.92%) | 0.13 | 0.718 | 1.04 (0.85–1.27) |
| aCCI | 3 (2–6) | 3 (1–5) | 149.65 | < 0.001 | / |
| ICU admission | 519 (21.37%) | 999 (14.37%) | 90.64 | < 0.001 | 2.1 (1.8–2.45) |
| Admission from the Emergency | 934 (38.45%) | 2089 (30.04%) | 82.62 | < 0.001 | 1.77 (1.57–2.01) |
| Underlying diseases | |||||
| Hypertension | 761 (31.33%) | 2014 (28.97%) | 6.35 | 0.012 | 1.16 (1.03–1.3) |
| Tuberculosis | 86 (3.54%) | 249 (3.58%) | 0.02 | 0.890 | 0.98 (0.7–1.36) |
| Respiratory failure | 263 (10.83%) | 416 (5.98%) | 71.27 | < 0.001 | 2.22 (1.85–2.67) |
| Heart failure | 350 (14.41%) | 733 (10.54%) | 45.30 | < 0.001 | 1.88 (1.56–2.26) |
| Malignant tumors | 661 (27.21%) | 1791 (25.76%) | 9.96 | 0.002 | 1.4 (1.14–1.73) |
| Hematological diseases | 113 (4.65%) | 302 (4.34%) | 0.24 | 0.625 | 1.11 (0.74–1.66) |
| Pancreatitis | 87 (3.58%) | 238 (3.42%) | 0.57 | 0.450 | 1.19 (0.76–1.85) |
| Diabetes | 464 (19.1%) | 953 (13.71%) | 45.52 | < 0.001 | 1.58 (1.38–1.81) |
| Antimicrobial administration | |||||
| Pyrroles | 260 (10.7%) | 562 (8.08%) | 13.44 | < 0.001 | 1.43 (1.18–1.73) |
| Amphotericin B | 42 (1.73%) | 96 (1.38%) | 0.79 | 0.374 | 1.23 (0.78–1.94) |
| Caspofungin | 88 (3.62%) | 124 (1.78%) | 27.42 | < 0.001 | 2.26 (1.67–3.07) |
| Nitroimidazole | 64 (2.63%) | 164 (2.36%) | 0.24 | 0.626 | 1.08 (0.79–1.47) |
| Penicillin | 21 (0.86%) | 93 (1.34%) | 3.95 | 0.047 | 0.6 (0.37–0.99) |
| Aztreonam | 14 (0.58%) | 65 (0.93%) | 3.32 | 0.069 | 0.58 (0.32–1.04) |
| Macrolides | 2 (0.08%) | 9 (0.13%) | 0.27 | 0.604 | 0.67 (0.14–3.09) |
| Linezolid | 62 (2.55%) | 106 (1.52%) | 8.62 | 0.003 | 1.64 (1.18–2.27) |
| Quinolones | 424 (17.46%) | 1470 (21.14%) | 24.48 | < 0.001 | 0.71 (0.63–0.82) |
| β-lactam/β-lactamase inhibitors | 1333 (54.88%) | 2215 (31.86%) | 440.04 | < 0.001 | 3.39 (3.02–3.79) |
| Carbapenems | 501 (20.63%) | 1068 (15.36%) | 33.54 | < 0.001 | 1.51 (1.31–1.73) |
| Imipenem | 332 (13.67%) | 686 (9.87%) | 25.36 | < 0.001 | 1.52 (1.29–1.79) |
| Meropenem | 90 (3.71%) | 217 (3.12%) | 1.31 | 0.252 | 1.17 (0.89–1.53) |
| Clindamycin | 197(8.11%) | 365 (5.25%) | 28.10 | < 0.001 | 1.72 (1.41–2.1) |
| First- and second-generation cephalosporins | 507 (20.87%) | 1456 (20.94%) | 0.22 | 0.639 | 0.96 (0.83–1.12) |
| Third-generation cephalosporins | 105 (4.32%) | 371 (5.34%) | 6.14 | 0.013 | 0.75 (0.59–0.94) |
| Cephamycins | 365 (15.03%) | 1366 (19.65%) | 34.31 | < 0.001 | 0.64 (0.55–0.74) |
| Tigecycline | 83 (3.42%) | 106 (1.52%) | 26.92 | < 0.001 | 2.29 (1.67–3.13) |
| Vancomycins | 264 (10.87%) | 531 (7.64%) | 17.75 | < 0.001 | 1.45 (1.22–1.73) |
| Aminoglycosides | 61 (2.51%) | 177 (2.55%) | 0.51 | 0.474 | 0.89 (0.66–1.22) |
| Other drugs | |||||
| Steroids | 1050 (43.23%) | 2770 (39.84%) | 7.41 | 0.006 | 1.17 (1.04–1.3) |
| Parenteral nutrition | 1104 (45.45%) | 2347 (33.76%) | 137.56 | < 0.001 | 2.03 (1.81–2.29) |
| Enteral nutrition | 763 (31.41%) | 1389 (19.98%) | 143.37 | < 0.001 | 2.11 (1.87–2.38) |
| Histamine type-2 (H2) receptor antagonists | 82 (3.38%) | 364 (5.24%) | 16.85 | < 0.001 | 0.58 (0.45–0.75) |
| Proton pump inhibitors | 1579 (65.01%) | 4184 (60.18%) | 20.54 | <0.001 | 1.31 (1.16–1.47) |
| Gastric mucosal protective agents | 193 (7.95%) | 649 (9.33%) | 5.73 | 0.017 | 0.81 (0.67–0.96) |
| Immunosuppressants | 56 (2.31%) | 237 (3.41%) | 11.34 | 0.001 | 0.56 (0.4–0.78) |
| Invasive procedures | |||||
| Mechanical ventilation | 842 (34.66%) | 1397 (20.09%) | 275.99 | < 0.001 | 3.05 (2.67–3.48) |
| Central venous catheterization | 617 (25.4%) | 1115 (16.04%) | 111.09 | < 0.001 | 2.02 (1.77–2.3) |
| Peripherally inserted central catheter | 122 (5.02%) | 294 (4.23%) | 0.94 | 0.331 | 1.12 (0.89–1.42) |
| Urinary catheterization | 1288 (53.03%) | 2945 (42.36%) | 124.29 | < 0.001 | 2.03 (1.79–2.29) |
| Blood purification | 59 (2.43%) | 89 (1.28%) | 13.12 | < 0.001 | 1.89 (1.34–2.67) |
| Surgery | 1383 (56.94%) | 4483 (64.48%) | 62.07 | < 0.001 | 0.64 (0.57–0.71) |
| Organ transplantation | 25 (1.03%) | 61 (0.88%) | 0.43 | 0.512 | 1.19 (0.71–1.99) |
| Tracheotomy | 174 (7.16%) | 243 (3.49%) | 61.31 | < 0.001 | 2.67 (2.09–3.41) |
| Cardiopulmonary bypass | 141 (5.8%) | 273 (3.93%) | 44.12 | < 0.001 | 5.7 (3.41–9.52) |
| Other examinations/operations | |||||
| Nasogastric tube feeding | 720 (29.64%) | 944 (13.58%) | 359.39 | < 0.001 | 4.09 (3.53–4.73) |
| Fiberoptic bronchoscopy | 502 (20.67%) | 940 (13.52%) | 96.32 | < 0.001 | 2.09 (1.8–2.42) |
| ERCP | 29 (1.19%) | 76 (1.09%) | 0.20 | 0.659 | 1.11 (0.7–1.77) |
| Nebulization and inhalation | 1026 (42.24%) | 2342 (33.68%) | 67.93 | < 0.001 | 1.59 (1.42–1.78) |
| Mechanically assisted expectoration of sputum | 279 (11.49%) | 649 (9.33%) | 13.21 | < 0.001 | 1.42 (1.18–1.72) |
| Sputum suctioning | 960 (39.52%) | 1485 (21.36%) | 390.17 | < 0.001 | 3.9 (3.41–4.46) |
| Bladder irrigation | 116 (4.78%) | 198 (2.85%) | 18.69 | < 0.001 | 1.84 (1.4–2.43) |
| Gastroscopy and duodenoscope | 109 (4.49%) | 480 (6.9%) | 21.77 | < 0.001 | 0.58 (0.46–0.73) |
| Colonoscopy | 30 (1.24%) | 191 (2.75%) | 20.98 | < 0.001 | 0.38 (0.25–0.57) |
| Negative pressure suction | 135 (5.56%) | 228 (3.28%) | 28.35 | < 0.001 | 2 (1.55–2.57) |
| Drainage | 180 (7.41%) | 463 (6.66%) | 2.47 | 0.116 | 1.19 (0.96–1.48) |
| Chest radiography | 658 (27.09%) | 1333 (19.17%) | 80.30 | < 0.001 | 1.81 (1.59–2.06) |
| Electrocardiogram | 919 (37.83%) | 2518 (36.21%) | 1.45 | 0.229 | 1.07 (0.96–1.2) |
| Bedside ultrasonography | 356 (14.66%) | 1062 (15.27%) | 0.55 | 0.459 | 0.95 (0.84–1.08) |
| Gastrointestinal decompression | 573 (23.59%) | 1154 (16.6%) | 74.10 | < 0.001 | 1.85 (1.61–2.12) |
| Enema | 150 (6.18%) | 336 (4.83%) | 5.45 | 0.020 | 1.29 (1.04–1.6) |
| Bathing | 410 (16.88%) | 612 (8.8%) | 136.75 | < 0.001 | 2.57 (2.19–3.01) |
aCCI age-adjusted Charlson Comorbidity Index, ERCP endoscopic retrograde cholangiopancreatography
Table 4.
Multivariate analysis of influencing factors for CSKP infection
| Characteristics | β | SE | Wald χ2 | P | OR(95% CI) |
|---|---|---|---|---|---|
| Penicillin | − 0.77 | 0.28 | 7.80 | 0.005 | 0.46 (0.27–0.79) |
| Quinolones | − 0.42 | 0.07 | 33.07 | < 0.001 | 0.66 (0.57–0.76) |
| β-lactam/β-lactamase inhibitors | 0.81 | 0.07 | 152.19 | < 0.001 | 2.24 (1.97–2.55) |
| Clindamycin | 0.54 | 0.12 | 21.09 | < 0.001 | 1.71 (1.36–2.15) |
| Third-generation cephalosporins | − 0.35 | 0.13 | 7.12 | 0.008 | 0.71 (0.55–0.91) |
| Cephamycins | − 0.39 | 0.09 | 20.52 | < 0.001 | 0.68 (0.57–0.8) |
| Parenteral nutrition | 0.23 | 0.07 | 10.72 | 0.001 | 1.26 (1.1–1.45) |
| Histamine type-2 (H2) receptor antagonists | − 0.44 | 0.14 | 9.59 | 0.002 | 0.64 (0.49–0.85) |
| Gastric mucosal protective agents | − 0.29 | 0.10 | 8.32 | 0.004 | 0.75 (0.61–0.91) |
| Urinary catheterization | 0.42 | 0.08 | 26.10 | < 0.001 | 1.53 (1.3–1.8) |
| Nasogastric tube feeding | 0.75 | 0.09 | 65.38 | < 0.001 | 2.11 (1.76–2.52) |
| Fiberoptic bronchoscopy | 0.35 | 0.09 | 15.00 | < 0.001 | 1.42 (1.19–1.69) |
| Cardiopulmonary bypass | 1.02 | 0.29 | 12.73 | < 0.001 | 2.77 (1.58–4.84) |
| Gastroscopy and duodenoscope | − 0.37 | 0.13 | 8.10 | 0.004 | 0.69 (0.53–0.89) |
| Female | − 0.34 | 0.06 | 35.43 | < 0.001 | 0.71 (0.64–0.8) |
| Surgery | − 0.87 | 0.07 | 152.15 | < 0.001 | 0.42 (0.37–0.48) |
| Age | 0.01 | 0.00 | 7.88 | 0.005 | 1.01 (1–1.01) |
| aCCI | 0.09 | 0.02 | 30.03 | < 0.001 | 1.09 (1.06–1.13) |
| Mechanical ventilation | 0.48 | 0.09 | 28.47 | < 0.001 | 1.62 (1.36–1.93) |
The independent risk factors of CSKP infection included β-lactam/β-lactamase inhibitors use (OR: 2.24, 95% CI: 1.97–2.55; P < 0.001), clindamycin use (OR: 1.71, 95% CI: 1.36–2.15; P < 0.001), parenteral nutrition (OR: 1.26, 95% CI: 1.10–1.45; P = 0.001), urinary catheterization (OR: 1.53, 95% CI: 1.30–1.80; P < 0.001), nasogastric tube feeding (OR: 2.11, 95% CI: 1.76–2.52; P < 0.001), fiberoptic bronchoscopy (OR: 1.42, 95% CI: 1.19–1.69; P < 0.001), cardiopulmonary bypass (OR: 2.77, 95% CI: 1.58–4.84; P < 0.001), age (OR: 1.01, 95% CI: 1.00–1.01; P = 0.005), aCCI (OR: 1.09, 95% CI: 1.06–1.13; P < 0.001), and mechanical ventilation (OR: 1.62, 95% CI: 1.36–1.93; P < 0.001).
The preventive factors of CSKP infection included penicillin use (OR: 0.46, 95% CI: 0.27–0.79; P = 0.005), quinolones use (OR: 0.66, 95% CI: 0.57–0.76; P < 0.001), third-generation cephalosporin use (OR: 0.71, 95% CI: 0.55–0.91; P = 0.008), cephamycins use (OR: 0.68, 95% CI: 0.57–0.80; P < 0.001), H2 receptor antagonists use (OR: 0.64, 95% CI: 0.49–0.85; P = 0.002), sucralfate (OR: 0.75, 95% CI: 0.61–0.91; P = 0.004), gastroscopy and duodenoscope (OR: 0.69, 95% CI: 0.53–0.89; P = 0.004), female (OR: 0.71, 95% CI: 0.64–0.80; P < 0.001), and surgery (OR: 0.42, 95% CI: 0.37–0.48; P < 0.001).
Comparing the two case-control studies to identity risk factors of carbapenem resistance in K. pneumoniae
Statistically significant factors in the multivariate analysis of the CRKP-case and the CSKP-case groups represent risk factors for K. pneumoniae infection. Factors that were statistically significant in the multivariate analysis of the CRKP-case-control study but not in the CSKP-case-control study were risk factors for carbapenem resistance in K. pneumoniae. In contrast, factors that were statistically significant in the multivariate analysis of the CSKP-case-control study but not in the CRKP-case-control study were risk factors for CSKP infection (Table 5).
Table 5.
Risk factors comparing the two case-control studies
| Classification | Multivariate analysis for CRKP | Multivariate analysis for CSKP |
|---|---|---|
| Risk factors for resistance to carbapenem of K. pneumoniae | ICU admission | |
| respiratory failure | ||
| admission from the Emergency | ||
| imipenem | ||
| Risk factors for K. pneumoniae infection | aCCI | aCCI |
| Risk factors for CSKP infection | β-lactam/β-lactamase inhibitors | |
| Clindamycin | ||
| Parenteral nutrition | ||
| Urinary catheterization | ||
| Nasogastric tube feeding | ||
| Fiberoptic bronchoscopy | ||
| Cardiopulmonary bypass | ||
| Age | ||
| Mechanical ventilation |
Discussion
For studies of risk factors for CRKP infection, the selection of the control group is critical to generate correct conclusions and needs to represent the source population of CRKP cases. Many studies selected CSKP cases as the controls [13–20], which may introduce a considerable selection bias because CSKP infection only accounts for a small number of hospitalized cases, which are not representative. Therefore, the OR obtained does not reflect the true situation. In addition, there is another important bias commonly found in studies of risk factors of infections due to antimicrobial resistant pathogens. CSKP may not be detected in the inpatients using carbapenems as CSKP is susceptible to and would be killed by carbapenems. As a consequence, killing those susceptible bacteria may lead to the overgrowth of CRKP in the presence of selective pressure. Using CSKP cases as the controls may therefore result in an overestimation of the effect of carbapenem use. Alternatively, a few studies have used patients not infected with CRKP as the controls [21–27]. However, there are two effects in such a scenario, K. pneumoniae infection and carbapenem resistance of K. pneumoniae, and these two effects cannot be separately analyzed in these studies.
Therefore, we adopted a case-case-control study to select comparable controls from inpatients for the patients with CRKP/CSKP infection to identify the risk factors of CRKP/CSKP infection and directly compare the results of the two multivariate analyses to explore the factors associated with resistance to carbapenems in K. pneumoniae. Similarly, several studies have adopted case-case-control studies to analyze the risk factor of CRKP infection/colonization. However, in these studies, the same control group was commonly selected for the CRKP-case group and the CSKP-case group [28–31]. This may reduce the comparability between the cases and the controls as some matching conditions cannot be used, among which adjustment of the risk time is critical. For instance, the longer the patients stay in hospital, there is higher possibility for them to obtain CRKP infection. Therefore, it is necessary to ensure that the matched control and the case have at least the same exposure time and lengths of hospital stay prior to the identification of risk factors of CRKP/CSKP. Collectively, one critical matching condition is that the hospital stay of the control group is not less than the hospital stay of the case group before the examination.
Statistically significant factors identified in both multivariate analyses of the CRKP-case and the CSKP-case groups represent risk factors for K. pneumoniae infection. Factors that were statistically significant in the multivariate analysis of the CRKP-case-control study (i.e., Study 1) but not in the CSKP-case-control study (i.e., Study 2) are risk factors for carbapenem resistance in K. pneumoniae. In contrast, factors that were statistically significant in the multivariate analysis of the CSKP-case-control study but not in the CRKP-case-control study are risk factors for CSKP infection [32]. Our study identified that four risk factors, namely ICU admission, respiratory failure, admission from the Emergency, and imipenem use, were significant in the CRKP-case-control study but were not significant in the CSKP-case-control study, indicating that these were risk factors for K. pneumoniae resistance to carbapenem. In contrast, the use of first- and second-generation cephalosporins were the preventive factors for K. pneumoniae resistance to carbapenems.
Agreeing with many previous studies [33–36], ICU admission is an independent risk factor for CRKP infection. Respiratory failure is newly identified as an independent risk factor for CRKP, although several previous studies have shown that chronic obstructive pulmonary disease (COPD) is a risk factor for CRKP infection [37–40]. Patients with respiratory failure usually have more serious disease conditions than those with COPD and are commonly managed in ICU as they often require mechanical ventilation and therefore are more likely to be infected/colonized with CRKP in the airway. In this study, half of the CRKP isolates were recovered from lower respiratory specimen such as generic sputum (n = 216), tracheal secretion (n = 28), bronchoalveolar lavage (n = 4), and bronchial washings fluid(n = 4), suggesting that it is necessary to pay special attention to these underlying diseases and the operations involved in the respiratory tract.
Studies of the relationship between admission from the Emergency and CRKP infection are scarce, and only three relevant reports are available [38, 41, 42]. However, multivariate analysis was not performed significantly in any of them. An additional study has shown that admission from the Emergency is a risk factor for patients with positive CRKP screening results [43]. Nevertheless, the study has focused on the population undergoing active screening only. To the best of our knowledge, we discovered for the first time that admission from the Emergency is a risk factor for CRKP infection. The common problems in the emergency departments in China include crowdedness with patients, slow patient turnover, heavy workload of medical staff, limited hospital-bed spacing due to extra beds, and inadequate implementation of infection control measures (e.g., hand hygiene and environmental cleaning), which may lead to the cross-transmission of CRKP within the emergency department. In addition, many patients are transferred to the inpatient departments to continue hospitalization after being admitted to the emergency department, which also increases CRKP transmission to other wards. Adopting prevention and control measures and strategies against infection in the emergency department requires sufficient attention to control CRKP transmission within the department.
In this study, carbapenem use was a risk factor for K. pneumoniae resistance to carbapenems, in consistent with previous studies [44–46]. As mentioned above, our study adopted a case-case-control study and compared with other studies using CSKP as the control group; our results truly reflected the effect of carbapenem use. In addition, most of the previous studies focused on analyzing carbapenems but not the specific agent. Univariate analysis of our CRKP-case-control study showed that imipenem and meropenem use were risk factors. However, our multivariate analysis of imipenem and meropenem identified that imipenem use was an independent risk factor for K. pneumoniae resistance to carbapenems. The difference in patient’s characteristics of those treated with imipenem or meropenem is summarized in Supplementary Table S1. Patients treated with imipenem had a higher proportion of pancreatitis (35.57% vs. 12.55%, P < 0.001) and a lower proportion of ICU admission (45.12% vs. 67.21%, P < 0.001) than those treated with meropenem. As the retrospective nature of this study with intrinsic uncontrollable bias, the exact reason why imipenem but not meropenem for carbapenem resistance in K. pneumoniae is not clear and warrants further prospective studies.
Charlson Comorbidity Index reflects the severity of the patient’s condition. Patients with high severity of illness are more likely to develop CRKP infection, which is consistent with previous studies [16, 47]. An unexpected finding is that the use of the first- and second-generation cephalosporins was a preventive factor for K. pneumoniae resistance to carbapenems. However, this has also been reported in a previous study [48]. It is likely that patients who received the first- and second-generation cephalosporins were in milder disease conditions and therefore have lower risks to be infected with CRKP. It is also likely that some patients may receive the first- and second-generation cephalosporins for prophylaxis rather than treatment and these patients hospitalized for surgery usually had shorter the hospital stays, which reduced the risks of CRKP infection.
This study has a few limitations. First, as a single-center study, the generation of our study is intrinsically compromised. Nevertheless, our study has a large sample size, including 494 cases in the CRKP-case-control study and 2429 cases in the CSKP-case-control study, far exceeding the numbers of previous case-control studies. The large sample size may help us to generate robust findings. Second, using a retrospective design, our study may have selection biases. However, our study included all of the CRKP/CSKP inpatients during the observation period, and only less than 10% of the cases were lost in matching, which effectively reduced the selection bias. Third, the analysis in this study was not stratified according to infection types and therefore could not capture risk factors specific for certain infections. Fourth, the clinical microbiology lab in our hospital has not routinely detected the production of carbapenemases for clinical isolates of the Enterobacterales. Notably, we could not exclude that there were some carbapenemase-producing isolates exhibiting susceptible to carbapenems and might have been regarded as CSKP in this study. We also did not detect the genes and carbapenemase producers for carbapenem resistance in CRKP. We are therefore unable to examine differences in the risk factors between different resistance genotypes for the perspective of molecular epidemiology. Fifth, data were collected from 2016 to 2018. While epidemiology has changed in the last 4 years, particularly due to COVID-19 pandemics. However, it is a new stage for the prevention and control of COVID-19 in China in 2023, and we believe that the research will still be representative in 2023. Finally, the information about the exact history of patient’s hospitalization was lacking due to the absence of an effective system for sharing patient records between hospitals here.
In conclusion, we performed a case-case-control study and identified risk factors for resistance to carbapenems in K. pneumoniae, which comprise ICU admission, respiratory failure, admission from the Emergency, and administration of imipenem.
Supplementary information
The difference in patient's characteristics of those treated with imipenem or meropenem.
Acknowledgements
We would like acknowledge the Department of Electronic Medical Record system of West China Hospital.
Author contribution
Wenzhi Huang, Zhiyong Zong, and Wei Zhang contributed to study conception and design. Yuhua Deng, Shichao Zhu, and Jingwen Li contributed to acquisition of data. Wenzhi Huang and Fu Qiao analyzed and interpreted data. Wenzhi Huang, Zhiyong Zong, and Wei Zhang drafted the manuscript. All authors revised the manuscript for important intellectual content. All authors read and approved the final manuscript.
Funding
The work was supported by grants from the National Natural Science Foundation of China (project no. 81861138055), and the Sichuan Preventive Medicine Association, (project no. SCGK201806).
Data availability
The datasets during the current study available from the corresponding author on reasonable request.
Declarations
Consent for publication
All authors gave their consent for publication.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Wenzhi Huang, Email: feihongyaoshi@qq.com.
Fu Qiao, Email: qiaofu2005@gmail.com.
Yuhua Deng, Email: 304792438@qq.com.
Shichao Zhu, Email: 515599380@qq.com.
Jingwen Li, Email: 173734960@qq.com.
Zhiyong Zong, Email: zongzhiy@scu.edu.cn.
Wei Zhang, Email: weizhang27@163.com.
References
- 1.Tacconelli E, Carrara E, Savoldi A, Harbarth S, Mendelson M, Monnet DL, et al. Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis. Lancet Infect Dis. 2018;18(3):318–327. doi: 10.1016/S1473-3099(17)30753-3. [DOI] [PubMed] [Google Scholar]
- 2.CDC (2019) Antibiotic resistance threats in the United States, 2019. Atlanta, GA: U.S. Department of Health and Human Services, CDC. 10.15620/cdc:82532
- 3.CHINET ((2021) The drug resistance rate of K. pneumoniae to carbapenems is changing by year. http://www.chinets.com/Data/GermYear
- 4.Kaier K, Frank U. In search of useful methods for measuring health and economic consequences of antimicrobial resistance. Clin Infect Dis. 2013;57(8):1220–1222. doi: 10.1093/cid/cit478. [DOI] [PubMed] [Google Scholar]
- 5.Evans SR, Harris AD. Methods and issues in studies of CRE. Virulence. 2017;8(4):453–459. doi: 10.1080/21505594.2016.1213473. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Harris AD, Karchmer TB, Carmeli Y, Samore MH. Methodological principles of case-control studies that analyzed risk factors for antibiotic resistance: a systematic review. Clin Infect Dis. 2001;32(7):1055–1061. doi: 10.1086/319600. [DOI] [PubMed] [Google Scholar]
- 7.CLSI, editor. Performance standards for antimicrobial susceptibility testing. 26th ed. CLSI supplement M100. Clinical And Laboratory Standards Institute: Wayne, PA; 2016. [Google Scholar]
- 8.Wacholder S, McLaughlin JK, Silverman DT, Mandel JS. Selection of controls in case-control studies. I Princ Am J Epidemiol. 1992;135(9):1019–1028. doi: 10.1093/oxfordjournals.aje.a116396. [DOI] [PubMed] [Google Scholar]
- 9.Harris ST, Zeng X, Ford L. International classification of diseases, 10th Revision: it's coming, ready or not. Health Care Manag (Frederick) 2011;30(3):227–235. doi: 10.1097/HCM.0b013e318225e0a2. [DOI] [PubMed] [Google Scholar]
- 10.de Kraker ME, Wolkewitz M, Davey PG, Koller W, Berger J, Nagler J, et al. Clinical impact of antimicrobial resistance in European hospitals: excess mortality and length of hospital stay related to methicillin-resistant Staphylococcus aureus bloodstream infections. Antimicrob Agents Chemother. 2011;55(4):1598–1605. doi: 10.1128/AAC.01157-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Koletsi D, Pandis N. Conditional logistic regression. Am J Orthod Dentofacial Orthop. 2017;151(6):1191–1192. doi: 10.1016/j.ajodo.2017.04.009. [DOI] [PubMed] [Google Scholar]
- 12.Hosmer DW, Lemeshow S (2000) Applied logistic regression, Second Edition. John Wiley, New York, pp. 147–156
- 13.Zhang H, Guo Z, Chai Y, Fang YP, Mu X, Xiao N, et al. Risk factors for and clinical outcomes of Carbapenem-resistant Klebsiella pneumoniae nosocomial infections: a retrospective study in a tertiary hospital in Beijing, China. Infect Drug Resist. 2021;14:1393–1401. doi: 10.2147/IDR.S298530. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Weston G, Jahufar F, Sharma N, Su C, Bellin E, Ostrowsky B. Derivation of a model to guide empiric therapy for Carbapenem-resistant Klebsiella pneumoniae bloodstream infection in an endemic area. Open Forum Infect Dis. 2020;7(7):ofaa070. doi: 10.1093/ofid/ofaa070. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Pan H, Lou Y, Zeng L, Wang L, Zhang J, Yu W, et al. Infections caused by Carbapenemase-producing Klebsiella pneumoniae: microbiological characteristics and risk factors. Microb Drug Resist. 2019;25(2):287–296. doi: 10.1089/mdr.2018.0339. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Wang Z, Qin RR, Huang L, Sun LY. Risk factors for Carbapenem-resistant Klebsiella pneumoniae infection and mortality of Klebsiella pneumoniae infection. Chin Med J (Engl) 2018;131(1):56–62. doi: 10.4103/0366-6999.221267. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Hu YM, Ping YT, Li LQ, Xu HM, Yan XF, Dai HB. A retrospective study of risk factors for carbapenem-resistant Klebsiella pneumoniae acquisition among ICU patients. J Infect Dev Countr. 2016;10(3):208–213. doi: 10.3855/jidc.6697. [DOI] [PubMed] [Google Scholar]
- 18.Jiao Y, Qin YH, Liu JJ, Li Q, Dong YC, Shang Y, et al. Risk factors for carbapenem-resistant Klebsiella pneumoniae infection/colonization and predictors of mortality: a retrospective study. Pathog Glob Health. 2015;109(2):68–74. doi: 10.1179/2047773215Y.0000000004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Pouch SM, Kubin CJ, Satlin MJ, Tsapepas DS, Lee JR, Dube G, et al. Epidemiology and outcomes of carbapenem-resistant Klebsiella pneumoniae bacteriuria in kidney transplant recipients. Transpl Infect Dis. 2015;17(6):800–809. doi: 10.1111/tid.12450. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Vardakas KZ, Matthaiou DK, Falagas ME, Antypa E, Koteli A, Antoniadou E. Characteristics, risk factors and outcomes of carbapenem-resistant Klebsiella pneumoniae infections in the intensive care unit. J Infect. 2015;70(6):592–599. doi: 10.1016/j.jinf.2014.11.003. [DOI] [PubMed] [Google Scholar]
- 21.Papadimitriou-Olivgeris M, Fligou F, Bartzavali C, Zotou A, Spyropoulou A, Koutsileou K, et al. Carbapenemase-producing Klebsiella pneumoniae bloodstream infection in critically ill patients: risk factors and predictors of mortality. Eur J Clin Microbiol. 2017;36(7):1125–1131. doi: 10.1007/s10096-017-2899-6. [DOI] [PubMed] [Google Scholar]
- 22.Cronin KM, Lorenzo YSP, Olenski ME, Bloch AE, Visvanathan K, Waters MJ, et al. Risk factors for KPC-producing Enterobacteriaceae acquisition and infection in a healthcare setting with possible local transmission: a case-control study. J Hosp Infect. 2017;96(2):111–115. doi: 10.1016/j.jhin.2017.02.010. [DOI] [PubMed] [Google Scholar]
- 23.Varotti G, Dodi F, Terulla A, Santori G, Mariottini G, Bertocchi M et al (2017) Impact of carbapenem-resistant Klebsiella pneumoniae (CR-KP) infections in kidney transplantation. Transpl Infect Dis 19(6). 10.1111/tid.12757 [DOI] [PubMed]
- 24.Mazza E, Prosperi M, Panzeri MF, Limuti R, Nichelatti M, De Gasperi A. Carbapenem-resistant Klebsiella pneumoniae infections early after liver transplantation: a single-center experience. Transpl P. 2017;49(4):677–681. doi: 10.1016/j.transproceed.2017.02.028. [DOI] [PubMed] [Google Scholar]
- 25.Giacobbe DR, Del Bono V, Bruzzi P, Corcione S, Giannella M, Marchese A, et al. Previous bloodstream infections due to other pathogens as predictors of carbapenem-resistant Klebsiella pneumoniae bacteraemia in colonized patients: results from a retrospective multicentre study. Eur J Clin Microbiol. 2017;36(4):663–669. doi: 10.1007/s10096-016-2843-1. [DOI] [PubMed] [Google Scholar]
- 26.Freire MP, Abdala E, Moura ML, de Paula FJ, Spadao F, Caiaffa HH, et al. Risk factors and outcome of infections with Klebsiella pneumoniae carbapenemase-producing K-pneumoniae in kidney transplant recipients. Infection. 2015;43(3):315–323. doi: 10.1007/s15010-015-0743-4. [DOI] [PubMed] [Google Scholar]
- 27.Micozzi A, Gentile G, Minotti C, Cartoni C, Capria S, Ballaro D, et al. Carbapenem-resistant Klebsiella pneumoniae in high-risk haematological patients: factors favouring spread, risk factors and outcome of carbapenem-resistant Klebsiella pneumoniae bacteremias. BMC Infect Dis. 2017;17(1):203. doi: 10.1186/s12879-017-2297-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Kofteridis DP, Valachis A, Dimopoulou D, Maraki S, Christidou A, Mantadakis E, et al. Risk factors for carbapenem-resistant Klebsiella pneumoniae infection/colonization: a case-case-control study. J Infect Chemother. 2014;20(5-6):293–297. doi: 10.1016/j.jiac.2013.11.007. [DOI] [PubMed] [Google Scholar]
- 29.Rueda VG, Tobon JJZ. Risk factors for infection with carbapenem-resistant Klebsiella pneumoniae: a case-case-control study. Colomb Med. 2014;45(2):54–60. doi: 10.25100/cm.v45i2.1417. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Kritsotakis EI, Tsioutis C, Roumbelaki M, Christidou A, Gikas A. Antibiotic use and the risk of carbapenem-resistant extended-spectrum-beta-lactamase-producing Klebsiella pneumoniae infection in hospitalized patients: results of a double case-control study. J Antimicrob Chemoth. 2011;66(6):1383–1391. doi: 10.1093/jac/dkr116. [DOI] [PubMed] [Google Scholar]
- 31.Schwaber MJ, Klarfeld-Lidji S, Navon-Venezia S, Schwartz D, Leavitt A, Carmeli Y. Predictors of carbapenem-resistant Klebsiella pneumoniae acquisition among hospitalized adults and effect of acquisition on mortality. Antimicrob Agents Chemother. 2008;52(3):1028–1033. doi: 10.1128/AAC.01020-07. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Kaye KS, Harris AD, Samore M, Carmeli Y. The case-case-control study design: addressing the limitations of risk factor studies for antimicrobial resistance. Infect Control Hosp Epidemiol. 2005;26(4):346–351. doi: 10.1086/502550. [DOI] [PubMed] [Google Scholar]
- 33.Zuo Y, Zhao D, Song G, Li J, Xu Y, Wang Z. Risk factors, molecular epidemiology, and outcomes of Carbapenem-resistant Klebsiella pneumoniae infection for hospital-acquired pneumonia: a matched case-control study in Eastern China During 2015-2017. Microb Drug Resist. 2021;27(2):204–211. doi: 10.1089/mdr.2020.0162. [DOI] [PubMed] [Google Scholar]
- 34.Yuan Y, Wang J, Yao Z, Ma B, Li Y, Yan W, et al. Risk factors for Carbapenem-resistant Klebsiella pneumoniae bloodstream infections and outcomes. Infect Drug Resist. 2020;13:207–215. doi: 10.2147/IDR.S223243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Hilliquin D, Le Guern R, Seegers VT, Neulier C, Lomont A, Marie V, et al. Risk factors for acquisition of OXA-48-producing Klebsiella pneumonia among contact patients: a multicentre study. J Hosp Infect. 2018;98(3):253–259. doi: 10.1016/j.jhin.2017.08.024. [DOI] [PubMed] [Google Scholar]
- 36.Giannella M, Graziano E, Marconi L, Girometti N, Bartoletti M, Tedeschi S, et al. Risk factors for recurrent carbapenem resistant Klebsiella pneumoniae bloodstream infection: a prospective cohort study. Eur J Clin Microbiol. 2017;36(10):1965–1970. doi: 10.1007/s10096-017-3020-x. [DOI] [PubMed] [Google Scholar]
- 37.Fang L, Xu H, Ren X, Li X, Ma X, Zhou H, et al. Epidemiology and risk factors for Carbapenem-resistant Klebsiella pneumoniae and subsequent MALDI-TOF MS as a tool to cluster KPC-2-producing Klebsiella pneumoniae, a retrospective study. Front Cell Infect Microbiol. 2020;10:462. doi: 10.3389/fcimb.2020.00462. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Salsano A, Giacobbe DR, Sportelli E, Olivieri GM, Brega C, Di Biase C, et al. Risk factors for infections due to carbapenem-resistant Klebsiella pneumoniae after open heart surgery. Interact Cardiovasc Thorac Surg. 2016;23(5):762–768. doi: 10.1093/icvts/ivw228. [DOI] [PubMed] [Google Scholar]
- 39.Nouvenne A, Ticinesi A, Lauretani F, Maggio M, Lippi G, Guida L, et al. Comorbidities and disease severity as risk factors for Carbapenem-resistant Klebsiella pneumoniae colonization: report of an experience in an internal medicine Unit. Plos One. 2014;9(10):e110001. doi: 10.1371/journal.pone.0110001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Liu SW, Chang HJ, Chia JH, Kuo AJ, Wu TL, Lee MH. Outcomes and characteristics of ertapenem-nonsusceptible Klebsiella pneumoniae bacteremia at a university hospital in Northern Taiwan: a matched case-control study. J Microbiol Immunol. 2012;45(2):113–119. doi: 10.1016/j.jmii.2011.09.026. [DOI] [PubMed] [Google Scholar]
- 41.Kontopoulou K, Iosifidis E, Antoniadou E, Tasioudis P, Petinaki E, Malli E, et al. The clinical significance of Carbapenem-resistant Klebsiella pneumoniae rectal colonization in critically ill patients: from colonization to bloodstream infection. J Med Microbiol. 2019;68(3):326–335. doi: 10.1099/jmm.0.000921. [DOI] [PubMed] [Google Scholar]
- 42.Akgul F, Bozkurt I, Sunbul M, Esen S, Leblebicioglu H. Risk factors and mortality in the Carbapenem-resistant Klebsiella pneumoniae infection: case control study. Pathog Glob Health. 2016;110(7-8):321–325. doi: 10.1080/20477724.2016.1254976. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Salomao MC, Freire MP, Boszczowski I, Raymundo SF, Guedes AR, Levin AS. Increased risk for Carbapenem-resistant Enterobacteriaceae colonization in intensive care units after hospitalization in emergency department. Emerg Infect Dis. 2020;26(6):1156–1163. doi: 10.3201/eid2606.190965. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Hsu JY, Chuang YC, Wang JT, Chen YC, Hsieh SM. Healthcare-associated carbapenem-resistant Klebsiella pneumoniae bloodstream infections: risk factors, mortality, and antimicrobial susceptibility, 2017-2019. J Formos Med Assoc. 2021;120(11):1994–2002. doi: 10.1016/j.jfma.2021.04.014. [DOI] [PubMed] [Google Scholar]
- 45.Cienfuegos-Gallet AV, AMO d l R, Viana PS, Brinez FR, Castro CR, Villamil GR, et al. Risk factors and survival of patients infected with Carbapenem-resistant Klebsiella pneumoniae in a KPC endemic setting: a case-control and cohort study. BMC Infect Dis. 2019;19(1):830. doi: 10.1186/s12879-019-4461-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Mills JP, Talati NJ, Alby K, Han JH. The epidemiology of Carbapenem-resistant Klebsiella pneumoniae colonization and infection among long-term acute care hospital residents. Infect Control Hosp Epidemiol. 2016;37(1):55–60. doi: 10.1017/ice.2015.254. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Soares de Moraes L, Gomes Magalhaes GL, Material Soncini JG, Pelisson M, Eches Perugini MR, Vespero EC. High mortality from Carbapenem-resistant Klebsiella pneumoniae bloodstream infection. Microb Pathog. 2022;167:105519. doi: 10.1016/j.micpath.2022.105519. [DOI] [PubMed] [Google Scholar]
- 48.Schwartz-Neiderman A, Braun T, Fallach N, Schwartz D, Carmeli Y, Schechner V. Risk factors for Carbapenemase-producing carbapenem-resistant Enterobacteriaceae (CP-CRE) acquisition among contacts of newly diagnosed CP-CRE patients. Infect Control Hosp Epidemiol. 2016;37(10):1219–1225. doi: 10.1017/ice.2016.153. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
The difference in patient's characteristics of those treated with imipenem or meropenem.
Data Availability Statement
The datasets during the current study available from the corresponding author on reasonable request.