1. Introduction
The detection rate of carbapenem-resistant Enterobacteriaceae (CRE) strains has been steadily rising, presenting a significant public health challenge [
1,
2,
3]. CRE infections are particularly concerning due to their high mortality rates, increased healthcare costs, and limited treatment options [
4,
5]. The management and control of CRE infections are especially difficult in Intensive Care Unit (ICU) patients [
6]. These multidrug-resistant organisms have drawn considerable global attention, with both the World Health Organization (WHO) and the U.S. Centers for Disease Control and Prevention (CDC) classifying CRE as an urgent public health threat [
7,
8]. As CRE infections continue to spread, there is a pressing need to understand the factors contributing to their spread and persistence.
A growing body of research has investigated potential risk factors for CRE colonization and infection. These factors include prolonged antibiotic use, extended hospitalization, the presence of indwelling medical devices, and immunosuppressive conditions [
9,
10,
11]. Additionally, studies have highlighted that certain patient populations—such as those with liver disease, hematological disorders, or those undergoing organ transplantation—may be particularly vulnerable to CRE infections [
10,
12,
13]. This suggests that the risk factors for CRE infection may vary considerably depending on a patient’s underlying health conditions and exposure to healthcare environments.
Among the various clinical manifestations of CRE infections, bloodstream infections (BSIs) are of particular concern due to their high severity, challenging treatment options, and significant impact on patient outcomes [
4,
14]. Despite this, much of the research surrounding CRE infections has focused primarily on CRE BSI, while the risk factors and outcomes of CRE infections in other infection sites have received relatively less attention. The lack of comprehensive studies exploring risk factors across different types of CRE infections raises important questions about whether these risk factors differ based on the anatomical site of infection and what the potential implications might be for clinical management.
To address this gap, the aim of this study is to analyze the risk factors for CRE infections in different infection sites, investigate the potential differences in these risk factors, and evaluate the outcomes of CRE infections across different infection sites. The goal is to provide insights that could inform better prevention and treatment strategies for CRE infections.
3. Discussion
ICU patients face a higher risk of CRE infections and treatment failure due to immunosuppression, prolonged hospitalization, and frequent antibiotic use, posing significant challenges to their clinical management [
15,
16,
17]. However, the severity of CRE infections varies by anatomical site, and the associated risk factors differ accordingly. This study primarily focused on comparing the differences in risk factors for CRE infections at different anatomical sites and exploring risk factors for mortality in CRE-infected patients.
Previous studies have identified several risk factors for CRE infections, including CRE colonization, mechanical ventilation, prolonged hospitalization, immunosuppressive conditions, and long-term antibiotic use [
18,
19,
20]. Through univariate, multivariate, and logistic regression analyses, we systematically evaluated the risk factors and their predictive value. We identified CRE colonization as a common risk factor across all three groups, highlighting its central role in the pathogenesis of CRE infections. In addition, our study revealed distinct site-specific risk factors: mechanical ventilation in the RTI group, trauma in the UTI group, and gastrointestinal injury in the BSI group. Although some of these factors have been reported previously [
21,
22,
23], our study provides the systematic comparison across different infection sites, underscoring the unique risk patterns of CRE infections by anatomical location. These findings also suggest potential differences in the sources or transmission pathways of CRE across sites. Furthermore, ROC curve analysis demonstrated good discriminatory ability, supporting its clinical utility in the early identification of high-risk patients.
Furthermore, patients with BSI caused by CRE exhibited significantly higher levels of inflammatory markers than those in the other groups. This finding suggests a more pronounced systemic inflammatory response in BSI cases, which may contribute to the increased severity and mortality observed in this group. As previously reported, BSI caused by CRE has received widespread attention due to its high mortality rate and severe clinical consequences [
24,
25,
26]. In our study, the BSI group had the highest mortality rate; however, the difference was not statistically significant compared to the RTI and UTI groups. This may be attributed to the relatively small sample size, which could have limited the statistical power and affected the significance of our findings. Interestingly, although CRE-related BSI are particularly concerning, our study found that CRE strains in the BSI group had the lowest resistance rates to CZA and polymyxin B among the three infection groups. In recent years, the emergence of CRE strains resistant to both CZA and polymyxin B has become an increasingly concerning issue [
27,
28]. This observation has not been widely reported in previous studies and may reflect potential differences in resistance characteristics among CRE strains from different infection sites. Possible explanations for this finding include variations in host immune status, selective pressures specific to the bloodstream environment, and differences in prior antibiotic exposures among patients. It is also possible that these patterns are influenced by local epidemiological factors and may not be generalizable to other regions. Given the limited sample size and the single-center nature of our study, further multicenter studies with larger cohorts are needed to validate these findings and to explore the underlying biological and epidemiological mechanisms.
Moreover, previous studies have reported that immunosuppressive conditions, such as malignancies and organ transplantation, as well as antibiotic use, are associated with increased mortality in CRE-infected patients [
10,
29,
30,
31]. Our study supports this trend, univariate and multivariate analyses of survivors and non-survivors revealed that prior use of carbapenems and antifungal agents was independently associated with increased mortality, consistent with previous findings [
29,
32]. Interestingly, trauma was more frequent in survivors than in non-survivors, suggesting that while trauma may predispose to CRE infection, it is not a direct determinant of mortality. We further observed significantly higher PCT levels in the non-survivor group. Although the difference was not statistically significant in univariate analysis, the log-transformed PCT (Ln[PCT]) was retained in the final prognostic model. In line with prior studies, this supports the role of excessive inflammatory responses in disease progression and death, where marked elevations in inflammatory markers serve as a warning signal. Overall, prudent antibiotic use and timely control of infection-associated inflammation are crucial for improving patient outcomes.
This study has several limitations. First, it was conducted in a single center with a limited sample size, which may reduce the robustness of the multivariate models. Second, the lack of statistical significance in mortality differences among the three groups may be attributed to the limited number of patients. Third, although we observed distinctive resistance patterns in CRE strains from BSI patients, these findings may merely reflect local epidemiological characteristics rather than generalizable trends. Fourth, in the Kaplan–Meier survival analysis, data for surviving patients were censored at discharge, as no post-discharge follow-up was performed; this may affect the accuracy of survival estimates. Therefore, larger multicenter studies with greater statistical power are needed to validate and expand upon our observations.
4. Materials and Methods
4.1. Study Subjects
Patients admitted to the ICU of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, between January 2021 and September 2023, who voluntarily underwent CRE screening and subsequently contracted CRE were included in this study. Based on the anatomical site of infection, these patients were categorized into three groups: RTI, UTI, and BSI. Additionally, a control group of 40 ICU patients who underwent voluntary CRE screening during the same period but did not develop a CRE infection was randomly selected. The control group was set at twice the size of the group with the fewest cases among the three groups to balance statistical power across groups. Furthermore, CRE-infected patients were classified into Survived and Deceased groups according to in-hospital mortality (up to the point of discharge). This study was approved by the Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (ID: 2021-S013).
4.2. Design and Definition
Each patient provided a perirectal swab to assess for the presence of CRE colonization. The collected rectal swabs were immediately inoculated onto a chromogenic agar plate containing carbapenem as a selective agent (CHROMagar, La Plaine Saint-Denis, France) for CRE screening. All isolated bacterial strains were identified using a MALDI-TOF mass spectrometer (Bruker Daltonics, San Jose, CA, USA) for accurate species identification to ensure accurate species identification. The antimicrobial susceptibility of the isolates, specifically to meropenem and imipenem, was determined using the Kirby–Bauer disk diffusion method. The results were interpreted according to the Clinical and Laboratory Standards Institute (CLSI) M100-ED30 [
33] guidelines for breakpoint determination, ensuring standardized and reliable susceptibili assessment.
4.3. Data Collection
The data were collected retrospectively from electronic medical records, mainly including variables potentially related to CRE infection. These variables encompassed general information (gender, age, department), underlying conditions (such as hypertension, diabetes, solid organ tumors, hematological malignancies, impaired immune function, gastrointestinal injury), invasive procedures and devices (hematopoietic stem cell transplantation, surgery, mechanical ventilation, central venous catheter, urinary catheter, gastric tube, drainage tube), antibiotic exposure (defined as the use of the specific antibiotic during the period from hospital admission to the occurrence of CRE infection), and routine laboratory data (including WBC count, neutrophil percentage, PCT, and hsCRP, with laboratory data collected on the day the CRE-positive sample was submitted).
4.4. Statistical Analysis
Continuous variables were expressed as mean ± standard deviation (SD) or median (interquartile range, IQR), and comparisons between groups were performed using the Mann–Whitney U test. Categorical variables were expressed as number (%), and group comparisons were conducted using the Chi-square test or Fisher’s exact test. Univariate analyses were first performed to identify potential risk factors associated with outcomes. Variables with p < 0.05 in the univariate analysis were then included in a multivariate logistic regression model to determine independent risk factors. ROC curves were plotted based on the established logistic model. KM survival curves were constructed according to patient outcomes. Statistical significance was defined as p < 0.05. Statistical analyses were conducted using SPSS version 19.0 (SPSS, Chicago, IL, USA) and GraphPad Prism 8.0 (GraphPad Software, San Diego, CA, USA).