ABSTRACT
In this study, the genetic differences and clinical impact of the carbapenemase-encoding genes among the community and healthcare-acquired infections were assessed. This retrospective, multicenter cohort study was conducted in Colombia and included patients infected with carbapenem-resistant Gram-negative rods between 2017 and 2021. Carbapenem resistance was identified by Vitek, and carbapenemase-encoding genes were identified by whole-genome sequencing (WGS) to classify the alleles and sequence types (STs). Descriptive statistics were used to determine the association of any pathogen or gene with clinical outcomes. A total of 248 patients were included, of which only 0.8% (2/248) had community-acquired infections. Regarding the identified bacteria, the most prevalent pathogens were Pseudomonas aeruginosa and Klebsiella pneumoniae. In the WGS analysis, 228 isolates passed all the quality criteria and were analyzed. The principal carbapenemase-encoding gene was blaKPC, specifically blaKPC-2 [38.6% (88/228)] and blaKPC-3 [36.4% (83/228)]. These were frequently detected in co-concurrence with blaVIM-2 and blaNDM-1 in healthcare-acquired infections. Notably, the only identified allele among community-acquired infections was blaKPC-3 [50.0% (1/2)]. In reference to the STs, 78 were identified, of which Pseudomonas aeruginosa ST111 was mainly related to blaKPC-3. Klebsiella pneumoniae ST512, ST258, ST14, and ST1082 were exclusively associated with blaKPC-3. Finally, no particular carbapenemase-encoding gene was associated with worse clinical outcomes. The most identified genes in carbapenemase-producing Gram-negative rods were blaKPC-2 and blaKPC-3, both related to gene co-occurrence and diverse STs in the healthcare environment. Patients had several systemic complications and poor clinical outcomes that were not associated with a particular gene.
IMPORTANCE
Antimicrobial resistance is a pandemic and a worldwide public health problem, especially carbapenem resistance in low- and middle-income countries. Limited data regarding the molecular characteristics and clinical outcomes of patients infected with these bacteria are available. Thus, our study described the carbapenemase-encoding genes among community- and healthcare-acquired infections. Notably, the co-occurrence of carbapenemase-encoding genes was frequently identified. We also found 78 distinct sequence types, of which two were novel Pseudomonas aeruginosa, which could represent challenges in treating these infections. Our study shows that in low and middle-income countries, such as Colombia, the burden of carbapenem resistance in Gram-negative rods is a concern for public health, and regardless of the allele, these infections are associated with poor clinical outcomes. Thus, studies assessing local epidemiology, prevention strategies (including trials), and underpinning genetic mechanisms are urgently needed, especially in low and middle-income countries.
KEYWORDS: antimicrobial resistance, carbapenem resistance, carbapenemase-encoding genes, KPC, sequence analysis
INTRODUCTION
Antimicrobial resistance (AMR) is responsible for more than 4.95 million deaths globally (1), and it is forecasted that the mortality rate due to AMR will increase by up to 10 million annually by 2050. Moreover, the World Bank calculates an annual fall of the global gross domestic product by 1.1%–3.8%; this shortfall would exceed $1–3.4 trillion annually, secondary to AMR (2). This scenario worsens when Gram-negative rods become resistant to carbapenems used as part of the last-line antimicrobial treatments (3, 4). Notably, the frequency of carbapenem-resistant infections is three times higher in low and middle-income countries (LMIC) (5), especially in South America, due to the carriage of carbapenemase-encoding genes (6).
Previous worldwide studies have shown that the carbapenem resistance epidemiology of carbapenemase-encoding genes varies. blaKPC infections most commonly occur in the United States, metallo-β-lactamases in the Indian Subcontinent and some European countries, and the epicenter of blaOXA-48-like is in Turkey and its surroundings (7). Colombia has a high prevalence of infections caused by carbapenemase-producing Gram-negative rods (8); for instance, the country described the first blaKPC-producing Pseudomonas aeruginosa in 2006 (9, 10). Interestingly, the co-occurrence of carbapenemase-encoding genes has also been reported, such as blaKPC + blaVIM, blaNDM + blaOXA-48-like, and blaVIM + blaOXA-48-like (11, 12). Co-occurrence has become frequent in Latin America and represents a significant diagnostic and therapeutic challenge since it creates major difficulty for clinical treatment, leaving healthcare professionals without therapeutic alternatives for infected patients (13, 14).
Carbapenem-resistant infections are frequently acquired in healthcare-related environments (15). However, in recent years, the rate of community-acquired resistant infections has increased (16), and current evidence is scarce on this topic. Moreover, there is scarce data that describe these infections in Colombia, especially reports from community and healthcare-acquired infections and their impact on clinical outcomes. Thus, this project aims to bridge this gap in the literature. We used a comprehensive clinical and molecular approach to describe the genotypic characteristics of carbapenemase-producing Gram-negative rods in Colombia, an LMIC. We hypothesize that the description of the carbapenemase-encoding genes in these bacteria may vary, particularly in healthcare and community settings.
RESULTS
A total of 248 patients were included in the study, all with single bacterial isolation (Fig. 1). Most of the patients were male [71.4% (177/248)], and the median (interquartile range, IQR) age was 61.5 years old (47.0–72.3). The main identified comorbidities were arterial hypertension [50.0% (124/248)], diabetes mellitus [25.4% (63/248)], smoking history [26.2% (65/248)], and obesity [20.2% (50/248)]. Regarding treatments and interventions, more than half of the patients required invasive mechanical ventilation [61.3% (152/248)]. Also, two-thirds were admitted to the intensive care unit (ICU) [76.2% (189/248)] with a prolongated median (IQR) ICU length of stay (LOS) [25.0 days (14.0–36.0)]. Finally, mortality was reported in more than a third of the patients [33.9% (84/248)]. All patients’ baseline characteristics are shown in Table 1.
Fig 1.
Study flowchart.
TABLE 1.
Demographic characteristics of all patients and stratification between infection acquisition
| General cohort (n = 248) | Community acquired (n = 2) |
Healthcare acquired (n = 246) |
|
|---|---|---|---|
| Demographic characteristics | |||
| Age, median (IQR) | 61.5 (47.0–72.3) | 75.0 (68.5–81.5) | 61.0 (47.0–72.0) |
| Male, n (%) | 177 (71.4) | 0 (0.0) | 177 (72.0) |
| Charlson index, median (IQR) | 3.0 (1.0–5.0) | 3.5 (2.8–4.3) | 3.0 (1.0–5.0) |
| Comorbid condition, n (%) | |||
| Smoking history | 65 (26.2) | 0 (0.0) | 65 (26.4) |
| Alcoholism | 17 (6.9) | 0 (0.0) | 17 (6.9) |
| Chronic obstructive pulmonary disease (COPD) | 45 (18.1) | 1 (50.0) | 44 (17.9) |
| Diabetes mellitus | 63 (25.4) | 0 (0.0) | 63 (25.6) |
| Hypertension | 124 (50.0) | 0 (0.0) | 124 (50.4) |
| Obesity | 50 (20.2) | 0 (0.0) | 50 (20.3) |
| Congestive heart failure | 35 (14.1) | 0 (0.0) | 35 (14.2) |
| Coronary disease | 28 (11.3) | 0 (0.0) | 28 (11.4) |
| Atrial fibrillation | 20 (8.1) | 0 (0.0) | 20 (8.1) |
| Dyslipidemia | 32 (12.9) | 0 (0.0) | 32 (13.0) |
| Liver disease | 5 (2.0) | 0 (0.0) | 5 (2.0) |
| Chronic kidney failure | 47 (19.0) | 0 (0.0) | 47 (19.1) |
| Autoimmune disease | 12 (4.8) | 0 (0.0) | 12 (4.9) |
| Cancer | 11 (4.4) | 0 (0.0) | 11 (4.5) |
| HIV | 3 (1.2) | 0 (0.0) | 3 (1.2) |
| Epilepsy | 11 (4.4) | 0 (0.0) | 11 (4.5) |
| Previous hospital admission | 54 (21.8) | 0 (0.0) | 54 (22.0) |
| Previous use of antibiotic | 43 (17.3) | 0 (0.0) | 43 (17.5) |
| Vital signs at admission, median (IQR) | |||
| Heart rate | 85.0 (75.0–102.0) | 87.5 (85.8–89.3) | 86.0 (75.0–102.0) |
| Respiratory rate | 19.0 (18.0–22.0) | 17.5 (17.3–17.8) | 19.0 (18.0–22.0) |
| Systolic blood pressure | 120.0 (107.0–133.0) | 143 (128.0–158.0) | 120.0 (107.0–133.0) |
| Diastolic blood pressure | 74.0 (65.0–80.0) | 64.5 (55.3–73.8) | 74.0 (52.0–80.0) |
| Mean arterial pressure | 86.0 (75.0–96.0) | 94 (81.0–107.0) | 86.0 (75.0–96.0) |
| Temperature | 36.4 (36.0–36.5) | 36.3 (36.1–36.4) | 36.4 (36.0–36.5) |
| Saturation | 92.0 (87.0–94.0) | 92.0 (91.0–93.0) | 92.0 (87.0–94.0) |
| Glasgow | 15.0 (13.0–15.0) | 14.5 (14.3–14.8) | 15.0 (13.0–15.0) |
| Laboratory testing at admission, median (IQR) | |||
| Leucocytes | 10.1 (7.3–14.5) | 18.3 (14.3–22.3) | 10.1 (7.2–14.4) |
| Hemoglobin | 13.5 (10.4–15.5) | 8.5 (7.8–9.1) | 13.6 (10.5–15.5) |
| Blood urea nitrogen | 22.0 (17.0–36.0) | 106 (84.0–128.0) | 22.0 (17.0–35.0) |
| Creatinine | 1.0 (1.0–2.0) | 6.7 (4.9–8.5) | 1.0 (0.8–1.7) |
| Sodium | 138.0 (135.0–141.0) | 149 (143.0–155.0) | 138.0 (135.0–141.0) |
| Potassium | 4.3 (3.9–4.9) | 6.5 (6.4–6.5) | 4.3 (3.9–4.8) |
| Reactive C protein | 100.0 (32.0–100.0) | NAa | 100.0 (32.0–100.0) |
| Severity scores, median (IQR) | |||
| Sequential organ failure assessment (SOFA) at admission | 4 (3.0–6.0) | NA | 4 (3.0–6.0) |
| Acute physiology and chronic health evaluation disease classification system (APACHE) at admission | 12 (8.0–18.5) | NA | 12 (8.0–18.5) |
| SOFA at isolation | 6 (3.0–9.0) | NA | 6 (3.0–9.0) |
| APACHE at isolation | 16 (8.0–21.0) | NA | 16 (8.0–21.0) |
| Treatments and interventions | |||
| Invasive mechanical ventilation, n (%) | 152 (61.3) | 0 (0.0) | 152 (61.8) |
| IMV days, median (IQR) | 19.5 (11.0–28.0) | NA | 19.5 (11.0–28.0) |
| Vasopressor, n (%) | 154 (62.1) | 0 (0.0) | 154 (62.6) |
| Inotropic, n (%) | 81 (32.7) | 0 (0.0) | 81 (32.9) |
| Antibiotics days, median (IQR) | 14.0 (10.0–17.0) | 6.0 (5.5–6.5) | 14.0 (10.0–17.0) |
| Outcomes, n (%) | |||
| Admission to the intensive care unit | 189 (76.2) | 1 (50.0) | 188 (76.4) |
| Hospital LOS, median (IQR) | 33.0 (19.0–57.0) | 7.5 (6.3–8.8) | 33.5 (19.0–57.0) |
| ICU LOS, median (IQR) | 25.0 (14.0–36.0) | 2.0 (2.0–2.0) | 25.0 (14.0–36.0) |
| In-hospital mortality | 84 (33.9) | 1 (50.0) | 83 (33.7) |
| General cohort (n = 228) | Community acquired (n = 2) | Healthcare acquired (n = 226) | |
| Alleles according to WGS, n (%) | |||
| blaKPC-2 | 88 (38.6) | 0 (0.0) | 88 (38.9) |
| blaKPC-3 | 83 (36.4) | 1 (50.0) | 82 (36.3) |
| blaOXA-152 | 1 (0.4) | 0 (0.0) | 1 (0.4) |
| blaOXA-244 | 1 (0.4) | 0 (0.0) | 1 (0.4) |
| blaVIM-2 | 29 (12.7) | 0 (0.0) | 29 (12.8) |
| blaVIM-24 | 3 (1.3) | 0 (0.0) | 3 (1.3) |
| blaGES-5 | 1 (0.4) | 0 (0.0) | 1 (0.4) |
| blaNDM-1 | 16 (7.0) | 0 (0.0) | 16 (7.1) |
| NA | 31 (13.6) | 1 (50.0) | 30 (13.3) |
Not applicable.
Most patients had healthcare-acquired infections [99.2% (246/248)]. Those with community-acquired infections were [median (IQR)] older [CA: 75.0 years (68.5–81.5); HA: 61.0 (47.0–72.0)] and had a higher [median (IQR)] Charlson index [CA: 3.5 (2.8–4.3); HA: 3.0 (1.0–5.0)]. At admission, although patients in both groups had similar vital signs and paraclinical data, those with community-acquired infections had higher leucocytes [CA: 18.3 (14.3–22.3); HA: 10.1 (7.2–14.4)] and creatinine levels [6.7 (4.9–8.5); 1.0 (0.8–1.7)]. Notably, ICU admission was notoriously higher among those with healthcare-acquired infections [CA: 50.0% (1/2); HA: 76.4% (188/246)], but not in-hospital mortality [CA: 50.0% (1/2); HA: 33.7% (83/246)] (Table 1).
In this study, the comprehensive analysis of clinical diagnoses revealed that the predominant infections were urinary tract infections [28.6% (71/248)], ventilator-associated pneumonia [17.7% (44/248)], primary bloodstream infection [16.9% (42/248)], and peritonitis [12.1% (30/248)] (Fig. 2). Regarding the community-acquired infections, these were either urinary tract infections [50.0% (1/2)] or primary bloodstream infections [50.0% (1/2)], while healthcare-acquired infections were dominated by urinary tract infections [28.5% (70/246)] and ventilator-associated pneumonia [17.9% (44/246)] (Fig. 2).
Fig 2.
Patients’ diagnoses. Distribution of patients’ diagnoses is shown: those with community-acquired infections (blue) and healthcare-acquired infections (orange). UTI, urinary tract infection; VAP, ventilator-associated pneumonia; PBI, primary blood infection; SSTI, skin and soft tissue infection; SSI, surgical site infection; BSI, bacterial superinfection; CLABSI, central line-associated bloodstream infection; CAP, community-acquired pneumonia; and HAP, hospital-acquired infection.
The initial bacterial identification was done at each institution by Vitek. Subsequently, these were recognized by WGS to determine the pathogen’s species accurately. Although all isolates were identified as carbapenem-resistant, during the genetic characterization using WGS, seven isolates did not pass quality control. In 13, a known carbapenemase gene was not identified. Consequently, 228 bacterial isolates were included in the WGS analysis. As expected, some discrepancies were observed among the identification strategies used (Vitek and WGS). For instance, 17 distinct species were represented by Vitek and 34 by WGS (Table S1). However, for both methods, the most prevalent species identified were P. aeruginosa [Vitek: 35.1% (87/248); WGS: 38.2% (87/228)] and Klebsiella pneumoniae [Vitek: 36.3% (90/248); WGS: 28.5% (65/228)] (Table S1).
Genetic analysis by WGS
A total of 228 isolates passed all quality checks for WGS analysis. Information regarding the susceptibility to aminoglycosides, colistin, fosfomycin, fluoroquinolones, rifampicin, sulfonamides, tetracyclines, trimethoprim, beta-lactamases, extended-spectrum beta-lactamases (ESBLs), SHV gene mutations, Omp gene mutations, colistin mutations, and fluoroquinolone mutations can be found in Table S2. Respecting the identified genes related to carbapenem resistance, the leading genotypic group was blaKPC, specifically, blaKPC-2 [38.6% (88/228)] and blaKPC-3 [36.4% (83/228)] as the predominant alleles. These results were followed by blaVIM-2 [12.7% (29/228)] and blaNDM-1 [7.0% (16/228)]. Carbapenemase-encoding genes blaOXA-152 [0.4% (1/228)], blaOXA-244 [0.4% (1/228)], and blaGES-5 [0.4% (1/228)] were the least prevalent identified. Notably, the only identified allele among community-acquired infections was blaKPC-3 [50.0% (1/2)]. All WGS results are shown in Fig. 3 and Table 1.
Fig 3.
WGS identification. (a) Phylogenetic tree (midpoint rooted) showing the relationship of all species detected in WGS (one representative per species), the number of STs detected is shown next to the tree, and heatmap that shows the proportion of genomes carrying a particular carbapenemase gene identified by WGS. (b) Bar chart indicating the total number of genomes per species that either carried a carbapenemase gene (black) or not (gray).
It is essential to clarify that in 31 confirmed carbapenemase-producing genomes, we could not detect carbapenemase-encoding genes. The majority of these were P. aeruginosa [58.0% (18/31)], representing 20.7% of all P. aeruginosa isolates. This phenomenon was also observed in smaller proportions with K. pneumoniae, Enterobacter hormaechei, Escherichia coli, and Shigella sonnei (Fig. 3b).
Isolates with co-occurring carbapenemase genes were detected in 9.6% (22/228) of genomes (Table S3). A total of 20 microorganisms had two carbapenem resistance genes, these being P. aeruginosa [55.0% (11/20)], K. pneumoniae [20.0% (4/20)], E. hormaechei [15.0% (3/20)], Klebsiella variicola [5.0% (1/20)], and P. rettgeri [5.0% (1/20)]. Contrastingly, only two isolates expressed three carbapenem resistance genes, both being K. pneumoniae [100.0% (2/2)]. Regarding co-occurring alleles, 10 were blaKPC-3 + blaVIM-2 [P. aeruginosa: 100.0% (10/10)], 9 were blaKPC-2 + blaNDM-1 [K. pneumoniae: 44.4% (4/9), E. hormaechei: 33.3% (3/9), Klebsiella variicola sub sp. variicola: 11.1% (1/9), and Providencia rettgeri: 11.1% (1/9)], 2 were blaKPC-2 + blaNDM-1 + blaVIM-24 [K. pneumoniae: 100.0% (2/2)], and 1 blaKPC-3 + blaNDM-1 [P. aeruginosa: 100.0% (1/1)] (Table S4).
Multi-locus sequence type (MLST) schemes were available for 23 of the 34 species identified in the WGS analysis, and 78 distinct STs were identified. A total of 56 were represented by only one isolate each, indicating a high diversity of carbapenemase-producing Gram-negative rods. However, eight STs appeared to be overrepresented and were identified among ≥5 genomes each. Regarding P. aeruginosa, these were ST111 [65.5% (57/87)] and ST235 [13.8% (12/87)]. For K. pneumoniae ST258 [15.4% (10/65)], ST14 [10.8% (7/65)], ST219 [10.8% (7/65)], ST236 [10.8% (7/65)], and ST1082 [7.7% (5/65)]. Finally, for E. hormaechei, only ST175 [52.9% (9/17)] (Table S2).
The distribution of carbapenemase genes among STs was explored for the most frequently identified pathogens, P. aeruginosa and K. pneumoniae. Results were separated according to the source of infection (community-acquired and healthcare-acquired). Isolates carrying more than one carbapenemase gene were counted once for each gene. With respect to P. aeruginosa, ST111 was primarily associated with blaKPC-3 and blaVIM-2; both were related to healthcare-acquired infections. Also, two novel P. aeruginosa STs were identified; notably, one was recognized in a community-acquired infection (Fig. 4a). For K. pneumoniae, 14 STs were associated with blaKPC-2, all from healthcare-acquired infections. blaKPC-3 was associated exclusively with healthcare-acquired ST512 [100.0% (2/2)], ST258 [100.0% (10/10)], ST14 [100.0% (7/7)], and ST1082 [100.0% (5/5)] (Fig. 4b). Only ST219 was related to community-acquired infections [16.7% (1/6)].
Fig 4.
Gene correlation with STs of Pseudomonas aeruginosa and Klebsiella pneumoniae. (a) Heatmap shows the proportion of genes associated with the different STs of Pseudomonas aeruginosa. (b) Heatmap shows the proportion of genes associated with the different STs of Klebsiella pneumoniae. CA, community-acquired; HA, healthcare-acquired; and NA, non-detected.
We sought to understand the relationship between isolates in our collection and those from other geographies represented in public genome collections. We focused on the three STs for which ≥10 genomes were available in our collection (P. aeruginosa ST111 and ST235, K. pneumoniae ST258) and used maximum likelihood phylogenetic analyses to compare them to public genomes of the same ST identified via the Pathogenwatch genomic surveillance platform (https://pathogen.watch/; see Table S5 and Materials and Methods). The P. aeruginosa ST111 genomes from our collection formed three clusters in the phylogeny (Fig. S1), consistent with at least three independent introductions. All three clusters fell within a large sub-clade that was not well-resolved in the phylogeny and was dominated by genomes from Europe and North America carrying blaVIM carbapenemases; however, this was unsurprising given the overwhelming bias toward these regions among the public ST111 genomes. Nine of our P. aeruginosa ST235 genomes formed a cluster in the phylogeny, whereas the remaining three appeared unrelated to each other. The cluster of nine genomes was most closely related to a subclade comprising genomes from diverse geographic regions, but primarily Asia and North America, and mostly without any detectable carbapenemases (Fig. S2). All our K. pneumoniae ST258 genomes were clustered together in the phylogeny and sister clade to a group dominated by genomes from North America (Fig. S3). As is characteristic of ST258, most genomes carried blaKPC carbapenemase alleles. In all cases, it is difficult to draw conclusions about the potential origins of the isolates in our collection, due to the vast overrepresentation of public data from Europe and North America and the lack of representation of other sites in Colombia or, indeed, many South American countries.
Clinical impact
Bivariate analysis between the different alleles identified by WGS. These showed no association or difference with hospital mortality (P = 0.83), ICU admission (P = 0.52), vasopressor requirement (P = 0.61), inotropic requirement (P = 0.65), or mechanical ventilation requirement (P = 0.25) (Table S5).
DISCUSSION
This cohort of patients infected with carbapenemase-producing Gram-negative rods is novel in describing the molecular characteristics and epidemiological profile of a large cohort in an LMIC in South America. The most common isolated bacteria were P. aeruginosa and K. pneumoniae, and the primary detected carbapenemase-encoding gene was blaKPC, alleles blaKPC-2 and blaKPC-3. Also, co-occurrence was frequently detected. Moreover, a small number of ST-carbapenemase combinations were overrepresented among healthcare-acquired infections, which may indicate transmission within the hospital setting. These results are essential to generate recommendations to treat patients with these infections in LMICs.
The prevalence of AMR appears notably elevated in the context of hospital-acquired infections (17). This correlates with our results, where most isolates originated from a hospital setting (99.2%). In contrast, a 2022 population-based surveillance conducted in the United States revealed a higher proportion, with 10% of carbapenem-resistant Enterobacterales identified as community-acquired (18). These disparities in prevalence can be attributable to variations in the definitions employed or potential biases within the cohort selection process, which underscores the importance of standardizing definitions and ensuring accuracy in their application. Furthermore, the epidemiological profile of our cohort was similar to the worldwide description of carbapenem resistance, P. aeruginosa and K. pneumoniae being the most prevalent bacteria (19, 20). A 2022 global systematic review identified these pathogens as part of the six most resistant microorganisms associated with increased mortality (1, 21, 22). Enterobacter spp. was also a commonly isolated species in our study, which is considered an emerging global threat and has increased in Colombia during the last decade (23, 24). Unlike other countries, resistant Acinetobacter baumannii was not a frequently identified pathogen in our study. In the United States, it caused 22% of 29,742 reported infections between 2009 and 2013 (25). These advocate that LMICs’ epidemiology has differences that must be studied further.
The principal identified carbapenemase-encoding gene in our study was Class A blaKPC, which is in alignment with American and Latin American epidemiology (26, 27). In our cohort, blaKPC-2 and blaKPC-3 were the most frequently detected alleles in healthcare-acquired infections. blaKPC-2 is a commonly found resistance gene in Colombia. Latest studies have reported an increase in P. aeruginosa and Enterobacter cloacae, possibly mediated by plasmid transmission. Regarding blaKPC-3 infections, these have been described in Colombia since 2011 (28), and different cities still struggle with in-hospital outbreaks (29, 30). Notably, previous outbreaks associated with blaKPC-3 K. pneumoniae ST258 have been reported (29), our most common ST in this pathogen. Moreover, P. aeruginosa ST111 has been closely related to blaVIM-2 (31–33); however, in our study, its primary production was blaKPC-3, which is uncommon and has not been published before. These findings open a possibility of gene clonality in the healthcare environment either through an inter-species transfer of antimicrobial resistance plasmids in combination with local clonal expansion, which is the subject of ongoing analyses in our team, or patient-to-patient or from a reservoir within the hospital (e.g., contaminated equipment or sink drains), as have been implicated previously for these organisms (34–36).
Carbapenem resistance is known to have a negative effect on clinical outcomes, especially in LMICs (16, 37). Despite this, our results demonstrate that the different carbapenemase-producing Gram-negative rods and carbapenemase-encoding genes have similar effects on clinical endpoints. This could be in relation to the different treatment recommendations based on the etiological agent and/or its resistance mechanism (38). For instance, ceftolozane-tazobactam is a new antimicrobial against resistant P. aeruginosa and K. pneumoniae; however, it has no activity for class A serine carbapenemases or class B metallo-β-lactamases (39–41). Ceftazidime-avibactam and meropenem/vaborbactam are novel antibiotics active against OXA and AmpC and class A carbapenemases producing Enterobacterales, respectively (42–45). These have a higher reported effectivity than aminoglycosides and colistin (46–48). In a systematic review, Soriano et al. (47) also described that blaKPC resistance secondary to ceftazidime-avibactam use is infrequent. Since the principal carbapenemase gene in our population was blaKPC, we hypothesize that using these new treatments may reduce healthcare expenses and disease burden and improve clinical outcomes. Nevertheless, blaKPC co-occurrence with blaVIM and blaNDM was frequently identified in our study and could bring challenging implications regarding antimicrobial treatments.
Our study has limitations and strengths that are important to recognize. Our comprehensive approach has highlighted the burden of carbapenem-resistant infections in our setting and the extensive diversity of the underlying pathogens associated with community-acquired and healthcare-acquired infections. However, these results reflect the current state of carbapenemase-producing Gram-negative rods only in two Colombian centers, and, therefore, we cannot extrapolate the specific trends to other countries and/or regions. Second, we did not have data from the last 2 years or a sufficient sample size to detect statistical differences between the community-acquired and healthcare-acquired pathogen populations in terms of species and ST distributions. Third, most isolates in our study meet a definition for acquisition in the hospital environment, and the dissemination of carbapenem-resistant Gram-negative rods in the community is an aspect we could not elucidate. For future studies, different methodological approaches could be addressed, such as evaluating fecal carriage in well-selected samples of healthy subjects in the community (49) or evaluating an exclusive cohort of community-acquired isolates (50). Finally, we did not have access to information regarding the antimicrobial treatment of the patients or their prior contact with agriculture or livestock, which could have been valuable to provide results in the context of antimicrobial resistance. Nonetheless, our data highlight key aspects of carbapenem-resistant Gram-negative infections that should motivate similar works in other LMICs.
In conclusion, carbapenem resistance is a rising problem in LMICs such as Colombia. The most common carbapenemase-producing Gram-negative rods were P. aeruginosa and K. pneumoniae. Moreover, blaKPC-2 and blaKPC-3 were the most frequent carbapenemase-encoding genes related to gene co-occurrence and diverse ST in the healthcare environment. Notably, these patients had several systemic complications and poor clinical outcomes without being associated with a particular gene. These data highlight the need for better prevention, diagnosis, and management of multidrug-resistant infections in LMICs and globally.
MATERIALS AND METHODS
This was a multicenter, retrospective cohort study conducted in Colombia between July 2017 and July 2021. It was performed in hospitalized patients infected with carbapenem-resistant Gram-negative rods, which could have been acquired in the community or the healthcare facility. Bacterial pathogens were identified using biochemical profiling during clinical practice. For this analysis, investigators collected all the clinical information by chart review. All the clinical data, laboratory results, and microbiological isolates were collected using the Research Electronic Data Capture (REDCap) electronic data collection form hosted by the Universidad de La Sabana. Informed consent was waived since this retrospective study used chart reviews to extract clinical data and bacteria kept for epidemiological vigilance in the microbiology labs.
Setting
This study was carried out in two reference hospitals in Colombia. The Clínica Universidad de La Sabana, a trauma reference academic health center located in the surroundings of Bogotá, Colombia and the Fundación Clínica Shaio, a cardiovascular reference hospital in Bogotá, Colombia.
Study population and data collection
All patients older than 18 years old hospitalized during the study period with a Gram-negative rod infection, with at least one carbapenem resistance in the antibiogram, were included. Isolates from patients without documented active infection (colonization) were excluded. The study’s definitions for infection and colonization can be found in the supplemental material. Patients who were transferred from another healthcare institution without available information regarding their previous hospitalization, those identified as duplicates, and individuals with more than one concomitant bacterial isolate were excluded from the study.
A community-acquired infection was defined as a direct admission from home, with a positive carbapenem-resistant culture documented within 48 h after admission and none of the following: (i) hospitalization within 30 days prior to admission, (ii) previous residency in a long-term care facility within 30 days prior to admission, (iii) chronic kidney disease stage G4, G5, or in dialysis, (iv) chronic liver disease Child-Pug B, Child-Pub C, or cirrhosis, (v) actively immunocompromised [i.e., chronic use of oral corticosteroids, chemotherapy, and acquired immunodeficiency syndrome), (vi) active cancer, (vii) pregnancy, or (viii) permanent use of a medical device (i.e., permanent bladder catheter, tracheostomy, nasogastric tube, and subclavian catheter) (Fig. 1).
The following variables were gathered in the data set: age, sex, past medical history (comorbidities), clinical diagnosis, treatments (medications), physiological and paraclinical variables, severity scores [Sequential Organ Failure Assessment (51) and Acute Physiology and Chronic Health disease Classification System (52)], LOS, ICU admission, days of antibiotic therapy, days of mechanical ventilation, ventilator support, vasopressor and inotropic support, and mortality. Physiological and paraclinical variables were collected during the first 24 h of admission and at the time of the bacterial isolation. All the study’s definitions are in the supplemental material.
Sample size estimation
Taking a population size of 2,000 isolations, the proportions of carbapenem-resistant Gram-negative rods expected was 50% due to our country’s unknown prevalence of carbapenem resistance (not representative data). The confidence level assumed was 95%, with a design effect of 1 and a 6% precision. A minimum requirement of 236 bacteria was needed to have the mentioned confidence level that the real value is within ±6% of the isolates’ value.
Bacterial isolates and procedures
Samples were taken according to the “Sample Collection Manual” of each institution. Both protocols can be found in the supplemental material. The identification of all the bacterial isolates and the antibiotic susceptibility testing were initially done by broth culture with Vitek identification according to the manufacturer’s instructions. Antibiotic resistance profiles were performed using a subculture of the identified strain in thioglycolate broth and incubated at 37°C for 24 h. Subsequently, the suspension was plated on a MacConkey agar plate and incubated at 37°C for 18–24 h. To detect carbapenem resistance, phenotypic tests and immunoassays were performed, such as the modified Hodge test, boronic acid sensi-discs synergy test, ethylenediaminetetraacetic acid discs synergy test, RESIST-4–O.K.N.V lateral flow immunoassays, and NG-Test CARBA 5 lateral flow immunoassay (53). All tests were performed consecutively by the same microbiology laboratory personnel, using the Clinical and Laboratory Standards Institute methods. The specific protocols for each test have been published elsewhere and can be found in the supplemental material (53).
The bacterial DNA extraction was done using the Qiagen DNeasy️ Blood & Tissue extraction kit, following the manufacturer’s instructions and subsequently tested in the NanoDrop to determine DNA quality; the cut-off point was 50 (ng/µL). Then, isolates were subjected to whole-genome sequencing. The sequencing libraries were generated using the Nextera DNA Flex kit (Illumina Inc.) and sequenced on the Illumina NovaSeq to create 150 bp paired-end reads. WGS data were used to confirm species identifications and identify 7-gene MLST and carbapenemase alleles (see supplemental material for full methodological details).
During the genetic characterization using WGS, 7 isolates did not pass quality control, and in 13, a known carbapenemase gene was not identified, and subsequent phenotypic re-testing revealed that the isolate received by the sequencing laboratory was not carbapenem-resistant (Table S6), suggesting that either (i) the original culture may have been mixed (one or more carbapenemase-producing strains plus one or more carbapenem-susceptible strains); (ii) the isolate had lost a resistance plasmid during culture; or (iii) a labeling error had occurred. Unfortunately, we could not determine which of these possibilities was most likely. Therefore, these 20 isolates were excluded from further analyses.
Statistical analysis
Data with missing values of less than 30% were imputed. A descriptive analysis was performed based on qualitative variables presented with percentages and absolute frequencies and continuous variables with median (interquartile range) or mean (standard derivation) according to their distribution. Then, normally distributed continuous data were tested using Welch’s two-sample t-tests for data from two groups and ANOVA for three or more groups. When the data follow a non-parametric distribution, the Mann-Whitney U was used to compare differences between two groups or the Kruskal-Wallis tests for three or more groups. Qualitative variables were performed by chi-squared to assess the association. Statistical significance was chosen at 5%. Analyses were conducted in R Studio (R Foundation for Statistical Computing, Vienna, Austria) or SPSS 25 (StataCorp LLC, TX, USA).
ACKNOWLEDGMENTS
This work was supported by MSD-Colombia, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA. This study was partially supported by the Universidad de La Sabana (MED-315-2021).
E.D.I.-P., I.G.B., D.F.J., and L.F.R. contributed to conception of the study; E.D.I.P., I.G.B., D.F.J., L.M., E.G.S., Y.V.F., C.C.S.-M., L.J., and L.F.R. designed the work; E.D.I.-P., I.G.B., D.F.J., L.M., E.G.-S., A.R.-C., and L.F.R. acquisition of data; L.M.J. and T.H. performed whole-genome sequencing; J.H. and K.L.W. performed genomic data analysis; E.D.I.-P., I.G.B., D.F.J., L.M., E.G.-S., Y.V.F., C.C.S.-M., E.S., L.J., J.H., K.L.W., and L.F.R. interpreted the data; E.D.I.-P., I.G.B., D.F.J., L.M., E.G.-S., Y.V.F., C.C.S.-M., E.S., L.J., T.H., H.F.A., J.U.-R., C.C.B., S.M., R.L., O.B., A.J.S., K.L.W., and L.F.R. drafted and revised the work. L.F.R. takes responsibility for the project and the data presented in this manuscript. All authors have approved the submitted version and agreed to be personally accountable for the author's contributions and to ensure that questions related to the accuracy or integrity of any part of the work.
Contributor Information
Luis Felipe Reyes, Email: luis.reyes5@unisabana.edu.co.
John Osei Sekyere, University of Pretoria, Pretoria, Gauteng, South Africa.
DATA AVAILABILITY
All the genomes are located in the following repository: PRJNA937403. All the data can be found in the supplemental material and Tables S1 to S6.
ETHICS APPROVAL
The Institutional Review Board/Independent Ethics Committee (IRB/EC) reviewed and authorized the study per local regulations.
SUPPLEMENTAL MATERIAL
The following material is available online at https://doi.org/10.1128/spectrum.01714-23.
Sample collection manual for Shaio Clinic Foundation.
Sample collection manual for Clinica Universidad de La Sabana.
Supplemental text, tables, and figures.
Table S2.
ASM does not own the copyrights to Supplemental Material that may be linked to, or accessed through, an article. The authors have granted ASM a non-exclusive, world-wide license to publish the Supplemental Material files. Please contact the corresponding author directly for reuse.
REFERENCES
- 1. Antimicrobial Resistance Collaborators . 2022. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet 399:629–655. doi: 10.1016/S0140-6736(21)02724-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Bank IBfRaDTW . 2017. Drug-resistant infections. https://documents1.worldbank.org/curated/en/323311493396993758/pdf/final-report.pdf. [PubMed]
- 3. Codjoe FS, Donkor ES. 2017. Carbapenem resistance: a review. Med Sci (Basel) 6:1. doi: 10.3390/medsci6010001 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Zhou R, Fang X, Zhang J, Zheng X, Shangguan S, Chen S, Shen Y, Liu Z, Li J, Zhang R, Shen J, Walsh TR, Wang Y. 2021. Impact of carbapenem resistance on mortality in patients infected with enterobacteriaceae: a systematic review and meta-analysis. BMJ Open 11:e054971. doi: 10.1136/bmjopen-2021-054971 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Tilahun M, Kassa Y, Gedefie A, Ashagire M. 2021. Emerging carbapenem-resistant enterobacteriaceae infection, its epidemiology and novel treatment options: a review. Infect Drug Resist 14:4363–4374. doi: 10.2147/IDR.S337611 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Escandón-Vargas K, Reyes S, Gutiérrez S, Villegas MV. 2017. The epidemiology of carbapenemases in Latin America and the Caribbean. Expert Rev Anti Infect Ther 15:277–297. doi: 10.1080/14787210.2017.1268918 [DOI] [PubMed] [Google Scholar]
- 7. van Duin D, Doi Y. 2017. The global epidemiology of carbapenemase-producing enterobacteriaceae. Virulence 8:460–469. doi: 10.1080/21505594.2016.1222343 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Rojas LJ, Weinstock GM, De La Cadena E, Diaz L, Rios R, Hanson BM, Brown JS, Vats P, Phillips DS, Nguyen H, Hujer KM, Correa A, Adams MD, Perez F, Sodergren E, Narechania A, Planet PJ, Villegas MV, Bonomo RA, Arias CA. 2017. An analysis of the epidemic of Klebsiella pneumoniae carbapenemase-producing K. pneumoniae: convergence of two evolutionary mechanisms creates the "perfect storm" J Infect Dis 217:82–92. doi: 10.1093/infdis/jix524 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Naas T, Dortet L, Iorga BI. 2016. Structural and functional aspects of class A carbapenemases. Curr Drug Targets 17:1006–1028. doi: 10.2174/1389450117666160310144501 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Villegas MV, Lolans K, Correa A, Kattan JN, Lopez JA, Quinn JP, Colombian Nosocomial Resistance Study G. 2007. First identification of Pseudomonas aeruginosa isolates producing a KPC-type carbapenem-hydrolyzing beta-lactamase . Antimicrob Agents Chemother 51:1553–1555. doi: 10.1128/AAC.01405-06 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Bianco G, Boattini M, Comini S, Casale R, Iannaccone M, Cavallo R, Costa C. 2022. Occurrence of multi-carbapenemases producers among carbapenemase-producing Enterobacterales and in vitro activity of combinations including cefiderocol, ceftazidime-avibactam, meropenem-vaborbactam, and aztreonam in the COVID-19 era. Eur J Clin Microbiol Infect Dis 41:573–580. doi: 10.1007/s10096-022-04408-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Saavedra SY, Bernal JF, Montilla-Escudero E, Arévalo SA, Prada DA, Valencia MF, Moreno J, Hidalgo AM, García-Vega ÁS, Abrudan M, Argimón S, Kekre M, Underwood A, Aanensen DM, Duarte C, Donado-Godoy P, NIHR Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance . 2021. Complexity of genomic epidemiology of carbapenem-resistant Klebsiella pneumoniae isolates in Colombia urges the reinforcement of whole genome sequencing-based surveillance programs. Clin Infect Dis 73:S290–S299. doi: 10.1093/cid/ciab777 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Lasko MJ, Nicolau DP. 2020. Carbapenem-resistant Enterobacterales: considerations for treatment in the era of new antimicrobials and evolving enzymology. Curr Infect Dis Rep 22:6. doi: 10.1007/s11908-020-0716-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. García-Betancur JC, Appel TM, Esparza G, Gales AC, Levy-Hara G, Cornistein W, Vega S, Nuñez D, Cuellar L, Bavestrello L, Castañeda-Méndez PF, Villalobos-Vindas JM, Villegas MV. 2021. Update on the epidemiology of carbapenemases in Latin America and the Caribbean. Expert Rev Anti Infect Ther 19:197–213. doi: 10.1080/14787210.2020.1813023 [DOI] [PubMed] [Google Scholar]
- 15. Kelly AM, Mathema B, Larson EL. 2017. Carbapenem-resistant enterobacteriaceae in the community: a scoping review. Int J Antimicrob Agents 50:127–134. doi: 10.1016/j.ijantimicag.2017.03.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Stewardson AJ, Marimuthu K, Sengupta S, Allignol A, El-Bouseary M, Carvalho MJ, Hassan B, Delgado-Ramirez MA, Arora A, Bagga R, et al. 2019. Effect of carbapenem resistance on outcomes of bloodstream infection caused by enterobacteriaceae in low-income and middle-income countries (PANORAMA): a multinational prospective cohort study. Lancet Infect Dis 19:601–610. doi: 10.1016/S1473-3099(18)30792-8 [DOI] [PubMed] [Google Scholar]
- 17. Avershina E, Shapovalova V, Shipulin G. 2021. Fighting antibiotic resistance in hospital-acquired infections: current state and emerging technologies in disease prevention, diagnostics and therapy. Front Microbiol 12:707330. doi: 10.3389/fmicb.2021.707330 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Shrestha R, Luterbach CL, Dai W, Komarow L, Earley M, Weston G, Herc E, Jacob JT, Salata R, Wong D, Anderson D, Rydell KB, Arias CA, Chen L, van Duin D, MDRO Investigators . 2022. Characteristics of community-acquired carbapenem-resistant Enterobacterales. J Antimicrob Chemother 77:2763–2771. doi: 10.1093/jac/dkac239 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Logan LK, Weinstein RA. 2017. The epidemiology of carbapenem-resistant enterobacteriaceae: the impact and evolution of a global menace. J Infect Dis 215:S28–S36. doi: 10.1093/infdis/jiw282 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Garg A, Garg J, Kumar S, Bhattacharya A, Agarwal S, Upadhyay GC. 2019. Molecular epidemiology & therapeutic options of carbapenem-resistant Gram-negative bacteria. Indian J Med Res 149:285–289. doi: 10.4103/ijmr.IJMR_36_18 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Brink AJ. 2019. Epidemiology of carbapenem-resistant gram-negative infections globally. Curr Opin Infect Dis 32:609–616. doi: 10.1097/QCO.0000000000000608 [DOI] [PubMed] [Google Scholar]
- 22. Babiker A, Clarke LG, Saul M, Gealey JA, Clancy CJ, Nguyen MH, Shields RK. 2021. Changing epidemiology and decreased mortality associated with carbapenem-resistant Gram-negative bacteria, 2000-2017. Clin Infect Dis 73:e4521–e4530. doi: 10.1093/cid/ciaa1464 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Vanegas JM, Parra OL, Jiménez JN. 2016. Molecular epidemiology of carbapenem resistant gram-negative bacilli from infected pediatric population in tertiary - care hospitals in Medellin, Colombia: an increasing problem. BMC Infect Dis 16:463. doi: 10.1186/s12879-016-1805-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Annavajhala MK, Gomez-Simmonds A, Uhlemann AC. 2019. Multidrug-resistant Enterobacter cloacae complex emerging as a global, diversifying threat. Front Microbiol 10:44. doi: 10.3389/fmicb.2019.00044 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Cai B, Echols R, Magee G, Arjona Ferreira JC, Morgan G, Ariyasu M, Sawada T, Nagata TD. 2017. Prevalence of Ccarbapenem-resistant Gram-negative infections in the United States predominated by Acinetobacter baumannii and Pseudomonas aeruginosa. Open Forum Infect Dis 4:ofx176. doi: 10.1093/ofid/ofx176 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. van Duin D, Arias CA, Komarow L, Chen L, Hanson BM, Weston G, Cober E, Garner OB, Jacob JT, Satlin MJ, et al. 2020. Molecular and clinical epidemiology of carbapenem-resistant Enterobacterales in the USA (CRACKLE-2): a prospective cohort study. The Lancet Infectious Diseases 20:731–741. doi: 10.1016/S1473-3099(19)30755-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Hansen GT. 2021. Continuous evolution: perspective on the epidemiology of carbapenemase resistance among Enterobacterales and other Gram-negative bacteria. Infect Dis Ther 10:75–92. doi: 10.1007/s40121-020-00395-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Lopez JA, Correa A, Navon-Venezia S, Correa AL, Torres JA, Briceño DF, Montealegre MC, Quinn JP, Carmeli Y, Villegas MV. 2011. Intercontinental spread from Israel to Colombia of a KPC-3-producing Klebsiella pneumoniae strain. Clin Microbiol Infect 17:52–56. doi: 10.1111/j.1469-0691.2010.03209.x [DOI] [PubMed] [Google Scholar]
- 29. Ocampo Ana María, Vargas CA, Sierra PM, Cienfuegos AV, Jiménez JN. 2015. Molecular characterization of an outbreak of carbapenem-resistant Klebsiella pneumoniae in a tertiary care hospital in Medellin, Colombia. Biomedica 35:496–504. doi: 10.7705/biomedica.v35i4.2610 [DOI] [PubMed] [Google Scholar]
- 30. Ocampo Ana M, Chen L, Cienfuegos AV, Roncancio G, Chavda KD, Kreiswirth BN, Jiménez JN. 2016. A two-year surveillance in five Colombian tertiary care hospitals reveals high frequency of non-CG258 clones of carbapenem-resistant Klebsiella pneumoniae with distinct clinical characteristics. Antimicrob Agents Chemother 60:332–342. doi: 10.1128/AAC.01775-15 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Papagiannitsis CC, Verra A, Galani V, Xitsas S, Bitar I, Hrabak J, Petinaki E. 2020. Unravelling the features of success of VIM-producing ST111 and ST235 Pseudomonas aeruginosa in a Greek hospital. Microorganisms 8:1884. doi: 10.3390/microorganisms8121884 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Pirzadian J, Persoon MC, Severin JA, Klaassen CHW, de Greeff SC, Mennen MG, Schoffelen AF, Wielders CCH, Witteveen S, van Santen-Verheuvel M, Schouls LM, Vos MC, Dutch CPE surveillance Study Group . 2021. National surveillance pilot study unveils a multicenter, clonal outbreak of VIM-2-producing Pseudomonas aeruginosa ST111 in the Netherlands between 2015 and 2017. Sci Rep 11:21015. doi: 10.1038/s41598-021-00205-w [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Urbanowicz P, Izdebski R, Baraniak A, Żabicka D, Hryniewicz W, Gniadkowski M. 2021. Molecular and genomic epidemiology of VIM/IMP-like metallo-beta-lactamase-producing Pseudomonas aeruginosa genotypes in Poland. J Antimicrob Chemother 76:2273–2284. doi: 10.1093/jac/dkab188 [DOI] [PubMed] [Google Scholar]
- 34. Ochoa SA, Cruz-Córdova A, Mancilla-Rojano J, Escalona-Venegas G, Esteban-Kenel V, Franco-Hernández I, Parra-Ortega I, Arellano-Galindo J, Hernández-Castro R, Perez-López CF, De la Rosa-Zamboni D, Xicohtencatl-Cortes J. 2020. Control of methicillin-resistant Staphylococcus aureus strains associated with a hospital outbreak involving contamination from anesthesia equipment using UV-C. Front Microbiol 11:600093. doi: 10.3389/fmicb.2020.600093 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Loftus RW, Dexter F, Robinson ADM. 2018. High-risk Staphylococcus aureus transmission in the operating room: a call for widespread improvements in perioperative hand hygiene and patient decolonization practices. Am J Infect Control 46:1134–1141. doi: 10.1016/j.ajic.2018.04.211 [DOI] [PubMed] [Google Scholar]
- 36. Carling PC. 2018. Wastewater drains: epidemiology and interventions in 23 carbapenem-resistant organism outbreaks. Infect Control Hosp Epidemiol 39:972–979. doi: 10.1017/ice.2018.138 [DOI] [PubMed] [Google Scholar]
- 37. Martin A, Fahrbach K, Zhao Q, Lodise T. 2018. Association between carbapenem resistance and mortality among adult, hospitalized patients with serious infections due to enterobacteriaceae: results of a systematic literature review and meta-analysis. Open Forum Infect Dis 5:ofy150. doi: 10.1093/ofid/ofy150 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Karaiskos I, Lagou S, Pontikis K, Rapti V, Poulakou G. 2019. The "old" and the "new" antibiotics for MDR Gram-negative pathogens: for whom, when, and how. Front Public Health 7:151. doi: 10.3389/fpubh.2019.00151 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Popejoy MW, Paterson DL, Cloutier D, Huntington JA, Miller B, Bliss CA, Steenbergen JN, Hershberger E, Umeh O, Kaye KS. 2017. Efficacy of ceftolozane/tazobactam against urinary tract and intra-abdominal infections caused by ESBL-producing Escherichia coli and Klebsiella pneumoniae: a pooled analysis of phase 3 clinical trials. J Antimicrob Chemother 72:268–272. doi: 10.1093/jac/dkw374 [DOI] [PubMed] [Google Scholar]
- 40. Alatoom A, Elsayed H, Lawlor K, AbdelWareth L, El-Lababidi R, Cardona L, Mooty M, Bonilla MF, Nusair A, Mirza I. 2017. Comparison of antimicrobial activity between ceftolozane-tazobactam and ceftazidime-avibactam against multidrug-resistant isolates of Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Int J Infect Dis 62:39–43. doi: 10.1016/j.ijid.2017.06.007 [DOI] [PubMed] [Google Scholar]
- 41. Sucher AJ, Chahine EB, Cogan P, Fete M. 2015. Ceftolozane/tazobactam: a new cephalosporin and beta-lactamase inhibitor combination. Ann Pharmacother 49:1046–1056. doi: 10.1177/1060028015593293 [DOI] [PubMed] [Google Scholar]
- 42. Bassetti M, Peghin M. 2020. How to manage KPC infections. Ther Adv Infect Dis 7:2049936120912049. doi: 10.1177/2049936120912049 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43. Xu M, Zhao J, Xu L, Yang Q, Xu H, Kong H, Zhou J, Fu Y. 2022. Emergence of transferable ceftazidime-avibactam resistance in KPC-producing Klebsiella pneumoniae due to a novel CMY AmpC beta-lactamase in China. Clin Microbiol Infect 28:136. doi: 10.1016/j.cmi.2021.05.026 [DOI] [PubMed] [Google Scholar]
- 44. Nukaga M, Papp-Wallace KM, Hoshino T, Lefurgy ST, Bethel CR, Barnes MD, Zeiser ET, Johnson JK, Bonomo RA. 2018. Probing the mechanism of inactivation of the FOX-4 cephamycinase by avibactam. Antimicrob Agents Chemother 62:e02371-17. doi: 10.1128/AAC.02371-17 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45. Jeon JH, Hong MK, Lee JH, Lee JJ, Park KS, Karim AM, Jo JY, Kim JH, Ko KS, Kang LW, Lee SH. 2014. Structure of ADC-68, a novel carbapenem-hydrolyzing class C extended-spectrum beta-lactamase isolated from Acinetobacter baumannii. Acta Crystallogr D Biol Crystallogr 70:2924–2936. doi: 10.1107/S1399004714019543 [DOI] [PubMed] [Google Scholar]
- 46. Shields RK, Nguyen MH, Chen L, Press EG, Potoski BA, Marini RV, Doi Y, Kreiswirth BN, Clancy CJ. 2017. Ceftazidime-avibactam is superior to other treatment regimens against carbapenem-resistant Klebsiella pneumoniae bacteremia. Antimicrob Agents Chemother 61:e00883-17. doi: 10.1128/AAC.00883-17 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Soriano A, Carmeli Y, Omrani AS, Moore LSP, Tawadrous M, Irani P. 2021. Ceftazidime-avibactam for the treatment of serious Gram-negative infections with limited treatment options: a systematic literature review. Infect Dis Ther 10:1989–2034. doi: 10.1007/s40121-021-00507-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Wunderink RG, Giamarellos-Bourboulis EJ, Rahav G, Mathers AJ, Bassetti M, Vazquez J, Cornely OA, Solomkin J, Bhowmick T, Bishara J, Daikos GL, Felton T, Furst MJL, Kwak EJ, Menichetti F, Oren I, Alexander EL, Griffith D, Lomovskaya O, Loutit J, Zhang S, Dudley MN, Kaye KS. 2018. Effect and safety of meropenem-vborbactam versus best-available therapy in patients with carbapenem-resistant enterobacteriaceae infections: the TANGO II randomized clinical trial. Infect Dis Ther 7:439–455. doi: 10.1007/s40121-018-0214-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49. Arum N, Ghafur A, Kazi M, Rao R, Rodrigues C, Ratnamani MS, J. P, Alaparthi S, Gnanasoundari P, Premachandran KP, Thirunarayanan MA. 2022. Prevalence of faecal carriage of carbapenemase producing enterobacteriaceae in healthy Indian subjects from the community. Indian Journal of Medical Microbiology 40:374–377. doi: 10.1016/j.ijmmb.2022.05.010 [DOI] [PubMed] [Google Scholar]
- 50. Brkić S, Božić DD, Stojanović N, Bulbuk D, Ćirković I, Mihajlo Jovanović . 2023. Carbapenemase-producing Klebsiella pneumoniae in community settings: a cross-sectional study in Belgrade, Serbia. Future Microbiol 18:389–397. doi: 10.2217/fmb-2022-0201 [DOI] [PubMed] [Google Scholar]
- 51. Vincent J-L, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, Reinhart CK, Suter PM, Thijs LG. 1996. The SOFA (sepsis-related organ failure assessment) score to describe organ dysfunction/failure. On behalf of the working group on sepsis-related problems of the European society of Iintensive care medicine.. Intensive Care Med 22:707–710. doi: 10.1007/BF01709751 [DOI] [PubMed] [Google Scholar]
- 52. Knaus WA, Draper EA, Wagner DP, Zimmerman JE. 1985. APACHE II: a severity of disease classification system. Crit Care Med 13:818–829. doi: 10.1128/spectrum.01080-21 [DOI] [PubMed] [Google Scholar]
- 53. Josa M D, Leal R, Rojas J, Torres M I, Cortés-Muñoz F, Esparza G, Reyes LF. 2022. Comparative evaluation of phenotypic synergy tests versus RESIST-4 O.K.N.V. and NG test carba 5 lateral flow immunoassays for the detection and differentiation of carbapenemases in Enterobacterales and Pseudomonas aeruginosa. Microbiol Spectr 10:e0108021. doi: 10.1128/spectrum.01080-21 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Sample collection manual for Shaio Clinic Foundation.
Sample collection manual for Clinica Universidad de La Sabana.
Supplemental text, tables, and figures.
Table S2.
Data Availability Statement
All the genomes are located in the following repository: PRJNA937403. All the data can be found in the supplemental material and Tables S1 to S6.