Mortality Associated with Bacteremia Caused by Carbapenem-Resistant Klebsiella pneumoniae : The Crucial Role of Therapy in Clinical Outcome

Abstract

This study analyzed factors associated with mortality in Klebsiella pneumoniae bacteremia, particularly the role of combination therapy. Medical records of 109 patients (2012–2018) were reviewed to assess risk factors for carbapenem-resistant K. pneumoniae (CRKP) bacteremia. The total 30-day mortality was 41.3%. Excess mortality was calculated for the following groups: multidrug-resistant (MDR) K. pneumoniae, CRKP, and carbapenem-susceptible K. pneumoniae. Of 109 isolates, 64.2% were CRKP. All patients received empirical therapy; 20.2% received monotherapy, while the remainder received combination therapy, which was linked to longer intensive care unit stays and higher primary bacteremia rates. Overall, inappropriate empirical treatment occurred in 62.4% of patients. Both monotherapy (40.9%) and combination therapy (36.8%) groups showed similarly high rates of inappropriate treatment. Hemodialysis catheter use was a risk factor (p = 0.0238). Third- and fourth-generation cephalosporins had the highest mortality (45.9%), whereas MDR strains showed the lowest (4.51%). Although combination therapy alone did not significantly reduce mortality, Kaplan–Meier analysis revealed no survival benefit. However, monotherapy increased mortality, suggesting that combination therapy may still play a role in mitigating outcomes. Carbapenem resistance in K. pneumoniae bacteremia remains alarmingly high and correlates with excess mortality and inappropriate empirical treatment.

Keywords

carbapenem-resistant MDR mortality

Introduction

Klebsiella pneumoniae is considered one of the main causes of hospital infections and is mentioned by the World Health Organization as a priority antimicrobial-resistant pathogen that requires new control strategies.^1,2 The emergence and global spread of carbapenem-resistant K. pneumoniae (CRKP) have posed a major threat to public health, particularly in low- and middle-income countries such as Brazil, due to the difficulties in treating these infections and the high associated mortality.^3–5

In a specific region of Brazil, the estimated incidence rate of carbapenem-resistant K. pneumoniae (CRKP) bacteremia increased from 43.4% to 56.3%.^6,7 Furthermore, the reported mortality rate of CRKP has varied widely in most studies, ranging from 53.1% to 83%.^8,9 Therefore, accurate diagnosis and management of bloodstream infections (BSIs), along with the application of appropriate antimicrobial therapy, can significantly improve patient survival rates.

It is important to emphasize that surveillance studies should be continuously conducted to better understand the epidemiology of these pathogens at the regional level. In this context, the increasing prevalence of CRKP complicates the empirical treatment of these infections, and health care institutions must adapt prevention and control measures to each region.

Objectives

We aimed to identify the variables associated with mortality in K. pneumoniae bacteremia, with particular attention to the impact of targeted combination therapy.

Methods

Study design and data collection

This retrospective cohort study analyzed Bloodstream Infection (BSI) caused by K. pneumoniae in adult patients admitted to the intensive care unit (ICU) of a teaching referral hospital in Brazil between 2011 and 2019. Data for this study were obtained from the bacteremia registry of the Microbiology Laboratory of the Hospital. Only patients hospitalized in the unit for at least 48 hours before the bacteremia diagnosis were eligible. This study aimed to identify predictors of mortality and to evaluate the clinical consequences of resistance and the impact of inappropriate therapy. The primary outcome was 30-day in-hospital mortality. Information collected from hospital records included demographics and clinical characteristics (illness severity, comorbidities), use of invasive devices, length of total hospital stay, length of ICU stay, and invasive procedures. The medical history of the patient’s underlying conditions, such as heart failure, nephropathy, malignancy, diabetes mellitus, chronic lung disease, and vascular disease, was also included. We also assessed the sources of bacteremia, treatment regimes, and instances of inappropriate antimicrobial treatment.

Identification and antimicrobial susceptibility

Microbial identification and antimicrobial susceptibility testing were performed at the hospital using the Vitek-2 system (bioMérieux, Marcy l’Etoile, France). Antibiotics tested included aminoglycosides (gentamicin, amikacin), carbapenems (imipenem, meropenem), cephalosporins (cefepime), fluoroquinolones (ciprofloxacin), and β-lactamase inhibitors (piperacillin-tazobactam). Susceptibilities were determined according to the standards of the Clinical and Laboratory Standards Institute (CLSI 2011–2019).

Definitions

Bacteremia is defined as the presence of viable microorganisms in the bloodstream, confirmed by a positive blood culture.¹⁰ It is considered acquired in unit care intensive if the infection develops more than 48 hours after hospital admission and there is no clinical evidence of infection at the time of admission.¹⁰ The episodes were classified into three categories according to the causative pathogens: carbapenem-susceptible K. pneumoniae (CSKP), CRKP, and multidrug-resistant (MDR) K. pneumoniae. CRKP, as defined, included all applicable K. pneumoniae with a result of intermediate (I) or resistant (R) to imipenem or meropenem unless otherwise noted.¹¹

Bacteremia is classified as primary when a recognized pathogen is isolated from one or more blood cultures and is not linked to an infection at another site. Secondary bacteremia occurs when a recognized pathogen isolated from one or more blood cultures is associated with a known focus of infection (pneumonia, urinary tract infection, catheter).¹⁰

MDR is defined based on antibiotic susceptibility testing. To qualify as MDR, the organism must demonstrate nonsusceptibility (I or R) to at least one agent within a given antibiotic class, thereby establishing nonsusceptibility to that entire class. This condition must be met for a minimum of three specified antibiotic classes.¹¹

Antimicrobial therapy was classified as empirical when initiated before the availability of antimicrobial susceptibility testing results (typically 48–72 hours after blood culture collection) and as definitive once susceptibility data were available. Empirical therapy was deemed appropriate if all the following criteria were satisfied: administration of at least one antimicrobial agent according to clinical guidelines, in vitro susceptibility of the isolated pathogen to the administered agent, and initiation of the first dose within 24 hours of blood culture collection. Inappropriate empirical therapy was assigned for any empirical regimen that failed to meet one or more of the above criteria.¹⁰

Excess mortality is the most frequently chosen measure to estimate deaths attributable to a specific cause.¹²

Statistical analysis

Student t test was used to compare continuous variables, and χ² or Fisher’s exact test was used to compare categorical variables. Survival curves were constructed using the Kaplan–Meier method. The log-rank test was used for comparisons between patients receiving inappropriate and appropriate therapy, different sources of infection, and different therapy groups (monotherapy and combination therapy). All p values were two-tailed, and p ≤ 0.05 was considered statistically significant. Analyses were carried out using the GraphPad Prism software package (La Jolla, CA, USA).

The excess number of deaths associated with BSIs caused by MDR K. pneumoniae, CRKP, and CSKP was then calculated for each group using an equation derived from Bender and Blettner (Equation 1; aOR, adjusted odds ratio; P₀, p value).

Excess o f death = \frac{# BSI \times P_{0} \times (aOR - 1) \times (1 - P_{0})}{aOR \times P_{0} + (1 - P_{0})}

(1)

Results

Of the 109 K. pneumoniae isolates, 64.2% were resistant to carbapenems. All patients received empirical therapy with anti-Gram-negative antibiotics, administered at currently recommended doses, either as monotherapy or in combination. Based on the antimicrobial susceptibility test and the initiation of treatment within 24 hours of diagnosis, empirical therapy was classified as inappropriate in 62.4% of the total patients. Specifically, inappropriate therapy rates were 40.9% for patients receiving monotherapy and 36.8% for those on combination therapy.

The definitive treatment regimen was determined by the responsible physician based on the results of the antimicrobial susceptibility test. Monotherapy was administered to 20.2% of patients. A comparison between patients receiving monotherapy and those receiving combination therapy revealed that the latter group had a longer ICU stay and a higher frequency of primary bacteremia. The 30-day mortality rate was high at 41.3%, with rates of 27.3% in the monotherapy group and 44.8% in the combination therapy group, according to Table 1. Regarding the underlying conditions, most patients presented with at least one, such as heart failure (45.0%), diabetes mellitus (17.4%), and nephropathy (15.6%). Primary bacteremia and lung infection were the most frequent sources of infection (51.4% and 33.0%, respectively).

Table 1.

Characteristics of Patients with Bacteremia Due to Klebsiella pneumoniae Receiving Monotherapy or Combination Therapy

Variable	TotalN = 109	Monotherapy/Without therapy^apatients N = 22 (%)	Combination therapy patients N = 87 (%)	Univariate analysis
Variable	TotalN = 109	Monotherapy/Without therapy^apatients N = 22 (%)	Combination therapy patients N = 87 (%)	p Value	OR (95% CI)
Age (years), mean ± SD	53.0 ± 19.3	56.2 ± 16.2	52.2 ± 20.0	0.3888^b	—
Length of hospitalization until ICU admission (days), median (IQR)	2.0 (1.0–6.0)	1 (0.0–3.2)	2 (1.0 ± 7.0)	0.1903^c	—
Length of hospitalization ICU, median (IQR)	16.0 (10.0–22.0)	14.5 (8.2–20.2)	16.0 (11.0–23.0)	0.4979^c	—
Length of hospitalization (days), median (IQR)	20.0 (14.0–30.0)	16.0 (10.2–34.2)	22.0 (14.0–30.0)	0.1881^c	—
Comorbid condition
Heart failure	45.0 (41.3)	13.0 (59.1)	32.0 (36.8)	0.0884^d	2.483 (0.9782–6.101)
Nephropathy	17.0 (15.6)	4.0 (18.2)	13.0 (14.9)	0.7448^d	1.265 (0.4105–4.145)
Malignancy	13.0 (11.2)	1.0 (4.5)	12.0 (13.8)	0.4598^d	0.2976 (0.02660–1.888)
Diabetes mellitus	19.0 (17.4)	3.0 (13.6)	16.0 (18.4)	<0.0001^d	36.05 (9.964–121.8)
Chronic lung disease	7.0 (6.4)	1.0 (4.5)	6.0 (6.9)	0.7590^d	0.7007 (0.2003–2.463)
Vascular disease	11.0 (10.1)	1.0 (4.5)	10.0 (11.5)	0.4567^d	0.3667 (0.03231–2.479)
Charlson comorbidity index ≥3	26.0 (23.9)	5.0 (22.7)	21.0 (24.1)	>0.9999^d	0.9244 (0.3410–2.813)
Admission ward:
Medical	46.0 (42.2)	9.0 (40.9)	37.0 (42.5)	>0.9999^d	0.9356 (0.3831–2.352)
Surgical	22.0 (20.2)	4.0 (18.2)	18.0 (20.7)	>0.9999^d	0.8519 (0.2844–2.557)
Traumatology	41.0 (37.6)	9.0 (40.9)	32.0 (36.8)	0.8068^d	1.190 (0.4829–3.022)
Source of infection
Primary bacteremia	56.0 (51.4)	13.0 (59.1)	43.0 (49.4)	0.4792^d	1.478 (0.5903–3.593)
Lung infection	36.0 (33.0)	6.0 (27.3)	30.0 (34.5)	0.6172^d	0.125 (0.2509–1.941)
Urinary tract infection	17.0 (15.6)	3.0 (13.6)	14.0 (16.1)	>0.9999^d	0.8233 (0.2328–3.003)
Mortality in 30 days	45.0 (41.3)	6.0 (27.3)	39.0 (44.8)	0.1537^d	0.4615 (0.1650–1.234)

Three patients without therapy are included in this group, and one death occurred within this subgroup.

^bStudent t test.

^cMann–Whitney test.

^dFisher’s exact test.

ICU, intensive care unit; IQR, interquartile range; SD, standard deviation.

The association between different treatment regimens and crude 30-day mortality is shown in Table 2. Mortality was particularly notable in patients treated with third- and fourth-generation cephalosporins in monotherapy, with a rate of 28.6% for those receiving carbapenems. Combination therapy, on its own, was not associated with a reduction in mortality, with rates exceeding 45.6%.

Table 2.

Outcome of Patients with Bacteremia Due to Klebsiella pneumoniae according to Treatment Regimen

Treatment regimen	Patients treated	Patients dead	Mortality (%)
Monotherapy	19	5	26.3
Other beta-lactams	7	2	28.6
Carbapenems	4	1	25.0
Fluoroquinolones	1	0	0.0
Glycopeptides	1	0	0.0
Cephalosporins thirdª and fourthª generation	6	2	33.3
Without therapy	3	1	33.3
Combination therapy	87	40	46.0
Quadruple therapy	8	4	50.0
Triple therapy	38	18	47.4
Bi-therapy	41	18	43.9

The bold values are used to differentiate between the three comparison groups: monotherapy, no therapy, and combination therapy. Because the monotherapy and combination therapy groups have sub groups.

The main characteristics of the survivor and nonsurvivor subgroups are presented in Table 3. Univariate analysis identified the use of a hemodialysis catheter as the main risk factor (p = 0.0238). Compared with survivors, nonsurvivors were older, more frequently admitted to the ICU, more likely to have comorbidities, more commonly had primary bacteremia, and less frequently had urinary tract infection as the source of infection. They also less frequently received the appropriate antibiotic therapy within 24 hours of infection onset.

Table 3.

Univariate Analysis of Variables Associated with 30-Day Mortality in Patients with Bacteremia Due to Klebsiella pneumoniae

Variable	30-day mortality		Univariate analysis
Variable	SurvivorN = 64 (%)	NonsurvivorN = 45 (%)	p Value	OR (95% CI)
Age (years) median (IQR)	53.0 (35.0–61.0)	58.0 (44.0–71.5)	0.0625	—
Length of hospitalization, median (IQR)	20.5 (14.0–34.8)	18.0 (12.5–29.0)	0.4012	—
Length of hospitalization in ICU, median (IQR)	15.0 (10.3–22.8)	16.0 (9.5–22.0)	0.7003	—
Charlson comorbidity index ≥3	15.0 (23.4)	11.0 (24.4)	0.8226	0.8916 (0.3553–2.156)
Source of bacteremia
Primary bacteremia	34.0 (53.1)	22.0 (48.9)	0.7004	1.185 (0.5544–2.554)
Lung	22.0 (34.4)	14.0 (31.1)	0.6832	1.272 (0.5542–2.858)
Urinary tract	8.0 (12.5)	9.0 (20.0)	0.2989	0.5714 (0.1946–1.582)
Invasive procedures
Mechanical ventilation	8.0 (12.5)	8.0 (17.8)	0.5837	0.6607 (0.2176–2.011)
Hemodialysis catheter	15.0 (23.4)	20.0 (44.4)	0.0238	0.3827 (0.1660–0.9113)
Bladder catheter	57.0 (89.1)	39.0 (86.7)	0.7687	1.253 (0.3707–3.743)
Comorbidities
Malignancy	4.0 (6.2)	5.0 (11.1)	0.4840	0.5333 (0.1569–1.950)
Nephropathy	9.0 (9.4)	8.0 (17.8)	0.6038	0.7568 (0.2744–2.225)
Diabetes mellitus	11.0 (17.2)	8.0 (17.8)	>0.9999	0.9599 (0.3374–2.678)
Infection for K. pneumoniae MDR	42.0 (65.6)	28.0 (62.2)	0.8394	1.159 (0.5461–2.628)
Carbapenem-resistant K. pneumoniae	38.0 (59.4)	32.0 (71.1)	0.2296	0.5938 (0.2559–1.361)
Target treatment
Monotherapy/Without therapy^a	16.0 (25.0)	6.0 (13.3)	0.1537	2.167 (0.8102–6.060)
Combination therapy	48.0 (75.0)	39.0 (86.7)	0.1537	0.4615 (0.1650–1.234)
Inappropriate empirical therapy	40.0 (62.5)	28.0 (62.2)	>0.9999	1.012 (0.4778–2.253)
Therapy included carbapenem	36.0 (56.2)	31.0 (68.9)	0.2313	0.5806 (0.2606–1.300)

There are three patients without therapy in this group.

CI, confidence interval; MDR, multidrug resistance; OR, odds ratio.

The Kaplan–Meier curves for targeted treatment with monotherapy or with combination therapy are presented in Figure 1A, which shows that combination therapy by itself was not associated with decreased mortality. Mortality is higher in the monotherapy group for infections caused by MDR K. pneumoniae (Fig. 1B). The Kaplan–Meier curves for targeted treatment with monotherapy or combination therapy in patients with and without appropriate empirical therapy are presented in Figure 1C, which depicts that patients receiving appropriate therapy had lower mortality than those receiving inappropriate antibiotic therapy.

FIG. 1.

Kaplan–Meier curves for the survival of patients with bacteremia caused by Klebsiella pneumoniae: (A) Groups of therapy, (B) Multidrug resistance within therapy groups, (C) Appropriate or inappropriate empirical therapy, (D) Carbapenem resistance profile.

The lowest attributable mortality was found in patients with MDR K. pneumoniae (4.51%), while the highest was found in those with CRKP (12.95%) (Fig. 2).

FIG. 2.

Study timeline of patient events, concerning hospital admission, exposures, and outcomes. CRKP, carbapenem-resistant Klebsiella pneumoniae; CSKP, carbapenem-sensitive K. pneumoniae.

Discussion

Our study emphasizes the correlation between the CRKP and CSKP infections and patient outcomes in BSI, providing important insights into both monotherapy and combination therapy for these infections. Over the past 10 years, several observational studies and meta-analyses have highlighted higher mortality in patients with CRKP BSI compared with those with CSKP BSI.^3,5,9,13

The increasing prevalence of severe CRKP infections, with high mortality rates, highlights the urgent need for effective treatments and is a significant health care concern, especially in low- and middle-income countries such as Brazil. The literature supports this finding, highlighting the high prevalence of this phenotype in Brazilian hospitals, with rates ranging from 63% to 96%.^6,14,15

The overall mortality in our patient cohort was high (42.2%), similar to rates observed in other studies,^5,6,8,9 likely reflecting the severity of patients with BSI. Survival analysis revealed that 62.2% of deaths occurred within 30 days of KP-BSI onset, and these patients had received inappropriate empirical therapy.

In our cohort, timely and appropriate antibiotic therapy was possibly associated with a reduced mortality risk. The interval between the onset of BSI and the initiation of appropriate antibiotic treatment has been linked to better outcomes in patients with CRKP infections.^2,10,12 It is worth noting that while we assessed the impact of inappropriate antimicrobial therapy, we did not investigate the effects of specific antibiotic regimens on patient outcomes. Thus, further studies are needed to explore the outcomes of patients receiving different empirical antibiotics with demonstrated in vitro activity.

In this way, the 30-day crude mortality rate among patients with CRKP BSI was 45.9%, a figure similar to those reported in other countries and considerably higher than the 33.3% observed in patients with CSKP.^9,16 In addition, we estimated the attributable mortality for three types of K. pneumoniae isolates (MDR K. pneumoniae, CRKP, and CSKP) in a group of patients with bacteremia. Attributable mortality ranged from 12.95% in CRKP patients to an unexpected −10.43% in those with CSKP bacteremia, suggesting that treatment is more efficient in these infections.

Despite the absence of robust multivariate modeling, the strong signal from our univariate analysis remains crucial. It clearly identifies the group CRKP as a critical, high-risk factor for early mortality and directly reflects the grim reality of daily clinical practice in our high-resistance setting. In this real-world context, the clinical decision to employ combination therapy is typically reserved for patients with the highest comorbidity burden and most severe presentations, precisely to mitigate the risk of death.¹⁷ The lack of statistical significance for combination therapy is thus largely a function of the selection bias (target treatment) and a reflection that patients’ outcomes are ultimately highly dependent on the complex interplay between the extreme virulence of K. pneumoniae and the individual’s physiological response to the severe infection and the subsequent rigorous treatment regimen.

Our study was conducted in Brazil, a country with a high incidence of CRKP. Regional data on CRKP are of great importance as they provide valuable information about these strains, allowing for a deeper understanding of the regional impact of these infections.^4,5,9 Thus, our data may reflect what occurs in countries with similar characteristics, but they cannot be generalized to countries with a low prevalence of resistant K. pneumoniae. However, the Brazilian experience is crucial for other countries to understand the impact of this phenotype on mortality and clinical practice.

Although no direct impact on mortality was observed in some specific analyses, the presence of antibiotic-resistant pathogens increases the disease burden by replacing their antibiotic-susceptible counterparts and raising the overall number of infections. These infections can increase mortality in critically ill patients with comorbidities and generate additional costs due to prolonged health care exposure and the use of expensive antimicrobials, which may further select for antimicrobial-resistant pathogens. Therefore, early recognition and the implementation of effective control measures are essential to minimize the impact and mortality risk associated with CRKP BSI.

Conclusion

Bacteremia caused by CRKP is clearly associated with high mortality rates, including excess mortality, representing a significant threat to critically ill patients. Although the direct impact of inappropriate empirical therapy on mortality was not statistically significant (p = 0.1058), it was associated with a higher early death rate compared with patients who received appropriate treatment.

Authors’ Contributions

C.P.R. and E.R.d.A.-J. drafted the article and conducted molecular and data analysis. V.L.D. isolated and provided the strains with routine phenotypical data. R.M.R. provided essential supervision, validation, review, and editing.

Footnotes

Acknowledgments

The authors thank the management of the participating hospital for the consent and collaboration, as well as the staff members for their contributions to this study.

Ethical Statement

The study was approved by the Research Ethics Committee of the Federal University of Uberlandia, Minas Gerais, and ethical approval was granted under protocol number 239/11. Verbal and written consent were obtained from each hospital representative and from all individual participants in the study. At all stages of the study, the principles of confidentiality and nonmaleficence were applied, and the identities of hospitals and patients were kept confidential.

Disclosure Statement

No competing financial interests exist.

Funding Information

This work was supported by public agencies dedicated to the promotion of scientific and technological research: Minas Gerais State Agency for Research and Development (FAPEMIG), Decit/SECTICS/MS—CNPq, CAPES.

References

Falcone

, Tiseo

, Carbonara

, Advancing knowLedge on Antimicrobial Resistant Infections Collaboration Network (ALARICO Network)

et al.. Mortality attributable to bloodstream infections caused by different carbapenem-resistant gram-negative bacilli: Results from a nationwide study in Italy (AfromCO network). Clin Infect Dis 2023;76(12):2059–2069; doi: 10.1093/cid/ciad100

2. Wang

, Zeng

, Li

, et al. Mortality associated with carbapenem resistance in Klebsiella pneumoniae bloodstream infection: A propensity score-matched study. Infect Control Hosp Epidemiol 2024;45(7):839–846; doi: 10.1017/ice.2024.21

3. Wilhelm

, Antochevis

, Magagnin

, et al. Susceptibility evaluation of novel beta-lactam/beta-lactamase inhibitor combinations against carbapenem-resistant Klebsiella pneumoniae from bloodstream infections in hospitalized patients in Brazil. J Glob Antimicrob Resist 2024;38:247–251; doi: 10.1016/j.jgar.2024.06.007

4. Sellera

, Lincopan

, Fuentes-Castillo

, et al. Rapid evolution of pan-β-lactam resistance in enterobacterales co-producing KPC and NDM: Insights from global genomic analysis after the COVID-19 pandemic. Lancet Microbe 2024;5(5):e412–e413; doi: 10.1016/S2666-5247(24)00018-1

5. Krul

, Rodrigues

, Siqueira

, et al. High-risk clones of carbapenem-resistant klebsiella pneumoniae recovered from pediatric patients in Southern Brazil. Braz J Microbiol 2024;55(2):1437–1443; doi: 10.1007/s42770-024-01299-w

6. Silva

DDC

, Rampelotto

, Lorenzoni

, et al. Phenotypic methods for screening carbapenem-resistant enterobacteriaceae and assessment of their antimicrobial susceptibility profile. Rev Soc Bras Med Trop 2017;50(2):173–178; doi: 10.1590/0037-8682-0471-2016

7. Vivas

, Dolabella

, Barbosa

AAT

, et al. Prevalence of klebsiella pneumoniae carbapenemase—and New Delhi metallo-beta-lactamase-positive K. pneumoniae in sergipe, Brazil, and combination therapy as a potential treatment option. Rev Soc Bras Med Trop 2020;53:e20200064; doi: 10.1590/0037-8682-0064-2020

8. Ramos-Castañeda

, Ruano-Ravina

, Barbosa-Lorenzo

, et al. Mortality due to KPC carbapenemase-producing klebsiella pneumoniae infections: Systematic review and meta-analysis. J Infect 2018;76(5):438–448; doi: 10.1016/j.jinf.2018.02.007

9. Gonçalves Barbosa

, Silva E Sousa

, Bordoni

, et al. Elevated mortality risk from CRKp associated with comorbidities: Systematic review and meta-analysis. Antibiotics (Basel) 2022;11(7):874; doi: 10.3390/antibiotics11070874

10.

10. Russotto

, Cortegiani

, Graziano

, et al. Bloodstream infections in intensive care unit patients: Distribution and antibiotic resistance of bacteria. Infect Drug Resist 2015;8:287–296; doi: 10.2147/IDR.S48810

11.

Sievert

, Ricks

, Edwards

, National Healthcare Safety Network (NHSN) Team and Participating NHSN Facilities

et al.. Antimicrobial-resistant pathogens associated with healthcare-associated infections: Summary of data reported to the national healthcare safety network at the centers for disease control and prevention, 2009-2010. Infect Control Hosp Epidemiol 2013;34(1):1–14; doi: 10.1086/668770

12.

12. Temkin

, Carmeli

. Zero or more: Methodological challenges of counting and estimating deaths related to antibiotic-resistant infections. Clin Infect Dis 2019;69(11):2029–2034; doi: 10.1093/cid/ciz414

13.

13. Borghi

, Pereira

, Schuenck

. The presence of virulent and multidrug-resistant clones of carbapenem-resistant klebsiella pneumoniae in southeastern Brazil. Curr Microbiol 2023;80(9):286; doi: 10.1007/s00284-023-03403-z

14.

14. Munoz-Price

, Poirel

, Bonomo

, et al. Clinical epidemiology of the global expansion of klebsiella pneumoniae carbapenemases. Lancet Infect Dis 2013;13(9):785–796; doi: 10.1016/S1473-3099(13)70190-7

15.

15. Vásquez-Ponce

, Bispo

, Becerra

, et al. Emergence of KPC-113 and KPC-114 variants in ceftazidime-avibactam-resistant klebsiella pneumoniae belonging to high-risk clones ST11 and ST16 in South America. Microbiol Spectr 2023;11(5):e00374-23; doi: 10.1128/spectrum.00374-23

16.

16. Lai

, Ma

, Luo

, et al. Factors influencing mortality in intracranial infections caused by carbapenem-resistant klebsiella pneumoniae. Sci Rep 2024;14(1):20670; doi: 10.1038/s41598-024-71660-4

17.

17. Ture

, Güner

, Alp

. Antimicrobial stewardship in the intensive care unit. J Intensive Med 2023;3(3):244–253; doi: 10.1016/j.jointm.2022.10.001