SEARCH

SEARCH BY CITATION

Keywords:

  • Acinetobacter ;
  • cost;
  • length of stay;
  • mortality;
  • resistance

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Funding
  9. Transparency Declaration
  10. References

Acinetobacter baumannii is a major cause of healthcare-associated infection, often affecting critically ill patients. The purpose of the study was to examine the associations of carbapenem resistance with mortality, length of hospital stay and hospital costs among patients infected with A. baumannii in intensive-care units (ICUs) in Colombia. A prospective, multicentre cohort study was conducted among 165 patients with A. baumannii infection admitted to ICUs between April 2006 and April 2010. Patients with carbapenem-resistant A. baumannii had higher risk of 30-day mortality than patients with carbapenem-susceptible A. baumannii in the univariate analysis (unadjusted hazard ratio = 2.12; 95% CI 1.14–3.95; p 0.018). However, carbapenem resistance was not significantly associated with risk of mortality (adjusted hazard ratio = 1.45; 95% CI 0.74–2.87; p 0.28) after adjusting for APACHE II score and other confounding factors. We did not find a significant difference in length of stay in ICU after the onset of infection between the two groups in the multivariate analysis (adjusted mean = 13.1 days versus 10.5 days; p 0.14). The average total cost of hospitalization among patients with carbapenem-resistant A. baumannii was significantly higher than that among patients with carbapenem-susceptible A. baumannii in the multivariate analysis (adjusted cost; US$ 11 359 versus US$ 7049; p <0.001). Carbapenem resistance was not significantly associated with mortality, though we are unable to rule out an increased risk due to the limited sample size. Carbapenem resistance was associated with an additional cost of hospitalization.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Funding
  9. Transparency Declaration
  10. References

Healthcare-associated infections are associated with an increase in morbidity, mortality and healthcare costs. Acinetobacter baumannii is a major cause of healthcare-associated infection, often affecting critically ill patients [1-3]. This pathogen has become one of the most difficult pathogens to control and treat because of its prolonged survival and possibly airborne transmission [3-5]. Moreover, multidrug-resistant A. baumannii is rapidly emerging due to its capability to acquire resistance to multiple classes of antimicrobials [6-9]. The rapid increase and worldwide spread of carbapenem-resistant Abaumannii infection is a major threat. Rates of carbapenem resistance are generally higher in Latin America and Asia than in North America and Europe [2]. In recent studies, rates of resistance to carbapenem in A. baumannii infection ranged from 50% to 75% in Latin America [10, 11].

The health and economic impacts of carbapenem resistance in patients with A. baumannii infection remain uncertain. There is ongoing controversy regarding whether patients infected with carbapenem-resistant A. baumannii (CRAB) are at greater risk of mortality than patients infected with carbapenem-susceptible A. baumannii (CSAB). Previous studies from North America, Europe and Asia have reported inconsistent results regarding a potential association between carbapenem resistance and mortality [12-24]. Furthermore, the literature on the economic impact of carbapenem resistance is limited, with a few studies suggesting that resistance may be associated with prolonged hospitalization and increased hospital costs in patients with A. baumannii infection [9, 14]. To our knowledge, no study has examined the impact of carbapenem resistance on clinical and economic outcomes in Latin America.

The objective of this study was to examine the associations of carbapenem resistance with mortality, length of hospital stay and hospital costs among patients infected with A. baumannii in intensive-care units (ICUs) in Colombia.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Funding
  9. Transparency Declaration
  10. References

Study design and population

This prospective cohort study was conducted in the ICUs of three tertiary-care hospitals in Bogota, Colombia. The first hospital consisted of 214 beds (17 of which were in the ICU), the second one consisted of 398 beds (15 of which were in the ICU), and the third one consisted of 275 beds (ten of which were in the ICU). We included all adult patients diagnosed with A. baumannii infection between 1 April 2006 and 1 April 2010. Patients were included in the study if they had been hospitalized for more than 48 h. The study was approved by the participating institutions and Universidad Nacional de Colombia through their respective research ethics committees.

Microbiological examination

Microbiological and antimicrobial susceptibility of A. baumannii was determined using microbiological cultures processed in the microbiology laboratories using with automated systems. Testing was carried out according to the methods recommended by the CLSI [25]. The species were identified at participating sites by the Vitek System® (bioMérieux Vitek; bioMérieux, Marcy l'Etoile, France) and MicroScan® (MicroScan Siemens; Siemens, Erlangen, Germany). Isolates identified as intermediate or resistant to antibiotics were classified as resistant to the agents. Carbapenem resistance was defined as resistance to imipenem or meropenem.

Data collection

We collected data regarding demographics, site of infection, Acute Physiology and Chronic Health Evaluation (APACHE) II score, comorbidities and the dates of hospital and ICU admission. Patients were classified as having pneumonia (ventilator-associated pneumonia and healthcare-associated pneumonia), primary bacteraemia, central venous catheter-associated infection, surgical site infection, urinary tract infection, skin and soft tissue infection and intra-abdominal infection [26]. The number of diagnoses was defined as the total number of comorbidities and complications present on the day of A. baumannii diagnosis [27]. We considered the empirical antibiotic treatment appropriate if the patient received at least one antibiotic to which the A. baumannii isolated in vitro was susceptible. Additionally, such a drug had to be administered within at least 72 h from the time of culture collection.

Mortality was defined as a death occurring within 30 days after diagnosis of A. baumannii. The lengths of ICU and hospital stay after infection were defined as time from the day of culture collection until discharge from the ICU or hospital, or until death. We used an incidence-based approach to determine costs for individual patients (i.e. micro costing) during their ICU stay. Costs were analysed from the perspective of a third-party payer because hospitals are responsible for funding infection control and quality improvement programmes. The total cost of hospitalization included days of stay in the ICU, fees for health professionals, surgical procedures, laboratory tests, microbiological cultures and radiological examinations, and antimicrobial therapy and other drugs used as a consequence of the infection. The total cost of hospitalization for each patient was obtained by multiplying the number of resource units consumed by unit cost. Because the study was conducted over 4 years, we adjusted costs to 2011 currency using the Consumer Price Index for Colombia. We initially measured costs in Colombian Pesos and then converted them to US dollars.

Data analysis

To compare the characteristics of patients with CRAB versus CSAB, we used the chi-squared test or Fisher's exact test for categorical variables, Student's t-test for normally distributed continuous variables and the Wilcoxon rank sum test for non-normally distributed continuous variables. We employed the Kaplan–Meier method to construct survival curves. We used Cox proportional hazards models to investigate the association between carbapenem resistance and risk of mortality. The multivariate model was built using a backward selection procedure. We first considered variables with p <0.05 in the univariate analysis as candidates for the multivariate model, then kept variables with p <0.05 and previous known risk factors in the final model.

To examine the associations of carbapenem resistance with the length of hospital stay and cost of hospitalization, we employed generalized linear models with a γ distribution and a log link function. Univariate and multivariate analyses were conducted. We estimated predicted lengths of stay and cost based on average marginal effects from a generalized linear model. Non-parametric bootstrap estimation was used to construct 95% CI and p-values. All statistical analyses were conducted using SAS version 9.2 (SAS Institute, Cary, NC, USA).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Funding
  9. Transparency Declaration
  10. References

The cohort comprised a total of 165 patients, the majority of which were male (64%) and had CRAB infection (63%). The average age (±SD) was 50 years (±19 years) and the average APACHE II score at onset of infection was 13 (±6). Compared with patients with CSAB, patients with CRAB had higher APACHE II scores at onset of infection and lower albumin levels (p <0.01 and p 0.04, respectively; Table 1). Patients with CRAB were more likely to receive inappropriate empirical antibiotic treatment than patients with CSAB (38.5% versus 16.4%; p 0.003).

Table 1. Baseline characteristics comparing patients with carbapenem-resistant Acinetobacter baumannii and patients with carbapenem-susceptible A. baumannii (n = 165)
Baseline characteristicsCarbapenem-resistant (n = 104)aCarbapenem-susceptible (n = 61)apb
  1. APACHE II, Acute Physiology and Chronic Health Evaluation II; ICU, intensive-care unit.

  2. a

    Mean ± SD or n (%).

  3. b

    Chi-squared or Fisher's exact test was used for categorical variables. Student's t-test was used for continuous variables. However, for lengths of hospital and ICU stays, we used Wilcoxon rank sums test.

Age51.2 ± 19.447.7 ± 19.00.006
Gender, male63 (60.6%)42 (68.9%)0.29
APACHE II score
At admission to ICU12.8 ± 5.410.1 ± 4.60.001
At onset of infection14.2 ± 6.211.6 ± 5.20.006
Number of diagnoses
<562 (59.6%)39 (63.9%)0.58
≥542 (40.4%)22 (36.1%) 
White blood cell count at onset of infection (/mm3)17 800 ± 610019 300 ± 58000.14
Albumin (mg/dL)2.93 ± 0.783.20 ± 0.780.038
Acute respiratory distress syndrome38 (36.5%)25 (41.0%)0.57
Length of hospital stay before infection (days)20.2 ± 23.516.8 ± 14.50.44
Length of ICU stay before infection (days)10.3 ± 8.310.1 ± 10.10.43
Inappropriate empirical antimicrobial treatment40 (38.5%)10 (16.4%)0.003
Site of infection
Pneumonia30 (28.9%)27 (44.3%)0.044
Bacteraemia14 (13.5%)10 (16.5%)0.61
Central venous catheter-associated infection13 (12.5%)7 (11.5%)0.85
Surgical infection28 (26.9%)12 (19.7%)0.29
Urinary tract10 (9.6%)1 (1.6%)0.06
Soft tissue4 (3.9%)3 (4.9%)0.71
Intra-abdominal5 (4.8%)1 (1.6%)0.41
Primary and secondary bacteraemia30 (28.9%)17 (27.8%)0.89
Diagnostic category
Elective surgery10 (9.6%)7 (11.5%)0.70
Emergency surgery24 (23.1%)21 (34.4%)0.11
Medical54 (51.9%)20 (32.8%)0.017
Trauma16 (15.4%)13 (21.3%)0.33
Comorbidities
Diabetes7 (6.8%)3 (4.9%)0.75
Hypertension17 (16.5%)12 (19.7%)0.38
Chronic obstructive pulmonary disease12 (11.7%)10 (16.4%)0.59
Neoplasia1 (1.0%)1 (1.6%)1.0
Renal insufficiency1 (1.0%)0 (0%)1.0

Within 30 days of the onset of infection, 55 patients died (33%). Patients with CRAB had significantly higher risk of 30-day mortality than patients with CSAB in the univariate analysis (40% versus 21%; unadjusted hazard ratio (HR) = 2.12; 95% CI 1.14–3.95; p <0.05; Fig. 1 and Table 2). However, after adjusting for age, gender, APACHE II score, number of diagnoses and inappropriate empirical antimicrobial treatment in the multivariate model, carbapenem resistance was not significantly associated with risk of mortality (adjusted HR = 1.45; 95% CI 0.74–2.87; p 0.28).

Table 2. Carbapenem-resistance and other risk factors associated with 30-day mortality among patients infected with Acinetobacter baumannii
Risk factorsn/NaUnadjusted HR (95% CI)bpAdjusted HR (95% CI)bp
  1. APACHE II, Acute Physiology and Chronic Health Evaluation II; HR, hazard ratio; ICU, intensive-care unit.

  2. a

    Number who died (n) / Number at risk (N).

  3. b

    Unadjusted and adjusted hazard ratios and 95% CIs were estimated from Cox proportional hazards model.

Carbapenem
Resistant42/1042.12 (1.14–3.95)0.0181.45 (0.74–2.87)0.28
Susceptible13/611.0 1.0 
Age
<65 years34/1231.0 1.0 
≥65 years21/422.27 (1.32–3.92)0.0031.89 (1.07–3.35)0.03
Gender
Male31/1051.0 1.0 
Female24/601.49 (0.87–2.53)0.141.56 (0.88–2.76)0.13
APACHE II
<102/521.0 1.0 
10–1923/779.12 (2.15–38.68)0.0039.32 (2.19–39.70)0.003
≥2030/3638.37 (9.12–161.31)<0.00123.06 (5.31–100.16)<0.001
Number of diagnoses
<519/1011.0 1.0 
≥536/643.60 (2.06–6.29)<0.0012.22 (1.18–4.18)0.01
Empirical antimicrobial treatment
Inappropriate21/501.48 (0.86–2.56)0.151.39 (0.78–2.46)0.26
Appropriate34/1151.0 1.0 
Length of hospital stay before infection
<10 days14/481.0  
10–19 days23/671.13 (0.59–2.16)0.72  
≥20 days17/481.12 (0.56–2.24)0.75  
Length of ICU stays before infection
<10 days33/1081.0  
≥10 days22/571.25 (0.73–2.15)0.41  
Albumin
≥2.5 mg/dL37/1251.0  
<2.5 mg/dL17/391.67 (0.94–2.96)0.08  
Acute respiratory distress syndrome
Presence19/630.90 (0.52–1.56)0.70 
Absence36/1021.0   
Primary and secondary bacteraemia
Presence16/471.07 (0.60–1.92)0.81  
Absence39/1181.0   
Site of infection
Pneumonia17/571.0  
Bacteraemia8/241.15 (0.50–2.67)0.74  
Catheter-associated7/201.15 (0.48–2.78)0.75  
Surgery infection14/401.11 (0.55–2.26)0.77  
Urinary tract7/112.36 (0.98–5.69)0.06  
Soft tissue or skin1/70.40 (0.05–2.99)0.37  
Intra-abdominal1/60.52 (0.07–3.89)0.52  
Diagnostic category
Emergency surgery12/451.00  
Elective surgery7/171.73 (0.68–4.39)0.25  
Medical28/741.45 (0.74–2.85)0.28  
Trauma8/290.99 (0.40–2.41)0.97  
image

Figure 1. Risk of 30-day mortality comparing patients with carbapenem-resistant Acinetobacter baumannii and patients with carbapenem-susceptible A. baumannii (log rank test, p 0.02).

Download figure to PowerPoint

Patients with CRAB had longer ICU stays after the onset of infection than patients with CSAB in the univariate analysis (mean = 13.2 days versus 10.1 days; p 0.04; Table 3). However, the association was attenuated in the multivariate model (adjusted mean = 13.1 days versus 10.5 days; p 0.14). We did not find a significant difference in length of hospital stay after infection between the two groups (adjusted mean = 19.3 days versus 16.2 days; p 0.58).

Table 3. Length of hospital and intensive-care unit stays comparing patients with carbapenem-resistant Acinetobacter baumannii and patients with carbapenem-susceptible A. baumannii
Length of stay after infectionUnadjustedAdjusteda
Carbapenem-resistant, Mean ± SDCarbapenem-susceptible, Mean ± SDpbCarbapenem-resistant, Mean (95% CI)Carbapenem-susceptible, Mean (95% CI)p
  1. a

    Predicted lengths of stay based on average marginal effects from a generalized linear model with a log link function and γ distribution that adjusted for age, gender, APACHE II score and site of infection. 95% CIs and p-values were estimated by non-parametric bootstrapping.

  2. b

    Based on Wilcoxon rank sums test.

Hospital days19.0 ± 17.216.2 ± 18.00.2019.3 (16.0, 22.5)16.2 (11.5, 19.9)0.58
Intensive-care unit days13.2 ± 13.810.1 ± 8.70.0413.1 (10.8, 15.4)10.5 (8.2, 12.8)0.14

The average total cost of hospitalization among patients with CRAB was significantly higher than that among patients with CSAB in both the univariate and multivariate analyses (adjusted US$ 11 359 versus US$ 7049; p <0.01; Table 4). Carbapenem resistance was associated with an additional treatment cost of US$ 4309 (95% CI US$ 2819–5645; p <0.01) after adjusting for age, gender, APACHE II score and site of infection. Patients with CRAB had significantly higher costs for hospital-related cost and for cost of antimicrobial drugs than patients with CSAB (both p <0.01 and p <0.01).

Table 4. Cost of hospitalization (US$) comparing patients with carbapenem-resistant Acinetobacter baumannii and patients with carbapenem-susceptible A. baumannii
Cost (US$)UnadjustedAdjusteda
Carbapenem-resistant, Mean ± SDCarbapenem-susceptible, Mean ± SDpbCarbapenem-resistant, Mean (95% CI)Carbapenem-susceptible, Mean (95% CI)Mean difference (95% CI)p
  1. a

    Predicted cost based on average marginal effects from a generalized linear model with a log link function and gamma distribution that adjusted for age, gender, APACHE II score, and site of infection. 95% CIs and p-values were estimated by non-parametric bootstrapping.

  2. b

    p-value based on Wilcoxon rank sums test.

Total cost11 822 ± 73347178 ± 3938<0.00111 359 (10 053–12 483)7049 (6206–8021)4309 (2819–5645)<0.001
Hospital-related cost7726 ± 44584704 ± 3287<0.0017596 (6736–8440)4539 (3824–5291)3057 (1943–4134)<0.001
Cost of antimicrobials4096 ± 40262475 ± 20420.0023657 (3069–4159)2520 (2009–3073)1137 (386–1894)0.002

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Funding
  9. Transparency Declaration
  10. References

In this prospective cohort study of patients with A. baumannii infection in Colombia, we found that carbapenem resistance was not significantly associated with risk of 30-day mortality after adjusting for severity of illness and other confounding factors. Our study demonstrated that the average total cost of hospitalization among patients infected with CRAB was significantly higher than that among patients infected with CSAB in the multivariate analysis.

Patients infected with CRAB are more likely to have severe illness and less likely to receive appropriate empirical antibiotic treatment than patients infected with CSAB. Therefore, in the unadjusted analysis, the higher mortality rate in patients with CRAB compared with patients with CSAB may be partly a result of the severe underlying disease status of patients with CRAB. Though the adjusted HR was attenuated and not statistically significant, it is possible that carbapenem resistance may have contributed to an increased risk of mortality; however, our study may not have enough statistical power to detect a statistically significant association. Previous studies have reported conflicting results as to whether high risk of death in patients with CRAB is the result of carbapenem resistance or greater severity of underlying illness [12-24]. Among 13 previous studies of patients with A. baumannii infection, five studies found that carbapenem resistance may increase risk of mortality after adjusting for severity of illness and other confounding factors [13-17]. However, other studies did not find statistically significant association in the multivariate analysis and reported that higher crude mortality rates in patients with CRAB were due to severity of illness, inappropriate antimicrobial therapy or primary source of infection [18-24]. Most studies had a limited sample size. It is also important to note substantial differences in the methodology, rates of carbapenem resistance, study population and study country, which may have resulted in conflicting findings. Furthermore, previous studies have mostly examined patients with bacteraemia who may be at greater risk of resistant infection.

We demonstrated that carbapenem resistance was significantly associated with higher average cost of hospitalization (adjusted cost for CRAB US$ 11 359 versus CSAB US$ 7049). Longer ICU stays and higher costs from antimicrobial drugs have contributed to the higher cost in patients with CRAB. Similarly, Lautenbach et al. [14] found that patients with CRAB compared with patients with CSAB have higher hospital charges in the USA (US$ 33 4516 versus US$ 276 059; p 0.03). Lee et al. [9] also found that average costs for patients infected with multidrug-resistant A. baumannii were higher than those of patients infected with non-multidrug-resistant A. baumannii in Taiwan (US$ 9349 versus US$ 4863; p <0.05). Researchers have also found that antimicrobial resistance is associated with higher hospital costs in other gram-negative bacterial infections, such as Pseudomonas aeruginosa [28, 29].

Our study has several notable strengths. The present study is the first in Latin America to examine the clinical and economic impacts of carbapenem resistance among patients with A. baumannii infection. Furthermore, we prospectively collected clinical and cost data, which are not typically collected systematically in Colombia. We also carefully collected and adjusted for a number of important confounding factors.

Several limitations are worth noting. Although we adjusted for many known risk factors for outcomes, as with any observational study, it is difficult to infer causation because of possible unmeasured factors, including hospital or individual level characteristics. Carbapenem resistance in A. baumannii may result from a number of mechanisms, including production of β-lactamases, over-expression of efflux pump, alterations in outer membrane proteins, or penicillin-binding protein modifications [30]. We did not conduct molecular level analysis to characterize mechanisms of carbapenem resistance. Another limitation is that our study may not have sufficient statistical power to detect a statistically significant difference in the mortality rate. Combining results from previous studies using meta-analysis techniques may further elucidate whether such an association exists.

In conclusion, we observed a high rate of carbapenem resistance (63%) in patients with A. baumannii infection admitted to the ICU. Carbapenem resistance was not significantly associated with risk of 30-day mortality, though we are unable to rule out an increased risk due to the limited sample size. Our study demonstrated that A. baumannii infection leads to substantial hospital costs, with carbapenem resistance adding additional costs. In addition to prevention and control of healthcare-associated infections, timely and appropriate antimicrobial treatment is critical for patients with A. baumannii infection, particularly those infected by carbapenem-resistant strains.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Funding
  9. Transparency Declaration
  10. References

We would like to thank Dr Narda Olarte, Jefe Alberto Valderrama and Jefe Karlo Reyes from Hospital el Tunal; Dr Fabio Barrera, Jefe Ana Gilma, Sánchez de Parada, Dr Blanca Arango and Dr Luz Dary Teheran from Hospital Occidente de Kennedy; Dr Edgar Ruiz Luengas, Dr Fabio Corredor, Dr Diego Villarraga, Dr Norma Montoya and Dr Martha Salinas from Clínica del Occidente; and Dr Julio Cesar Castillo Inocencio and Dr Liliana Raquel Lemos Luengas from FUDASAI. We also thank Alison Tse Kawai for editorial assistance.

Funding

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Funding
  9. Transparency Declaration
  10. References

The time of the professionals and research assistants involved in the present research was supported by the participating institutions. We did not receive any external funding.

Transparency Declaration

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Funding
  9. Transparency Declaration
  10. References

The authors declare no conflict of interest related to this article.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Funding
  9. Transparency Declaration
  10. References
  • 1
    Munoz-Price LS, Weinstein RA. Acinetobacter infection. N Engl J Med 2008; 358: 12711281.
  • 2
    Peleg AY, Seifert H, Paterson DL. Acinetobacter baumannii: emergence of a successful pathogen. Clin Microbiol Rev 2008; 21: 538582.
  • 3
    Falagas ME, Karveli EA, Siempos II, Vardakas KZ. Acinetobacter infections: a growing threat for critically ill patients. Epidemiol Infect 2008; 136: 10091019.
  • 4
    Wagenvoort JH, Joosten EJ. An outbreak Acinetobacter baumannii that mimics MRSA in its environmental longevity. J Hosp Infect 2002; 52: 226227.
  • 5
    Bernards AT, Frenay HM, Lim BT, Hendriks WD, Dijkshoorn L, van Boven CP. Methicillin-resistant Staphylococcus aureus and Acinetobacter baumannii: an unexpected difference in epidemiologic behavior. Am J Infect Control 1998; 26: 544551.
  • 6
    Sunenshine RH, Wright MO, Maragakis LL et al. Multidrug-resistant Acinetobacter infection mortality rate and length of hospitalization. Emerg Infect Dis 2007; 13: 97103.
  • 7
    Young L, Sabel A, Price C. Epidemiologic, clinical, and economic evaluation of an outbreak of clonal multidrug-resistant Acinetobacter baumannii infection in a surgical intensive care unit. Infect Control Hosp Epidemiol 2007; 28: 413419.
  • 8
    Lemos EV, De la Hoz Restrepo F, Alvis N, Quevedo E, Canon O, Leon Y. Acinetobacter baumannii-related mortality in intensive care units in Colombia. Rev Panam Salud Publica 2011; 30: 287294.
  • 9
    Lee NY, Lee HC, Ko NY et al. Clinical and economic impact of multidrug resistance in nosocomial Acinetobacter baumannii bacteremia. Infect Control Hosp Epidemiol 2007; 28: 713719.
  • 10
    Bertrand X, Dowzicky MJ. Antimicrobial susceptibility among gram-negative isolates collected from intensive care units in North America, Europe, the Asia-Pacific Rim, Latin America, the Middle East, and Africa between 2004 and 2009 as part of the Tigecycline Evaluation and Surveillance Trial. Clin Ther 2012; 34: 124137.
  • 11
    Gales AC, Castanheira M, Jones RN, Sader HS. Antimicrobial resistance among Gram-negative bacilli isolated from Latin America: results from SENTRY Antimicrobial Surveillance Program (Latin America, 2008–2010). Diagn Microbiol Infect Dis 2012; 73: 354360.
  • 12
    The Brooklyn Antibiotic Resistance Task Force. The cost of antibiotic resistance: effect of resistance among Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudmonas aeruginosa on length of hospital stay. Infect Control Hosp Epidemiol 2002; 23: 106108.
  • 13
    Kwon KT, Oh WS, Song JH et al. Impact of imipenem resistance on mortality in patients with Acinetobacter bacteraemia. J Antimicrob Chemother 2007; 59: 525530.
  • 14
    Lautenbach E, Synnestvedt M, Weiner MG et al. Epidemiology and impact of imipenem resistance in Acinetobacter baumannii. Infect Control Hosp Epidemiol 2009; 30: 11861192.
  • 15
    Metan G, Sariguzel F, Sumerkan B. Factors influencing survival in patients with multi-drug-resistant Acinetobacter bacteraemia. Eur J Intern Med 2009; 20: 540544.
  • 16
    Kim YJ, Kim SI, Hong KW, Kim YR, Park YJ, Kang MW. Risk factors for mortality in patients with carbapenem-resistant Acinetobacter baumannii bacteremia: impact of appropriate antimicrobial therapy. J Korean Med Sci 2012; 27: 471475.
  • 17
    Sheng WH, Liao CH, Lauderdale TL et al. A multicenter study of risk factors and outcome of hospitalized patients with infections due to carbapenem-resistant Acinetobacter baumannii. Int J Infect Dis 2010; 14: e764e769.
  • 18
    Routsi C, Pratikaki M, Platsouka E, Sotiropoulou C. Carbapenem-resistant versus carbapenem-susceptible Acinetobacter baumannii bacteremia in a Greek intensive care unit: risk factors, clinical features and outcomes. Infection 2010; 38: 173180.
  • 19
    Jamulitrat S, Arunpan P, Phainuphong P. Attributable mortality of imipenem-resistant nosocomial Acinetobacter baumannii bloodstream infection. J Med Assoc Thai 2009; 92: 413419.
  • 20
    Esterly JS, Griffith M, Qi C, Malczynski M, Postelnick MJ, Scheetz MH. Impact of carbapenem resistance and receipt of active antimicrobial therapy on clinical outcomes of Acinetobacter baumannii bloodstream infections. Antimicrob Agents Chemother 2011; 55: 48444849.
  • 21
    Aydemir H, Celebi G, Piskin N et al. Mortality attributable to carbapenem-resistant nosocomial Acinetobacter baumannii infections in a Turkish university hospital. Jpn J Infect Dis 2012; 65: 6671.
  • 22
    Deris Z, Shafei M, Harun A. Risk factors and outcomes of imipenem-resistant Acinetobacter bloodstream infection in North-eastern Malaysia. Asian Pac J Trop Biomed 2011; 1: 313315.
  • 23
    Huang ST, Chiang MC, Kuo SC et al. Risk factors and clinical outcomes of patients with carbapenem-resistant Acinetobacter baumannii bacteremia. J Microbiol Immunol Infect 2012; 45: 356362.
  • 24
    Chang HC, Chen YC, Lin MC et al. Mortality risk factors in patients with Acinetobacter baumannii ventilator-associated pneumonia. J Formos Med Assoc 2011; 110: 564571.
  • 25
    Clinical and Laboratory Standards Institute. Performance standards for antimicrobial susceptibility testing. Wayne (PA): Clinical Laboratory Standards Institute, 2006; 16th Informational Supplement M100-S16.
  • 26
    Horan TC, Andrus M, Dudeck MA. CDC/NHSN surveillance definition of health care-associated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control 2008; 36: 309332.
  • 27
    Haley RW. Measuring the costs of nosocomial infections: methods for estimating economic burden on the hospital. Am J Med 1991; 91: 32S38S.
  • 28
    Tansarli GS, Karageorgopoulos DE, Kapaskelis A, Falagas ME. Impact of antimicrobial multidrug resistance on inpatient care cost: an evaluation of the evidence. Expert Rev Anti Infect Ther 2013; 11: 321331.
  • 29
    Neidell MJ, Cohen B, Furuya Y et al. Costs of healthcare- and community-associated infections with antimicrobial-resistant versus antimicrobial-susceptible organisms. Clin Infect Dis 2012; 55: 807815.
  • 30
    Poirel L, Nordmann P. Carbapenem resistance in Acinetobacter baumannii: mechanisms and epidemiology. Clin Microbiol Infect 2006; 12: 826836.