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Article

Surveillance and Correlation of Antibiotic Consumption and Resistance of Acinetobacter baumannii complex in a Tertiary Care Hospital in Northeast China, 2003–2011

1
Department of Laboratory Medicine, First Hospital of Jilin University, Changchun 130021, China
2
Department of Pharmacy, First Hospital of Jilin University, Changchun 130021, China
3
Department of Pediatrics, First Hospital of Jilin University, Changchun 130021, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2013, 10(4), 1462-1473; https://doi.org/10.3390/ijerph10041462
Submission received: 6 February 2013 / Revised: 28 March 2013 / Accepted: 29 March 2013 / Published: 9 April 2013

Abstract

:
This study investigated the changes in resistance of Acinetobacter baumannii complex and the association of carbapenem-resistant A. baumannii complex (CRAB) infection and hospital antimicrobial usage from 2003 to 2011 in a tertiary care hospital in northeast China. In vitro susceptibilities were determined by disk diffusion test and susceptibility profiles were determined using zone diameter interpretive criteria, as recommended by the Clinical and Laboratory Standards Institute (CLSI). Data on consumption of various antimicrobial agents, expressed as defined daily dose/1,000 patients/day, were collected retrospectively from hospital pharmacy computer database. Most of 2,485 strains of A. baumannii complex were collected from respiratory samples (1,618 isolates, 65.1%), secretions and pus (465, 18.7%) over the years. The rates of antimicrobial resistance in A. baumannii complex increased significantly over the years. The rates of CRAB were between 11.3% and 59.1% over the years. The quarterly use of anti-pseudomonal carbapenems, but not other classes of antibiotics, was strongly correlated with the increase of quarterly CRAB (β = 1.661; p < 0.001). Dedicated use of anti-pseudomonal carbapenems would be an important intervention to control the increase of CRAB.

1. Introduction

Acinetobacter baumannii complex has emerged as an important pathogen causing a variety of infections, including urinary tract infections, skin and soft tissue infections, and pneumonia and bloodstream infections [1]. A. baumannii complex used to be an easy-to-treat pathogen because it was susceptible to a wide range of antibiotic agents [2], however, over the last decade, A. baumannii complex has developed various resistance mechanisms to antibiotics [3,4]. The ability to chronically colonize patients and cause outbreaks which are usually hard to eradicate poses significant challenges to infection control and increases healthcare expenditure [5]. The threat of antimicrobial resistance has extended from the hospital setting to the community setting. The trend in increased antimicrobial resistance among bacterial pathogens severely limits the choice of effective antimicrobial agents in both settings. Imipenem and meropenem were traditionally the most effective antimicrobials against A. baumannii complex [6], but carbapenem-resistant A. baumannii complex (CRAB) has become common worldwide [7]. Due to treatment failure, drug-resistant strains have been associated with higher mortality and prolonged hospital stay compared with susceptible ones. The major risk factors for spread of multidrug-resistant organisms, including CRAB, are poor adherence to infection control measures and overuse of certain antimicrobials [8].
The misuse and overuse of antibiotics is widespread, not only in developing countries, but also in the developed world, and this inappropriate use of antibiotics has led to the rise in antimicrobial resistance. The emergence and spread of antimicrobial resistance is a complex problem that is driven by numerous interconnected factors such as under- or overuse of antimicrobials [9]. However, it is also known that the genetic mechanism used by bacteria to acquire resistance to antibiotics not only promotes their spread within hospital environments, but also confers stability on the resistance genes, even subsequently, in situations of absence of exposure to antimicrobials [10]. In recent years, an increased effort has been directed towards controlling antibiotic use and raising public awareness of the need for prudent use of antibiotics. Over the past decade, many surveillance efforts have drawn attention to this phenomenon [11,12].
This interaction between antibiotic consumption and the development of bacterial resistance to them is of particular interest with regard to A. baumannii complex. Given that new therapeutic options for treating infections caused by A. baumannii complex with high levels of resistance are not expected to become available in the near future, it becomes imperative to study measures that might be capable of improving the antimicrobial susceptibility of these bacterial agents, thereby making it possible to use the drugs that are available. Studies showing the effects of modifications to antibiotic prescription patterns are especially of interest in relation to combating the emergence of resistance in A. baumannii complex [9]. The objectives of this study were to give an overview of changes in antibiotic consumption and resistance of A. baumannii complex isolated from a tertiary care hospital in northeast China in nine consecutive years (2003 through 2011).

2. Experimental Section

2.1. Hospital Setting and Definitions

First Hospital is a teaching hospital affiliated with Jilin University in northeast China. It offers both primary and tertiary referral care. The bed capacities of hospital were 921, 1,084, 1,084, 1,240, 1,731, 1,960, 2,373, 2,572, and 2,898 from 2003 to 2011, respectively. The total numbers of inpatients were 29,323, 36,222, 41,922, 51,185, 59,907, 65,471, 83,172, 94,768, and 110,107 from 2003 to 2011, respectively. The median duration of hospital stays was 12.0, 11.9, 11.5, 10.9, 10.6, 10.1, 10.0, 9.7, and 9.2 days from 2003 to 2011, respectively. Centers for Diseases Control (CDC) criteria were used for the diagnosis of nosocomial infections. Hospital-acquired infection (HAI) was defined as occurrence of infection after hospital admission, without evidence that the infection was present or incubating (≤48 h) on admission.

2.2. Bacterial Isolates

For Acinetobacter spp., isolates were subcultured to blood agar and McConkey agar plates at this laboratory for purity check and to confirm species identification. Identification was performed using the VITEK 2 system (bioMérieux, Marcy l’Etoile, France) in the microbiological laboratory of the hospital. In addition, conventional biochemical tests including oxidase, Triple Sugar Iron, 42 °C, malonate, and hemolysis on sheep blood agar were used to aid in confirmation of the A. baumannii complex. Two thousand four hundred and eighty-five consecutive nonduplicate nosocomial isolates of A. baumannii complex were collected during the period from 2003 to 2011 in the hospital. Isolates of the same species from the same patient collected during the same in-patient stay were considered duplicate isolates, and only the first isolate was included from the analysis.

2.3. Antimicrobial Susceptibility Testing

In vitro susceptibilities of A. baumannii complex to 17 antimicrobial agents were determined by the disk diffusion method and susceptibility profiles were determined using zone diameter interpretive criteria, as recommended by the Clinical and Laboratory Standards Institute (CLSI) in 2011 (M100-S21). Breakpoints of cefoperazone/sulbactam were interpreted according to the supplier’s recommendations. Mueller-Hinton agar (Oxoid) was used for all susceptibility tests. The proportion of resistant isolates was calculated by dividing the number of resistant isolates of A. baumannii complex by the total number of the isolates tested against the corresponding antibiotic multiplied by 100. Escherichia coli ATCC 25922, Escherichia coli ATCC 35218, Klebsiella pneumoniae ATCC 700603, and Pseudomonas aeruginosa ATCC 27853 were used as quality control strains for each batch of tests. Imipenem-resistant or meropenem-resistant A. baumannii complex was considered as CRAB. For analysis of susceptibility rates in different year and patient groups, we used the WHONET software.

2.4. Antimicrobial Utilization

We retrospectively obtained the antimicrobial utilization information for all patients by using the hospital pharmacy computer database. The evaluated periods were from 2003 to 2011. Defined daily dose (DDD) was developed by the World Health Organization (WHO) Anatomical Therapeutical Chemical (ATC)/DDD Index 2011 to standardize the comparative usage of various drugs between themselves or between different healthcare environments for all adult wards, and is defined as the assumed average maintenance dose per day for a drug used for its main indication. The amount of the antimicrobials used was calculated as DDD/1,000 patients/day as follows: total consumption measured in DDDs/(number of days in the period of data collection × number of patients) × 1,000 [9]. The six classes of antimicrobial agents analyzed in this study were: anti-pseudomonal penicillins (including mezlocillin, piperacillin, and ticarcillin), β-lactam/β-lactamase inhibitors with anti-pseudomonal effects (ampicillin/sulbactam, cefoperazone/sulbactam, piperacillin/tazobactam, and ticarcillin/clavulanate), anti-pseudomonal cephalosporins (ceftazidime, cefotaxime, ceftriaxone, cefoperazone, and cefepime), anti-pseudomonal carbapenems (imipenem/cilastatin, and meropenem), anti-pseudomonal fluoroquinolones (ciprofloxacin, levofloxacin, and gatifloxacin), and aminoglycosides (amikacin, tobramycin, gentamicin, and netilmicin), modified from suggestion by CLSI in 2011.

2.5. Statistical Analysis

Time series analysis model was used to analyze the relationships between the trend in quarterly antimicrobial consumption and the rates of CRAB over time by taking into account the possible time lags (delay for observing an effect of antimicrobial use) and the autocorrelation patterns. AIC were used to check for possible autocorrelation. Logistic regression analysis was performed to analyze the trends in rates of susceptibility of A. baumannii to antimicrobials within the study period. All analyses were performed with the Statistical Package for the Social Sciences version 18.0 (SPSS, Chicago, IL, USA). All reported p values were two-sided, and values of p < 0.05 were considered statistically significant.

3. Results and Discussion

3.1. Bacterial Isolates

During the 9-year study period, 2,485 consecutive nosocomial isolates of A. baumannii complex were isolated in the hospital. Among the isolates, the mean age of the patients was 60.6 ± 18.1 years. The strains were cultured from respiratory samples (1,618 isolates, 65.1%), followed by secretions and pus (465, 18.7%), urine (137, 5.5%), blood (115, 4.6%), pleural fluid and abdominal fluid (104, 4.2%), and others (46, 1.9%). Nine hundred and sixty-four (38.8%) were from intensive care unit (ICU). Table 1 lists the source breakdown of the isolates.
Management of multidrug-resistant A. baumannii complex infections is a great challenge for physicians and clinical microbiologists. Its ability to survive in a hospital milieu and its ability to persist for extended periods of time on surfaces makes it a frequent cause for healthcare-associated infections and it has led to multiple outbreaks [13,14]. In humans, A. baumannii complex has been isolated from all culturable sites. A. baumannii complex can form part of the bacterial flora of the skin, particularly in moist regions such as the axillae, groin, and toe webs, and up to 43.0% of healthy adults can have colonization of skin and mucous membranes, with higher rates among hospital personnel and patients [15]. The most common specimen types in the present study were respiratory samples, secretions and pus over the years in this hospital.

3.2. Changes in Resistance to Different Antimicrobial Agents over the Years

Antibiotic susceptibility testing showed that over 40.0% of A. baumannii complex isolates were resistant to all 17 antimicrobial agents in 2011. The rates of antimicrobial resistance in A. baumannii complex increased significantly in the recent nine years. The resistance rates of A. baumannii complex to piperacillin, piperacillin/tazobactam, ticarcillin/clavulanic acid, trimethoprim/sulfamethoxazole, ampicillin/sulbactam, ceftazidime, cefotaxime, ceftriaxone, cefepime and gentamicin were almost more than 60.0%, especially in recent five years. The resistance rates for imipenem, meropenem, amikacin, cefoperazone/sulbactam, ciprofloxacin, levofloxacin and gatifloxacin were shown a relative low, however, they were almost more than 30.0% with a substantial increase during the nine years in the hospital. Resistance to piperacillin, ticarcillin/clavulanic acid, cefoperazone/sulbactam, imipenem, meropenem, cefotaxime, ceftriaxone, amikacin, ciprofloxacin, levofloxacin, and gatifloxacin increased slowly before 2006, then increased significantly thereafter (Table 2). The resistance rate of these antimicrobials did not increase significantly from 2003 to 2006, maybe due to small case number in this period. In contrast, the rates of resistance to piperacillin/tazobactam, ampicillin/sulbactam, ceftazidime, cefepime, and trimethoprim/sulfamethoxazole increased constantly over the years (Table 2).
The secular trend of resistance to piperacillin, ticarcillin/clavulanic acid, piperacillin/tazobactam, imipenem, ceftazidime, gentamicin, amikacin, and gatifloxacin over the years is shown in Figure 1 to highlight the sharp increase of piperacillin/tazobactam resistance from 12.5% in 2003 to 70.4% in 2011 (p < 0.001; odds ratio (OR), 1.415; 95% confidence interval (CI), 1.358 to 1.475) and imipenem resistance from 8.8% in 2003 to 41.9% in 2011 (p < 0.001; OR, 1.289; 95% CI, 1.232 to 1.349). The rates of CRAB were 11.3%, 13.0%, 19.8%, 22.1%, 31.0%, 39.7%, 46.5%, 53.5%, and 59.1% between 2003 and 2011. The rates of resistance to different antimicrobial agents between 2003 and 2011 are shown in Table 2.
Due to long-term evolutionary exposure to soil organisms that produce antibiotics, A. baumannii complex can develop antibiotic resistance at a much faster pace than other Gram-negative organisms [16]. The emergence of antimicrobial-resistant A. baumannii complex is due both to the selective pressure exerted by the use of broad-spectrum antimicrobials and transmission of strains among patients, although the relative contributions of these mechanisms are not yet known [17]. Carbapenems such as imipenem and meropenem are the last resort of drugs for the treatment of multidrug-resistant pathogens including A. baumannii complex. However, the incidence of carbapenem resistance in A. baumannii complex increased steadily in the 2000s [7,18]. This study of 2,485 A. baumannii complex over the years revealed the continuous increase of antimicrobial resistance. Resistance to carbapenems, which is often accompanied with resistance to multiple other agents, has increased in all parts of the world. Our study revealed the rapid increase in the prevalence of CRAB over the years the hospital, from 11.3% in 2003 to 59.1% in 2011. The results of the present study indicate a strong burden of CRAB in the hospital.
Table 1. Source breakdown of A. baumannii complex isolated from First Hospital of Jilin University, 2003–2011.
Table 1. Source breakdown of A. baumannii complex isolated from First Hospital of Jilin University, 2003–2011.
Strata200320042005200620072008200920102011Total
n %n %n %n %n %n %n %n %n %n %
Patient location
ICU2531.33232.03936.84738.56038.711538.715540.117940.431239.296438.8
Non-ICU5568.86868.06763.27561.59561.318261.323259.926459.648360.7152161.2
Specimen type
Respiratory5265.06565.06864.27964.810064.519465.325866.728764.851564.8161865.1
Secretions and pus1518.81818.02018.92318.92818.15618.97018.18920.114618.446518.7
Urine56.355.065.775.795.8165.4194.9225.0486.01375.5
Blood45.055.054.764.995.8134.4184.7194.3364.51154.6
Pleural fluid and abdominal fluid22.544.054.754.163.9144.7174.4184.1334.21044.2
Others22.533.021.921.631.941.351.381.8172.1461.9
Total 80 100 106 122 155 297 387 443 795 2485
Table 2. Antimicrobial resistance of A. baumannii complex isolated from First Hospital of Jilin University, 2003–2011.
Table 2. Antimicrobial resistance of A. baumannii complex isolated from First Hospital of Jilin University, 2003–2011.
Antimicrobial agentsResistance rate (%) by year2003 to 20062006 to 2011
2003 (n = 80)2004 (n = 100)2005 (n = 106)2006 (n = 122)2007 (n = 155)2008 (n = 297)2009 (n = 387)2010 (n = 443)2011 (n = 795)pOR95% CIpOR95% CI
Piperacillin56.361.064.663.977.474.173.979.078.60.2741.3790.775–2.4530.0012.0741.381–3.114
Ticarcillin/Clavulanic acid48.851.055.761.564.563.363.672.274.00.0751.6780.949–2.9670.0041.7801.196–2.649
Piperacillin/Tazobactam12.513.013.541.045.257.258.770.270.40.0014.8612.286–10.3370.0013.4312.319–5.077
Cefoperazone/Sulbactam13.813.013.220.543.927.940.140.644.70.2231.6170.746–3.5040.0013.1301.974–4.965
Ampicillin/Sulbactam37.539.044.461.071.069.063.673.475.60.0012.5691.438–4.5910.0012.0091.350–2.991
Imipenem8.810.014.014.822.627.634.440.441.90.2101.8050.717–4.5420.0014.1652.476–7.003
Meropenem7.59.09.615.623.227.339.539.540.30.0952.2750.867–5.9730.0013.6522.194–6.079
Ceftazidime31.340.049.055.758.166.362.870.265.40.0012.7701.532–5.0110.0391.5021.021–2.209
Cefotaxime45.050.056.659.063.968.771.174.576.70.0521.7600.996–3.1100.0012.2901.540–3.404
Ceftriaxone48.851.059.660.765.271.770.875.076.70.0961.6210.917–2.8640.0012.1391.435–3.187
Cefepime28.830.034.052.558.168.061.270.266.00.0012.7351.500–4.9860.0041.7621.200–2.588
Gentamicin62.570.074.477.983.972.465.979.878.60.0302.0001.071–3.7340.6781.1030.695–1.751
Amikacin40.042.045.741.848.455.250.158.359.10.7991.0770.607–1.9130.0012.0131.368–2.963
Ciprofloxacin28.831.033.337.745.255.246.560.459.70.1901.5000.817–2.7520.0012.4521.656–3.632
Levofloxacin19.019.022.631.139.447.136.453.556.60.0521.9600.993–3.8680.0012.8831.917–4.336
Gatifloxacin21.321.023.126.229.032.333.140.641.90.4201.3180.674–2.5760.0012.0271.322–3.108
Trimethoprim/Sulfamethoxazole47.549.051.964.870.270.464.974.477.40.0162.0311.143–3.6080.0031.8601.238–2.794
Table 3. Correlation between quarterly consumption of antimicrobial agents and rates of CRAB in First Hospital of Jilin University, 2003–2011.
Table 3. Correlation between quarterly consumption of antimicrobial agents and rates of CRAB in First Hospital of Jilin University, 2003–2011.
Antimicrobial agentsPenicillinsβ-lactam/β-lactamase inhibitorsCephalosporinsCarbapenemsAminoglycosidesFluoroquinolones
Antimicrobial consumption (DDDs/1,000 patients/day) by quarter20031st quarter1.873.7139.83.144.146.7
2nd quarter1.976.6143.73.244.143.4
3rd quarter1.975.9141.63.243.845.1
4th quarter1.875.1139.13.443.844.1
20041st quarter1.7146.2123.64.944.849.9
2nd quarter1.7147.5117.85.144.153.1
3rd quarter1.6159.5120.15.143.951.1
4th quarter1.6169.3112.35.344.852.3
20051st quarter1.6217.959.36.945.363.8
2nd quarter1.7289.353.17.644.865.7
3rd quarter1.7300.950.18.143.969.7
4th quarter1.8278.948.28.244.668.6
20061st quarter1.5180.592.48.543.850.3
2nd quarter1.2170.5103.88.842.349.8
3rd quarter1.3161.2120.49.142.150.6
4th quarter1.5160.7129.59.943.249.1
20071st quarter2.1120.3147.810.939.741.8
2nd quarter2.7112.2159.311.940.942.1
3rd quarter2.9101.1172.612.641.639.1
4th quarter2.991.2165.113.140.639.5
20081st quarter3.959.8151.713.935.636.3
2nd quarter4.460.1140.714.133.437.2
3rd quarter4.952.1136.714.530.931.4
4th quarter4.854.2130.915.131.331.3
20091st quarter3.180.3189.923.938.343.2
2nd quarter3.076.9198.826.636.743.6
3rd quarter2.179.4195.425.435.643.6
4th quarter2.475.1190.125.038.142.9
20101st quarter0.859.3146.727.569.830.3
2nd quarter0.456.7151.228.577.727.4
3rd quarter0.452.1140.128.978.831.2
4th quarter0.353.9138.528.173.627.1
20111st quarter15.269.6157.329.925.540.8
2nd quarter16.171.9149.429.125.146.3
3rd quarter16.774.2159.230.424.145.9
4th quarter15.876.1145.229.923.944.2
Time-series analysis modelβ0.199−0.015−0.0211.661−0.001−0.010
p0.4730.5460.5610.0010.9870.936

3.3. Association of Hospital Antimicrobial Usage and the Rates of CRAB

Overall, the consumption of anti-pseudomonal carbapenems significantly increased during the 9-year study period. In contrast, the annual use of β-lactam/β-lactamase inhibitors with anti-pseudomonal effect, and fluoroquinolones significantly decreased. Use of anti-pseudomonal aminoglycosides, and cephalosporins remained stable, whereas the penicillins use fluctuated over the years (Table 3). The association between the rates of CRAB and quarterly consumption of antimicrobial agents of different classes from 2003 to 2011 are shown in Table 3.
Figure 1. The secular trend of resistance to different antimicrobial agents over the years. Rapid increase of piperacillin/tazobactam resistance (p < 0.001; OR, 1.415; 95% CI, 1.358 to 1.475) and imipenem-resistance in A. baumannii complex (p < 0.001; OR, 1.289; 95% CI, 1.232 to 1.349) compared with the other antimicrobial agents resistance.
Figure 1. The secular trend of resistance to different antimicrobial agents over the years. Rapid increase of piperacillin/tazobactam resistance (p < 0.001; OR, 1.415; 95% CI, 1.358 to 1.475) and imipenem-resistance in A. baumannii complex (p < 0.001; OR, 1.289; 95% CI, 1.232 to 1.349) compared with the other antimicrobial agents resistance.
Ijerph 10 01462 g001
Table 3 shows correlation between quarterly consumption of antimicrobial agents used for treatment of infections due to A. baumannii complex and rates of CRAB. The results indicate that the quarterly use of anti-pseudomonal carbapenems was strongly correlated with the increase of quarterly CRAB (β = 1.661; p < 0.001). None of the other classes of antimicrobial agents was significantly associated with the increase in quarterly CRAB (Table 3).
Previous studies on the influence of antibiotic exposure on the risk for acquiring CRAB demonstrated that prior usage of carbapenem [8,19,20], and cephamycin [21] might play a role. Carbapenems may be considered the treatment of choice for empirical treatment of patients with ESBL-producing Enterobacteriaceae bacteraemia in China. This followed an outbreak of CRAB infections due to ESBL-producing Enterobacteriaceae during which use of carbapenems increased substantially in China. We found that prior exposure of imipenem and meropenem was associated with CRAB acquisition in this study. Imipenem and meropenem are broad-spectrum antibiotics with activities against most Gram-negative bacteria, including many nonfermentative Gram-negative bacilli. Therefore, it is understandable that carbapenems usage could change the bacterial flora in patients and facilitate the colonization and/or infection of resistant bacteria, such as CRAB. We found that the quarterly use of anti-pseudomonal carbapenems was strongly correlated with the increase of quarterly CRAB; however, none of the other classes of antimicrobial agents was significantly associated with the increase in quarterly CRAB.
Environmental contamination was also found to be important in the outbreaks of CRAB. Implicated items included respiratory equipment, ventilator tubing, suctioning equipment, bed rails, curtains, ambu bags, washbasins, trunking, peak flow meters, intravenous catheters, etc. [22]. Contaminated hands of healthcare workers were found to be involved in a significant number of cases [22]. It is obvious that multiple factors result in the outbreaks of CRAB in hospital.
The limitation of this paper is that we have no pulse field electrophoresis data of A. baumannii complex. We could not determine the outbreak of A. baumannii complex in different wards. Our research is an ecological study that use aggregated population-level data. Indeed, multilevel analysis makes possible the exploration of joint effects of exposures to antimicrobial agents at individual level and group level on the acquisition of resistant bacteria.

4. Conclusions

Thus, to decrease the spread of A. baumannii complex infections and reduce the pace of emergence of resistance in multidrug-resistant (MDR) A. baumannii complex, it is important to promote the rational use of antimicrobials with microbiology laboratory support in hospitals. Dedicated use of anti-pseudomonal carbapenems would be an important intervention to control the increase of CRAB. Hand hygiene and barrier nursing are important to keep the spread of infection in check. Surveillance is therefore important in providing useful information for physicians in choosing empirical antibiotics. It also helps to address specific resistant issues within a region to help identify targeted intervention measure.

Acknowledgments

We are grateful to Jing Jiang and Suyan Tian who have assisted us in the statistical analysis.

Conflict of Interest

The authors declare no conflict of interest.

References

  1. Peleg, A.Y.; Seifert, H.; Paterson, D.L. Acinetobacter baumannii: Emergence of a successful pathogen. Clin. Microbiol. Rev. 2008, 21, 538–582. [Google Scholar] [CrossRef]
  2. Bergogne-Berezin, E. The increasing significance of outbreaks of Acinetobacter spp.: The need for control and new agents. J. Hosp. Infect. 1995, 30 (Suppl.), 441–452. [Google Scholar] [CrossRef]
  3. Bou, G.; Cervero, G.; Dominguez, M.A.; Quereda, C.; Martinez-Beltran, J. Characterization of a nosocomial outbreak caused by a multiresistant Acinetobacter baumannii strain with a carbapenem-hydrolyzing enzyme: High-level carbapenem resistance in A. baumannii is not due solely to the presence of beta-lactamases. J. Clin. Microbiol. 2000, 38, 3299–3305. [Google Scholar]
  4. Quale, J.; Bratu, S.; Landman, D.; Heddurshetti, R. Molecular epidemiology and mechanisms of carbapenem resistance in Acinetobacter baumannii endemic in New York City. Clin. Infect. Dis. 2003, 37, 214–220. [Google Scholar] [CrossRef]
  5. Dijkshoorn, L.; Nemec, A.; Seifert, H. An increasing threat in hospitals: Multidrug-resistant Acinetobacter baumannii. Nat. Rev. Microbiol. 2007, 5, 939–951. [Google Scholar] [CrossRef]
  6. Unal, S.; Garcia-Rodriguez, J.A. Activity of meropenem and comparators against Pseudomonas aeruginosa and Acinetobacter spp. isolated in the MYSTIC Program, 2002–2004. Diagn. Microbiol. Infect. Dis. 2005, 53, 265–271. [Google Scholar]
  7. Perez, F.; Hujer, A.M.; Hujer, K.M.; Decker, B.K.; Rather, P.N.; Bonomo, R.A. Global challenge of multidrug-resistant Acinetobacter baumannii. Antimicrob. Agents Chemother. 2007, 51, 3471–3484. [Google Scholar] [CrossRef]
  8. Su, C.H.; Wang, J.T.; Hsiung, C.A.; Chien, L.J.; Chi, C.L.; Yu, H.T.; Chang, F.Y.; Chang, S.C. Increase of carbapenem-resistant Acinetobacter baumannii infection in acute care hospitals in Taiwan: Association with hospital antimicrobial usage. PLoS ONE 2012, 7, e37788. [Google Scholar] [CrossRef]
  9. Arda, B.; Sipahi, O.R.; Yamazhan, T.; Tasbakan, M.; Pullukcu, H.; Tunger, A.; Buke, C.; Ulusoy, S. Short-term effect of antibiotic control policy on the usage patterns and cost of antimicrobials, mortality, nosocomial infection rates and antibacterial resistance. J. Infect. 2007, 55, 41–48. [Google Scholar] [CrossRef]
  10. Burke, J.P. Antibiotic resistance—Squeezing the balloon? JAMA 1998, 280, 1270–1271. [Google Scholar] [CrossRef]
  11. Molstad, S.; Erntell, M.; Hanberger, H.; Melander, E.; Norman, C.; Skoog, G.; Lundborg, C.S.; Soderstrom, A.; Torell, E.; Cars, O. Sustained reduction of antibiotic use and low bacterial resistance: 10-year follow-up of the Swedish Strama programme. Lancet Infect. Dis. 2008, 8, 125–132. [Google Scholar]
  12. Vander Stichele, R.H.; Elseviers, M.M.; Ferech, M.; Blot, S.; Goossens, H. Hospital consumption of antibiotics in 15 European countries: Results of the ESAC Retrospective Data Collection (1997–2002). J. Antimicrob. Chemother. 2006, 58, 159–167. [Google Scholar] [CrossRef]
  13. Jawad, A.; Heritage, J.; Snelling, A.M.; Gascoyne-Binzi, D.M.; Hawkey, P.M. Influence of relative humidity and suspending menstrua on survival of Acinetobacter spp. on dry surfaces. J. Clin. Microbiol. 1996, 34, 2881–2887. [Google Scholar]
  14. Fournier, P.E.; Richet, H. The epidemiology and control of Acinetobacter baumannii in health care facilities. Clin. Infect. Dis. 2006, 42, 692–699. [Google Scholar] [CrossRef]
  15. Seifert, H.; Dijkshoorn, L.; Gerner-Smidt, P.; Pelzer, N.; Tjernberg, I.; Vaneechoutte, M. Distribution of Acinetobacter species on human skin: Comparison of phenotypic and genotypic identification methods. J. Clin. Microbiol. 1997, 35, 2819–2825. [Google Scholar]
  16. Manchanda, V.; Sanchaita, S.; Singh, N. Multidrug resistant acinetobacter. J. Glob. Infect. Dis. 2010, 2, 291–304. [Google Scholar] [CrossRef]
  17. Maragakis, L.L.; Perl, T.M. Acinetobacter baumannii: Epidemiology, antimicrobial resistance, and treatment options. Clin. Infect. Dis. 2008, 46, 1254–1263. [Google Scholar] [CrossRef]
  18. Peleg, A.Y.; Paterson, D.L. Multidrug-resistant Acinetobacter: A threat to the antibiotic era. Intern. Med. J. 2006, 36, 479–482. [Google Scholar] [CrossRef]
  19. Tsai, H.T.; Wang, J.T.; Chen, C.J.; Chang, S.C. Association between antibiotic usage and subsequent colonization or infection of extensive drug-resistant Acinetobacter baumannii: A matched case-control study in intensive care units. Diagn. Microbiol. Infect. Dis. 2008, 62, 298–305. [Google Scholar] [CrossRef]
  20. Goel, N.; Wattal, C.; Oberoi, J.K.; Raveendran, R.; Datta, S.; Prasad, K.J. Trend analysis of antimicrobial consumption and development of resistance in non-fermenters in a tertiary care hospital in Delhi, India. J. Antimicrob. Chemother. 2011, 66, 1625–1630. [Google Scholar] [CrossRef]
  21. Song, W.; Cao, J.; Mei, Y.L. Correlation between cephamycin consumption and the incidence of antimicrobial resistance in Acinetobacter baumannii at a university hospital in China from 2001 to 2009. Int. J. Clin. Pharmacol. Ther. 2011, 49, 765–771. [Google Scholar]
  22. Falagas, M.E.; Kopterides, P. Risk factors for the isolation of multi-drug-resistant Acinetobacter baumannii and Pseudomonas aeruginosa: A systematic review of the literature. J. Hosp. Infect. 2006, 64, 7–15. [Google Scholar] [CrossRef]

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MDPI and ACS Style

Xu, J.; Sun, Z.; Li, Y.; Zhou, Q. Surveillance and Correlation of Antibiotic Consumption and Resistance of Acinetobacter baumannii complex in a Tertiary Care Hospital in Northeast China, 2003–2011. Int. J. Environ. Res. Public Health 2013, 10, 1462-1473. https://doi.org/10.3390/ijerph10041462

AMA Style

Xu J, Sun Z, Li Y, Zhou Q. Surveillance and Correlation of Antibiotic Consumption and Resistance of Acinetobacter baumannii complex in a Tertiary Care Hospital in Northeast China, 2003–2011. International Journal of Environmental Research and Public Health. 2013; 10(4):1462-1473. https://doi.org/10.3390/ijerph10041462

Chicago/Turabian Style

Xu, Jiancheng, Zhihui Sun, Yanyan Li, and Qi Zhou. 2013. "Surveillance and Correlation of Antibiotic Consumption and Resistance of Acinetobacter baumannii complex in a Tertiary Care Hospital in Northeast China, 2003–2011" International Journal of Environmental Research and Public Health 10, no. 4: 1462-1473. https://doi.org/10.3390/ijerph10041462

APA Style

Xu, J., Sun, Z., Li, Y., & Zhou, Q. (2013). Surveillance and Correlation of Antibiotic Consumption and Resistance of Acinetobacter baumannii complex in a Tertiary Care Hospital in Northeast China, 2003–2011. International Journal of Environmental Research and Public Health, 10(4), 1462-1473. https://doi.org/10.3390/ijerph10041462

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