Intensive Care Antimicrobial Resistance Epidemiology Research Articles

Improvement plan for the korean nationwide surveillance of antimicrobial resistance program.

In recent years, the sudden increase in the prevalence of antimicrobial-resistant bacteria and the emergence of multidrug-resistant bacteria have become serious worldwide problems. Therefore, in 2000, the World Health Organization (WHO) declared antimicrobial resistance to be an international danger, and has been working with its member nations to promote the appropriate use of antimicrobials as a solution to the antimicrobial resistance threat [1]. The recent emergence of New Delhi metallo-β-lactamase carbapenem-resistant Enterobacteriaceae has motivated us to increase our alertness to antimicrobial-resistant organisms [2]. Thus, surveillance of healthcare-associated infection has been enhanced. Surveillance for antimicrobial resistance is being executed mainly in European countries and in the U.S. In Korea, with the enactment of the Infectious Disease Control and Prevention Act in December 2010, infectious diseases caused by 6 types of multidrug-resistant bacteria-vancomycin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus, methicillin-resistant S. aureus, multidrug-resistant Pseudomonas aeruginosa, multidrug-resistant Acinetobacter baumannii, and carbapenem-resistant Enterobacteriaceae-were legally designated for sentinel surveillance [3]. The prevalence of antimicrobial resistance in bacteria varies substantially from country to country and according to the date of the analysis and the hospital characteristics, because it is influenced significantly by the use of antimicrobial drugs and the degree of success of efforts to control the spread of resistant bacteria. The purposes of an antimicrobial resistance surveillance system (ARSS) are as follows: (1) to detect antimicrobial susceptibility patterns; (2) to monitor the identity, transmission, and expression of antimicrobial-resistance genes; (3) to provide important information on the development of bacterial resistance mechanisms in different regions; and (4) to allow changes in antimicrobial prescription practices and participation of infection control professionals. Well-designed antimicrobial resistance surveillance systems are needed when fighting bacterial resistance. The parameters of an ideal ARSS are as follows: global geography, year-on-year longevity, multiple species selection, centralized methods and test sites, large sample size, monitoring for many antimicrobial drugs, incorporation of epidemiology, and frequent data distribution [4]. Implementation of an ARSS requires 4 components: administrative commitments, system organization (participant, expert, and coordinator), financial support (from government agencies and the pharmaceutical industry), and data analysis and reporting systems (online and offline). The scope of ARSS networks is divided into global, continental, and nationwide. The global representative ARSSs are the Alexander Project, MYSTIC Program, SENTRY Program, PROTEKT System, and WHO Program. The European ARSS (EARSS; EARS-Net) is the surveillance system implemented in Europe, and the ARSSs available in the U.S. are the National Nosocomial Infections Surveillance, Intensive Care Antimicrobial Resistance Epidemiology, National Antimicrobial Resistance Monitoring System, International Surveillance Program for Emerging Antimicrobial Resistance, and Surveillance for Emerging Antimicrobial Resistance Connected to healthcare. In Korea, the nationwide ARSSs are the Korean Nationwide Surveillance of Antimicrobial Resistance (KONSAR), Korean Nosocomial Infections Surveillance System, and Korean Antimicrobial Resistance Monitoring System. Since 1997, the KONSAR program has been collecting data on antimicrobial-resistant bacteria from participating laboratories [5], and has therefore played an integral role in informing interested parties about the current state and severity of domestic antimicrobial resistance in bacteria by analyzing and reporting bacterial antimicrobial susceptibility data. However, the KONSAR program releases all its laboratory data to research papers or newsletters only after analysis; therefore, a web-based system that can analyze data in real time is needed [6]. To create such a system, a knowledge-based rule check system capable of detecting errors by setting the exact data variables as the definition of the specimen, the species identification method, and the antimicrobial susceptibility test methods must be defined. Furthermore, various analysis functions such as data comparison between entire hospitals and participating laboratories, and between peer groups, must be made possible on the internet. According to a recent KONSAR report [7], susceptibility to antimicrobials, including colistin, was analyzed without dividing Acinetobacter spp. into A. baumannii and non-baumannii Acinetobacter. This is a problem that has yet to be resolved. At the government level, blaOXA-23-like or ISAba1-activated blaOXA-51-like gene tests for detecting carbapenem-resistant A. baumannii need to be supported. For manufacturers that supply identification kits and for clinical microbiology laboratories, the development of testing methods that can accurately identify A. baumannii is also needed.

The contribution of antibiotic use on the frequency of antibiotic resistance in hospitals.

Abundant evidence suggests a relationship between antibiotic resistance and use, including animal models, consistent associations between resistance and antibiotic use in hospitals, concomitant variation in resistance as antibiotic use varies, and a dose-response relationship for many pathogen/antibiotic combinations. Much of the evidence has come from studies performed in single hospitals. Most multicentre studies on resistance have not included data on antibiotic usage. Despite this substantial body of evidence, some studies have failed to demonstrate an association between antibiotic resistance and use, suggesting other contributing factors such as cross-transmission, inter-hospital transfer of resistance, a community contribution to resistance, or a complex relationship between resistance and the use of a variety of antibiotics. A multicentre study, project ICARE (Intensive Care Antimicrobial Resistance Epidemiology), implemented in 1994 by Centers for Disease Control and Prevention and Rollins School of Public Health, Emory University, has found dramatic differences in the patterns of antibiotic usage and resistance in US hospitals. The findings suggest that antibiotic usage is the major risk factor in development of antibiotic resistance in hospitals but the relationship can be complex with additional factors involved. Understanding the problem of antibiotic resistance in a hospital cannot be achieved without knowledge of the hospital's pattern of antibiotic use.

Surveillance of antimicrobial use and antimicrobial resistance in intensive care units (SARI): 1. Antimicrobial use in German intensive care units

To study antimicrobial use for benchmarking and ensuring quality of antimicrobial treatment and to identify risk factors associated with the high use of antimicrobials in German intensive care units (ICUs) through implementation of the SARI (Surveillance of Antimicrobial Use and Antimicrobial Resistance in ICUs) system. Prospective, unit-based surveillance on antimicrobial use from February, 2000, until June, 2002. The data are standardised by use of the defined daily dose (DDD) for each antimicrobial defined by the WHO and by calculating use per 1000 patient days. The data were obtained from 35 German ICUs and stratified by type of ICU (medical, surgical, interdisciplinary). To date, the project covers a total of 266,013 patient days in 744 reported ICU months and 354,356 DDDs. Mean antimicrobial use density (AD) was 1,332 DDD/1000 patient days and was correlated with length of stay. Penicillins with beta-lactamase inhibitor (AD 338.3) and quinolones (155.5) were the antimicrobial group with the highest ADs. Comparison with US ICARE (Intensive Care Antimicrobial Resistance Epidemiology)/AUR (Antimicrobial Use and Resistance) data revealed a higher AD for glycopeptides and 3rd generation cephalosporins in ICARE/AUR ICUs, but a higher AD for carbapenems in German SARI ICUs regardless of the type of ICU. In the multivariate analysis, length of stay was an independent risk factor for an AD above the 75% percentile of the total amount of antimicrobials used (OR 1.96 per day); likewise, for the AD above the 75% percentile of carbapenems (OR 1.90 per day) and penicillins with extended spectrum (OR 2.01 per day). High use of glycopeptides and quinolones (AD >75% percentile) correlated with central venous catheter (CVC) rate (OR 1.14 per CVC day per 100 patient days and 1.16, respectively). The SARI data on antimicrobials serve ICUs as a benchmark by which to improve the quality of antimicrobial drug administration and for international comparison.

Utility of NCCLS guidelines for identifying extended-spectrum beta-lactamases in non-Escherichia coli and Non-Klebsiella spp. of Enterobacteriaceae.

NCCLS screening and confirmation methods for detecting extended-spectrum beta-lactamases (ESBLs) apply only to Escherichia coli and Klebsiella spp., yet ESBLs have been found in other members of the family Enterobacteriaceae. We evaluated the effectiveness of NCCLS methods for detecting ESBLs in 690 gram-negative isolates of Enterobacteriaceae that excluded E. coli, Klebsiella pneumoniae, and Klebsiella oxytoca. Isolates were collected between January 1996 and June 1999 from 53 U.S. hospitals participating in Project ICARE (Intensive Care Antimicrobial Resistance Epidemiology). The antimicrobial susceptibility patterns of the isolates were determined by using the NCCLS broth microdilution method (BMD), and those isolates for which the MIC of ceftazidime, cefotaxime, ceftriaxone, or aztreonam was >or=2 microg/ml or the MIC of cefpodoxime was >or=8 microg/ml (positive ESBL screen test) were further tested for a clavulanic acid (CA) effect by BMD and the disk diffusion method (confirmation tests). Although 355 (51.4%) of the isolates were ESBL screen test positive, only 15 (2.2%) showed a CA effect. Since 3 of the 15 isolates were already highly resistant to the five NCCLS indicator drugs, ESBL detection would have an impact on the reporting of only 1.7% of the isolates in the study. Only 6 of the 15 isolates that showed a CA effect contained a bla(TEM), bla(SHV), bla(CTX-M), or bla(OXA) beta-lactamase gene as determined by PCR (with a corresponding isoelectric focusing pattern). Extension of the NCCLS guidelines for ESBL detection to Enterobacteriaceae other than E. coli and Klebsiella spp. does not appear to be warranted in the United States at present, since the test has poor specificity for this population and would result in changes in categorical interpretations for only 1.7% of Enterobacteriaceae tested.

Antimicrobial resistance among gram-negative organisms in the intensive care unit.

We review the hospital-acquired gram-negative organisms commonly encountered among patients in the intensive care unit and discuss pertinent surveillance data, resistance mechanisms and patterns, and optimal treatment regimens for these pathogens. There has been a notable increase in antibiotic resistance among gram-negative intensive care unit pathogens. Data from surveillance programs such as National Nosocomial Infections Surveillance System, Intensive Care Antimicrobial Resistance Epidemiology, and others have documented undesirable trends in antibiotic resistance, indicating decreasing efficacy of antibiotic classes such as third-generation cephalosporins, carbapenems, and fluoroquinolones, The increased prevalence of extended-spectrum beta-lactamases has contributed to the finding of multidrug resistance among bacteria such as Klebsiella and Escherichia coli. Furthermore, organisms such as Acinetobacter baumannii, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia display intrinsic resistance to many antibiotics, making selection of optimal therapy difficult. Studies have correlated infection by these organisms with prior antibiotic exposure, and containment of the spread of infection can be achieved by careful antibiotic use and infection control practices. Antibiotic resistance continues to rise among hospital-acquired gram-negative pathogens. Optimal management of these infections requires knowledge of local epidemiology and practices to control their spread.

Antimicrobial susceptibility testing of carbapenems: multicenter validity testing and accuracy levels of five antimicrobial test methods for detecting resistance in Enterobacteriaceae and Pseudomonas aeruginosa isolates.

From January 1996 to May 1999, Project ICARE (Intensive Care Antimicrobial Resistance Epidemiology) received 448 nonduplicate clinical isolates of Enterobacteriaceae and Pseudomonas aeruginosa that were reported to be imipenem intermediate or resistant. However, broth microdilution (BMD) confirmatory testing at the Project ICARE central laboratory confirmed this result in only 11 of 123 (8.9%) Enterobacteriaceae isolates and 241 of 325 (74.2%) P. aeruginosa isolates. To investigate this overdetection of imipenem resistance, we tested 204 selected isolates from the Project ICARE collection plus five imipenem-resistant challenge strains at the Centers for Disease Control and Prevention against imipenem and meropenem by agar dilution, disk diffusion, Etest (AB BIODISK North America, Inc., Piscataway, N.J.), two MicroScan WalkAway conventional panels (Neg MIC Plus 3 and Neg Urine Combo 3) (Dade MicroScan, Inc., West Sacramento, Calif.), and two Vitek cards (GNS-116 containing meropenem and GNS-F7 containing imipenem) (bioMérieux Vitek, Inc., Durham, N.C.). The results of each test method were compared to the results of BMD testing using in-house-prepared panels. Seven imipenem-resistant and five meropenem-resistant isolates of Enterobacteriaceae and 43 imipenem-resistant and 21 meropenem-resistant isolates of P. aeruginosa were identified by BMD. For Enterobacteriaceae, the imipenem and meropenem test methods produced low numbers of very major and major errors. All test systems in the study produced low numbers of very major and major errors when P. aeruginosa was tested against imipenem and meropenem, except for Vitek testing (major error rate for imipenem, 20%). Further testing conducted in 11 of the participating ICARE hospital laboratories failed to pinpoint the factors responsible for the initial overdetection of imipenem resistance. However, this study demonstrated that carbapenem testing difficulties do exist and that laboratories should consider using a second, independent antimicrobial susceptibility testing method to validate carbapenem-intermediate and -resistant results.

Summaires for patients. Factors associated with the development of antibiotic-resistant bacteria.

Summaries for Patients7 August 2001Factors Associated with the Development of Antibiotic-Resistant BacteriaSearch for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-135-3-200108070-00005 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail What is the problem and what is known about it so far?Unnecessary use of antibiotics is thought to be an important cause of bacterial resistance to antibiotics. One type of bacteria known as vancomycin-resistant enterococci (VRE), which is usually found in the bowel, can cause serious or fatal infections and is extremely difficult to treat. Limited information is available on exactly where VRE occur in hospitals and what factors are associated with their presence.Why did the researchers do this particular study?To evaluate how patterns of antibiotic use affected the frequency of finding VRE in hospital intensive care ... Author, Article, and Disclosure InformationAffiliations: The summary below is from the full report titled “The Effect of Vancomycin and Third-Generation Cephalosporins on Prevalence of Vancomycin-Resistant Enterococci in 126 U.S. Adult Intensive Care Units.” It is in the 7 August 2001 issue of Annals of Internal Medicine (volume 135, pages 175-183). The authors are SK Fridkin, JR Edwards, JM Courval, H Hill, FC Tenover, R Lawton, RP Gaynes, and JE McGowan Jr., for the Intensive Care Antimicrobial Resistance Epidemiology (ICARE) Project and the National Nosocomial Infections Surveillance (NNIS) System Hospitals.Summaries for Patients are a service provided by Annals to help patients better understand the complicated and often mystifying language of modern medicine.Summaries for Patients are presented for informational purposes only. These summaries are not a substitute for advice from your own medical provider. If you have questions about this material, or need medical advice about your own health or situation, please contact your physician. The summaries may be reproduced for not-for-profit educational purposes only. Any other uses must be approved by the American College of Physicians-American Society of Internal Medicine. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoThe Effect of Vancomycin and Third-Generation Cephalosporins on Prevalence of Vancomycin-Resistant Enterococci in 126 U.S. Adult Intensive Care Units Scott K. Fridkin , Jonathan R. Edwards , Jeanne M. Courval , Holly Hill , Fred C. Tenover , Rachel Lawton , Robert P. Gaynes , John E. McGowan Jr. , and Metrics 7 August 2001Volume 135, Issue 3Page: I-27KeywordsAntibioticsBacteriaInpatientsIntensive care unitsNosocomial infectionsNumber needed to inviteOutpatient clinicsSurgeryVancomycinVancomycin resistant enterococcus ePublished: 7 August 2001 Issue Published: 7 August 2001 Copyright & PermissionsCopyright © 2001 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...

Characterization of clinical isolates of Klebsiella pneumoniae from 19 laboratories using the National Committee for Clinical Laboratory Standards extended-spectrum beta-lactamase detection methods.

Extended-spectrum beta-lactamases (ESBLs) are enzymes found in gram-negative bacilli that mediate resistance to extended-spectrum cephalosporins and aztreonam. In 1999, the National Committee for Clinical Laboratory Standards (NCCLS) published methods for screening and confirming the presence of ESBLs in Klebsiella pneumoniae, Klebsiella oxytoca, and Escherichia coli. To evaluate the confirmation protocol, we tested 139 isolates of K. pneumoniae that were sent to Project ICARE (Intensive Care Antimicrobial Resistance Epidemiology) from 19 hospitals in 11 U.S. states. Each isolate met the NCCLS screening criteria for potential ESBL producers (ceftazidime [CAZ] or cefotaxime [CTX] MICs were > or =2 microg/ml for all isolates). Initially, 117 (84%) isolates demonstrated a clavulanic acid (CA) effect by disk diffusion (i.e., an increase in CAZ or CTX zone diameters of > or =5 mm in the presence of CA), and 114 (82%) demonstrated a CA effect by broth microdilution (reduction of CAZ or CTX MICs by > or =3 dilutions). For five isolates, a CA effect could not be determined initially by broth microdilution because of off-scale CAZ results. However, a CA effect was observed in two of these isolates by testing cefepime and cefepime plus CA. The cefoxitin MICs for 23 isolates that failed to show a CA effect by broth microdilution were > or =32 microg/ml, suggesting either the presence of an AmpC-type beta-lactamase or porin changes that could mask a CA effect. By isoelectric focusing (IEF), 7 of the 23 isolates contained a beta-lactamase with a pI of > or =8.3 suggestive of an AmpC-type beta-lactamase; 6 of the 7 isolates were shown by PCR to contain both ampC-type and bla(OXA) genes. The IEF profiles of the remaining 16 isolates showed a variety of beta-lactamase bands, all of which had pIs of < or =7.5. All 16 isolates were negative by PCR with multiple primer sets for ampC-type, bla(OXA), and bla(CTX-M) genes. In summary, 83.5% of the K. pneumoniae isolates that were identified initially as presumptive ESBL producers were positive for a CA effect, while 5.0% contained beta-lactamases that likely masked the CA effect. The remaining 11.5% of the isolates studied contained beta-lactamases that did not demonstrate a CA effect. An algorithm based on phenotypic analyses is suggested for evaluation of such isolates.

Ability of laboratories to detect emerging antimicrobial resistance in nosocomial pathogens: a survey of Project ICARE laboratories

A proficiency testing project was conducted among 48 microbiology laboratories participating in Project ICARE (Intensive Care Antimicrobial Resistance Epidemiology). All laboratories correctly identified the Staphylococcus aureus challenge strain as oxacillin- resistant and an Enterococcus faecium strain as vancomycin-resistant. Thirty-one (97%) of 32 laboratories correctly reported the Streptococcus pneumoniae strain as erythromycin-resistant. All laboratories testing the Pseudomonas aeruginosa strain against ciprofloxacin or ofloxacin correctly reported the organism as resistant. Of 40 laboratories, 30 (75%) correctly reported resistant MICs or zone sizes for the imipenem- and meropenem-resistant Serratia marcescens. For the extended-spectrum β-lactamase (ESBL)-producing strain of Klebsiella pneumoniae, 18 (42%) of 43 laboratories testing ceftazidime correctly reported ceftazidime MICs in the resistant range. These results suggest that current testing generally produces accurate results, although some laboratories have difficulty detecting resistance to carbapenems and extended-spectrum cephalosporins. This highlights the need for monitoring how well susceptibility test systems in clinical laboratories detect emerging resistance.

Surveillance of antimicrobial use and antimicrobial resistance in United States hospitals: project ICARE phase 2. Project Intensive Care Antimicrobial Resistance Epidemiology (ICARE) hospitals.

The search for the means to understand and control the emergence and spread of antimicrobial resistance has become a public health priority. Project ICARE (Intensive Care Antimicrobial Resistance Epidemiology) has established laboratory-based surveillance for antimicrobial resistance and antimicrobial use at a subset of hospitals participating in the National Nosocomial Infection Surveillance system. These data illustrate that for most antimicrobial-resistant organisms studied, rates of resistance were highest in the intensive care unit (ICU) areas and lowest in the outpatient areas. A notable exception was ciprofloxacin- or ofloxacin-resistant Pseudomonas aeruginosa, for which resistance rates were highest in the outpatient areas. For most of the antimicrobial agents associated with this resistance, the rate of use was highest in the ICU areas, in parallel to the pattern seen for resistance. These comparative data on use and resistance among similar areas (i.e., ICU or other inpatient areas) can be used as a benchmark by participating hospitals to focus their efforts at addressing antimicrobial resistance.

Antimicrobial use and resistance in eight US hospitals: complexities of analysis and modeling. Intensive Care Antimicrobial Resistance Epidemiology Project and National Nosocomial Infections Surveillance System Hospitals.

To evaluate the relation between antimicrobial use and resistance in intensive-care unit (ICU) and non-ICU inpatient areas in eight US hospitals. We determined antimicrobial use in terms of defined daily doses, antimicrobial-use density (defined daily doses/1,000 patient days), and percentage resistance for five antimicrobial-organism combinations in the ICU and non-ICU inpatient areas of eight US hospitals participating in project Intensive Care Antimicrobial Resistance Epidemiology. Antimicrobial resistance and use varied tremendously among the eight hospitals. Antimicrobial resistance among these five nosocomial pathogens was significantly higher within the inpatient setting of these hospitals, compared with the outpatient setting. One hospital consistently ranked highest for use of all classes of antimicrobials examined. High antimicrobial use was not associated necessarily with high resistance for a particular antimicrobial-organism pair. Antimicrobial use varied significantly across these hospitals, but generally was higher in ICUs. These results suggest that concomitant surveillance of both antimicrobial resistance and antimicrobial use is helpful in interpreting antimicrobial resistance in a hospital or ICU and that further analysis is required to determine the role of variables other than antimicrobial use in a statistical model for predicting antimicrobial resistance.

Antimicrobial Use and Resistance in Eight US Hospitals: Complexities of Analysis and Modeling

Antimicrobial Use and Resistance in Eight US Hospitals: Complexities of Analysis and Modeling