Prediction rules to identify patients with methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci upon hospital admission

Clinical prediction tools for identifying antimicrobial-resistant organism (ARO) carriage on hospital admissions: a systematic review

BACKGROUND

Increasing prevalence of antimicrobial-resistant organisms (AROs) is a growing economic and healthcare challenge. Increasing utilization of electronic medical record (EMR) systems and improvements in computation and analytical techniques afford an opportunity to reduce the spread of AROs through the development of clinical prediction tools to identify ARO carriers on admission to hospital.

AIM

To identify existing clinical prediction tools for meticillin-resistant Staphylococcus aureus (MRSA) and carbapenemase-producing organisms (CPOs), their predictive performance, and risk factors utilized in these tools.

METHODS

The CHARMS checklist was followed. Medline, EMBASE, Cochrane SR, CRD databases (DARE, NHS EED), CINAHL and Web of Science were searched from database inception to 26^th July 2021. Full-text articles were assessed independently, and quality assessment was conducted using the Prediction Model Risk of Bias Assessment Tool.

FINDINGS

In total, 3809 abstracts were identified and 22 studies were included. Among these studies, risk score models were the most common prediction tool (N=16). Previous admission, recent antibiotic exposure, age and sex were the most common risk factors for ARO carriage. Prediction tools were commonly evaluated on sensitivity and specificity with ranges of 15-100% and 46-98.6%, respectively, for MRSA, and 30-81.3% and 79.8-99.9%, respectively, for CPOs.

CONCLUSION

There is no gold standard ARO prediction tool. However, high-performance clinical prediction tools and identification of key risk factors for the early detection of AROs exist. Risk score models are easier to use and interpret; however, with recent improvements in machine learning techniques, highly robust models can be developed with data stored in an EMR.

A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms

Background

The rising prevalence of multi-drug resistant organisms (MDROs), such as Methicillin-resistant Staphylococcus aureus (MRSA), Vancomycin-resistant Enterococci (VRE), and Carbapenem-resistant Enterobacteriaceae (CRE), is an increasing concern in healthcare settings.

Materials and Methods

Leveraging data from electronic healthcare records and a unique MDRO universal screening program, we developed a data-driven modeling framework to predict MRSA, VRE, and CRE colonization upon intensive care unit (ICU) admission, and identified the associated socio-demographic and clinical factors using logistic regression (LR), random forest (RF), and XGBoost algorithms. We performed threshold optimization for converting predicted probabilities into binary predictions and identified the cut-off maximizing the sum of sensitivity and specificity.

Results

Four thousand six hundred seventy ICU admissions (3,958 patients) were examined. MDRO colonization rate was 17.59% (13.03% VRE, 1.45% CRE, and 7.47% MRSA). Our study achieved the following sensitivity and specificity values with the best performing models, respectively: 80% and 66% for VRE with LR, 73% and 77% for CRE with XGBoost, 76% and 59% for MRSA with RF, and 82% and 83% for MDRO (i.e., VRE or CRE or MRSA) with RF. Further, we identified several predictors of MDRO colonization, including long-term care facility stay, current diagnosis of skin/subcutaneous tissue or infectious/parasitic disease, and recent isolation precaution procedures before ICU admission.

Conclusion

Our data-driven modeling framework can be used as a clinical decision support tool for timely predictions, characterization and identification of high-risk patients, and selective and timely use of infection control measures in ICUs.

Active surveillance at the time of hospital admission for multidrug-resistant microorganisms among patients who had recently been hospitalized at health care facilities

BACKGROUND

This study aimed to investigate the epidemiology of multidrug-resistant microorganism (MDRO) carriage at hospital admission and to identify risk factors for MDRO influx into hospital settings.

METHODS

This cohort study was conducted at a 1,051-bed university-affiliated hospital in the Republic of Korea between July 1 and December 31, 2017. Active surveillance for MDRO carriage was performed within 48 hours of hospitalization in all adult patients who had prior hospitalization within the preceding 3 months.

RESULTS

During the study, 575 patients were admitted with a hospitalization history within 3 months. Active surveillance at hospital admission was performed in 192 eligible patients. Thirty-three (17.2%) patients with MDRO carriage were identified from active surveillance. In the multivariate logistic regression analysis, prior exposure to antibiotics within 90 days, hospitalization for ≥60 days before admission, cognitive dysfunction, percutaneous drainage, and underlying pulmonary diseases were identified as independent risk factors for MDRO influx.

CONCLUSIONS

Our findings suggest a significant prevalence of MDRO acquisition at acute care hospital admission in patients who had been recently hospitalized. To control the spread of MDRO, collaborations among health care institutions and targeted screening at hospital admission according to patient risk factors are warranted.

Performance of an Easy and Simple New Scoring Model in Predicting Multidrug-Resistant Enterobacteriaceae in Community-Acquired Urinary Tract Infections

Background

Multidrug resistance (MDR) is a growing global problem in bacterial community-acquired urinary tract infections (CUTIs). We aimed to propose an easy-to-use clinical prediction model to identify patients with MDR in CUTI.

Methods

We conducted a retrospective study including 770 patients with documented CUTI diagnosed during 2010–2017. Logistic regression–based prediction scores were calculated based on variables independently associated with MDR. Sensitivities and specificities at various cutoff points were determined, and the area under the receiver operating characteristic curve (AUROC) was computed.

Results

We found MDR Enterobacteriaceae in 372 cases (45.1%). Multivariate analysis showed that age ≥70 years (adjusted odds ratio [aOR], 2.5; 95% confidence interval [CI], 1.8–3.5), diabetes mellitus (aOR, 1.65; 95% CI, 1.19–2.3), history of urinary tract surgery in the last 12 months (aOR, 4.5; 95% CI, 1.22–17), and previous antimicrobial therapy in the last 3 months (aOR, 4.6; 95% CI, 3–7) were independent risk factors of MDR in CUTI. The results of Hosmer-Lemshow chi-square testing were indicative of good calibration of the model (χ² = 3.4; P = .49). At a cutoff of ≥2, the score had an AUROC of 0.71, a sensitivity of 70.5%, a specificity of 60%, a positive predictive value of 60%, a negative predictive value of 70%, and an overall diagnostic accuracy of 65%. When the cutoff was raised to 6, the sensitivity dropped (43%), and the specificity increased appreciably (85%).

Conclusions

We developed a novel scoring system that can reliably identify patients likely to be harboring MDR in CUTI.

Research Methods in Healthcare Epidemiology and Antimicrobial Stewardship: Use of Administrative and Surveillance Databases

Administrative and surveillance data are used frequently in healthcare epidemiology and antimicrobial stewardship (HE&AS) research because of their wide availability and efficiency. However, data quality issues exist, requiring careful consideration and potential validation of data. This methods paper presents key considerations for using administrative and surveillance data in HE&AS, including types of data available and potential use, data limitations, and the importance of validation. After discussing these issues, we review examples of HE&AS research using administrative data with a focus on scenarios when their use may be advantageous. A checklist is provided to help aid study development in HE&AS using administrative data.

Infect Control Hosp Epidemiol 2016;1–10

Demographic and infection characteristics of patients with carbapenem-resistant Enterobacteriaceae in a community hospital: Development of a bedside clinical score for risk assessment

BACKGROUND

The objective of this study was to identify risk factors associated with the presence of carbapenem-resistant Enterobacteriaceae (CRE) infections to develop a clinical prediction model that can be used at patient bedside to identify subjects likely infected with a CRE pathogen.

METHODS

This case-control study included patients aged ≥18 years admitted to Novant Health Forsyth Medical Center between January 1, 2012, and December 31, 2013, with CRE infections (cases) or non-CRE infections (controls). Controls were matched to their corresponding resistant case (3:1) based on pathogen, place of likely acquisition, isolate source, year of admission, and level of care. A risk prediction model was developed using variables independently associated with CRE isolation. Sensitivities and specificities were obtained at various point cutoffs, and a determination of the receiver operator characteristic (ROC) area under the curve (AUC) was performed.

RESULTS

A total of 164 subjects were included. Independent risk factors for CRE included recent antibiotic therapy, recent immunosuppression, and Charlson Comorbidity Index score ≥4. Adjusted odds ratios were 13.37 (95% confidence interval [CI], 4.16-61.19), 6.69 (95% CI, 1.85-29.65), and 3.30 (95% CI, 1.34-8.40), respectively. Diagnostic performance of various score cutoffs for the model indicated a score ≥5 correlated with the highest accuracy (79%). The ROC AUC was 0.83.

CONCLUSION

The risk prediction model displayed good discrimination and was an excellent predictor of CRE infection.

Variable performance of models for predicting methicillin-resistant Staphylococcus aureus carriage in European surgical wards

Background

Predictive models to identify unknown methicillin-resistant Staphylococcus aureus (MRSA) carriage on admission may optimise targeted MRSA screening and efficient use of resources. However, common approaches to model selection can result in overconfident estimates and poor predictive performance. We aimed to compare the performance of various models to predict previously unknown MRSA carriage on admission to surgical wards.

Methods

The study analysed data collected during a prospective cohort study which enrolled consecutive adult patients admitted to 13 surgical wards in 4 European hospitals. The participating hospitals were located in Athens (Greece), Barcelona (Spain), Cremona (Italy) and Paris (France). Universal admission MRSA screening was performed in the surgical wards. Data regarding demographic characteristics and potential risk factors for MRSA carriage were prospectively collected during the study period. Four logistic regression models were used to predict probabilities of unknown MRSA carriage using risk factor data: “Stepwise” (variables selected by backward elimination); “Best BMA” (model with highest posterior probability using Bayesian model averaging which accounts for uncertainty in model choice); “BMA” (average of all models selected with BMA); and “Simple” (model including variables selected >50% of the time by both Stepwise and BMA approaches applied to repeated random sub-samples of 50% of the data). To assess model performance, cross-validation against data not used for model fitting was conducted and net reclassification improvement (NRI) was calculated.

Results

Of 2,901 patients enrolled, 111 (3.8%) were newly identified MRSA carriers. Recent hospitalisation and presence of a wound/ulcer were significantly associated with MRSA carriage in all models. While all models demonstrated limited predictive ability (mean c-statistics <0.7) the Simple model consistently detected more MRSA-positive individuals despite screening fewer patients than the Stepwise model. Moreover, the Simple model improved reclassification of patients into appropriate risk strata compared with the Stepwise model (NRI 6.6%, P = .07).

Conclusions

Though commonly used, models developed using stepwise variable selection can have relatively poor predictive value. When developing MRSA risk indices, simpler models, which account for uncertainty in model selection, may better stratify patients’ risk of unknown MRSA carriage.

Electronic Prediction Rules for Methicillin-ResistantStaphylococcus aureusColonization

Background.

Considerable hospital resources are dedicated to minimizing the number of methicillin-resistantStaphylococcus aureus(MRSA) infections. One tool that is commonly used to achieve this goal is surveillance for MRSA colonization. This process is costly, and false-positive test results lead to isolation of individuals who do not carry MRSA. The performance of this technique would improve if patients who are at high risk of colonization could be readily targeted.

Methods.

Five MRSA colonization prediction rules of varying complexity were derived in a population of 23,314 patients who were consecutively admitted to a US hospital and tested for colonization. Rules incorporated only prospectively collected, structured electronic data found in a patient's record within 1 day of hospital admission. These rules were tested in a validation cohort of 26,650 patients who were admitted to 2 other hospitals.

Results.

The prevalence of MRSA at hospital admission was 2.2% and 4.0% in the derivation and validation cohorts, respectively. Multivariable modeling identified predictors of MRSA colonization among demographic, admission-related, pharmacologic, laboratory, physiologic, and historical variables. Five prediction rules varied in their performance, but each could be used to identify the 30% of patients who accounted for greater than 60% of all cases of MRSA colonization and approximately 70% of all MRSA-associated patient-days. Most rules could also identify the 20% of patients with a greater than 8% chance of colonization and the 40% of patients among whom colonization prevalence was 2% or less.

Conclusions.

We report electronic prediction rules that can fully automate triage of patients for MRSA-related hospital admission testing and that offer significant improvements on previously reported rules. The efficiencies introduced may result in savings to infection control programs with little sacrifice in effectiveness.

Predictors of methicillin-resistant Staphylococcus aureus colonization at hospital admission

BACKGROUND

The best strategy for active surveillance for methicillin-resistant Staphylococcus aureus (MRSA) remains unclear. We attempted to identify a risk factor score to predict MRSA colonization at hospital admission.

METHODS

Data on 9 variables reported as risk factors for MRSA colonization were analyzed, and a risk factor score to predict MRSA colonization was generated using multivariable logistic regression and receiver operating characteristic curve analyses. This risk score was then prospectively validated.

RESULTS

Four risk factors (nursing home residence, diabetes, hospitalization in the past year, and chronic skin condition/infection) were significantly associated with MRSA colonization (c-statistic = 0.846). A cut-off score of 8 or greater would result in screening 20% of admissions and would detect 71% of MRSA-colonized patients. In the prospective validation study, a cut-off score of 8 or greater required screening 21% of admissions and detected 54% of MRSA. Nursing home residence was the best predictor of MRSA colonization.

CONCLUSION

A similar risk factor-based screening strategy could be used to predict MRSA colonization in other institutions. Our data support routine screening of nursing home patients at hospital admission.

Risk of acquiring extended-spectrum β-lactamase-producing Klebsiella species and Escherichia coli from prior room occupants in the intensive care unit

OBJECTIVE. To quantify the association between admission to an intensive care unit (ICU) room most recently occupied by a patient positive for extended-spectrum β-lactamase (EBSL)-producing gram-negative bacteria and acquisition of infection or colonization with that pathogen. DESIGN. Retrospective cohort study. SETTING AND PATIENTS. The study included patients admitted to medical and surgical ICUs of an academic medical center between September 1, 2001, and June 30, 2009. METHODS. Perianal surveillance cultures were obtained at admission to the ICU, weekly, and at discharge from the ICU. Patients were included if they had culture results that were negative for ESBL-producing gram-negative bacteria at ICU admission and had an ICU length of stay longer than 48 hours. Pulsed-field gel electrophoresis (PFGE) was performed on ESBL-positive isolates from patients who acquired the same bacterial species (eg, Klebsiella species or Escherichia coli) as the previous room occupant. RESULTS. Among 9,371 eligible admissions (7,651 unique patients), 267 (3%) involved patients who acquired an ESBL-producing pathogen in the ICU; of these patients, 32 (12%) were hospitalized in a room in which the prior occupant had been positive for ESBL. Logistic regression results suggested that the prior occupant's ESBL status was not significantly associated with acquisition of an ESBL-producing pathogen (adjusted odds ratio, 1.39 [95% confidence interval, 0.94-2.08]) after adjusting for colonization pressure and antibiotic exposure in the ICU. PFGE results suggested that 6 (18%) of 32 patients acquired a bacterial strain that was the same as or closely related to the strain obtained from the prior occupant. CONCLUSIONs. These data suggest that environmental contamination may not play a substantial role in the transmission of ESBL-producing pathogens among ICU patients. Intensifying environmental decontamination may be less effective than other interventions in preventing transmission of ESBL-producing pathogens.

Utility of a clinical risk factor scoring model in predicting infection with extended-spectrum β-lactamase-producing enterobacteriaceae on hospital admission

OBJECTIVE

To validate the utility of a previously published scoring model (Italian) to identify patients infected with community-onset extended-spectrum β-lactamase-producing Enterobacteriaceae (ESBL-EKP) and develop a new model (Duke) based on local epidemiology.

METHODS

This case-control study included patients 18 years of age or more admitted to Duke University Hospital between January 1, 2008, and December 31, 2010, with culture-confirmed infection due to an ESBL-EKP (cases). Uninfected controls were matched to cases (3:1). The Italian model was applied to our patient population for validation. The Duke model was developed through logistic-regression-based prediction scores calculated on variables independently associated with ESBL-EKP isolation. Sensitivities and specificities at various point cutoffs were determined, and determination of the area under the receiver operating characteristic curve (ROC AUC) was performed.

RESULTS

A total of 123 cases and 375 controls were identified. Adjusted odds ratios and 95% confidence intervals for variables previously identified in the Italian model were as follows: hospitalization (3.20 [1.62-6.55]), transfer (4.31 [2.15-8.78]), urinary catheterization (5.92 [3.09-11.60]), β-lactam and/or fluoroquinolone therapy (3.76 [2.06-6.95]), age 70 years or more (1.55 [0.79-3.01]), and Charlson Comorbidity Score of 4 or above (1.06 [0.55-2.01]). Sensitivity and specificity were, respectively, more than or equal to 95% and less than or equal to 47% for scores 3 or below and were less than or equal to 50% and more than or equal to 96% for scores 8 or above. The ROC AUC was 0.88. Variables identified in the Duke model were as follows: hospitalization (2.63 [1.32-5.41]), transfer (5.30 [2.67-10.71]), urinary catheterization (6.89 [3.62-13.38]), β-lactam and/or fluoroquinolone therapy (3.47 [1.91-6.41]), and immunosuppression (2.34 [1.14-4.80]). Sensitivity and specificity were, respectively, more than or equal to 94% and less than or equal to 65% for scores 3 or below and were less than or equal to 58% and more than or equal to 95% for scores 8 or above. The ROC AUC was 0.89.

CONCLUSION

While the previously reported model was an excellent predictor of community-onset ESBL-EKP infection, models utilizing factors based on local epidemiology may be associated with improved performance.

A comparison of methicillin-resistant and methicillin-susceptible Staphylococcus aureus reveals no clinical and epidemiological but molecular differences

Most studies on Staphylococcus aureus have focused on the molecular epidemiology of methicillin-resistant S. aureus (MRSA) infections. In contrast, little information is available regarding the molecular epidemiology of currently circulating methicillin-susceptible S. aureus (MSSA) isolates in hospital settings, an epoch when the epidemiology of S. aureus has undergone significant changes. We conducted a cross-sectional study to compare the clinical, epidemiological, and genetic characteristics of MSSA and MRSA isolates at 3 tertiary-care hospitals in Medellín, Colombia, from February 2008 to June 2010. The infections were classified according to the Centers for Disease Control and Prevention (CDC) definitions. Genotypic analysis included spa typing, multilocus sequence typing (MLST) and staphylococcal cassette chromosome (mec) (SCCmec) typing. A total of 810 patients was enrolled. One hundred infections (12.3%) were classified as community-associated (31 CA-MSSA, 69 CA-MRSA), 379 (46.8%) as healthcare-associated community-onset (136 HACO-MSSA, 243 HACO-MRSA), and 331 (40.9%) as healthcare-associated hospital-onset (104 HAHO-MSSA, 227 HAHO-MRSA). Genotype analyses showed a higher diversity and a more varied spa type repertoire in MSSA than in MRSA strains. Most of the clinical-epidemiological characteristics and risk factors evaluated did not allow for discriminating MRSA- from MSSA-infected patients. The lack of equivalence among the genetic backgrounds of the major MSSA and MRSA clones would suggest that the MRSA clones are imported instead of arising from successful MSSA clones. This study emphasizes the importance of local surveillance to create public awareness on the changing S. aureus epidemiology.

Infecção ou colonização por micro-organismos resistentes: identificação de preditores

OBJETIVO: Identificar os fatores preditores de infecção ou colonização por micro-organismos resistentes. MÉTODOS: Foi realizado estudo quantitativo de coorte prospectivo. Foram realizadas a análise descritiva, para conhecimento da população do estudo, e a análise discriminante, para identificação dos fatores preditores. RESULTADOS: Foram incluídos 85 pacientes com infecções por micro-organismos resistentes: Pseudomonas aeruginosas resistente aos carbapenêmicos (24,7%), Acinetobacter resistente aos carbapenêmicos (21,2%), Staphylococcus aureus resistente à meticilina (25,9%), Enterococcus spp. resistente à vancomicina (17,6%) e Klebsiella pneumoniae resistente aos carbapenêmicos (10,6%). A análise discriminante identificou transferências de outros hospitais e internação na Unidade de Terapia Intensiva como fatores preditores para ocorrência de infecção pelos grupos S. aureus resistente à meticilina, Acinetobacter resistente aos carbapenêmicos e K. pneumoniae resistente aos carbapenêmicos. Nenhuma das variáveis estudadas foi discriminante para Enterococcus spp. resistente à vancomicina e P. aeruginosas resistente aos carbapenêmico. CONCLUSÃO: Os fatores preditores encontrados foram: internação na UTI e a transferências de outros hospitais.

Risk factors for previously unknown meticillin-resistant Staphylococcus aureus carriage on admission to 13 surgical wards in Europe

BACKGROUND

Early identification of meticillin-resistant Staphylococcus aureus (MRSA) carriers may be helpful for clinical and epidemiological reasons.

AIM

To identify and compare risk factors of previously unknown MRSA carriage on admission to 13 surgical wards in France, Greece, Italy, and Spain.

METHODS

The study was a prospective observational cohort study which enrolled consecutive patients screened for MRSA on admission to surgical wards. Sociodemographic data, comorbidities and possible risk factors for MRSA were recorded. A multivariate logistic regression model was used to predict probabilities of previously unknown MRSA colonization on admission based on patient characteristics. Prediction rules for MRSA carriage were developed and evaluated using the c-statistic.

FINDINGS

Of 2901 patients enrolled, admission screening identified 111 (3.8%) new MRSA carriers. Independent risk factors for MRSA carriage were urinary catheterization (odds ratio: 4.4; 95% confidence interval: 2.0-9.9), nursing home residency (3.8; 1.9-7.7), chronic skin disease (2.9; 1.5-5.8), wounds/ulcers (2.4; 1.5-4.0), recent hospitalization (2.2; 1.5-3.3), diabetes (1.6, 1.02-2.5), and age >70 years (1.5; 1.03-2.3). However, risk factors varied between centres. The c-statistic for the common prediction rule for all centres was 0.64, indicating limited predictive power.

CONCLUSIONS

Risk profiles for MRSA carriers vary between surgical wards in European countries. Identifying local risk factors is important, as a common European prediction rule was found to be of limited clinical value.

Clinical prediction rule for identifying patients with vancomycin-resistant enterococci (VRE) at the time of admission to the intensive care unit in a low VRE prevalence setting

OBJECTIVES

The purpose of this study was to develop and validate a clinical prediction rule to screen patients at risk of vancomycin-resistant enterococci (VRE) carriage at intensive care unit (ICU) admission in a hospital setting with low VRE prevalence.

METHODS

This study was retrospectively conducted in the ICUs of a university-affiliated hospital in Korea, where active surveillance cultures for VRE had been run at ICU admission and weekly thereafter. In the derivation cohort from April 2008 to September 2010, risk factors for VRE carriage at ICU admission were determined and assigned weighted point values using a multivariate logistic regression model. In the validation cohort from October 2010 to March 2011, predictability of the prediction rule was evaluated.

RESULTS

Of a total of 4445 cultures taken from patients at ICU admission, 153 (3.4%) patients carried VRE. In the derivation cohort, independent risk factors (assigned points) for VRE carriage at ICU admission were ICU readmission during hospitalization (1 point), chronic obstructive lung disease (2 points), recent antibiotic treatment (3 points) and recent vancomycin use (2 points). In the validation cohort, the sensitivity, specificity, and positive and negative predictive values of the prediction rule, on the basis of risk scores ≥3 points, were 84.2%, 82.5%, 15.2% and 99.3%, respectively.

CONCLUSIONS

This clinical prediction rule for identifying VRE carriage at the time of ICU admission is expected to markedly reduce the screening volume (by 80.1%) in our healthcare facility. For use in clinical practice, the rule needs to be prospectively validated in other settings.

Long-term care facilities: important participants of the acute care facility social network?

BACKGROUND

Acute care facilities are connected via patient sharing, forming a network. However, patient sharing extends beyond this immediate network to include sharing with long-term care facilities. The extent of long-term care facility patient sharing on the acute care facility network is unknown. The objective of this study was to characterize and determine the extent and pattern of patient transfers to, from, and between long-term care facilities on the network of acute care facilities in a large metropolitan county.

METHODS/PRINCIPAL FINDINGS

We applied social network constructs principles, measures, and frameworks to all 2007 annual adult and pediatric patient transfers among the healthcare facilities in Orange County, California, using data from surveys and several datasets. We evaluated general network and centrality measures as well as individual ego measures and further constructed sociograms. Our results show that over the course of a year, 66 of 72 long-term care facilities directly sent and 67 directly received patients from other long-term care facilities. Long-term care facilities added 1,524 ties between the acute care facilities when ties represented at least one patient transfer. Geodesic distance did not closely correlate with the geographic distance among facilities.

CONCLUSIONS/SIGNIFICANCE

This study demonstrates the extent to which long-term care facilities are connected to the acute care facility patient sharing network. Many long-term care facilities were connected by patient transfers and further added many connections to the acute care facility network. This suggests that policy-makers and health officials should account for patient sharing with and among long-term care facilities as well as those among acute care facilities when evaluating policies and interventions.

Risk factors for positive admission surveillance cultures for methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci in a neurocritical care unit

OBJECTIVE

Hospitals are under increasing pressure to perform active surveillance cultures for methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus. This study aimed to identify patients at low and high risk for positive admission surveillance cultures for methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus in a neurocritical care unit using readily ascertainable historical factors.

DESIGN

Before/after study with nested case/control study.

SETTING

Neurocritical care unit of an academic hospital.

PATIENTS

During the intervention period (July 2007 to June 2008), after implementation of an admission surveillance culture screening program for methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus, 2,059 patients were admitted to the neurocritical care unit for a total of 5,957 patient days.

INTERVENTIONS

Cases had positive methicillin-resistant Staphylococcus aureus or vancomycin-resistant Enterococcus admission surveillance cultures within 48 hrs of hospital admission. Controls had negative cultures.

MEASUREMENTS AND MAIN RESULTS

Admission surveillance cultures grew methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus in 35 of 823 (4.3%) and 19 of 766 (2.5%) patients, respectively. Factors significantly associated with both methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus colonization were intravenous antibiotics and hospitalization in the past year, immunocompromised health status, intravenous drug use, long-term hemodialysis, and known prior carrier status. Transfer from an outside hospital and residence in a long-term care facility in the past year were associated with vancomycin-resistant Enterococcus colonization. Classification and regression tree analysis was used to identify variables that best predicted positive methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus surveillance cultures. A classification and regression tree model with six of these variables yielded an overall cross-validated predictive accuracy of 87.12% to detect methicillin-resistant Staphylococcus aureus colonization. For vancomycin-resistant Enterococcus, a four-variable classification and regression tree model (intravenous antibiotics, hospitalization and long-term patient care in the past year, and not being "admitted same day of procedure") optimized the predictive accuracy (94.91%). There were no cases of vancomycin-resistant Enterococcus colonization in patients admitted same day of procedure.

CONCLUSIONS

Colonization with methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus in neurocritical care patients can be predicted with a high predictive accuracy using decision trees that include four to six readily attainable risk factors. In our setting, in the absence of these risk factors and in patients admitted from home for neurosurgical procedures, routine admission surveillance cultures to the intensive care unit may not be cost-effective.

Identifying patients harboring extended-spectrum-beta-lactamase-producing Enterobacteriaceae on hospital admission: derivation and validation of a scoring system

Increases in community-acquired infections caused by extended-spectrum-β-lactamase (ESBL)-producing Enterobacteriaceae have important implications for hospital infection control and empirical antibiotic therapy protocols. We developed and validated a tool for identifying patients harboring these organisms at hospital admission. We retrospectively analyzed chart data for 849 adult inpatients. The derivation cohort included 339 patients admitted to a large hospital in Rome during 2008, with (n = 113) or without (n = 226) culture positivity for ESBL-producing Escherichia coli, Klebsiella spp., or Proteus mirabilis within 48 h after admission. Logistic-regression-based prediction scores were calculated based on variables independently associated with the outcome. The model was validated in a second cohort (n = 510) selected with identical criteria in hospitals in Genoa and Turin during 2009. Prediction scores were based on the following six variables (reported with odds ratio for study outcome and the 95% confidence intervals in brackets): recent (≤ 12 months before admission) hospitalization (5.69 [2.94 to 10.99]), transfer from another health care facility (5.61 [1.65 to 19.08]), Charlson comorbidity score ≥ 4 (3.80 [1.90 to 7.59]), recent (≤ 3 months before admission) β-lactam and/or fluoroquinolone treatment (3.68 [1.96 to 6.91]), recent urinary catheterization (3.52 [1.96 to 6.91]), and age ≥ 70 years (3.20 [1.79 to 5.70]). The model displayed good calibration and good-to-excellent discrimination in the derivation and validation sets (Hosmer-Lemshow χ(2) = 15.28 and 14.07; P = 0.17 and 0.23; areas under the receiver-operating characteristic curve, 0.83 and 0.92). It reliably identified patients likely to be harboring ESBL-producing Enterobacteriaceae at hospital admission who may need special infection control measures. Further study is needed to confirm this model's potential as a guide for prescribing empirical antibiotic therapy.

Targeted surveillance of methicillin-resistant Staphylococcus aureus and its potential use to guide empiric antibiotic therapy

The present study aimed to determine the frequency of methicillin-resistant Staphylococcus aureus (MRSA)-positive clinical culture among hospitalized adults in different risk categories of a targeted MRSA active surveillance screening program and to assess the utility of screening in guiding empiric antibiotic therapy. We completed a prospective cohort study in which all adults admitted to non-intensive-care-unit locations who had no history of MRSA colonization or infection received targeted screening for MRSA colonization upon hospital admission. Anterior nares swab specimens were obtained from all high-risk patients, defined as those who self-reported admission to a health care facility within the previous 12 months or who had an active skin infection on admission. Data were analyzed for the subcohort of patients in whom an infection was suspected, determined by (i) receipt of antibiotics within 48 h of admission and/or (ii) the result of culture of a sample for clinical analysis (clinical culture) obtained within 48 h of admission. Overall, 29,978 patients were screened and 12,080 patients had suspected infections. A total of 46.4% were deemed to be at high risk on the basis of the definition presented above, and 11.1% of these were MRSA screening positive (colonized). Among the screening-positive patients, 23.8% had a sample positive for MRSA by clinical culture. Only 2.4% of patients deemed to be at high risk but found to be screening negative had a sample positive for MRSA by clinical culture, and 1.6% of patients deemed to be at low risk had a sample positive for MRSA by clinical culture. The risk of MRSA infection was far higher in those who were deemed to be at high risk and who were surveillance culture positive. Targeted MRSA active surveillance may be beneficial in guiding empiric anti-MRSA therapy.

Effectiveness of universal screening for vancomycin-resistant enterococcus and methicillin-resistant Staphylococcus aureus on admission to a burn-trauma step-down unit

Vancomycin-resistant enterococcus (VRE) and methicillin-resistant Staphylococcus aureus (MRSA) are significant healthcare-associated pathogens. We sought to identify factors that could be used to predict which patients carry or are infected with VRE or MRSA on admission so that we could obtain cultures selectively from high-risk patients on our burn-trauma unit. We conducted a case-control study of patients admitted to our burn-trauma unit from September 2000 to March 2005 who were colonized or infected with either VRE or MRSA (cases) and patients who were not colonized or infected with one of these organisms (controls). We used logistic regression to construct a model that we subsequently validated based on data collected prospectively from patients admitted from September 2006 to August 2007. In the case-control study, colonization or infection with MRSA or VRE on admission were independently associated with the total days of antimicrobial treatment, age, prior hospitalization, prior operations, and admitting diagnosis (admission for a burn injury was protective). In the cohort study, a prior hospitalization with a length of stay>or=7 days and operations within the past 6 months were significantly associated with colonization or infection on admission. The latter model was 59.3% sensitive. If, we used this model to identify which patients should be cultured on admission, we would have missed 24 (39.3%) of the colonized or infected patients. These patients would not have been placed in isolation (434 missed isolation days, 71.0%) and may have been the source of transmission to other patients. Our model lacked the sensitivity to identify patients colonized or infected with VRE or MRSA. We recommend that units, which care for patients who are at high risk of hospital-acquired infection and having prevalence and transmission rates of VRE or MRSA similar to those in our study, screen all patients for these organisms on admission to the unit.

Acquisition of vancomycin-resistant enterococci in internal medicine wards

BACKGROUND

Our institution experienced an increase in the frequency of vancomycin-resistant enterococci (VRE) clinical isolates, which rose 5-fold from 2004 to 2005. We sought to measure the prevalence of VRE carriage among medical inpatients in a tertiary hospital in Jerusalem and estimate the rate of acquisition during hospitalization.

METHODS

During 2006, we performed 3 cross-sectional surveys, including 1039 patients, representing 3 phases of hospitalization: admission, hospital stay, and discharge. Perianal/stool samples were cultured for VRE.

RESULTS

VRE carriage was 3.8% (95% confidence interval [CI] = 1.8% to 6.9%) on admission, 15% (95% CI = 9% to 23%) at discharge, and 32% (95% CI = 24% to 40%) among inpatients. Among inpatient carriers, 60% of the isolates represented a single strain. Recent previous hospitalization was the most significant predictor for identifying carriers on admission.

CONCLUSIONS

Our study demonstrates that substantial VRE transmission occurred during hospitalization. Identification of carriers on admission should supplement effective application of infection control methods in attempting to decrease VRE nosocomial spread and burden.

Development of a prediction rule for methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococcus carriage in a Veterans Affairs Medical Center population

A history of hospital admission in the prior year was the most sensitive predictor of methicillin-resistant Staphylococcus aureus or vancomycin-resistant Enterococcus colonization at admission to a Veterans Affairs Medical Center (VAMC) but missed more than one-third of carriers and required screening more than one-half of admitted patients.

Validation study of artificial neural network models for prediction of methicillin-resistant Staphylococcus aureus carriage

OBJECTIVE

Use of active surveillance cultures for methicillin-resistant Staphylococcus aureus (MRSA) for all patients admitted to the intensive care unit has been shown to reduce nosocomial transmission. However, the cost-effectiveness and the utility of implementing use of active surveillance cultures nationwide remain controversial. We sought to develop an artificial neural network (ANN) model that would predict the likelihood of MRSA colonization.

SETTING

Two acute care hospitals, one in Pittsburgh (hospital A) and one in Kaohsiung, Taiwan (hospital B).

METHODS

Nasal cultures were performed for all patients admitted to the hospitals. A total of 46 potential risk factors in hospital A and 86 potential risk factors in hospital B associated with MRSA colonization were assessed. Culture results were obtained; 75% of the data were used for training our ANN model, and the remaining 25% were used for validating our ANN model. The culture results were the "gold standard" for determining the accuracy of the model predictions.

RESULTS

The ANN model predictions were accurate 95.2% of the time for hospital A (sensitivity, 94.3%; specificity, 96.0%) and 94.2% of the time for hospital B (sensitivity, 96.6%; specificity, 91.8%), integrating all potential risk factors into the model. Only 17 potential risk factors were needed for the hospital A ANN model (accuracy, 90.9%; sensitivity, 98.5%; specificity, 83.4%), and only 20 potential risk factors were needed for the hospital B ANN model (accuracy, 90.5%; sensitivity, 96.6%; specificity, 84.3%), if the minimal risk factor method was used. Cross-validation analysis showed an average accuracy of 85.6% (sensitivity, 91.3%; specificity, 80.0%).

CONCLUSION

Our ANN model can be used to predict with an accuracy of more than 90% which patients carry MRSA. The false-negative rates were significantly lower than the false-positive rates in the ANN predictions, which can serve as a safety buffer in case of patient misclassification.

Analyzing pathogen transmission in the dialysis unit: time for a (schedule) change?

BACKGROUND AND OBJECTIVES

Infectious diseases and antimicrobial-resistant microorganisms are a growing problem for the dialysis population. The frequency of patient visits and intimate, prolonged physical contact with the inanimate environment during dialysis treatments make these facilities potentially efficient venues for nosocomial pathogen transmission. Isolation measures and infection control practices can be inconvenient and consume limited resources. Quantitative tools for analyzing the effects of different containment strategies can help to identify optimal strategies for further study. However, spatial and temporal considerations germane to the dialysis unit greatly complicate analyses relying on conventional mathematical approaches.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

A stochastic, individual-based, Monte Carlo simulation tool that predicts the effects of various infection control strategies on pathogen dissemination through the dialysis unit in the face of diagnostic uncertainty was developed. The model was configured to emulate a medium-sized dialysis unit. The predicted consequences of various policies for scheduling patients who were suspected of being infectious were then explored, using literature-based estimates of pathogen transmissibility, prevalence, and diagnostic uncertainty.

RESULTS

Environmental decontamination was predicted to be of paramount importance in limiting pathogen dissemination. Temporal segregation (scheduling patients who were suspected of being infectious to dialysis shifts that are later in the day) was predicted to have the greatest effectiveness in reducing transmission, given adequate environmental decontamination between successive days.

CONCLUSIONS

Decontamination of the patient's environment (chair) can markedly attenuate pathogen dissemination. Temporal segregation could be a simple, low-cost, system-level intervention with significant potential to reduce nosocomial transmission in the dialysis unit.

Prevalence of and risk factors for methicillin-resistant Staphylococcus aureus carriage at hospital admission

To determine the prevalence of and risk factors for methicillin-resistant Staphylococcus aureus (MRSA) carriage at the time of admission to our hospital, we screened the medical records of 1,128 patients for demographic and clinical data. The antimicrobial resistance pattern and genotype of MRSA isolates were studied. The prevalence of MRSA carriage at hospital admission was 1.4%. Older patients and patients previously admitted to healthcare centers were the most likely to have MRSA carriage at admission.

Risk scoring and bloodstream infections

Risk-scoring systems are utilised in patients with bloodstream infections (BSI) to quantify disease-associated morbidity and mortality based on simple clinical or laboratory data usually obtained early in the course of illness. In order to reduce BSI-associated mortality, specific scores were elaborated to allow early diagnosis and prompt and appropriate antibiotic therapy. Risk scoring was also successfully derived and validated to identify patients at higher risk for antibiotic-resistant BSI, or colonisation, mainly due to methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci. However, a major limitation of risk-scoring systems is the relevance to the local epidemiological environment and the difficulty in generalising results from a single study. Intelligence technology recently utilised scores to predict risks for specific pathogens causing BSI. An example of this innovation, the TREAT system, was able to significantly reduce mortality, length of hospitalisation and costs in patients with BSI. New randomised clinical trials are needed to study the efficacy of clinical scores in reducing BSI-associated morbidity and mortality.

Predictors of Vancomycin-resistant Enterococcus (VRE) Carriage in the First Major VRE Outbreak in Singapore

Introduction: Until recently, vancomycin-resistant enterococcus (VRE) infection or colonisation was a rare occurrence in Singapore. The first major VRE outbreak involving a 1500-bed tertiary care institution in March 2005 presented major challenges in infection control and came at high costs. This study evaluates the predictors of VRE carriage based on patients’ clinical and demographic profiles. Materials and Methods: Study patients were selected from the hospital inpatient census population during the VRE outbreak (aged 16 years or more). Clinical information from 84 cases and 377 controls were analysed. Results: Significant predictors of VRE carriage included: age >65 years [Odds ratio (OR), 1.98; 95% CI (confidence interval), 1.14 to 3.43); female gender (OR, 2.15; 95% CI, 1.27 to 3.65); history of diabetes mellitus (OR, 1.94; 95% CI, 1.14 to 3.30), and staying in a crowded communal ward (OR, 2.75; 95% CI, 1.60 to 4.74). Each additional day of recent hospital stay also posed increased risk (OR, 1.03; 95% CI, 1.01 to 1.04). Conclusion: Elderly diabetic females with prolonged hospitalisation in crowded communal wards formed the profile that significantly predicted VRE carriage in this major hospital-wide outbreak of VRE in Singapore. It is imperative that active VRE surveillance and appropriate infection control measures be maintained in these wards to prevent future VRE outbreaks. Key words: Colonisation, Hospital-acquired, Infection

Value of performing active surveillance cultures on intensive care unit discharge for detection of methicillin-resistant Staphylococcus aureus

OBJECTIVE

To quantify the value of performing active surveillance cultures for detection of methicillin-resistant Staphylococcus aureus (MRSA) on intensive care unit (ICU) discharge.

DESIGN

Prospective cohort study.

SETTING

Medical ICU (MICU) and surgical ICU (SICU) of a tertiary care hospital.

PARTICIPANTS

We analyzed data on adult patients who were admitted to the MICU or SICU between January 17, 2001, and December 31, 2004. All participants had a length of ICU stay of at least 48 hours and had surveillance cultures of anterior nares specimens performed on ICU admission and discharge. Patients who had MRSA-positive clinical cultures in the ICU were excluded.

RESULTS

Of 2,918 eligible patients, 178 (6%) were colonized with MRSA on ICU admission, and 65 (2%) acquired MRSA in the ICU and were identified by results of discharge surveillance cultures. Patients with MRSA colonization confirmed by results of discharge cultures spent 853 days in non-ICU wards after ICU discharge, which represented 27% of the total number of MRSA colonization-days during hospitalization in non-ICU wards for patients discharged from the ICU.

CONCLUSIONS

Surveillance cultures of nares specimens collected at ICU discharge identified a large percentage of MRSA-colonized patients who would not have been identified on the basis of results of clinical cultures or admission surveillance cultures alone. Furthermore, these patients were responsible for a large percentage of the total number of MRSA colonization-days during hospitalization in non-ICU wards for patients discharged from the ICU.

Impact of empiric antibiotic therapy on outcomes in patients with Pseudomonas aeruginosa bacteremia

The impact of appropriate empirical antimicrobial therapy for Pseudomonas aeruginosa bacteremia on patient outcomes has not been clearly established. We assessed the effect of appropriate empirical therapy on in-hospital mortality and length of stay (LOS) among patients with P. aeruginosa bacteremia. This was a retrospective cohort study of inpatients with a positive blood culture for P. aeruginosa between January 2001 and June 2005. Empirical therapy was defined as appropriate if the patient received an antibiotic the organism was susceptible to between 8 h before culture collection and the time the susceptibility results were available. The severity of the illness was measured 24 h before culture collection. The data were analyzed using logistic regression (in-hospital mortality) and linear regression (LOS). Overall, there were 167 episodes of P. aeruginosa bacteremia, 123 (86%) of which received appropriate empirical antibiotics. Sixty-one patients died (36.5%). The median time from culture collection to susceptibility results was 3.4 days. After we adjusted for age, severity of illness, and time at risk, we found that the appropriate empirical therapy was not significantly associated with mortality (odds ratio = 0.96; 95% confidence interval = 0.31 to 2.93). There was a 7% reduction in the mean LOS for patients who had received appropriate therapy at the time susceptibility results were available compared to those who did not (P = 0.74). These data suggest that the use of appropriate empirical therapy, i.e., before susceptibility results are known may not be as critical to patient outcomes as other studies have suggested.

Comorbidity risk-adjustment measures were developed and validated for studies of antibiotic-resistant infections

OBJECTIVES

Comorbidities are often included in risk-factor models for nosocomial antibiotic-resistant bacterial infections, and aggregate comorbidity measures are valuable because they allow one variable to represent many. This study aimed to develop new aggregate comorbidity measures based upon the Chronic Disease Score (CDS) for assessing the comorbidity-attributable risk of methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) nosocomial infections.

STUDY DESIGN AND SETTING

For each outcome, two retrospective cohort studies of hospitalized patients were conducted. Outcomes were a first MRSA or VRE positive clinical culture obtained 48 hours or more postadmission. Each cohort was divided into development (July 1998-2001) and validation (August 2001-2003) samples. New comorbidity measures were created for MRSA (CDS-MRSA), VRE (CDS-VRE), or any nosocomial infection outcome (CDS-ID) using logistic regression and subsequently validated. Model discrimination was measured using the c-statistic.

RESULTS

Discrimination of the CDS-MRSA (c=0.60), CDS-VRE (c=0.65), and CDS-ID (MRSA: c=0.57; VRE: c=0.64) was greater than that of the original CDS (MRSA: c=0.52; VRE: c=0.57).

CONCLUSION

The CDS-MRSA, CDS-VRE, and CDS-ID are new infectious disease specific comorbidity risk-adjustment measures that will be useful for the quality of future epidemiologic studies of MRSA, VRE, and other infectious diseases.

Pathogen transmission and clinic scheduling

We developed a model of pathogen dissemination in the outpatient clinic that incorporates key kinetic aspects of the transmission process, as well as uncertainty regarding whether or not each incident patient is contagious. Assigning appointments late in the day to patients suspected of being infectious should decrease pathogen dissemination.

Evaluating the probability of previously unknown carriage of MRSA at hospital admission

PURPOSE

We determined the prevalence and risk profile of patients with previously unknown carriage of methicillin-resistant Staphylococcus aureus (MRSA) at hospital admission.

SUBJECTS AND METHODS

We conducted a 7-month, prospective case-controlled study in adult inpatients admitted to a university hospital with endemic MRSA. Multivariate conditional logistic regression for data sets matched 1:4 was performed to identify the risk profile of newly identified MRSA carriers.

RESULTS

Overall, 399 of 12072 screened admissions (prevalence, 3.3%) were found colonized (n = 368, 92%) or infected (n = 31, 8%) with MRSA. In 204 cases (prevalence, 1.7%), MRSA carriage was newly identified. Without screening on admission, 49% (196/399) of MRSA carriers would have been missed. We identified nine independent risk factors for newly identified MRSA carriage at admission (adjusted odds ratio): male sex (1.9); age greater than 75 years (2.0); receipt of fluoroquinolones (2.7), cephalosporins (2.1), and carbapenems (3.2) in the last 6 months; previous hospitalization (1.9) or intravenous therapy (1.7) during the last 12 months; urinary catheter at admission (2.0); and intrahospital transfer (2.4). A risk score (range, 0-13) was calculated by adding points assigned to these variables. On the basis of analysis of 1006 patients included in the case-controlled study, the probability of MRSA carriage was 8% (28/342) in patients with a low score (< or =1), 19% (92/482) in patients with an intermediate score (2-4), and 46% (84/182) in patients with a high score (> or =5). The risk score had good discrimination (c-statistic, 0.73) and showed excellent calibration (P = .88).

CONCLUSIONS

On-admission prevalence of previously unknown MRSA carriers was high. Applying the risk score to newly admitted patients with an intermediate or high probability of MRSA carriage could allow a more effective MRSA control strategy.

Guidelines for the prophylaxis and treatment of methicillin-resistant Staphylococcus aureus (MRSA) infections in the UK

These evidence-based guidelines have been produced after a literature review of the treatment and prophylaxis of methicillin-resistant Staphylococcus aureus (MRSA) infection. The guidelines were further informed by antibiotic susceptibility data on MRSA from the UK. Recommendations are given for the treatment of common infections caused by MRSA, elimination of MRSA from carriage sites and prophylaxis of surgical site infection. There are several antibiotics currently available that are suitable for use in the management of this problem and potentially useful new agents are continuing to emerge.

Methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococci co-colonization

High prevalence of co-colonization increases risk for colonization or infection by vancomycin-resistant Staphylococcus aureus.

We assessed the prevalence, risk factors, and clinical outcomes of patients co-colonized with vancomycin-resistant enterococci (VRE) and methicillin-resistant Staphylococcus aureus (MRSA) upon admission to the medical and surgical intensive care units (ICUs) of a tertiary-care facility between January 1, 2002, and December 31, 2003. Co-colonization was defined as a VRE-positive perirectal surveillance culture with an MRSA-positive anterior nares surveillance culture collected concurrently. Among 2,440 patients, 65 (2.7%) were co-colonized. Independent risk factors included age (odds ratio [OR] 1.03, 95% confidence interval [CI] 1.01–1.05), admission to the medical ICU (OR 4.38, 95% CI 2.46–7.81), male sex (OR 1.93, 95% CI 1.14–3.30), and receiving antimicrobial drugs on a previous admission within 1 year (OR 3.06, 95% CI 1.85–5.07). None of the co-colonized patients would have been identified with clinical cultures alone. We report a high prevalence of VRE/MRSA co-colonization upon admission to ICUs at a tertiary-care hospital.

Epidemiology and mechanisms of glycopeptide resistance in enterococci

PURPOSE OF REVIEW

This review updates epidemiologic trends and our understanding of glycopeptide resistance in enterococci.

RECENT FINDINGS

Colonization and infection rates with vancomycin resistant enterococci continue to increase throughout the world while factors contributing to this rise continue to be defined. While no interventions exist to eradicate colonization, infection control procedures are cost effective and decrease the prevalence of vancomycin resistant enterococcal colonization and infection. New molecular methods show great promise in strengthening our ability to detect colonization with these bacteria. Furthermore, our understanding of the origin of vancomycin resistant enterococci continues to grow. Paenibacillus species found in soil have been found to carry homologues of vanA-associated glycopeptide resistance genes found in enterococci. Also, additional evidence supports previous data that VanB-associated resistance may have been horizontally transferred from gastrointestinal tract bacteria to enterococci. Finally, glycopeptide resistance has been transferred to methicillin-resistant Staphylococcus aureus in clinical practice on several occasions.

SUMMARY

The prevalence of vancomycin resistant enterococci will likely continue to increase. Implementation of infection control strategies, in conjunction with deployment of advanced technologies for detection of vancomycin resistant enterococci, may curb this rise. The emergence of vancomycin resistant S. aureus is of concern.