BACKGROUND: The goal of this study was to develop a validated prediction rule for identification of patients harboring vancomycin-resistant enterococci (VRE) at hospital admission. METHODS: A model for the prediction of patients harboring VRE at admission was created and validated by assigning weighted point values to independent risk factors associated with harboring VRE at admission, in 2 different cohorts of patients from 2 tertiary care hospitals in Boston, Massachusetts. Patients with VRE isolated from clinical culture samples collected within 48 h of hospital admission were compared with patients not harboring VRE. To assess the diagnostic accuracy of the prediction rule, the main outcome measures were patient demographic characteristics, comorbid illnesses, hospitalizations, and antibiotic exposure. RESULTS: A total of 412 patients were enrolled. A risk index score was derived by using the following 6 independent risk factors associated with VRE recovery within 48 h of hospital admission: previous isolation of methicillin-resistant Staphylococcus aureus (MRSA), whether the patient was receiving long-term hemodialysis, transfer from a long-term care facility, antibiotic exposure, prior hospitalization, and age >60 years. On the basis of a point score >or=10, the sensitivity, specificity, and positive and negative predictive values of this prediction rule were 44%, 98%, 81%, and 90%, respectively. CONCLUSIONS: This validated clinical prediction rule provides a novel strategy for the identification of patients at high risk of harboring VRE at hospital admission. Implementation of this rule may reduce the influx of VRE into health care institutions and the overall prevalence of VRE, by targeting VRE-screening measures and contact isolation precautions for these high-risk patients.
BACKGROUND: The goal of this study was to develop a validated prediction rule for identification of patients harboring vancomycin-resistant enterococci (VRE) at hospital admission. METHODS: A model for the prediction of patients harboring VRE at admission was created and validated by assigning weighted point values to independent risk factors associated with harboring VRE at admission, in 2 different cohorts of patients from 2 tertiary care hospitals in Boston, Massachusetts. Patients with VRE isolated from clinical culture samples collected within 48 h of hospital admission were compared with patients not harboring VRE. To assess the diagnostic accuracy of the prediction rule, the main outcome measures were patient demographic characteristics, comorbid illnesses, hospitalizations, and antibiotic exposure. RESULTS: A total of 412 patients were enrolled. A risk index score was derived by using the following 6 independent risk factors associated with VRE recovery within 48 h of hospital admission: previous isolation of methicillin-resistant Staphylococcus aureus (MRSA), whether the patient was receiving long-term hemodialysis, transfer from a long-term care facility, antibiotic exposure, prior hospitalization, and age >60 years. On the basis of a point score >or=10, the sensitivity, specificity, and positive and negative predictive values of this prediction rule were 44%, 98%, 81%, and 90%, respectively. CONCLUSIONS: This validated clinical prediction rule provides a novel strategy for the identification of patients at high risk of harboring VRE at hospital admission. Implementation of this rule may reduce the influx of VRE into health care institutions and the overall prevalence of VRE, by targeting VRE-screening measures and contact isolation precautions for these high-risk patients.
Authors: Mario Tumbarello; Enrico Maria Trecarichi; Matteo Bassetti; Francesco Giuseppe De Rosa; Teresa Spanu; Eugenia Di Meco; Angela Raffaella Losito; Andrea Parisini; Nicole Pagani; Roberto Cauda Journal: Antimicrob Agents Chemother Date: 2011-05-02 Impact factor: 5.191
Authors: Steven W Johnson; Deverick J Anderson; D Byron May; Richard H Drew Journal: Infect Control Hosp Epidemiol Date: 2013-02-14 Impact factor: 3.254
Authors: Indumathi Venkatachalam; Jeanette Teo; Michelle N D Balm; Dale A Fisher; Roland Jureen; Raymond T P Lin Journal: Emerg Infect Dis Date: 2012-08 Impact factor: 6.883
Authors: Philipp Kohler; Rosamaria Fulchini; Werner C Albrich; Adrian Egli; Carlo Balmelli; Stephan Harbarth; Delphine Héquet; Christian R Kahlert; Stefan P Kuster; Christiane Petignat; Matthias Schlegel; Andreas Kronenberg Journal: Antimicrob Resist Infect Control Date: 2018-07-20 Impact factor: 4.887