819. Prediction of Fluoroquinolone Resistance in Patients with Gram-Negative Bloodstream Infection
Session: Poster Abstract Session: Bacteremia and Endocarditis
Friday, October 9, 2015
Room: Poster Hall
  • Poster Ansal MA revision2.pdf (577.7 kB)
  • Background:

    Increasing rates of fluoroquinolone resistance (FQ-R) among gram-negative bacilli have limited empirical antimicrobial treatment options. The aim of this nested case-control study is to develop a clinical risk score to predict FQ-R in patients with gram-negative bloodstream infections (BSI).



    Hospitalized adults with first episodes of gram-negative BSI at Palmetto Health Hospitals in Columbia, SC, USA from January 1, 2010 to December 31, 2013 were identified. Multivariate logistic regression was used to identify independent risk factors for FQ-R. Fluoroquinolone resistance score (FQRS) was developed by adding points allocated for each predictor of FQ-R based on regression coefficients in final logistic regression model. Area under receiver operating characteristic (ROC) curve was calculated to determine model discrimination.



    Among 824 patients with gram-negative BSI, 143 (17%) had BSI due to FQ-R organisms. Overall, Escherichia coli was the most common bloodstream isolate (53%) and the urinary tract was the most common source of infection (54%). Independent risk factors for FQ-R and point allocation in FQRS are shown in Table. Area under ROC curve for final logistic regression and FQRS models were 0.71 and 0.70, respectively. Patients with FQRS of 0, 3, 6 and ≥ 10 had estimated risk of FQ-R of 6%, 18%, 40% and 74%, respectively.


    FQRS provides clinicians with a simple tool to estimate risk of FQ-R with good discrimination using readily available clinical variables at the time of initial presentation with suspected gram-negative BSI. Once prospectively validated, application of FQRS may improve selection of empirical antimicrobial therapy in patients with gram-negative BSI, particularly those with severe or undocumented beta-lactam allergies.




    Table: Predictors of fluoroquinolone resistance and point allocation in fluoroquinolone resistance score



    Odds   ratio

    (95%   confidence intervals)

    Point   allocation

    Male gender




    Skilled nursing facility




    Diabetes mellitus




    Recent surgical   procedure




    Prior   fluoroquinolone use








               Within 90 days




               91-180 days




    Ansal Shah, MD1, Seejil Dan, MD2, Julie Ann Justo, Pharm D, MS3, P. Brandon Bookstaver, PharmD, FCCP, BCPS (AQ-ID), AAHIVP4, Joseph Kohn, PharmD, BCPS5, Helmut Albrecht, MD6 and Majdi Al-Hasan, MD6, (1)Department of Medicine, Division of Infectious Diseases, Palmetto Health/ University of South Carolina School of Medicine, Columbia, SC, (2)Internal Medicine, Palmetto Health Richland, Columbia, SC, (3)Department of Clinical Pharmacy and Outcomes Science, South Carolina College of Pharmacy, University of South Carolina, Columbia, SC, (4)Department of Clinical Pharmacy and Outcomes Sciences, South Carolina College of Pharmacy, University of South Carolina, Columbia, SC, (5)Palmetto Health Richland, Columbia, SC, (6)Department of Medicine, Division of Infectious Diseases, University of South Carolina School of Medicine, Columbia, SC


    A. Shah, None

    S. Dan, None

    J. A. Justo, Cempra Pharmaceuticals: Scientific Advisor , Consulting fee

    P. B. Bookstaver, Forest Labs: Grant Investigator and Scientific Advisor , Consulting fee

    J. Kohn, None

    H. Albrecht, None

    M. Al-Hasan, None

    Findings in the abstracts are embargoed until 12:01 a.m. PDT, Wednesday Oct. 7th with the exception of research findings presented at the IDWeek press conferences.