Prediction of Fluoroquinolone Resistance in Gram-Negative Bacteria Causing Bloodstream Infections

Abstract

Increasing rates of fluoroquinolone resistance (FQ-R) have limited empirical treatment options for Gram-negative infections, particularly in patients with severe beta-lactam allergy. This case-control study aims to develop a clinical risk score to predict the probability of FQ-R in Gram-negative bloodstream isolates. Adult patients with Gram-negative bloodstream infections (BSI) hospitalized at Palmetto Health System in Columbia, South Carolina, from 2010 to 2013 were identified. Multivariate logistic regression was used to identify independent risk factors for FQ-R. Point allocation in the fluoroquinolone resistance score (FQRS) was based on regression coefficients. Model discrimination was assessed by the area under receiver operating characteristic curve (AUC). Among 824 patients with Gram-negative BSI, 143 (17%) had BSI due to fluoroquinolone-nonsusceptible Gram-negative bacilli. Independent risk factors for FQ-R and point allocation in FQRS included male sex (adjusted odds ratio [aOR], 1.97; 95% confidence intervals [CI], 1.36 to 2.98; 1 point), diabetes mellitus (aOR, 1.54; 95% CI, 1.03 to 2.28; 1 point), residence at a skilled nursing facility (aOR, 2.28; 95% CI, 1.42 to 3.63; 2 points), outpatient procedure within 30 days (aOR, 3.68; 95% CI, 1.96 to 6.78; 3 points), prior fluoroquinolone use within 90 days (aOR, 7.87; 95% CI, 4.53 to 13.74; 5 points), or prior fluoroquinolone use within 91 to 180 days of BSI (aOR, 2.77; 95% CI, 1.17 to 6.16; 3 points). The AUC for both final logistic regression and FQRS models was 0.73. Patients with an FQRS of 0, 3, 5, or 8 had predicted probabilities of FQ-R of 6%, 22%, 39%, or 69%, respectively. The estimation of patient-specific risk of antimicrobial resistance using FQRS may improve empirical antimicrobial therapy and fluoroquinolone utilization in Gram-negative BSI.

FIG 1

Receiver operating characteristic plot of the fluoroquinolone resistance score. The black line indicates the receiver operating characteristic curve. The light-colored tangent line highlights the point in the curve that represents the best performance of the model. The area under the curve is 0.73.

FIG 2

Calibration plot of fluoroquinolone resistance score. The observed frequency of fluoroquinolone resistance plotted by deciles of predicted probability from the fluoroquinolone resistance score (black dots) is shown. Perfect calibration is represented by the gray y = x line.

FIG 3

Predicted probability of fluoroquinolone-nonsusceptible bloodstream isolates by fluoroquinolone resistance score. The size of the marker for point estimates is weighted approximately by the relative number of subjects with the corresponding score.

FIG 4

Comparison of predicted probabilities of ciprofloxacin-nonsusceptible bloodstream isolates by fluoroquinolone resistance score using different MIC susceptibility breakpoint criteria. CLSI, Clinical Laboratory and Standards Institute (MIC of ≤1); EUCAST, European Committee on Antimicrobial Susceptibility Testing (MIC of ≤0.5); USCAST, United States Committee on Antimicrobial Susceptibility Testing (MIC of ≤0.25 for Enterobacteriaceae and ≤0.5 for nonfermenting Gram-negative bacilli).