A Decision Tree Using Patient Characteristics to Predict Resistance to Commonly Used Broad-Spectrum Antibiotics in Children With Gram-Negative Bloodstream Infections

Abstract

Background: As rates of multidrug-resistant gram-negative infections rise, it is critical to recognize children at high risk of bloodstream infections with organisms resistant to commonly used empiric broad-spectrum antibiotics. The objective of the current study was to develop a user-friendly clinical decision aid to predict the risk of resistance to commonly prescribed broad-spectrum empiric antibiotics for children with gram-negative bloodstream infections.

Methods: This was a longitudinal retrospective cohort study of children with gram-negative bacteria cared for at a tertiary care pediatric hospital from June 2009 to June 2015. The primary outcome was a bloodstream infection due to bacteria resistant to broad-spectrum antibiotics (ie, cefepime, piperacillin-tazobactam, meropenem, or imipenem-cilastatin). Recursive partitioning was used to develop the decision tree.

Results: Of 689 episodes of gram-negative bloodstream infections included, 31% were resistant to broad-spectrum antibiotics. The decision tree stratified patients into high- or low-risk groups based on prior carbapenem treatment, a previous culture with a broad-spectrum antibiotic resistant gram-negative organism in the preceding 6 months, intestinal transplantation, age ≥3 years, and ≥7 prior episodes of gram-negative bloodstream infections. The sensitivity for classifying high-risk patients was 46%, and the specificity was 91%.

Conclusion: A decision tree offers a novel approach to individualize patients' risk of gram-negative bloodstream infections resistant to broad-spectrum antibiotics, distinguishing children who may warrant even broader antibiotic therapy (eg, combination therapy, newer β-lactam agents) from those for whom standard empiric antibiotic therapy is appropriate. The constructed tree needs to be validated more widely before incorporation into clinical practice.

Keywords: Antibiotic stewardship; bloodstream infections; multidrug-resistant gram-negative organisms; recursive partitioning.