A Clinical Decision Tree to Predict Whether a Bacteremic Patient Is Infected With an Extended-Spectrum beta-Lactamase-Producing Organism

作者：Goodman Katherine E; Lessler Justin; Cosgrove Sara E; Harris Anthony D; Lautenbach Ebbing; Han Jennifer H; Milstone Aaron M; Massey Colin J; Tamma Pranita D

来源：Clinical Infectious Diseases, 2016, 63(7): 896-903.

DOI：10.1093/cid/ciw425

• ESBL
• bacteremia
• carbapenem
• machine learning
• prediction

We developed a decision tree to predict the likelihood that a patient with bacteremia is infected with an extended-spectrum beta-lactamase-producing organism. Evaluating 1288 bacteremic patients, our decision tree's positive and negative predictive values were 90.8% and 91.9%, respectively.Methods.aEuro integral We included patients a parts per thousand yen18 years of age with bacteremia due to Escherichia coli or Klebsiella species from October 2008 to March 2015 at Johns Hopkins Hospital. Isolates with ceftriaxone minimum inhibitory concentrations a parts per thousand yen2 A mu g/mL underwent ESBL confirmatory testing. Recursive partitioning was used to generate a decision tree to determine the likelihood that a bacteremic patient was infected with an ESBL producer. Discrimination of the original and cross-validated models was evaluated using receiver operating characteristic curves and by calculation of C-statistics.
Results.aEuro integral A total of 1288 patients with bacteremia met eligibility criteria. For 194 patients (15%), bacteremia was due to a confirmed ESBL producer. The final classification tree for predicting ESBL-positive bacteremia included 5 predictors: history of ESBL colonization/infection, chronic indwelling vascular hardware, age a parts per thousand yen43 years, recent hospitalization in an ESBL high-burden region, and a parts per thousand yen6 days of antibiotic exposure in the prior 6 months. The decision tree's positive and negative predictive values were 90.8% and 91.9%, respectively.
Conclusions.aEuro integral Our findings suggest that a clinical decision tree can be used to estimate a bacteremic patient's likelihood of infection with ESBL-producing bacteria. Recursive partitioning offers a practical, user-friendly approach for addressing important diagnostic questions.

• 出版日期2016-10-1