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Background Appropriate empiric antibiotic selection is very important in severe infections. The rise of infection by multidrug-resistant Gram-negative organisms, especially those with the extended-spectrum β-lactamase phenotype (ESBL+), has led to increasing use of broad-spectrum antibiotics, which further selects for more antimicrobial resistance. Improving empiric antibiotic selection is an important goal to preserve the effectiveness of current antibiotics and slow the rise of antimicrobial resistance. A proposed clinical decision tree to predict ESBL+ bacteremia performed well at the developer’s institution, but its external validity, such as in a VA population, is not known. We sought to compare an existing clinical decision tree with standard of care for predicting ESBL+ bacteremia in a VA population. Methods Patients with positive blood cultures that grew E. coli and Klebsiella spp. were included For each patient, the first episode of bacteremia with the specified organisms was examined. Electronic medical records were examined for clinical and microbiological data. Previously described clinical decision tree was used to predict whether the isolate to be ESBL+. Empiric antibiotic selection (prior to antibiotic susceptibility testing reporting) by the emergency department and the primary inpatient service were collected. Results The clinical decision tree correctly predicted the antimicrobial resistance status in 48/54 (88.9%) of episodes of bacteremia and identified 4/10 (40%) of ESBL+ isolates. Standard of care empiric antimicrobial prescribing by the emergency department (n = 23) was overly-broad in 39.1%, the targeted spectrum in 47.8%, and overly-narrow in 13.0%. Empiric antimicrobial prescribing by the primary inpatient service (n = 31) was overly-broad in 38.7%, the targeted spectrum in 48.4%, and overly-narrow in 12.9%. Transitioning from the emergency department to an inpatient service (n = 32), antimicrobials were empirically escalated in 34.4%, unchanged in 40.6%, laterally (similar antimicrobial spectrum) changed in 12.5%, and de-escalated in 9.4%. Conclusion In a VA population, the clinical decision tree correctly predicted many patients, but performed less well in those who had ESBL+ bacteremia. Empiric prescribing by standard of care were suboptimal. Disclosures All authors: No reported disclosures.

Comparing a Clinical Decision Tree vs. Standard of Care for Predicting ESBL+ Bacteremia in a VA Population