A Pragmatic Biomarker-Driven Algorithm to Guide Antibiotic Use in the Pediatric Intensive Care Unit: The Optimizing Antibiotic Strategies in Sepsis (OASIS) Study.

Background.: Biomarkers that identify critically ill children with systemic inflammatory response syndrome (SIRS) at low risk for bacterial infection may help clinicians reduce unnecessary antibiotic use.

Methods.: We conducted a prospective cohort study of children with SIRS and suspected infection admitted to a pediatric intensive care unit from January 5, 2012 to March 7, 2014. We enrolled patients upon initiation of new antibiotics (Time 0) and measured a panel of 8 serum biomarkers daily over 72 hours. Microbiology, imaging, and clinical data were reviewed to classify bacterial infections using Centers for Disease Control and Prevention definitions. We identified cut points of biomarker combinations to maximize the negative predictive value (NPV) and specificity for bacterial infection. Excess antibiotics were calculated as days of therapy beyond day 2 after SIRS onset in patients without bacterial infection.

Results.: Infections were identified in 46 of 85 patients: bacterial (n = 22) and viral (24), whereas 39 patients had no infection identified. At Time 0, C-reactive protein (CRP) <5 mg/dL plus serum amyloid A <15.0 µg/mL had an NPV of 0.92 (95% confidence interval [CI], 0.79-1.0) and specificity of 0.54 (95% CI, 0.42-0.66) to identify patients without bacterial infection, whereas CRP <4 mg/dL plus procalcitonin <1.75 ng/mL had an NPV of 0.90 (95% CI, 0.79-1.0) and specificity of 0.43 (95% CI, 0.30-0.55). Patients without bacterial infection received a mean of 3.8 excess days of therapy.

Conclusions.: Early measurement of select biomarkers can identify children with SIRS in whom antibiotics might be safely discontinued when there is no other objective evidence of infection at 48 hours.