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

Background: Biomarkers can facilitate safe antibiotic discontinuation in critically ill patients without bacterial infection. Methods: We tested the ability of a biomarker-based algorithm to reduce excess antibiotic administration in patients with systemic inflammatory response syndrome (SIRS) without bacterial infections (uninfected) in our pediatric intensive care unit (PICU). The algorithm suggested that PICU clinicians stop antibiotics if (1) C-reactive protein <4 mg/dL and procalcitonin <1 ng/mL at SIRS onset and (2) no evidence of bacterial infection by exam/testing by 48 hours. We evaluated excess broad-spectrum antibiotic use, defined as administration on days 3-9 after SIRS onset in uninfected children. Incidence rate ratios (IRRs) compared unadjusted excess length of therapy (LOT) in the 34 months before (Period 1) and 12 months after (Period 2) implementation of this algorithm, stratified by biomarker values. Segmented linear regression evaluated excess LOT among all uninfected episodes over time and between the periods. Results: We identified 457 eligible SIRS episodes without bacterial infection, 333 in Period 1 and 124 in Period 2. When both biomarkers were below the algorithm's cut-points (n = 48 Period 1, n = 31 Period 2), unadjusted excess LOT was lower in Period 2 (IRR, 0.53; 95% confidence interval, 0.30-0.93). Among all 457 uninfected episodes, there were no significant differences in LOT (coefficient 0.9, P =. 99) between the periods on segmented regression. Conclusions: Implementation of a biomarker-based algorithm did not decrease overall antibiotic exposure among all uninfected patients in our PICU, although exposures were reduced in the subset of SIRS episodes where biomarkers were low.