Procalcitonin-guided algorithms of antibiotic therapy in the intensive care unit: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: There is increasing interest for strategies that could curtail antibiotic resistance in the critical care setting. We sought to determine the effectiveness and safety of procalcitonin-guided algorithms in the management of septic patients in the intensive care unit. DATA SOURCES: MEDLINE, Scopus, Cochrane Central Register of Controlled Trials (through April 2010), reference lists of retrieved publications, and queries of corresponding authors. No language restrictions were applied. STUDY SELECTION: We included only randomized controlled studies reporting on antibiotic use and clinical outcomes of intensive care unit patients managed with a procalcitonin-guided algorithm or according to routine practice. DATA EXTRACTION: Data on study characteristics, interventions, and outcomes were retrieved by two independent reviewers. Pooled odds ratios, weighted mean differences, and 95% confidence intervals were calculated by implementing both the Mantel-Haenszel fixed effect model and the DerSimonian-Laird random effects model. DATA SYNTHESIS: Seven randomized controlled studies involving 1131 intensive care unit patients (adults = 1010; neonates = 121) were included. In comparison with routine practice, the implementation of procalcitonin-guided algorithms decreased the duration of antibiotic therapy for the first episode of infection by approximately 2 days (weighted mean difference = -2.36 days; 95% confidence interval, -3.11 to -1.61) and the total duration of antibiotic treatment by 4 days (fixed effect model: weighted mean difference: -4.19 days; 95% confidence interval, -4.98 to -3.39). The comparison between the procalcitonin and the routine practice group was not associated with any apparent adverse clinical outcome: 28-day mortality (fixed effect model: odds ratio = 0.93; 95% confidence interval, 0.69 to 1.26), intensive care unit length of stay (fixed effect model: pooled weighted mean difference = -0.49 days, 95% confidence interval, -1.55 to 0.57), and relapsed/persistent infection rate (fixed effect model: odds ratio = 0.97; 95% confidence interval, 0.56 to 1.69).
CONCLUSIONS: The implementation of a procalcitonin-based algorithm may reduce antibiotic exposure in critically ill, septic patients without compromising clinical outcomes, but further research is necessary before the wide adoption of this strategy.