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.


METHODS
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.


METHODS
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.


METHODS
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.


RESULTS
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.
Kopterides
Petros
P
Second Critical Care Department, Attiko University Hospital, University of Athens Medical School, Athens, Greece. petkop@ath.forthnet.gr
Siempos
Ilias I
II
Tsangaris
Iraklis
I
Tsantes
Argirios
A
Armaganidis
Apostolos
A
D000328:Adult; D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000008:administration & dosage / Q000627:therapeutic use*; D015415:Biomarkers / Q000097:blood; D002116:Calcitonin / Q000097:blood*; D015740:Calcitonin Gene-Related Peptide; D003422:Critical Care / Q000379:methods; D006801:Humans; D007231:Infant, Newborn; D007362:Intensive Care Units; D007363:Intensive Care Units, Neonatal; D011498:Protein Precursors / Q000097:blood*; D012008:Recurrence; D018805:Sepsis / Q000097:blood / Q000175:diagnosis* / Q000188:drug therapy
D000900:Anti-Bacterial Agents; D015415:Biomarkers; C000606589:CALCA protein, human; D011498:Protein Precursors; D002116:Calcitonin; D015740:Calcitonin Gene-Related Peptide