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Benchmarking inappropriate empirical antibiotic treatment.

Authors
  • Kariv, G
  • Paul, M
  • Shani, V
  • Muchtar, E
  • Leibovici, L
Type
Published Article
Journal
Clinical Microbiology and Infection
Publisher
Elsevier
Publication Date
Jul 01, 2013
Volume
19
Issue
7
Pages
629–633
Identifiers
DOI: 10.1111/j.1469-0691.2012.03965.x
PMID: 22805537
Source
Medline
License
Unknown

Abstract

Inappropriate empirical antibiotic treatment for severe infections is associated with increased mortality. Superfluous treatment is associated with resistance induction. We aimed to define acceptable rates of inappropriate empirical antibiotic treatment. We included all prospective cohort studies published between 1975 and 2009 reporting the proportion of appropriate and inappropriate empirical antibiotic treatment of microbiologically documented infections. Studies were identified in PubMed and in reference lists of included studies. Funnel plots were drawn using the proportion of inappropriate empirical treatment as the effect size. A pooled estimate of inappropriate empirical antibiotic treatment was calculated using a β-binomial model. Control limits were calculated with the overdispersion factor technique and 20% winsorized data. Heterogeneity was assessed through subgroup analysis for categorical moderators and meta-regression for continuous variables. Eighty-seven studies, comprising 92 study groups, with 27 628 patients met inclusion criteria. The pooled rate of inappropriate empirical antibiotic treatment was 28.6% (95% CI 25.4-31.8). Funnel plot analysis yielded a dispersed graph with only 37 (40%) studies falling within the control limits. Using the overdispersion factor technique with 20% winsorizing, 79 (86%) studies fell within the control limits. None of the clinical or methodological factors could explain the large heterogeneity observed. The funnel plot presented can be used to benchmark rates of inappropriate empirical antibiotic treatment. Based on the control limits found, at least 500 patients should be evaluated before establishing a local rate. Lower and higher than expected rates might indicate overly aggressive treatment or poor performance, respectively.

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