Literature DB >> 27879280

Fifteen-minute consultation: the complexities of empirical antibiotic selection for serious bacterial infections-a practical approach.

Julia A Bielicki1,2,3, David A Cromwell2, Mike Sharland1.   

Abstract

Potentially life-threatening infections require immediate antibiotic therapy. Most early stage antibiotic treatment for these infections is empirical, that is, covering a range of possible target bacteria while awaiting culture results. Empirical antibiotic regimens need to reflect the epidemiology of most likely causative bacteria, type of infection and patient risk factors. Summary data from relevant isolates in similar patients help to identify appropriate empirical regimens. At present, such data are mostly presented as hospital or other aggregate antibiograms, showing antimicrobial susceptibility testing results by bacterial species. However, a more suitable method is to calculate weighted incidence syndromic combination antibiograms for different types of infections and regimens, allowing head-to-head comparisons of empirical regimens. Once there is confirmatory or negative microbiological evidence of infection, empirical regimens should be adapted to the identified bacterial species and susceptibilities or discontinued. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Entities:  

Keywords:  Infectious Diseases; Microbiology; Therapeutics

Mesh:

Substances:

Year:  2016        PMID: 27879280     DOI: 10.1136/archdischild-2016-310527

Source DB:  PubMed          Journal:  Arch Dis Child Educ Pract Ed        ISSN: 1743-0585            Impact factor:   1.309


  2 in total

1.  Classification and Drug Resistance Analysis of Pathogenic Bacteria in Patients with Bacterial Pneumonia in Emergency Intensive Care Unit.

Authors:  Kai Yin; Ling Liu; Guofeng Fan
Journal:  Contrast Media Mol Imaging       Date:  2022-09-30       Impact factor: 3.009

2.  An AI-based auxiliary empirical antibiotic therapy model for children with bacterial pneumonia using low-dose chest CT images.

Authors:  Mudan Zhang; Siwei Yu; Xuntao Yin; Xianchun Zeng; Xinfeng Liu; ZhiYan Shen; Xiaoyong Zhang; Chencui Huang; Rongpin Wang
Journal:  Jpn J Radiol       Date:  2021-06-08       Impact factor: 2.374

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.