Literature DB >> 27758065

Blood cultures and bacteraemia in an Australian emergency department: Evaluating a predictive rule to guide collection and their clinical impact.

Jeremy D Brown1,2, Scott Chapman2,3, Patricia E Ferguson2,4.   

Abstract

OBJECTIVE: The objective of the present study is to determine whether a predictive rule could safely reduce the number of negative blood cultures collected in an Australian ED and to assess the clinical impact of positive results from blood cultures taken in the ED.
METHODS: All positive blood cultures taken in the ED at a single facility were retrospectively identified for the calendar year 2012. Clinically significant bacteraemia episodes were assessed against a predictive rule using major and minor clinical and laboratory criteria gathered from medical records and pathology databases, and compared with a randomly generated sample of ED patient episode with negative blood cultures. The ED and final diagnoses and blood culture impact on clinical management were also collected.
RESULTS: The predictive rule has a high sensitivity (98.8%) and modest specificity (48.7%), and if applied stringently would have prevented almost half of all blood cultures in our ED but missed two positives. Blood cultures altered the clinical management of 94.3% bacteraemic patients, representing 3.4% of all ED patients with blood cultures performed. High discordance (54%) between ED diagnosis and discharge diagnosis of bacteraemic patients was noted.
CONCLUSIONS: Bacteraemia detected in the ED alters subsequent patient management. The predictive rule can be safely applied in the ED to determine need for blood culture collection. Blood cultures should not be omitted in the ED based entirely on preliminary diagnosis given the high discordance seen between ED and discharge diagnosis.
© 2016 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Entities:  

Keywords:  bacteraemia; blood culture; emergency department; prediction

Mesh:

Substances:

Year:  2016        PMID: 27758065     DOI: 10.1111/1742-6723.12696

Source DB:  PubMed          Journal:  Emerg Med Australas        ISSN: 1742-6723            Impact factor:   2.151


  2 in total

1.  Machine learning for fast identification of bacteraemia in SIRS patients treated on standard care wards: a cohort study.

Authors:  Franz Ratzinger; Helmuth Haslacher; Thomas Perkmann; Matilde Pinzan; Philip Anner; Athanasios Makristathis; Heinz Burgmann; Georg Heinze; Georg Dorffner
Journal:  Sci Rep       Date:  2018-08-15       Impact factor: 4.379

2.  The effectiveness of interventions to reduce peripheral blood culture contamination in acute care: a systematic review protocol.

Authors:  J A Hughes; C J Cabilan; Julian Williams; Mercedes Ray; Fiona Coyer
Journal:  Syst Rev       Date:  2018-11-30
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.