Systematic review and validation of prediction rules for identifying children with serious infections in emergency departments and urgent-access primary care
Thompson M, Van den Bruel A, Verbakel J, Lakhanpaul M, Haj-Hassan T, Stevens R, Moll H, Buntinx F, Berger M, Aertgeerts B, Oostenbrink R, Mant D
Record ID 32010000306
English
Authors' recommendations:
Study of prediction rules for serious childhood infection found that there are several clinical features which are helpful in diagnosing whether a child has a serious infection but that none on its own is sufficient. Clinical 'gut feeling' and diagnostic safety netting are used to fill this 'diagnostic gap'.
Details
Project Status:
Completed
Year Published:
2012
URL for published report:
http://www.hta.ac.uk/1751
English language abstract:
An English language summary is available
Publication Type:
Not Assigned
Country:
England, United Kingdom
MeSH Terms
- Child
- Infections
Contact
Organisation Name:
NIHR Health Technology Assessment programme
Contact Address:
NIHR Journals Library, National Institute for Health and Care Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK
Contact Name:
journals.library@nihr.ac.uk
Contact Email:
journals.library@nihr.ac.uk
Copyright:
2012 Queen's Printer and Controller of HMSO
This is a bibliographic record of a published health technology assessment from a member of INAHTA or other HTA producer. No evaluation of the quality of this assessment has been made for the HTA database.