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Journal article

Diagnostic host gene signature to accurately distinguish enteric fever from other febrile diseases

Abstract:

Misdiagnosis of enteric fever is a major global health problem resulting in patient mismanagement, antimicrobial misuse and inaccurate disease burden estimates. Applying a machine-learning algorithm to host gene expression profiles, we identified a diagnostic signature which could accurately distinguish culture-confirmed enteric fever cases from other febrile illnesses (AUROC<95%). Applying this signature to a culture-negative suspected enteric fever cohort in Nepal identified a further 12...

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Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.15252/emmm.201910431

Authors


More by this author
Institution:
University of Oxford
Department:
NDM
Role:
Author
ORCID:
0000-0002-1046-2968
More by this author
Institution:
University of Oxford
Department:
Paediatrics
Oxford college:
Trinity College
Role:
Author
ORCID:
0000-0003-1781-0053
More by this author
Role:
Author
ORCID:
0000-0002-1092-5715
Publisher:
EMBO Press
Journal:
EMBO Molecular Medicine More from this journal
Volume:
11
Issue:
10
Article number:
e10431
Publication date:
2019-08-30
Acceptance date:
2019-08-09
DOI:
EISSN:
1757-4684
ISSN:
1757-4676
Language:
English
Keywords:
Pubs id:
pubs:1038855
UUID:
uuid:cc68cbfa-7a94-420d-82a7-3c0ebb4e30d9
Local pid:
pubs:1038855
Source identifiers:
1038855
Deposit date:
2019-10-06

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