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A community approach to mortality prediction in sepsis via gene expression analysis

Abstract:

Improved risk stratification and prognosis prediction in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here, we present prognostic models for 30-day mortality generated independently by three scientific groups by using 12 discovery cohorts containing transcriptomic data collected from primarily community-onse...

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Publication status:
Published
Peer review status:
Peer reviewed

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Role:
Author
ORCID:
0000-0002-3596-1093
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Role:
Author
ORCID:
0000-0003-1168-8982
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Role:
Author
ORCID:
0000-0003-4980-845X
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Name:
Medical Research Council
Funding agency for:
Knight, J
Grant:
98082
98082
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Name:
European Research Council
Funding agency for:
Knight, J
Grant:
98082
FP7/2007–2013/ERC Grant agreement no. 281824
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Name:
Wellcome Trust
Funding agency for:
Knight, J
Grant:
98082
090532/Z/09/Z
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Name:
Army Research Office
Grant:
W911NF-15-1-0107
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Name:
Defense Advanced Research Projects Agency
Grant:
W911NF-15-1-0107
Publisher:
Springer Nature
Journal:
Nature Communications More from this journal
Volume:
9
Issue:
1
Article number:
694
Publication date:
2018-02-15
Acceptance date:
2018-01-18
DOI:
ISSN:
2041-1723
Pmid:
29449546
Language:
English
Pubs id:
pubs:825101
UUID:
uuid:c9a2ade7-915f-40ea-b032-c95065c37be0
Local pid:
pubs:825101
Source identifiers:
825101
Deposit date:
2018-02-19

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