A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections.
Acute Disease
/ mortality
Adult
Aged
Aged, 80 and over
Bacterial Infections
/ diagnosis
Datasets as Topic
Female
Gene Expression Profiling
/ methods
Hospital Mortality
Host-Pathogen Interactions
/ genetics
Humans
Intensive Care Units
/ statistics & numerical data
Male
Middle Aged
Neural Networks, Computer
RNA, Messenger
/ metabolism
ROC Curve
Sepsis
/ diagnosis
Support Vector Machine
Virus Diseases
/ diagnosis
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
04 03 2020
04 03 2020
Historique:
received:
18
06
2019
accepted:
13
02
2020
entrez:
6
3
2020
pubmed:
7
3
2020
medline:
27
6
2020
Statut:
epublish
Résumé
Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral infections. We use training data (N = 1069) from 18 retrospective transcriptomic studies. Using only 29 preselected host mRNAs, we train a neural-network classifier with a bacterial-vs-other area under the receiver-operating characteristic curve (AUROC) 0.92 (95% CI 0.90-0.93) and a viral-vs-other AUROC 0.92 (95% CI 0.90-0.93). We then apply this classifier, inflammatix-bacterial-viral-noninfected-version 1 (IMX-BVN-1), without retraining, to an independent cohort (N = 163). In this cohort, IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.86 (95% CI 0.77-0.93), and viral-vs.-other 0.85 (95% CI 0.76-0.93). In patients enrolled within 36 h of hospital admission (N = 70), IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.92 (95% CI 0.83-0.99), and viral-vs.-other 0.91 (95% CI 0.82-0.98). With further study, IMX-BVN-1 could provide a tool for assessing patients with suspected infection and sepsis at hospital admission.
Identifiants
pubmed: 32132525
doi: 10.1038/s41467-020-14975-w
pii: 10.1038/s41467-020-14975-w
pmc: PMC7055276
doi:
Substances chimiques
RNA, Messenger
0
Types de publication
Evaluation Study
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1177Subventions
Organisme : NHLBI NIH HHS
ID : K23 HL125663
Pays : United States
Organisme : NIAID NIH HHS
ID : U19 AI109662
Pays : United States
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