Blood transcriptomic discrimination of bacterial and viral infections in the emergency department: a multi-cohort observational validation study.

BMC Medicine
Dayle SampsonMahdad Noursadeghi

Abstract

There is an urgent need to develop biomarkers that stratify risk of bacterial infection in order to support antimicrobial stewardship in emergency hospital admissions. We used computational machine learning to derive a rule-out blood transcriptomic signature of bacterial infection (SeptiCyte™ TRIAGE) from eight published case-control studies. We then validated this signature by itself in independent case-control data from more than 1500 samples in total, and in combination with our previously published signature for viral infections (SeptiCyte™ VIRUS) using pooled data from a further 1088 samples. Finally, we tested the performance of these signatures in a prospective observational cohort of emergency department (ED) patients with fever, and we used the combined SeptiCyte™ signature in a mixture modelling approach to estimate the prevalence of bacterial and viral infections in febrile ED patients without microbiological diagnoses. The combination of SeptiCyte™ TRIAGE with our published signature for viral infections (SeptiCyte™ VIRUS) discriminated bacterial and viral infections in febrile ED patients, with a receiver operating characteristic area under the curve of 0.95 (95% confidence interval 0.90-1), compared to 0.79 (0.68-...Continue Reading

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Citations

Jan 20, 2021·The Journal of Antimicrobial Chemotherapy·Claire Y MasonGabriele Pollara
Apr 4, 2021·Science Advances·Mahashweta BasuSridhar Hannenhalli
Jun 16, 2021·Pediatric Research·Hector R Wong
Jun 22, 2021·Current Infectious Disease Reports·Anna Maria PeriPatrick N A Harris
Jun 14, 2021·European Journal of Clinical Investigation·Raquel AlmansaUNKNOWN PREVISE Study Group

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Methods Mentioned

BETA
PCR
RNAseq

Software Mentioned

RNAseq
Nanostring
SeptiCyteTM
GraphPad Prism
CalcJSDivergence
SpeticyteTM
R package textmineR
TRIAGE
Immunexpress

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