@article{discovery10126777,
           month = {July},
          volume = {18},
       publisher = {BMC},
            year = {2020},
           title = {Blood transcriptomic discrimination of bacterial and viral infections in the emergency department: a multi-cohort observational validation study},
          number = {1},
         journal = {BMC Medicine},
            note = {This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.},
            issn = {1741-7015},
          author = {Sampson, D and Yager, TD and Fox, B and Shallcross, L and McHugh, L and Seldon, T and Rapisarda, A and Brandon, RB and Navalkar, K and Simpson, N and Stafford, S and Gil, E and Venturini, C and Tsaliki, E and Roe, J and Chain, B and Noursadeghi, M},
             url = {https://doi.org/10.1186/s12916-020-01653-3},
        abstract = {Background: There is an urgent need to develop biomarkers that stratify risk of bacterial infection in order to support antimicrobial stewardship in emergency hospital admissions. / Methods: We used computational machine learning to derive a rule-out blood transcriptomic signature of bacterial infection (SeptiCyteTM 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 (SeptiCyteTM 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 SeptiCyteTM signature in a mixture modelling approach to estimate the prevalence of bacterial and viral infections in febrile ED patients without microbiological diagnoses. / Results: 
The combination of SeptiCyteTM TRIAGE with our published signature for viral infections (SeptiCyteTM 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 (0.68-0.91) for WCC and 0.73 (0.61-0.86) for CRP. At pre-test probabilities 0.35 and 0.72, the combined SeptiCyteTM score achieved a negative predictive value for bacterial infection of 0.97 (0.90-0.99) and 0.86 (0.64-0.96), compared to 0.90 (0.80-0.94) and 0.66 (0.48-0.79) for WCC and 0.88 (0.69-0.95) and 0.60 (0.31-0.72) for CRP. In a mixture modelling approach, the combined SeptiCyteTM score estimated that 24\% of febrile ED cases receiving antibacterials without a microbiological diagnosis were due to viral infections. Our analysis also suggested that a proportion of patients with bacterial infection recovered without antibacterials. / Conclusions: Blood transcriptional biomarkers offer exciting opportunities to support precision antibacterial prescribing in ED and improve diagnostic classification of patients without microbiologically confirmed infections.},
        keywords = {Blood transcriptional profiling; Bacterial infection, viral infection; Emergency department}
}