title: Robust classification of bacterial and viral infections via integrated host gene expression diagnostics.
abstract: Improved diagnostics for acute infections could decrease morbidity and mortality by increasing early antibiotics for patients with bacterial infections and reducing unnecessary antibiotics for patients without bacterial infections. Several groups have used gene expression microarrays to build classifiers for acute infections, but these have been hampered by the size of the gene sets, use of overfit models, or lack of independent validation. We used multicohort analysis to derive a set of seven genes for robust discrimination of bacterial and viral infections, which we then validated in 30 independent cohorts. We next used our previously published 11-gene Sepsis MetaScore together with the new bacterial/viral classifier to build an integrated antibiotics decision model. In a pooled analysis of 1057 samples from 20 cohorts (excluding infants), the integrated antibiotics decision model had a sensitivity and specificity for bacterial infections of 94.0 and 59.8%, respectively (negative likelihood ratio, 0.10). Prospective clinical validation will be needed before these findings are implemented for patient care.
authors.affiliation: Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA. Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA 94305, USA. tes17@stanford.edu pkhatri@stanford.edu.
authors.forename: Timothy E
authors.initials: TE
authors.lastname: Sweeney
authors.affiliation: Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, OH 45223, USA. Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA.
authors.forename: Hector R
authors.initials: HR
authors.lastname: Wong
authors.affiliation: Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA 94305, USA. Biomedical Informatics Research, Stanford University School of Medicine, Stanford, CA 94305, USA. tes17@stanford.edu pkhatri@stanford.edu.
authors.forename: Purvesh
authors.initials: P
authors.lastname: Khatri
mesh_terms: D000818:Animals; D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D001424:Bacterial Infections / Q000145:classification* / Q000188:drug therapy / Q000378:metabolism; D015870:Gene Expression; D006801:Humans; D008962:Models, Theoretical; D014777:Virus Diseases / Q000145:classification* / Q000188:drug therapy / Q000378:metabolism
chemical_list: D000900:Anti-Bacterial Agents