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Feasibility of informing syndrome-level empiric antibiotic recommendations using publicly available antibiotic resistance datasets.
Leclerc, Quentin J; Naylor, Nichola R; Aiken, Alexander M; Coll, Francesc; Knight, Gwenan M.
Afiliación
  • Leclerc QJ; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
  • Naylor NR; Centre for Mathematical Modelling of Infectious Diseases (CMMID), London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
  • Aiken AM; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
  • Coll F; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
  • Knight GM; Imperial College Healthcare NHS Trust, London, UK.
Wellcome Open Res ; 4: 140, 2019.
Article en En | MEDLINE | ID: mdl-32656364
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Wellcome Open Res Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Wellcome Open Res Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido