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Predicting sepsis using a combination of clinical information and molecular immune markers sampled in the ambulance.
Tuerxun, Kedeye; Eklund, Daniel; Wallgren, Ulrika; Dannenberg, Katharina; Repsilber, Dirk; Kruse, Robert; Särndahl, Eva; Kurland, Lisa.
Afiliação
  • Tuerxun K; School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden. kaya.tuerxun@oru.se.
  • Eklund D; Inflammatory Response and Infection Susceptibility Centre, (iRiSC), Faculty of Medicine and Health, Örebro University, Örebro, Sweden. kaya.tuerxun@oru.se.
  • Wallgren U; School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
  • Dannenberg K; Inflammatory Response and Infection Susceptibility Centre, (iRiSC), Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
  • Repsilber D; Gustavsbergs Vårdcentral, Gustavsberg, Stockholm, Sweden.
  • Kruse R; School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
  • Särndahl E; School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
  • Kurland L; School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
Sci Rep ; 13(1): 14917, 2023 09 10.
Article em En | MEDLINE | ID: mdl-37691028
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ambulâncias / Sepse Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Suécia
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ambulâncias / Sepse Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Suécia