Predictive value of clinical and laboratory features for the main febrile diseases in children living in Tanzania: A prospective observational study.
Fiche du document
2017
- doi: 10.1371/journal.pone.0173314
- issn: 1932-6203
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0173314
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/28464021
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/eissn/1932-6203
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_FA5A5C75DE071
info:eu-repo/semantics/openAccess , Copying allowed only for non-profit organizations , https://serval.unil.ch/disclaimer
Sujets proches
illnessCiter ce document
O. De Santis et al., « Predictive value of clinical and laboratory features for the main febrile diseases in children living in Tanzania: A prospective observational study. », Serveur académique Lausannois, ID : 10.1371/journal.pone.0173314
Métriques
Partage / Export
Résumé
To construct evidence-based guidelines for management of febrile illness, it is essential to identify clinical predictors for the main causes of fever, either to diagnose the disease when no laboratory test is available or to better target testing when a test is available. The objective was to investigate clinical predictors of several diseases in a cohort of febrile children attending outpatient clinics in Tanzania, whose diagnoses have been established after extensive clinical and laboratory workup. From April to December 2008, 1005 consecutive children aged 2 months to 10 years with temperature ≥38°C attending two outpatient clinics in Dar es Salaam were included. Demographic characteristics, symptoms and signs, comorbidities, full blood count and liver enzyme level were investigated by bi- and multi-variate analyses (Chan, et al., 2008). To evaluate accuracy of combined predictors to construct algorithms, classification and regression tree (CART) analyses were also performed. 62 variables were studied. Between 4 and 15 significant predictors to rule in (aLR+>1) or rule out (aLR+