Please use this identifier to cite or link to this item: https://www.arca.fiocruz.br/handle/icict/11782
Title: Clinical and laboratory features that discriminate dengue from other febrile illnesses: a diagnostic accuracy study in Rio de Janeiro, Brazil
Authors: Daumas, Regina P.
Passos, Sonia R. L.
Oliveira, Raquel V. C.
Nogueira, Rita M. R.
Georg, Ingebourg
Marzochi, Keyla B. F.
Brasil, Patrícia
Affilliation: Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública Rio de Janeiro, RJ, Brasil. Centro de Saúde Escola Germano Sinval Faria (CSEGSF). Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Laboratório de Epidemiologia Clínica. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Laboratório de Epidemiologia Clínica. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Departamento de Virologia. Rio de Janeiro, RJ, Brasil.
Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Serviço de Imunologia. Rio de Janeiro, RJ, Brasil.
Abstract: Background: Dengue is an acute febrile illness caused by an arbovirus that is endemic in more than 100 countries. Early diagnosis and adequate management are critical to reduce mortality. This study aims to identify clinical and hematological features that could be useful to discriminate dengue from other febrile illnesses (OFI) up to the third day of disease. Methods: We conducted a sectional diagnostic study with patients aged 12 years or older who reported fever lasting up to three days, without any evident focus of infection, attending an outpatient clinic in the city of Rio de Janeiro, Brazil, between the years 2005 and 2008. Logistic regression analysis was used to identify symptoms, physical signs, and hematological features valid for dengue diagnosis. Receiver-operating characteristic (ROC) curve analyses were used to define the best cut-off and to compare the accuracy of generated models with the World Health Organization (WHO) criteria for probable dengue. Results: Based on serological tests and virus genome detection by polymerase chain reaction (PCR), 69 patients were classified as dengue and 73 as non-dengue. Among clinical features, conjunctival redness and history of rash were independent predictors of dengue infection. A model including clinical and laboratory features (conjunctival redness and leukocyte counts) achieved a sensitivity of 81% and specificity of 71% and showed greater accuracy than the WHO criteria for probable dengue. Conclusions: We constructed a predictive model for early dengue diagnosis that was moderately accurate and performed better than the current WHO criteria for suspected dengue. Validation of this model in larger samples and in other sites should be attempted before it can be applied in endemic areas.
Keywords: Dengue/diagnosis
Signs and symptoms
Sensitivity and specificity
Fever/diagnosis
DeCS: Dengue
Febre
Diagnóstico
Issue Date: 2013
Publisher: BioMed Central
Citation: DAUMAS, Regina P.; et al. Clinical and laboratory features that discriminate dengue from other febrile illnesses: a diagnostic accuracy study in Rio de Janeiro, Brazil. BMC Infectious Diseases, v.13, n.77, 9p, 2013.
DOI: 10.1186/1471-2334-13-77
ISSN: 1471-2334
Copyright: open access
Appears in Collections:ENSP - Artigos de Periódicos
INI - Artigos de Periódicos
IOC - Artigos de Periódicos

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