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Use of simple clinical and laboratory predictors to differentiate influenza from dengue and other febrile illnesses in the emergency room

tetano

Editor, Senior Moderator
BMC Infect Dis. 2014 Nov 25;14(1):623. doi: 10.1186/s12879-014-0623-z.
Use of simple clinical and laboratory predictors to differentiate influenza from dengue and other febrile illnesses in the emergency room.
Huang SY, Lee IK1, Wang L, Liu JW, **** SC, Chen CC, Chang TY, Huang WC.
Author information
Abstract
BACKGROUND:

Clinical differentiation of influenza from dengue and other febrile illnesses (OFI) is difficult, and available rapid diagnostic tests have limited sensitivity.
METHODS:

We conducted a retrospective study to compare clinical and laboratory findings between (i) influenza and dengue and (ii) influenza and OFI.
RESULTS:

Of 849 enrolled patients, the mean time between illness onset and hospital presentation was 1.7, 3.7, and 3 days for influenza, dengue, and OFI, respectively. Among pediatric patients (≤18 years) (445 influenza, 24 dengue, and 130 OFI), we identified absence of rashes, no leukopenia, and no marked thrombocytopenia (platelet counts <100 ? 109 cells/L) as predictors to distinguish influenza from dengue, whereas rhinorrhea, malaise, sore throat, and mild thrombocytopenia (platelet counts 100-149 ? 109/L) were predictors that differentiated influenza from OFI. Among adults (>18 years) (81 influenza, 124 dengue, and 45 OFI), no leukopenia and no marked thrombocytopenia distinguished influenza from dengue, while rhinorrhea and malaise differentiated influenza from OFI. A diagnostic algorithm developed to distinguish influenza from dengue using rash, leukopenia, and marked thrombocytopenia showed >90% sensitivity to identify influenza in pediatric patients.
CONCLUSIONS:

This study identified simple clinical and laboratory parameters that can assist clinicians to distinguish influenza from dengue and OFI. These findings may help clinicians diagnose influenza and facilitate appropriate management of affected patients, particularly in resource-poor settings.

PMID:
25421019
[PubMed - in process]
PMCID:
PMC4245735

Free PMC Article

http://www.ncbi.nlm.nih.gov/pubmed/25421019
 
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