Abstract
BackgroundDengue causes 50 million infections per year, posing a large disease and economic burden in tropical and subtropical regions. Only a proportion of dengue cases require hospitalization, and predictive tools to triage dengue patients at greater risk of complications may optimize usage of limited healthcare resources. For severe dengue (SD), proposed by the World Health Organization (WHO) 2009 dengue guidelines, predictive tools are lacking.MethodsWe undertook a retrospective study of adult dengue patients in Tan Tock Seng Hospital, Singapore, from 2006 to 2008. Demographic, clinical and laboratory variables at presentation from dengue polymerase chain reaction-positive and serology-positive patients were used to predict the development of SD after hospitalization using generalized linear models (GLMs).Principal findingsPredictive tools compatible with well-resourced and resource-limited settings – not requiring laboratory measurements – performed acceptably with optimism-corrected specificities of 29% and 27% respectively for 90% sensitivity. Higher risk of severe dengue (SD) was associated with female gender, lower than normal hematocrit level, abdominal distension, vomiting and fever on admission. Lower risk of SD was associated with more years of age (in a cohort with an interquartile range of 27–47 years of age), leucopenia and fever duration on admission. Among the warning signs proposed by WHO 2009, we found support for abdominal pain or tenderness and vomiting as predictors of combined forms of SD.ConclusionsThe application of these predictive tools in the clinical setting may reduce unnecessary admissions by 19% allowing the allocation of scarce public health resources to patients according to the severity of outcomes.
Highlights
After successful eradication programs of the dengue vector Aedes mosquitoes in Latin America in the 1940s, both disease and vector have resurged and disseminated globally since the late 1970s [1], posing substantial disease and economic burdens on tropical and subtropical regions [2,3]
The application of these predictive tools in the clinical setting may reduce unnecessary admissions by 19% allowing the allocation of scarce public health resources to patients according to the severity of outcomes
We find that some common features such as age, gender, fever duration, fever on admission, vomiting or abdominal distension can be good predictors of severe dengue
Summary
After successful eradication programs of the dengue vector Aedes mosquitoes in Latin America in the 1940s, both disease and vector have resurged and disseminated globally since the late 1970s [1], posing substantial disease and economic burdens on tropical and subtropical regions [2,3]. As a result of reduced herd immunity [7], cyclical epidemics have occurred since the 1990s, leading to an estimated average annual economic impacts of US $115 million [8]. Dengue causes 50 million infections per year, posing a large disease and economic burden in tropical and subtropical regions. A proportion of dengue cases require hospitalization, and predictive tools to triage dengue patients at greater risk of complications may optimize usage of limited healthcare resources. For severe dengue (SD), proposed by the World Health Organization (WHO) 2009 dengue guidelines, predictive tools are lacking
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