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Predicting the severity of dengue fever in children on admission based on clinical features and laboratory indicators: application of classification tree analysis


Dengue fever is a re-emerging viral disease commonly occurring in tropical and subtropical areas. The clinical features and abnormal laboratory test results of dengue infection are similar to those of other febrile illnesses; hence, its accurate and timely diagnosis for providing appropriate treatment is difficult. Delayed diagnosis may be associated with inappropriate treatment and higher risk of death. Early and correct diagnosis can help improve case management and optimise the use of resources such as hospital staff, beds, and intensive care equipment. The goal of this study was to develop a predictive model to characterise dengue severity based on
early clinical and laboratory indicators using data mining and statistical tools.


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English
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NONE
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BMC Pediatrics (2018) 18:109
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