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An Evidence-Based Algorithm for Early Prognosis of Severe Dengue in the Outpatient Setting “Early Severe Dengue Identifier”

23.10.2017 Posted By : PathKind Labs Team Share :

Dengue is  one of the most common arboviral infection of humans and a public health burden in India. The doctor seeing a child with 3 days of fever in whom dengue is suspected is faced with a dilemma : to send the patient home with request that they return for follow up or to admit for observation as they approach the critical phase which usually falls between 4 to 6 days of infection. The hospitalization of a large number of dengue cases for observation inevitably places a burden on healthcare resources and has direct and indirect costs to patients and their families. As the great majority of clinically severe complications in dengue occur between 4th and 6th day of illness, there appeared to be a window of opportunity to both make a diagnosis and try to identify children at greatest risk of severe complications.

In order to develop an evidence based algorithm to identify children likely to progress to severe illness,  scientists in Australia together with doctors in Vietnam  prospectively investigated 7563 children with ≤3 days of fever recruited in the outpatient departments of 6 hospitals in southern Vietnam between 2010 and 2013. The analysis population comprised 7544 patients, of whom 2060 (27.3%) had laboratory-confirmed dengue; nested among these were 117 (1.5%) severe cases. In the multivariate logistic model, a history of vomiting, lower platelet count, elevated aspartate aminotransferase (AST) level, positivity in the nonstructural protein 1 (NS1) rapid test, and viremia magnitude were all independently associated with severe dengue. The final prognostic model (Early Severe Dengue Identifier [ESDI]) included history of vomiting, platelet count, AST level and NS1 rapid test status. These simple tools can be used in clinical practice.

After results of four parameters: 1. Vomiting; 2. NS1 Ag, 3. Platelet count and 4. AST  how many x of normal (taking 40 U/L as normal) is available, risk of severe dengue can be calculated. Draw horizontal lines from a predictive value to the point axis to the four variables. The sum of these points (total points) can then be translated to the corresponding risk factor for severe dengue.

For example: a patient with vomiting, a platelet count of 100,000 cells/ul, positive NS1 rapid test and an AST of 280 U/L (7 fold increase compared with the upper normal value of 40 U/L) has a score of 5 + 89 + 14+ 26= 134 and the corresponding risk of severe dengue is approximately 35 %.

In the present study use of ESDI has acceptable performance features (area under the curve – 0.95%, sensitivity 87%, specificity 88%, positive predictive value 10% and negative predictive value of 99%.) The high NPV indicates that while no serious case will be missed, due to low PPV (10%), many of the cases may resolve spontaneously.

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