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

Abstract

Background: Early prediction of severe dengue could significantly assist patient triage and case management.

Methods: We 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 primary endpoint of interest was severe dengue (2009 World Health Organization Guidelines), and predefined risk variables were collected at the time of enrollment to enable prognostic model development.

Results: 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.

Conclusions: The ESDI had acceptable performance features (area under the curve = 0.95, sensitivity 87% (95% confidence interval [CI], 80%-92%), specificity 88% (95% CI, 87%-89%), positive predictive value 10% (95% CI, 9%-12%), and negative predictive value of 99% (95% CI, 98%-100%) in the population of all 7563 enrolled children. A score chart, for routine clinical use, was derived from the prognostic model and could improve triage and management of children presenting with fever in dengue-endemic areas.

Keywords: dengue; diagnosis; tropical infectious diseases..

Figure 1.

Study profile with a description of the patient cohort and subgroups that were used to derive the prognostic models. Abbreviations: ELISA, enzyme-linked immunosorbent assay; IgM, immunoglobulin G; NS1, nonstructural protein 1; RT-PCR, reverse-transcription polymerase chain reaction.

Figure 2.

Performance of the Early Severe Dengue Identifier (ESDI) in reverse-transcription polymerase chain reaction–positive dengue patients. A, Possible sensitivity/specificity trade-offs for different cutoff values of the ESDI and the distance from the corresponding points on the receiver operating characteristic (ROC) curve to the upper left corner (perfect model). B, ROC curve. C, Calibration plot displaying a scatterplot-smoother of predicted vs observed risks (dashed line), predicted vs observed risks for 10 patient strata of equal size grouped according to predicted risks (triangles), and the ideal identity line (solid line). The rugs at the bottom of the graphs characterize the distribution of predicted risks in severe dengue and nonsevere dengue cases, respectively. Abbreviation: AUC, area under the curve.

Figure 3.

Nomogram of the prognostic model to predict the risk of severe dengue. A vertical line from a predictor value to the “points” axis assigns points to the 4 required variables: vomiting, platelet count (PLT), nonstructural protein 1 (NS1) rapid test status, and aspartate aminotransferase (AST) level. The sum of these points (total points) can then be translated to the corresponding predicted risk of severe dengue.