Simple Clinical and Laboratory Predictors of Chikungunya versus Dengue Infections in Adults
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Simple Clinical and Laboratory Predictors of Chikungunya versus Dengue Infections in Adults

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  • English

  • Details:

    • Alternative Title:
      PLoS Negl Trop Dis
    • Description:
      Background

      Dengue and chikungunya are co-circulating vector-borne diseases with substantial overlap in clinical presentations. It is important to differentiate between them during first presentation as their management, especially for dengue hemorrhagic fever (DHF), is different. This study compares their clinical presentation in Singapore adults to derive predictors to assist doctors in diagnostic decision-making.

      Methods

      We compared 117 patients with chikungunya infection diagnosed with reverse transcription-polymerase chain reaction (RT-PCR) with 917 dengue RT-PCR-positive adult patients (including 55 with DHF). We compared dengue fever (DF), DHF, and chikungunya infections by evaluating clinical characteristics of dengue and chikungunya; developing classification tools via multivariate logistic regression models and classification trees of disease etiology using clinical and laboratory factors; and assessing the time course of several clinical variables.

      Findings

      At first presentation to hospital, significantly more chikungunya patients had myalgia or arthralgia, and fewer had a sore throat, cough (for DF), nausea, vomiting, diarrhea, abdominal pain, anorexia or tachycardia than DF or DHF patients. From the decision trees, platelets <118×109/L was the only distinguishing feature for DF versus chikungunya with an overall correct classification of 89%. For DHF versus chikungunya using platelets <100×109/L and the presence of bleeding, the overall correct classification was 98%. The time course analysis supported platelet count as the key distinguishing variable.

      Interpretation

      There is substantial overlap in clinical presentation between dengue and chikungunya infections, but simple clinical and laboratory variables can predict these infections at presentation for appropriate management.

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