Journal of Clinical Virology
Volume 35, Issue 2 , Pages 147-153, February 2006

Distinguishing dengue fever from other infections on the basis of simple clinical and laboratory features: Application of logistic regression analysis

  • David Chadwick

      Affiliations

    • Department of Infectious Diseases, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore 308433, Singapore
    • Department of Infection and Travel Medicine, The James Cook university Hospital, Middlesbrough TS4 3BW, UK
    • Corresponding Author InformationCorresponding author. Tel.: +44 1642 854 339; fax: +44 1642 854 462.
  • ,
  • Barbara Arch

      Affiliations

    • Centre for Medical Statistics and Health Evaluation, University of Liverpool, Liverpool L69 3GS, UK
  • ,
  • Annelies Wilder-Smith

      Affiliations

    • Department of Infectious Diseases, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore 308433, Singapore
  • ,
  • Nicholas Paton

      Affiliations

    • Department of Infectious Diseases, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore 308433, Singapore

Received 13 April 2005; received in revised form 10 June 2005; accepted 17 June 2005. published online 01 August 2005.

Abstract 

Background

Dengue fever is a frequent cause of admission to hospital in South East Asia, however many of the clinical characteristics and abnormalities on laboratory investigations at presentation are found in other common infections.

Objectives

To describe the clinical and laboratory features of dengue fever and other common febrile illnesses in Singapore.

Study design

We performed a prospective study of consecutive adult admissions to an infectious diseases hospital. Logistic regression analysis was used to identify symptoms, physical signs and laboratory features that differentiated dengue fever from other febrile illnesses within the first 2 days of admission.

Results

Of the 381 patients studied, 148 had serologically confirmed dengue fever. Most of these had uncomplicated dengue fever, and only 9% had dengue haemorrhagic fever. A model based on clinical features alone (including a variety of cutaneous signs, pulse rate and the presence of pharyngeal injection) was able to differentiate dengue fever from other infections with a sensitivity of 74% and specificity of 79%. A model based on clinical features (rash) and laboratory parameters (white cell count, haemoglobin, prothrombin time, creatinine and bilirubin levels), achieved a sensitivity of 84% and specificity of 85%.

Conclusions

A combination of simple clinical and laboratory parameters are potentially able to predict dengue fever with a high level of accuracy in adults presenting to hospital with febrile illnesses in Singapore.

Keywords: Dengue, Fever, Clinical, Laboratory, Infections, Diagnosis

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PII: S1386-6532(05)00172-1

doi:10.1016/j.jcv.2005.06.002

Journal of Clinical Virology
Volume 35, Issue 2 , Pages 147-153, February 2006