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Portable Paper-Based Immunoassay Combined with Smartphone Application for Colorimetric and Quantitative Detection of Dengue NS1 Antigen
Published on: January 26, 2024
Reviewing the development, evidence base, and application of the revised dengue case classification
1Special Programme for Research and Training in Tropical Diseases (TDR_WHO), Geneva, Switzerland.
Pathogens and Global Health
|September 5, 2012
Summary
A new evidence-based dengue classification system was developed, improving clinical management and disease awareness. This revised model distinguishes dengue with warning signs and severe dengue, offering a more accurate approach than the previous DF/DHF/DSS scheme.
Area of Science:
- Tropical Medicine
- Infectious Diseases
- Public Health
Background:
- The existing dengue classification (DF/DHF/DSS) has limitations, including complexity in clinical practice and misclassification of severe cases.
- Clinicians question the emphasis on hemorrhage over plasma leakage in severe dengue and the low sensitivity of the tourniquet test.
Purpose of the Study:
- To prospectively develop and validate an evidence-based dengue case classification system.
- To improve the accuracy, standardization, and clinical applicability of dengue diagnosis and management.
Main Methods:
- Systematic literature review to identify shortcomings of the existing DF/DHF/DSS classification.
- Analysis of global dengue guidelines and prospective cohort studies in multiple countries.
- Expert consensus meetings and field testing of a revised classification scheme.
Main Results:
- The DF/DHF/DSS classification shows difficulties in application, variability, and does not accurately reflect disease severity.
- A revised classification distinguishing dengue with warning signs and severe dengue demonstrated superior applicability and accuracy.
- Field testing in 18 countries favored the revised classification for standardizing management and improving patient care.
Conclusions:
- The revised dengue case classification provides a more accurate and practical tool for clinical management and public health.
- This evidence-based approach can serve as a model for developing other disease classification systems.
- Further studies are ongoing to refine predictive values for warning signs and diagnostic criteria.

