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A Murine Model of Dengue Virus-induced Acute Viral Encephalitis-like Disease
Published on: April 28, 2019
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Establishment of SMS Dengue Severity Score
Sudhir Bhandari1, Govind Rankawat2, Barkha Goyal3
1Senior Professor.
The Journal of the Association of Physicians of India
|September 9, 2022
Summary
A new scoring system accurately predicts dengue infection severity using clinical data and routine tests. This tool aids in rapid assessment and timely treatment for dengue fever, dengue hemorrhagic fever, and dengue shock syndrome.
Area of Science:
- Infectious Diseases
- Clinical Medicine
- Public Health
Background:
- Dengue infection rapidly progresses to life-threatening conditions.
- Effective prediction of dengue severity is crucial for timely intervention.
- Current methods may lack practicality for rapid clinical assessment.
Purpose of the Study:
- To develop a practical scoring system for predicting dengue infection severity.
- To utilize clinical profiles and routine laboratory tests for severity assessment.
- To differentiate between dengue fever (DF), dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS).
Main Methods:
- A cross-sectional observational study involving 500 dengue patients.
- Collection of patient demographics, clinical symptoms, and laboratory results.
- Development of a scoring system based on identified clinical and laboratory predictors.
Main Results:
- Patients with DHF and DSS exhibited higher scores correlating with worsening clinical features and laboratory values.
- Key predictors of severity included older age, elevated WBC count, increased hematocrit, prolonged prothrombin time, decreased platelets, and organ involvement.
- The scoring system ranged from 0-12, with scores 0-3 for DF, 4-8 for DHF, and 9-12 for DSS.
- The system correctly classified original severity grades in 63% of cases.
Conclusions:
- The developed dengue infection severity score effectively classifies patients into DF, DHF, or DSS categories.
- This scoring system facilitates rapid assessment of dengue infections.
- Early and accurate categorization enables prompt initiation of appropriate treatment protocols.

