Factors Influencing Clinical Manifestations as Predictors of Dengue Severity: A Patient-Based Study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Dengue fever presents with a broad spectrum of symptoms, ranging from mild to life-threatening complications. Understanding the clinical symptoms based on demographic and biochemical predictors of severity is vital for early intervention. A cross-sectional study was conducted among 375 dengue patients. Clinical symptoms, demographic profiles, platelet counts, and infection history were analyzed. Then the level of severity has been categorized as Dengue Fever (DF), Dengue Fever with Warning Signs (DFWS), and Severe Dengue (SD), emphasizing warning signs like abdominal pain, nausea/vomiting, and hemorrhage as indicators of severity. Results show males were more affected, while females exhibited more severe symptoms, including hypotension, and hemorrhage. Pediatric patients showed higher prevalence of warning signs, such as abdominal pain and poor appetite, suggesting increased severity risk. Among occupations, homemakers had the highest incidence of warning signs, potentially due to delayed healthcare access and domestic mosquito exposure. Severe thrombocytopenia (<20k/μL) was associated with low blood pressure and hemorrhage. Secondary infections showed a strong association with severe manifestations, supporting the role of antibody-dependent enhancement. Female gender, younger age, homemaker occupation, low platelet counts, and secondary infections were strongly linked with severe dengue. These findings highlight the need for early detection of the severity level of dengue infections and management strategies to prevent disease progression in high-risk groups.
DOI: 10.5455/jbph.2025.05
Authors: Sumaya Sumaya, † †, Papri Biswas, † †, Banya Plaboni, Md. Hossain, Umme Salma, Tanvir Ahmmed, Md. Maruf, Nishat Omi, Erjan Khan, No author No author, Shifat Shipu, Jaber Hridoy, Md. Islam, Md. Hasan
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4412972654