Early Predictors of Severity in Dengue Fever: An Ambidirectional Cohort Study
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Abstract
Objective: To identify early clinical and laboratory predictors of severe dengue among hospitalized patients during the 2024 outbreak in Islamabad.
Method: This ambidirectional (mixed) cohort study included 281 laboratory confirmed dengue cases admitted to tertiary care hospital in Islamabad from July to December 2024. Dengue severity was classified according to the WHO criteria as dengue without warning signs, dengue with warning signs and severe dengue using purposive sampling technique. Detailed Clinical features with initial presenting features and laboratory parameters during first 4 days of illness were extracted from the record of the patients and patients were followed for change in severity and progression in the course of illness were analyzed. Uni-variate and multivariate logistic regression was performed to identify independent predictor of severe dengue at 5% alpha.
Results: Among the 281 study participants, 51.2%, 45.2% and 3.6% progressed to DF without warning signs, Dengue with warning sign & Severe dengue respectively. Severe dengue was significantly associated with age >35years (p<0.001), [dengue with non-severe disease has age 30.7±12.3, while dengue with severe disease has age 38.6±15.8], diabetes (p=0.035), hypertension (p=0.035), nausea, vomiting, diarrhea, arthralgia rash and bleeding manifestations (p<0.01). Early thrombocytopenia (<50,000/µL within 4 days of illness) strongly correlate with severity (p<0.001). IgM+IgG co-positivity increased significantly across severity categories (p<0.001). Multivariate analysis identified shortness of breath [OR:27.8(6.3-123.7) 95%CL p<0.001], bleeding manifestations [9.2 (3.7–22.4 CL 95%)(p<0.001)] and platelet count <50,000/µL within 4 days of illness [OR:8.6 (3.4–22.396%CI) p<0.001) as independent predictors of severe dengue.
Conclusion: Early onset thrombocytopenia, bleeding and shortness of breath are critical independent predictors of severe dengue. Incorporating these clinical indicators in initial assessment may improve risk stratification and reduce morbidity and mortality during outbreak in resource-limited setting.
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