Clinical Predictors of Severe Dengue

Abstract

Background: Dengue fever is a significant public health concern, with severe cases leading to life-threatening complications. Early identification of severe dengue can improve patient outcomes and optimize healthcare resource utilization. The objective of the study was to evaluate clinical and laboratory predictors of severe dengue and their utility in clinical decision-making.

Methods: A prospective cohort study was conducted at Ziauddin Hospital, Karachi, from February to September 2024. A sample size of 66 with a 95% confidence interval and 5% level of significance was calculated using OpenEpi. The convenience sampling technique was used.  Patients were categorized into two groups: Group A (≥3 warning signs or comorbidities) and Group B (≤3 warning signs, no comorbidities). Data were collected using a structured proforma and analyzed in SPSS 25. Logistic regression and receiver operating characteristic analysis were used to evaluate different predictors of severe dengue. Receiver operating characteristic analysis was used to evaluate different predictors of severe dengue. A p-value of less than 0.05 was considered significant.

Results: The mean age was 35.93±14.96 years, with 66.7% males. Significant predictors included a fall in pulse pressure (p=0.002), elevated AST levels (p=0.04), AST/platelet ratio (APR) (p=0.003), and hypoalbuminemia (p<0.0001). The predictive model, including APR and fall in pulse pressure (χ² = 4.651, p=0.702), explained 68.5% of severe dengue variance and had excellent discriminatory power (AUC=0.961) with 100% sensitivity and 91.1% specificity.

Conclusion: Clinical parameters such as pulse pressure and APR are reliable predictors of severe dengue. Further validation in larger cohorts can refine risk stratification and enhance management strategies.