Haematological parameters as predictors of severe dengue: a study from northern districts of West Bengal.

Abstract

Background objectives: A hike in dengue cases was recorded in last two years, resulting from both single and multiple-serotypes of dengue virus (DENV) and secondary infections, culminating in significant hospitalizations and deaths in India. This study focuses on evaluating symptomatic and haematological parameters in acute dengue patients of the northern part of West Bengal to predict disease severity early on and also to analyze the correlation between circulating DENV serotypes with severity.

Methods: Dengue patients (N=540) diagnosed as NS1 positives were categorized into 13.7% severe DHF (N=74) and 86.3% mild DF (N=466) and prediction of risk was done using logistic regression. DENV RNA was isolated from blood, converted to cDNA, and detected/serotyped via RT-qPCR by using DENV specific primers.

Results: Only 14.48% (N=11) patients showed single serotypic (DENV2 or DENV3) infection of dengue. In contrast, multi-serotypic infections (N=65) with the prevalence of DENV2 and DENV3 co-infections were found among the dengue patients, affecting severe changes in the most critical haematological parameters such as hematocrit and platelet count. The multivariate binary logistic regression model revealed that only six parameters viz., age (p=0.032), presence of joint pain (p=0.015), Haemoglobin level (p<0.001), total RBC count (p=0.024), total WBC count (p=0.003), lymphocyte% (p=0.019) were found to be significantly associated with the risk of DHF.

Interpretation conclusion: Most prevalent DENV2 and DENV3 infections significantly impact hematocrit and platelet counts in the study region. Our prediction model, incorporating age, joint pain, hemoglobin, RBC, WBC, and lymphocyte, may effectively predict dengue severity.