The application of automated cell population data for early diagnosis of dengue fever

Abstract

Background: Dengue fever is a common tropical illness caused by an arbovirus. A complete blood count is one of the standard investigations performed on a febrile patient. The automated hematology analyzer utilizes the principle of volume (V), conductivity (C), and scatter (S) to generate total and differential leukocyte counts. The present study analyzed the utility of volume, conductivity, and scatter (VCS) parameters in the early diagnosis of dengue. Subjects and Methods: In this study, 700 blood samples were analyzed in the Beckman Coulter LH 780 analyzer. Their total, differential leukocyte counts, lymphocyte, and monocyte VCS parameters were collected. Demographic and clinical details of the patients were retrieved, and statistical analysis was done using IBM SPSS statistics, version 23.0. Results: Among the 700 cases, 271 (38.7%) had viral illnesses and 429 (61.3%) were patients who had diagnoses of nonviral causes. Of 271 viral illnesses, 168 (62%) cases had dengue. There were statistically significant differences (P < 0.05) in total and differential leukocyte counts and VCS parameters of lymphocytes and monocytes in dengue and nondengue viral causes when compared with nonviral causes. For the diagnosis of dengue, mean lymphocyte volume at a cutoff value of above 77 achieved a sensitivity of 60% and specificity of 61% and mean monocyte volume above 145 had a sensitivity and specificity of 62% and 59%, respectively. Conclusion: This study showed changes in VCS parameters of lymphocytes and monocytes, which can be utilized for the early diagnosis of dengue. They can be used, without incurring additional costs, to generate flags to prompt specific testing independent of clinical suspicion.

Keywords

• cell population data
• dengue fever
• monocyte
• viral illnesses