Evaluation of Clinical and Hematological Parameters of Acute Febrile Illness Patients: A Dengue Predictive Model

Objectives: In tropical and subtropical nations dengue is a main public health matter. We try to find to analyze the clinical and hematological factors from a Complete Blood Count (CBC) which differentiate dengue infection. The purpose of the study was to categorize clinical features and hematological parameters and develop predictive model of high fever patients was treated as early marker and possible prognosticator factors of dengue. Methods: Demographic data analysis with variables like gender, place, age and clinical data analysis of clinical parameters with dengue confirmation test have been done develop predictive model factors to differentiate Dengue Infection (DI) from CBC data of Acute Febrile Illness (AFI) patients in Delhi-NCR, Sonepat region from 2015 to 2018. Results: Among 223 patients, 167 were confirmed with 100 primary and 67 secondary DI of maximum number male patients in the age group of 10-30 years from 2015 to 2018 while 56 had negative results. Badhkhalsa, Jakholi, Sewli and Rai were high dengue reported area in Delhi-NCR, Sonepat. There was a statistically significant value (p<0.05) of Total Leukocytes Count (TLC) cells/cmm during AFI phase from 2015 to 2018 using logistic regression and ROC graph. TLC (cells/cmm) had a higher area ± SE value from 2015 to 2018 (0.66 ± 0.07, 0.76 ± 0.10, 0.68 ± 0.07 and 0.79 ± 0.06) respectively which were statistically significant (p<0.05). Dengue diagnosis test of mean value of TLC (<4000 cells/cmm) from 2015 to 2018 were evaluated with a prevalence of dengue disease of 35.09%- 58.06%, sensitivity of 41.03%-100%, specificity of 24.10%-93.10% and accuracy rate of diagnosis evaluation of 62.07%-70.97% were related to danger sign DI in Delhi-NCR, Sonepat area. Conclusion: As per our study we can conclude that due to non-specific clinical features and delayed of confirmation test, among the clinical parameters TLC could be the useful feature for quick finding of DI which is unique, simple, easily available, cost effective approach mainly in rural area.