A benchmark dataset for analyzing hematological responses to dengue fever in BangladeshMendeley Data

Abstract

Dengue fever is an important public health problem in tropical and subtropical areas, and the understanding of its hematological changes is crucial for the improvement of diagnosis, treatment, and prognosis. This data set presents hematological parameters for the systematic record of patients suffering from dengue infection: age, sex, hemoglobin, WBC count, differential count, RBC panel, platelet count, and PDW. The dataset has in-depth records of patients admitted to Upazila Health Complex, Kalai, Jaipurhat, Bangladesh and thus offers an opportunity for further analysis of hematological changes produced by dengue infection. This dataset is valuable because of the potential contribution that these data will make to developing predictive models for disease severity and patient outcomes, enhancing clinical decision-making. It serves as a benchmark for the comparison of hematological responses across different demographics and geographical locations, adding value to the knowledge of dengue in the world. Moreover, the study has gone further to indicate how the characteristics related to blood may be affected by various treatment regimens, hence offering better treatment protocols. The data preprocessing in this study involved cleaning, normalization, and encoding of the variables before proceeding to perform the statistical analysis. This showed a Chi-Square test for no significant association of sex with the diagnostic outcome, as given by the p-value of 0.277. On the other hand, the Z-test and T-test results indicated a significant difference in the hemoglobin levels concerning gender; the obtained p-values are 2.534 × 10-8 and 4.325 × 10-8, respectively. These findings emphasize how gender influences hematological responses against dengue. In summary, this database will be a great help and will give a leading edge to the research studies of dengue, public health strategies, and improved diagnosis and treatment modalities for patients.

Keywords

• Dengue fever
• Hematological parameters
• Predictive models
• Clinical decision-making
• Gender influence
• Blood analysis