Abstract
Tuberculosis (TB), which is caused by Mycobacterium tuberculosis (MTB), is a serious infectious disease with high infection and mortality rates and is a public health problem around the world. According to the World Health Organization (WHO) report, one-third of the world's population is latently infected with MTB, and 5 to 10% of those with latent TB infection (LTBI) have the potential to develop active TB once in their lifetime. Therefore, TB management for promptly distinguishing LTBI from active TB and for proper treatment is important. LTBI is currently diagnosed using the tuberculin skin test (TST) and interferon gamma (IFN-γ) release assay (IGRA). However, this test is substantially limited by its inability to distinguish active TB from LTBI. It is necessary to discover indicators that can be used for effective TB management and to develop diagnostic methods. In the present study, we used IGRA and complete blood count (CBC) analysis for discrimination of active TB, LTBI, and healthy control groups. The results showed that the number of WBC was significantly increased in the group with active TB (p < 0.0100) and level of hemoglobin (Hb) was significantly decreased (p < 0.0010) in the CBC than those of the healthy control and LTBI groups. In the WBC differential count, the number of neutrophils and monocytes were increased (p < 0.0010) in active TB group, where as those of lymphocytes were significantly decreased (p < 0.0100) in active TB group compared healthy control group. Results verified that the levels of total WBC, Hb, neutrophils, lymphocytes and monocytes were statistically significant (p < 0.0500) and the AUC was approximately 0.8613. In addition, receiver operating characteristic (ROC) curve analysis was performed to confirm the clinical usefulness between active TB and healthy control groups. In conclusion, based on these data demonstrated that the usefulness of these potential indicators for differential diagnosis, according to the result can be provided for effective diagnosis and treatment by comparing the expression patterns of the markers in the whole blood of the active TB, LTBI, and healthy control groups. Furthermore, this study needs to investigate a larger number of clinical specimens later to develop biomarkers according to the state of infection with MTB such as LTBI and active TB, as well as after treatment.
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More From: Journal of Clinical Tuberculosis and Other Mycobacterial Diseases
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