Modelling Outcome of Drug Resistant Tuberculosis and Drug Susceptible Tuberculosis Patients in Oyo State

Author:

O. Omosebi,S.O. Olanrewaju,O.A. Adejumo

Abstract

TB is perhaps the most important contagious disease in the world and the leading cause of mortality by an infectious disease. As a result, WHO declared that achieving the reduction in TB incidence rate for achievement of the 90-90-90 target of the END-TB strategy will be an illusion, if something severe is not done. Therefore, it is imperative to assess the visibility of achieving the END-TB goal in the country (Nigeria) by assessing the success of TB treatments so far in the country. Hence, this paper aims to model the outcome of drug-resistant-tuberculosis and drug-susceptible-tuberculosis patients in Oyo state of Nigeria using the logit function of estimating binary logistic regression model vis-à-vis identifying the success of these TB treatments. At baseline, based on WHO categorization, the study revealed the commonest cases of patients receiving DS-TB seen are ‘New’ (90.5%) followed by relapse after failure (4.2%). Contrarily, the commonest cases of patients receiving DR-TB seen are treatment after failure (44.3%), new (27.5%) and relapse after failure cases (20.6%). Four months after starting treatment, 91.5% and 3.2% were reportedly alive and dead respectively for patients receiving DS-TB treatment while 85.3% and 11.5% were reportedly alive and dead respectively for receiving DR-TB treatment. Hence, the percentage success of DS-TB recorded was higher than the recorded for DR-TB patients. Furthermore, the chi-square results for DS-TB patients indicated that mortality significantly associated with DS-TB categorised patients (i.e. Relapse) and HIV status (i.e. Negative). Also, for the DR-TB patients, the results depicted that mortality significantly associated with DR-TB categorised patients (i.e. TAF, Treatment after Loss to Follow Up and New), both HIV status and Sputum Smear status (i.e. Positive). Nevertheless, among other findings, the binary logistic regression model estimations revealed that categorised New patients and Sputum Smear status unfavourably and significantly predicted the treatment outcome (mortality) of DS-TB and DR-TB patients. As well, categorised Relapse patients unfavourably and significantly predicted the treatment outcome (mortality) of DR-TB patients. Thus, the DS-TB method of treatment is recommended in order to achieve the target goal of the END-TB strategy in Oyo state Nigeria.

Publisher

African - British Journals

Subject

Sociology and Political Science,Applied Psychology,Religious studies,Social Psychology,Animal Science and Zoology,Cell Biology,Molecular Biology,General Medicine,Pathology and Forensic Medicine,Infectious Diseases,Microbiology (medical),General Immunology and Microbiology,Molecular Biology,Immunology and Allergy,Infectious Diseases,Microbiology (medical),General Immunology and Microbiology,General Medicine,Immunology and Allergy,Infectious Diseases,Public Health, Environmental and Occupational Health,General Medicine,Microbiology,Parasitology,Infectious Diseases,Microbiology (medical),Molecular Biology,Immunology,Immunology and Allergy,General Medicine,General Medicine,Pathology and Forensic Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3