Ekuka Godfrey, Kawooya Ismael, Kayongo Edward, Ssenyonga Ronald, Mugabe Frank, Chaiga Peter Awongo, Nsawotebba Andrew, Tweya Hannock, Mijumbi-Deve Rhona
National TB Reference Laboratory, Plot 106-1062 Butabika Road, Luzira, Kampala, Uganda.
The Center for Rapid Evidence Synthesis (ACRES), Makerere University College of Health Sciences, Kampala,Uganda.
Afr Health Sci. 2020 Jun;20(2):633-640. doi: 10.4314/ahs.v20i2.11.
Drop out of presumptive TB individuals before making a final diagnosis poses a danger to the individual and their community. We aimed to determine the proportion of these presumptive TB drop outs and their associated factors in Bugembe Health Centre, Jinja, Uganda.
We used data from the DHIS2, presumptive and laboratory registers of Bugembe Health Centre IV for 2017. Descriptive statistics were used to summarize the population characteristics. A modified Poisson regression model via the generalized linear model (GLM) with log link and robust standard errors was used for bivariate and multivariate analysis.We used data from the DHIS2, presumptive and laboratory registers of Bugembe Health Centre IV for 2017. Descriptive statistics were used to summarize the population characteristics. A modified Poisson regression model via the generalized linear model (GLM) with log link and robust standard errors was used for bivariate and multivariate analysis.
Among the 216 registered presumptive TB patients who were less than 1% of patients visiting the outpatients' department, 40.7% dropped out before final diagnosis was made. Age and HIV status were significantly associated with pre-diagnostic drop out while gender and distance from the health center were not.
A high risk to individuals and the community is posed by the significant proportion of presumptive TB patients dropping out before final diagnosis. Health systems managers need to consider interventions targeting young persons, male patients, HIV positive persons.
疑似结核病患者在最终诊断前失访对个人及其社区构成危险。我们旨在确定乌干达金贾布根贝健康中心这些疑似结核病失访者的比例及其相关因素。
我们使用了布根贝健康中心四号2017年的DHIS2数据、疑似病例和实验室登记数据。描述性统计用于总结人群特征。通过具有对数链接和稳健标准误差的广义线性模型(GLM)的修正泊松回归模型用于双变量和多变量分析。我们使用了布根贝健康中心四号2017年的DHIS2数据、疑似病例和实验室登记数据。描述性统计用于总结人群特征。通过具有对数链接和稳健标准误差的广义线性模型(GLM)的修正泊松回归模型用于双变量和多变量分析。
在216名登记的疑似结核病患者中,他们占门诊部就诊患者的比例不到1%,40.7%在最终诊断前失访。年龄和艾滋病毒感染状况与诊断前失访显著相关,而性别和与健康中心的距离则无关。
相当比例的疑似结核病患者在最终诊断前失访,这对个人和社区构成了高风险。卫生系统管理人员需要考虑针对年轻人、男性患者、艾滋病毒阳性者的干预措施。