Prediction of post-tuberculosis lung damage using CT lung imaging measures among adults in Malawi

The burden of tuberculosis (TB) is high globally and in sub-Saharan Africa (SSA). Although TB treatment regimens are now widely available, and with high success rates in most parts of the world, TB can lead to long-term health consequences. Evidence has shown that completion of TB treatment can mark the beginning of chronic lung damage and other sequelae. There is a need for early identification of individuals at risk of post-tuberculosis lung damage (PTLD) to necessitate its appropriate management. This study evaluated the significance of radiological features from computed tomography (CT) scan in describing PTLD patterns at treatment completion and predicting PTLD outcomes at 12 months post treatment, as a possible tool to detect risk of PTLD at an early stage. This thesis comprises three parts. Part A is the study protocol, which outlines the purpose, methods and ethical considerations of the proposed study. Part B is the literature review, which summarizes the existing literature on PTLD, the risk factors for PTLD, and the relationship between imaging data and PTLD. The objective of the literature review was to identify gaps in literature which would provide context for further research. Part C is the journal-ready manuscript, which provides the results of the conducted study and a discussion on the implication of these results. The results of the study showed that CT imaging features were important in determining concurrent abnormal spirometry at baseline in post-TB individuals. These features were not useful in predicting spirometry outcomes at 12 months after treatment completion. However, there is need for further validation of these results in other settings and the consideration of other lung damage outcomes.

Grantor

Department of Public Health and Family Medicine

Year dc:date.issued

2018

Author dc:creator

• Gunsaru, Vester Poyamba

Advisor dc:contributor.advisor

• Lesosky, Maia

• Epidemiology and Biostatistics

Handle dc:identifier.uri

http://hdl.handle.net/11427/36867

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/36867