Saturday, November 23, 2024
11/23/2024
PROJECT SUMMARY /ABSTRACT Prior infection with tuberculosis (TB) is increasingly recognized as an important risk factor for chronic respiratory disease and reduced quality of life. Patients with a history of TB have up to three times the risk of developing chronic lung disease at a younger age than their counterparts. However, TB programs are focused on screening and treatment of the acute infectious disease. Despite a good treatment success rate for drug- susceptible TB, many survivors do not return to full health. It is not known if health workers are aware of the post-TB morbidity since standard diagnostic criteria for post-TB lung disease applicable to low-income settings is currently under development. I hypothesize that health workers in our setting are unable to make a diagnosis of post-TB lung disease due to a non-existent diagnostic tool. The overarching goal for this K43 training grant is to develop and assess the feasibility of a post-TB lung disease diagnostic tool based on history and physical exam that can be easily deployed in a primary health care setting without access to specialized diagnostic procedures. The proposed studies and formal educational activities in this proposal will provide critical research training in three main areas; (a) risk modelling to create and validate a clinical diagnostic algorithm, (b) qualitative work to determine health workers’ knowledge and attitudes towards diagnosis of post- TB lung disease, (c) development and feasibility testing of an intervention for post-TB lung disease diagnosis in a setting with limited diagnostic resources. I will build on an existing cohort of adults who have been declared cured of TB at a tertiary hospital in Uganda to design and validate a diagnostic algorithm for post-TB lung disease (Aim 1). I will conduct a qualitative study to identify healthcare provider barriers and facilitators of diagnosing post-TB lung disease (Aim 2). I will subsequently determine the feasibility and acceptability of using the post-TB lung disease diagnostic algorithm at a primary health-care facilities in Uganda in a pilot intervention study (Aim 3). The findings of this proposal will have significant public health impact by improving the diagnosis of post-TB lung disease in a low-income TB endemic setting. Importantly, I will add to the growing body of post-TB lung disease literature, with potential generalization to other low-income settings. A collateral output of this training grant is that I will improve on post-TB lung disease knowledge among gatekeeper health facilities in our setting. The proposed mixed methods training will be the basis for my transition to an independent researcher and will provide important preliminary data for a competitive NIH-R01 grant proposal. In the fourth year of this award, I will develop an NIH-R01 protocol to conduct a larger effectiveness trial, or incorporation into trials of therapeutics for post-TB lung disease and ultimately improve person-centered post-TB lung disease care quality and outcomes in TB endemic areas.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
