This project is based at LHC and UM in Malaysia. Overview Project title: Algorithm modelled & applied in Sabah for Smear Negative Pulmonary Tuberculosis - AMASSMENT Programme: Infectious Diseases Based at: Luyang Health Clinic and Universiti Malaya in Malaysia Start date: End date: Principal investigator: Wai Khew Lee Project team: Yao Long Lew, Wai Khew Lee, Chee Kuan Wong, Helen Stagg Background Every year, three of the 10 million people with tuberculosis (TB) are not diagnosed or notified into a national surveillance system. Finding the ‘Missing Millions’ is essential if we are to meet the World Health Organization’s End TB Strategy. The primary approach for diagnosing pulmonary TB in most low-and middle-income countries (LMICs) is direct microscopy, which detects acid-fast bacilli from sputum smears. In LMICs with a low prevalence of HIV, initiating treatment for pulmonary TB is heavily reliant on sputum smears being positive. It is recognised that smear microscopy has low sensitivity, as it requires a high load of bacteria to be detected. Negative sputum smears often lead to missed and/or late diagnosis of smear negative pulmonary TB, resulting treatment delays. Other forms of testing- such as Xpert® MTB/RIF Ultra and culture- are very expensive to implement or slow, respectively. Aim and Impact Develop an algorithm (using clinical features including basic investigations and demographic information adapted from current evidence and consensus from experts) that is as sensitive and specific as Xpert® MTB/RIF Ultra and culture for diagnosing smear negative pulmonary TB in a resource-limited primary care setting. Related Links Learn about the complementary study, MTBHT based in India. This article was published on 2024-09-24
