Open AccessBrief Report: Yield and Efficiency of Intensified Tuberculosis Case-Finding Algorithms in 2 High-Risk HIV Subgroups in Uganda
Author(s) -
Fred C. Semitala,
Adithya Cattamanchi,
Alfred Andama,
Elly Atuhumuza,
Jane Katende,
Sandra Mwebe,
Lucy Asege,
Martha Nakaye,
Moses R. Kamya,
Christina Yoon
Publication year - 2019
Publication title -
journal of acquired immune deficiency syndromes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.162
H-Index - 157
eISSN - 1944-7884
pISSN - 1525-4135
DOI - 10.1097/qai.0000000000002162
Subject(s) - medicine , confidence interval , tuberculosis , human immunodeficiency virus (hiv) , sputum , algorithm , physical therapy , immunology , pathology , computer science
Tuberculosis (TB) risk varies among different HIV subgroups, potentially impacting intensified case finding (ICF) performance. We evaluated the performance of the current ICF algorithm [symptom screening, followed by Xpert MTB/RIF (Xpert) testing] in 2 HIV subgroups and evaluated whether ICF performance could be improved if TB screening was based on C-reactive protein (CRP) concentrations.