학술논문
Development of treatment-decision algorithms for children evaluated for pulmonary tuberculosis: an individual participant data meta-analysis
Document Type
Article
Author
Gunasekera, Kenneth S; Marcy, Olivier; Muñoz, Johanna; Lopez-Varela, Elisa; Sekadde, Moorine P; Franke, Molly F; Bonnet, Maryline; Ahmed, Shakil; Amanullah, Farhana; Anwar, Aliya; Augusto, Orvalho; Aurilio, Rafaela Baroni; Banu, Sayera; Batool, Iraj; Brands, Annemieke; Cain, Kevin P; Carratalá-Castro, Lucía; Caws, Maxine; Click, Eleanor S; Cranmer, Lisa M; García-Basteiro, Alberto L; Hesseling, Anneke C; Huynh, Julie; Kabir, Senjuti; Lecca, Leonid; Mandalakas, Anna; Mavhunga, Farai; Myint, Aye Aye; Myo, Kyaw; Nampijja, Dorah; Nicol, Mark P; Orikiriza, Patrick; Palmer, Megan; Sant'Anna, Clemax Couto; Siddiqui, Sara Ahmed; Smith, Jonathan P; Song, Rinn; Thuong Thuong, Nguyen Thuy; Ung, Vibol; van der Zalm, Marieke M; Verkuijl, Sabine; Viney, Kerri; Walters, Elisabetta G; Warren, Joshua L; Zar, Heather J; Marais, Ben J; Graham, Stephen M; Debray, Thomas P A; Cohen, Ted; Seddon, James A
Source
The Lancet Child & Adolescent Health; 20230101, Issue: Preprints
Subject
Language
ISSN
23524642; 23524650
Abstract
Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres.