After exposure to tuberculosis (TB) , children often progress to TB disease quicker than adults. However, many children with TB in low resource settings are not diagnosed and start on appropriate treatment. Treatment decision algorithms allow health workers at primary levels of care to take data obtained in the initial clinical consultation to decide on treatment initiation. Until recently, treatment decision algorithms were developed based on expert opinion but increasingly data collected from children being evaluated for TB has been used to develop novel algorithms. Diagnosis and treatment of tuberculosis in children is a necessary component in tackling TB worldwide.
The Imperial researcher working on this is Professor James Seddon.
Publications:
https://pubmed.ncbi.nlm.nih.gov/31221543/
https://www.thelancet.com/journals/lanchi/article/PIIS2352-4642(23)00004-4/fulltext
https://iris.who.int/bitstream/handle/10665/352522/9789240046764-eng.pdf?sequence=1
https://iris.who.int/bitstream/handle/10665/352523/9789240046832-eng.pdf
https://pubmed.ncbi.nlm.nih.gov/33449999/
https://www.medrxiv.org/content/10.1101/2024.11.08.24316648v1
