The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled.
View Article and Find Full Text PDFBackground: Asymptomatic Cryptococcal Antigenemia (CrAg) patients develop meningitis within a month of testing positive. Pre-emptive antifungal therapy can prevent progression to Cryptococcal meningitis (CM). In April 2016, a national CrAg screening program was initiated in 206 high-volume health facilities that provide antiretroviral therapy in Uganda.
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