A novel diagnostic model for tuberculous meningitis using Bayesian latent class analysis.

ABSTRACT:

Background

Diagnosis of tuberculous meningitis (TBM) is hampered by the lack of a gold standard. Current microbiological tests lack sensitivity and clinical diagnostic approaches are subjective. We therefore built a diagnostic model that can be used before microbiological test results are known.

Methods

We included 659 individuals aged [Formula: see text] years with suspected brain infections from a prospective observational study conducted in Vietnam. We fitted a logistic regression diagnostic model for TBM status, with unknown values estimated via a latent class model on three mycobacterial tests: Ziehl-Neelsen smear, Mycobacterial culture, and GeneXpert. We additionally re-evaluated mycobacterial test performance, estimated individual mycobacillary burden, and quantified

SUBMITTER: Dong THK 

PROVIDER: S-EPMC10845506 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature