The accuracy of tuberculous meningitis diagnostic tests using Bayesian latent class analysis

  • Huy Ngoc Le Vietnam National Lung Hospital, Hanoi, Vietnam
  • Hutcha Sriplung Epidemiology Unit, Prince of Songkla University, Hat Yai, Songkhla, Thailand
  • Virasakdi Chongsuvivatwong Epidemiology Unit, Prince of Songkla University, Hat Yai, Songkhla, Thailand
  • Nhung Viet Nguyen Vietnam National Lung Hospital, Hanoi, Vietnam
  • Tri Huu Nguyen Vietnam National Lung Hospital, Hanoi, Vietnam
Keywords: Tuberculous meningitis, Gene Xpert assay, Bayesian latent class analysis

Abstract

Introduction: Tuberculous meningitis (TBM) is the most dangerous form of tuberculosis with high mortality and disability rates. However, the delayed diagnostic process is often due to the absence of the gold standard tests leading to a lack of information about the sensitivity and specificity of diagnostic tests. This study aims to estimate the prevalence of TBM and determine the performance of four diagnostic procedures: the mycobacteria growth culture test, Gene Xpert assay, and analysis of protein levels and leukocyte count taken from cerebrospinal fluid.

Methodology: We used a Bayesian latent class analysis to estimate the prevalence of TBM with 95% credible interval (CI), and the specificity and sensitivity of the four diagnostic procedures. The area under the receiver operating characteristic curve (AUC) of the cerebrospinal protein levels and leukocyte count were also compared and estimated using different thresholds.

Results: A total of 1,213 patients suspected of having TBM were included. The estimated TBM prevalence was 34.8 % (95% CI: 28.8 – 41.3). The sensitivity of culture test and Gene Xpert assay was 62.7% (95% CI: 52.5 – 74.0), and 57.5% (95% CI: 51.0 – 64.0), and the specificity of Gene-Xpert was 95. 9% (95% CI: 92.0 – 99.8). The AUC for leukocyte count was 76.0%, and for protein level was 73.4%.

Conclusions: This study provided better information about the performance of four routine diagnostic tests and the prevalence of TBM which can enhance disease control and improve treatment outcomes.

Published
2020-05-31
How to Cite
1.
Le HN, Sriplung H, Chongsuvivatwong V, Nguyen NV, Nguyen TH (2020) The accuracy of tuberculous meningitis diagnostic tests using Bayesian latent class analysis. J Infect Dev Ctries 14:479-487. doi: 10.3855/jidc.11862
Section
Original Articles