Decision-making in the diagnosis of tuberculous meningitis

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dc.contributor.authorBoyles, Tom H.en_ZA
dc.contributor.authorLynen, Lutgardeen_ZA
dc.contributor.authorSeddon, James A.en_ZA
dc.contributor.authorTuberculous Meningitis International Research Consortiumen_ZA
dc.date.accessioned2022-04-13T07:25:26Z
dc.date.available2022-04-13T07:25:26Z
dc.date.issued2020-01-23
dc.descriptionCITATION: Boyles, Tom H. et al. 2020. Decision-making in the diagnosis of tuberculous meningitis. Wellcome Open Research, 5:11, doi:10.12688/wellcomeopenres.15611.1.en_ZA
dc.descriptionThe original publication is available at: https://pubmed.ncbi.nlm.nih.gov
dc.description.abstractENGLISH ABSTRACT: Tuberculous meningitis (TBM) is the most devastating form of tuberculosis (TB) but diagnosis is difficult and delays in initiating therapy increase mortality. All currently available tests are imperfect; culture of Mycobacterium tuberculosis from the cerebrospinal fluid (CSF) is considered the most accurate test but is often negative, even when disease is present, and takes too long to be useful for immediate decision making. Rapid tests that are frequently used are conventional Ziehl-Neelsen staining and nucleic acid amplification tests such as Xpert MTB/RIF and Xpert MTB/RIF Ultra. While positive results will often confirm the diagnosis, negative tests frequently provide insufficient evidence to withhold therapy. The conventional diagnostic approach is to determine the probability of TBM using experience and intuition, based on prevalence of TB, history, examination, analysis of basic blood and CSF parameters, imaging, and rapid test results. Treatment decisions may therefore be both variable and inaccurate, depend on the experience of the clinician, and requests for tests may be inappropriate. In this article we discuss the use of Bayes' theorem and the threshold model of decision making as ways to improve testing and treatment decisions in TBM. Bayes' theorem describes the process of converting the pre-test probability of disease to the post-test probability based on test results and the threshold model guides clinicians to make rational test and treatment decisions. We discuss the advantages and limitations of using these methods and suggest that new diagnostic strategies should ultimately be tested in randomised trials.en_ZA
dc.description.versionPublisher's version
dc.format.extent14 pagesen_ZA
dc.identifier.citationBoyles, Tom H. et al. 2020. Decision-making in the diagnosis of tuberculous meningitis. Wellcome Open Research, 5:11, doi:10.12688/wellcomeopenres.15611.1
dc.identifier.otherdoi:10.12688/wellcomeopenres.15611.1
dc.identifier.urihttp://hdl.handle.net/10019.1/124454
dc.language.isoen_ZAen_ZA
dc.publisherWellcome Open Researchen_ZA
dc.rights.holderAuthors retain copyrighten_ZA
dc.subjectThreshold Decisionen_ZA
dc.subjectMeningitis, Tuberculous -- Diagnosisen_ZA
dc.subjectMycobacterium tuberculosis -- Researchen_ZA
dc.titleDecision-making in the diagnosis of tuberculous meningitisen_ZA
dc.typeArticleen_ZA
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