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World J Crit Care Med. Mar 9, 2026; 15(1): 110763
Published online Mar 9, 2026. doi: 10.5492/wjccm.v15.i1.110763
Clinical scoring systems for diagnosing tuberculous meningitis: A systematic review
Elizabeth Teo, Karon Kung, Sarah Chen, Kay C See
Elizabeth Teo, Karon Kung, Sarah Chen, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
Kay C See, Division of Respiratory and Critical Care Medicine, Department of Medicine, National University Hospital, Singapore 119074, Singapore
Author contributions: Teo E, Kung K, and Chen S contributed to the conceptualization, data collection, analysis and interpretation of results; See KC supervised the project; Teo E, Kung K, Chen S, and See KC contributed to the writing of this manuscript; and all authors read and approved the manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Corresponding author: Elizabeth Teo, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Dr, Singapore 117597, Singapore. elizabethteomin@gmail.com
Received: June 16, 2025
Revised: August 18, 2025
Accepted: November 25, 2025
Published online: March 9, 2026
Processing time: 258 Days and 15.3 Hours
Core Tip

Core Tip: Tuberculous meningitis (TBM) is a severe complication of tuberculosis. Early diagnosis is crucial in improving patient outcomes, albeit difficult given the non-specific signs and symptoms of early TBM. Numerical diagnostic scoring systems may be a useful early diagnostic tool for clinicians, particularly in resource-constrained settings. Of all the scores currently published, we suggest using Thwaites (2002) and Marais (2010) as first line TBM screening tests due to their high sensitivities and extensive external validation. Nevertheless, clinicians are encouraged to select scores in accordance with the patient characteristics of the population of interest.