A novel diagnostic strategy of differential diagnosis of tuberculous meningitis and non-tuberculous meningitis: a retrospective observational cohort study

Sep 29, 2026

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Tuberculous meningitis (TBM) causes high disability and mortality, but early diagnosis is hindered by difficulty distinguishing it from non-TBM causes such as bacterial, cryptococcal, and viral meningitis. This study developed a differential diagnostic model for TBM versus non-TBM using basic data, laboratory results, and imaging findings, built and validated with R4.1.0 on 405 patients. An independent cohort of 30 patients and prospective follow-up of 10 suspected TBM cases further assessed performance. The model combined systemic tuberculosis symptoms, neurologic and meningeal signs, CSF protein, positive T-cell spot testing, and C-reactive protein, achieving AUCs of 0.872 and 0.844 and sensitivity/specificity of 88.9% and 85.7% in validation.

LanguageEnglish

CategoryHealthcare

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Pages15

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| Clinical Microbiology | Research Article A novel diagnostic strategy of differential diagnosis of tuberculous meningitis and non-tuberculous meningitis: a retrospective observational cohort study Qingwen Lin,1,2,3,4 Wenhua Fang,5,6 Kengna Fan,1,2 Weiqing Zhang,1,2 Xiaxia Qiu,1 Minjie Tang,1,2 Qi Wang,1,2 Huangcheng Shangguan,5,6 Qishui Ou,1,2,3,4 Xiaofeng Liu7,8 AUTHOR AFFILIATIONS See affiliation list on p. 13. ABSTRACT Tuberculous meningitis (TBM) leads to severe disability and mortality rates, making early diagnosis critical. However, it is challenging to distinguish it from other common forms of non-tuberculous meningitis (non-TBM), including bacterial meningitis, cryptococcal meningitis, and viral meningitis. This study aims to construct a diagnostic model between TBM and non-TBM. A total of 543 patients were enrolled, and 405 subjects remained and were subsequently divided into a training set and a validation set. Basic information, laboratory results, and imaging results of patients were collected, and R4.1.0 was used to construct and validate the diagnostic model. Subsequently, 30 patients were recruited as an independent validation cohort to verify the diagnostic efficacy of the model further. Finally, 10 patients with suspected TBM were prospectively observed, and the model was applied for diagnosis, with results compared to the final clinical diagnosis. The differential model of TBM and non-TBM was composed of the systemic symptoms of tuberculosis, altered consciousness, neurological deficits, meningeal irritation, cerebrospinal fluid protein, positive T-cell spot test for tuberculosis infection, and C-reactive protein. The areas under the receiver operating characteristic curve for the model in the training and validation sets were 0.872 (95% confidence interval [CI] = 0.833–0.913) and 0.844 (95% CI = 0.751–0.937), respectively. Furthermore, the validation cohort also shows good diagnostic performance with a sensitivity and specificity of 88.9% and 85.7%, respectively. Notably, 9 out of 10 patients had diagnoses consistent with model predictions. A novel diagnostic model was developed and validated using common clinical indicators and laboratory results to distinguish between TBM and non-TBM effectively. IMPORTANCE Tuberculous meningitis is a serious disease. Currently, there is no effective way to perform early differential diagnosis, particularly in resource-limited settings. This article presents a new, simple method. KEYWORDS tuberculous meningitis, non-tuberculous meningitis, diagnosis, model T uberculous meningitis (TBM), a severe form of extrapulmonary tuberculosis, accounts for 5%–10% of all extrapulmonary cases. The combined mortality and disability rate can reach 50%(1) . During the advanced stage of TBM, there may bea manifestation of altered mental status and focal neurological deficits. Complications such as cerebral ischemia, hydrocephalus, and cerebral infarction can lead to significant brain injury and neurological dysfunction (2, 3) . These complications are primarily due to the difficulties in achieving early diagnosis and initiating appropriate treatment. Differentiating TBM from bacterial meningitis (BM), viral meningitis (VM), and cryptococcal meningitis (CM) is particularly challenging in early stages due to Editor Florence Claude Doucet-Populaire, Assistance Publique-Hopitaux de Paris Universite Paris Saclay, Clamart, France Address correspondence to Qishui Ou, [ouqishui@fjmu.edu.cn](ouqishui@fjmu.edu.cn), or Xiaofeng Liu, [xfengliu05@126.com](xfengliu05@126.com). Qingwen Lin, Wenhua Fang, and Kengna Fan contributed equally to this article. The order of authors is determined in alphabetical order non-specific clinical, imaging, and cerebrospinal fluid (CSF) findings. Although the pathogenic microorganisms remain the gold standard for diagnosing TBM, its sensitivity is notably inadequate and the process is often time-consuming, typically requiring 2–6 weeks for resu

FAQs

Why is early differential diagnosis of tuberculous meningitis difficult?

TBM is hard to distinguish from other non-TBM meningitis forms because early clinical, imaging, and cerebrospinal fluid findings can be non-specific.

What data types were used to build the TBM vs non-TBM diagnostic model?

The model used patients’ basic information, laboratory results, and imaging results collected from meningitis cases.

Which clinical indicators and tests formed the differential model?

The model included systemic tuberculosis symptoms, altered consciousness, neurological deficits, meningeal irritation, cerebrospinal fluid protein, positive T-cell spot test for tuberculosis infection, and C-reactive protein.

Sep 29, 2026

Uploaded by Aran