Back to Search
Start Over
A New Scoring System to Differentially Diagnose and Distinguish Tuberculous Meningitis and Bacterial Meningitis in South China.
- Source :
-
Frontiers in neurology [Front Neurol] 2022 Mar 30; Vol. 13, pp. 830969. Date of Electronic Publication: 2022 Mar 30 (Print Publication: 2022). - Publication Year :
- 2022
-
Abstract
- Background: Tuberculous meningitis (TBM) is the most serious form of extrapulmonary tuberculosis caused by Mycobacterium tuberculosis , and is characterized by high morbidity and mortality. Unfortunately, it is difficult to distinguish TBM from bacterial meningitis (BM) based on clinical features alone. The latest diagnostic tests and neuroimaging methods are still not available in many developing countries. This study aimed to develop a simple diagnostic algorithm based on clinical and laboratory test results as an early predictor of TBM in South China.<br />Methods: A retrospective study was conducted to compare the clinical and laboratory characteristics of 114 patients with TBM and 47 with BM. Multivariate logistic regression analysis was performed on the characteristics of independently predicted TBM to develop a new diagnostic rule.<br />Results: Five characteristics were predictive of a diagnosis of TBM: duration of symptoms before admission; tuberculous symptoms; white blood cell (WBC) count, total cerebrospinal fluid WBC count, and cerebrospinal fluid chloride concentration. The sensitivity and specificity of the new scoring system developed in this study were 81.6 and 93.6%, respectively.<br />Conclusion: The new scoring system proposed in this study can help physicians empirically diagnose TBM and can be used in countries and regions with limited microbial and radiological resources.<br />Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br /> (Copyright © 2022 Wen, Liu, Cao, Zhou, Luo, Xiang, Hu, Zhang and Leng.)
Details
- Language :
- English
- ISSN :
- 1664-2295
- Volume :
- 13
- Database :
- MEDLINE
- Journal :
- Frontiers in neurology
- Publication Type :
- Academic Journal
- Accession number :
- 35432172
- Full Text :
- https://doi.org/10.3389/fneur.2022.830969