Journal of Clinical and Diagnostic Research, ISSN - 0973 - 709X

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Original article / research
Table of Contents - Year : 2017 | Month : April | Volume : 11 | Issue : 4 | Page : OC22 - OC24

Determination and Validation of a Lower Cut Off Value of Cerebrospinal Fluid Adenosine Deaminase (CSF-ADA) Activity in Diagnosis of Tuberculous Meningitis OC22-OC24

Raviraj, Renoy A Henry, G. Ganapathi Rao

Correspondence
Dr. Renoy A Henry,
Anjiparambil, PC Road, Ponurunny, Kochi-682019, Kerala, India.
E-mail: drrenoy@gmail.com

Introduction: Tuberculous meningitis is an infection of the meninges caused by Mycobacterium tuberculosis. It is one of the most common infectious diseases of the Central Nervous System (CNS) and a major health problem in developing countries like India. If there is delay in diagnosis and initiation of specific treatment, it causes significant morbidity and mortality. CSF-ADA 10 U/l is the standard cut off value that is used for differentiation between Tuberculous (TBM) and Non-Tuberculous Meningitis (non-TBM).

Aim: To determine and validate a lower cut off value for CSF-ADA for diagnosing TBM in an Indian setting.

Materials and Methods: This was a prospective study involving 85 cases of meningitis whose CSF were analysed and ADA estimated using an enzymatic deamination assay kit. Diagnosis of various types of meningitis was made based on specified diagnostic criteria. The comparison of mean value of CSF- ADA activity of the two types of meningitis was done using two Sample t-test. A p-value of <0.05 was considered as significant. Cut off value to differentiate between TBM and non-TBM meningitis was determined using ROC curve analysis.

Results: The CSF-ADA activity of TBM and non-TBM cases was compared. The mean CSF-ADA activity was found to be significantly higher in TBM patients (10.97±4.43; Mean±SD) than in non-TBM patients (5.09±1.53) which was statistically significant with a p-value of <0.001. A cut off value of 6.65 was calculated using ROC curve for the diagnosis of TBM which gave a sensitivity of 85.3% and a specificity of 84.3% for differentiating TBM from non-TBM. The positive predictive value was 78.3% and negative predictive value of 89.5% using the above cut off. The positive likelihood ratio was 5.44 and negative likelihood ratio of 0.17 when this lower cut off value was applied.

Conclusion: This study has demonstrated that CSF-ADA can be used as an important diagnostic tool in early diagnosis of TBM using a cut off value of 6.65. This cut off value gave a good sensitivity and specificity in differentiating it from non-TBM.