A proposed algorithm for diagnosis of subacte and chronic meningoencephalitis cases in India: An evidence based work up

Background: In Indian subcontinent, the preoccupied state of mind only finds tuberculous meningitis as sole diagnosis of chronic meningo-encephalitis. In recent times there are increasingly reported cases of Cryptococcus, brucella, scrub, histoplasma, carcinomatous and autoimmune encephalitis. But still a standard algorithm is missing that can be applied uniformly across the country. We have tried to develop an algorithm that can be easily used in wards and emergency to diagnose cases of chronic meningo-encephalitis Methods & Materials: We searched for term “meningitis”, ‘meningoencephalitis’ and ‘encephalitis’ on pubmed, Medind and google scholar for Indian studies since last 20 years. All the studies obtained were then screened for causes, clinical features, treatment and outcome with factors affecting. Case reports were kept in another category. We used the features and investigations to create stepwise algorithm to identify the cause. Exceptional cases were excluded as it was not our goal. Results: The maximum literature available was for tuberculosis followed by neurocysticercosis, cryptococus, bacterial, neurobrucellosis, sarcoidosis and aseptic meningitis. The clubbed clinical features, elevated protein with adenosine deaminase (ADA), lymphocytic predominant pleocytosis, hyderocephalus with basal exudate and negative procalcitonin were promted for tuberculosis. In absence of such marker next step was to identify neurocysticercosis by IDSA criteria. The next was to do fungal culture and CSF cryptococal antigen (CRAG) for fingal meningitis cryptococal being most common. The next was neurobrucellosis and sarcoidosis. A miscellaneous group was to investigate for uncommon causes. Among HIV patients we had a larger baseline test including cultures for mycobacterium, fungus and bacterial along with serology testing for toxoplasma, CRAG and NCC. A ring enhancing lesion was scanned by MR spectroscopy and then labelled with final diagnosis. We have started using this methodology for last 8 months and found 6 cryptoccoal meningitis and 2 neurobrucellosis apart from TBM, maligancy and NCC. Conclusion: A step wise algorithm helps us to find the potential diagnostic clues for the diagnosis early as well as provide a pathway to target relevant test for specific diagnosis w.r.t Indian subcontinent. This algorithm also allows us to look for tests required at our laboratory as well as to look for novel diagnostic markers.

Abstract licence: CC BY-NC-ND

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