Diagnosis Of Tuberculous Meningitis Research Articles

Evaluation of Loop-Mediated Isothermal Amplification Assay in Diagnosing Tuberculous Meningitis.

Resource-limited settings like India need a simple, quick, and temperature-independent point-of-care diagnostic test that can diagnose tuberculous meningitis (TBM) at the earliest. A prospective study was carried out at a tertiary care center in North India wherein 50 subjects suspected of TBM were recruited and followed up for six months between January 2019 and December 2020. The aim was to evaluate the performance of loop-mediated isothermal amplification (TB-LAMP) in diagnosing TBM as compared to a composite reference standard (CRS), mycobacteria growth indicator tube 960 (MGIT 960) culture, and GeneXpert®. Out of 50 patients, 32 were TBM cases (64%), and 18 were non-TBM cases (36%). The sensitivity of TB-LAMP and GeneXpert® for TBM diagnosis against CRS was 53% (17/32) for both, and the specificity was 78% (14/18) and 89% (16/18), respectively. On comparing TB-LAMP against GeneXpert® for TBM diagnosis, the two methods had almost perfect agreement (Cohen's kappa=0.83) with statistical significance (p<0.001). The performance of TB-LAMP assay is comparable to GeneXpert® in diagnosing TBM, and it may be used as a substitute for CSF GeneXpert® in resource-limited settings.

Performance of metagenomic next-generation sequencing in cerebrospinal fluid for diagnosis of tuberculous meningitis.

Purpose. Metagenomic next-generation sequencing (mNGS) has been widely used in the diagnosis of infectious diseases, while its performance in diagnosis of tuberculous meningitis (TBM) is incompletely characterized. The aim of this study was to assess the performance of mNGS in the diagnosis of TBM, and illustrate the sensitivity and specificity of different methods.Methods. We retrospectively recruited TBM patients between January 2021 and March 2023 to evaluate the performance of mNGS on cerebrospinal fluid (CSF) samples, in comparison with conventional microbiological testing, including culturing of Mycobacterium tuberculosis (MTB), acid-fast bacillus (AFB) stain, reverse transcription PCR and Xpert MTB/RIF.Results. Of the 40 enrolled, 34 participants were diagnosed with TBM, including 15(44.12 %) definite and 19(55.88 %) clinical diagnosis based upon clinical manifestations, CSF parameters, brain imaging, pathogen evidence and treatment response. The mNGS method identified sequences of Mycobacterium tuberculosis complex (MTBC) in 11 CSF samples. In patients with definite TBM, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of mNGS were 78.57, 100, 100, 66.67 and 85 %, respectively. Compared to conventional diagnostic methods, the sensitivity of mNGS (78.57 %) was higher than AFB (0 %), culturing (0 %), RT-PCR (60 %) and Xpert MTB/RIF (14.29 %).Conclusions. Our study indicates that mNGS of CSF exhibited an overall improved sensitivity over conventional diagnostic methods for TBM and can be considered a front-line CSF test.

Evaluation of seegene anyplex MTB/NTM real-time detection assay for diagnosis of tuberculous meningitis

BackgroundTuberculous meningitis (TBM) is a common central nervous system infectious disease. Polymerase chain reaction (PCR) assay is a useful method for the rapid diagnosis of TBM. The Seegene Anyplex MTB/NTM real-time detection assay has good sensitivity and specificity for detection of tuberculosis in respiratory specimens, though, data regarding other specimens are lacking. This study aims to define the diagnostic role of Seegene Anyplex MTB/NTM real-time detection assay in TBM in adults.MethodsThis was a retrospective study of 367 adults with symptomatic community acquired meningitis between December 2013 and December 2019. Cerebrospinal fluid (CSF) had been sent for conventional diagnosis, including culture to identify Mycobacterium tuberculosis, and Seegene Anyplex MTB/NTM real-time detection assay. Other diagnostic examinations were performed as necessary.ResultsOf the 367 patients in the study, 37 were diagnosed with TBM (14 with definite TBM and 23 with probable TBM). Between the total TBM cases (n = 37) and non-TBM cases (n = 330), clinical sensitivity was 32.4% and specificity was 100%, the positive predictive value was 100%, and the negative predictive value was 93.0%. Between the definite TBM cases (n = 14) and non-TBM cases (n = 330), clinical sensitivity was 50.0% and specificity was 100%, the positive predictive value was 100%, and the negative predictive value was 97.9%.ConclusionDue to lack of sensitivity, we suggest Seegeen Anyplex MTB/NTM real-time detection assay should not be used to rule out TBM but is useful for definite diagnosis.

Tuberculosis-targeted next-generation sequencing and machine learning: An ultrasensitive diagnostic strategy for paucibacillary pulmonary tuberculosis and tuberculous meningitis

BackgroundExisting diagnostic approaches for paucibacillary tuberculosis (TB) are limited by the low sensitivity of testing methods and difficulty in obtaining suitable samples. MethodsAn ultrasensitive TB diagnostic strategy was established, integrating efficient and specific TB targeted next-generation sequencing and machine learning models, and validated in clinical cohorts to test plasma cfDNA, cerebrospinal fluid (CSF) DNA collected from tuberculous meningitis (TBM) and pediatric pulmonary TB (PPTB) patients. ResultsIn the detection of 227 samples, application of the specific thresholds of CSF DNA (AUC = 0.974) and plasma cfDNA (AUC = 0.908) yielded sensitivity of 97.01 % and the specificity of 95.65 % in CSF samples and sensitivity of 82.61 % and specificity of 86.36 % in plasma samples, respectively. In the analysis of 44 paired samples from TBM patients, our strategy had a high concordance of 90.91 % (40/44) in plasma cfDNA and CSF DNA with both sensitivity of 95.45 % (42/44). In the PPTB patient, the sensitivity of the TB diagnostic strategy yielded higher sensitivity on plasma specimen than Xpert assay on gastric lavage (28.57 % VS. 15.38 %). ConclusionsOur TB diagnostic strategy provides greater detection sensitivity for paucibacillary TB, while plasma cfDNA as an easily collected specimen, could be an appropriate sample type for PTB and TBM diagnosis.

Development and validation of a new model for the early diagnosis of tuberculous meningitis in adults based on simple clinical and laboratory parameters

BackgroundThe differential diagnosis between tuberculous meningitis (TBM) and viral meningitis (VM) or bacterial meningitis (BM) remains challenging in clinical practice, particularly in resource-limited settings. This study aimed to establish a diagnostic model that can accurately and early distinguish TBM from both VM and BM in adults based on simple clinical and laboratory parameters.MethodsPatients diagnosed with TBM or non-TBM (VM or BM) between January 2012 and October 2021 were retrospectively enrolled from the General Hospital (derivation cohort) and Branch Hospital (validation cohort) of Ningxia Medical University. Demographic characteristics, clinical symptoms, concomitant diseases, and cerebrospinal fluid (CSF) parameters were collated. Univariable logistic analysis was performed in the derivation cohort to identify significant variables (P < 0.05). A multivariable logistic regression model was constructed using these variables. We verified the performance including discrimination, calibration, and applicability of the model in both derivation and validation cohorts.ResultsA total of 222 patients (70 TBM and 152 non-TBM [75 BM and 77 VM]) and 100 patients (32 TBM and 68 non-TBM [31 BM and 37 VM]) were enrolled as derivation and validation cohorts, respectively. The multivariable logistic regression model showed that disturbance of consciousness for > 5 days, weight loss > 5% of the original weight within 6 months, CSF lymphocyte ratio > 50%, CSF glucose concentration < 2.2 mmol/L, and secondary cerebral infarction were independently correlated with the diagnosis of TBM (P < 0.05). The nomogram model showed excellent discrimination (area under the curve 0.959 vs. 0.962) and great calibration (P-value in the Hosmer–Lemeshow test 0.128 vs. 0.863) in both derivation and validation cohorts. Clinical decision curve analysis showed that the model had good applicability in clinical practice and may benefit the entire population.ConclusionsThis multivariable diagnostic model may help clinicians in the early discrimination of TBM from VM and BM in adults based on simple clinical and laboratory parameters.

MRI advances in the imaging diagnosis of tuberculous meningitis: opportunities and innovations.

Tuberculous meningitis (TBM) is not only one of the most fatal forms of tuberculosis, but also a major public health concern worldwide, presenting grave clinical challenges due to its nonspecific symptoms and the urgent need for timely intervention. The severity and the rapid progression of TBM underscore the necessity of early and accurate diagnosis to prevent irreversible neurological deficits and reduce mortality rates. Traditional diagnostic methods, reliant primarily on clinical findings and cerebrospinal fluid analysis, often falter in delivering timely and conclusive results. Moreover, such methods struggle to distinguish TBM from other forms of neuroinfections, making it critical to seek advanced diagnostic solutions. Against this backdrop, magnetic resonance imaging (MRI) has emerged as an indispensable modality in diagnostics, owing to its unique advantages. This review provides an overview of the advancements in MRI technology, specifically emphasizing its crucial applications in the early detection and identification of complex pathological changes in TBM. The integration of artificial intelligence (AI) has further enhanced the transformative impact of MRI on TBM diagnostic imaging. When these cutting-edge technologies synergize with deep learning algorithms, they substantially improve diagnostic precision and efficiency. Currently, the field of TBM imaging diagnosis is undergoing a phase of technological amalgamation. The melding of MRI and AI technologies unquestionably signals new opportunities in this specialized area.

Incidence, risk factors and treatment of central nervous system immune reconstitution inflammatory syndrome in non‐HIV patients with tuberculous meningitis: a multicentre observational study

AbstractBackgroundImmune reconstitution inflammatory syndrome (IRIS) affecting the central nervous system (CNS) is associated with poor outcomes.AimsTo report on risk factors for CNS‐IRIS following tuberculous meningitis (TBM) in HIV‐negative patients.MethodsIn this retrospective multicentre study, all HIV‐negative adult patients admitted between 2003 and 2021 with microbiologically proven TBM were included. The primary outcome measure was IRIS onset over follow‐up. Characteristics of patients who developed IRIS were described. Factors associated with IRIS were identified using a multivariable logistic regression procedure.ResultsFifty‐six patients (33.0 (27.0–44.3) years, 39 (69.6%) men) with microbiologically proven TBM were studied. All patients received antituberculosis treatment and 48 (n = 48/56; 85.7%) steroids at TBM diagnosis. During a median follow‐up of 18.0 (12.0–27.3) months, IRIS occurred in 28 (n = 28/56, 50.0%) patients, at a median time of 2.0 (1.0–3.0) months after antituberculosis treatment was started. IRIS involved the CNS in all but one case. Imaging revealed new (n = 23/28, 82.1%) and/or worsening (n = 21/28; 75.0%) of previously recognised lesions. Multivariable analysis showed that meningeal enhancement on brain magnetic resonance imaging (MRI) (odds ratio (OR): 15.3; 95% confidence interval (CI): (1.19–1193.5)) at TBM diagnosis and high blood albumin level (OR: 1.21; 95% CI: (1.02–1.60)) were associated with the occurrence of CNS‐IRIS during follow‐up.ConclusionCNS‐IRIS following TBM in non‐HIV patients appears frequent and severe. Meningeal enhancement on brain MRI at tuberculosis diagnosis is a risk factor for CNS‐IRIS.

Study of cerebrospinal fluid adenosine deaminase activity for differential diagnosis of tuberculous and non-tuberculous meningitis

Background: Diagnosing a case of tuberculous meningitis (TBM) has always been challenging. Numerous previous studies have demonstrated that cerebrospinal fluid-Adenosine deaminase (CSF-ADA) estimation is useful in the diagnosis of TBM and can differentiate TBM from other types of meningitis. Aims and Objectives: The current study aims to look for a simple, rapid, cost-effective, and specific test to differentiate tubercular etiology from other causes of meningitis. Materials and Methods: A total of 80 patients admitted to the hospital with signs and symptoms of meningitis were selected and divided into two groups: Group 1 (Cases): 40 patients of TBM, Group 2 (Control): 40 patients of pyogenic and viral meningitis. The CSF ADA was estimated by enzymatic method, CSF Protein by turbidimetric method, and CSF Glucose by Glucose oxidase (GOD) and Peroxidase (POD) method. Results: CSF ADA levels (mean ± SD) in the TBM and non-TBM groups were 10.874+7.72 IU/L and 2.44+1.757 IU/L, respectively (highly significant, P&lt;0.001). With the CSF ADA cut off as &gt;6 IU/L, the sensitivity of the test was 95%, and the specificity of 92.5%. On comparison of the values of CSF ADA in the two groups, the t value is −6.75, and the difference in these two values was found to be highly significant (P&lt;0.01). Conclusion: ADA estimation in CSF is a simple, inexpensive, rapid, and specific method for making a diagnosis of tuberculous etiology in TBM. As a screening test, the determination of ADA activity in CSF can help the physician diagnose TBM early and reduce irreversible brain damage and neurologic sequelae by early administration of anti-tuberculous medications.

Tuberculous meningitis patient pathways and delays to diagnosis in Indonesia: a retrospective cohort study

IntroductionDelays in diagnosis and treatment contribute to high mortality of tuberculous meningitis (TBM). We studied TBM patient pathways including delays to diagnosis, and their alignment with available diagnostic services in...

Diagnostic challenges in tuberculous meningitis: a case report with negative genexpert result.

Tuberculous meningitis (TBM) is a severe form of tuberculosis affecting the meninges, primarily caused by Mycobacterium tuberculosis. Diagnosis of TBM poses numerous challenges due to its nonspecific clinical presentation and the limitations of diagnostic tests like GeneXpert. The authors report a case of a 22-year-old female from Eastern Nepal presenting with acute-onset fever, headache, vomiting, and neck pain. Cerebrospinal fluid (CSF) analysis showed lymphocytic pleocytosis, elevated protein, low glucose levels, and cobweb coagulum indicative of TBM. However, the GeneXpert test revealed negative results. In resource-limited settings like Nepal, where access to GeneXpert MTB/Rif is limited, CSF analysis and clinical algorithms play a crucial role in diagnosing TBM. Relying solely on GeneXpert results may lead to false negatives, so a high level of suspicion based on patient risk factors is essential. Prompt initiation of empirical antitubercular therapy is vital for a favorable outcome in TBM cases. Negative MTB PCR results from CSF can be misleading in diagnosis of tubercular meningitis. Therefore, comprehensive evaluations, including detailed patient history, physical examination, and CSF fluid analysis, are crucial in high tuberculous prevalence countries to ensure accurate and timely diagnosis.

The diagnosis of tuberculous meningitis: advancements in new technologies and machine learning algorithms.

Tuberculous meningitis (TBM) poses a diagnostic challenge, particularly impacting vulnerable populations such as infants and those with untreated HIV. Given the diagnostic intricacies of TBM, there's a pressing need for rapid and reliable diagnostic tools. This review scrutinizes the efficacy of up-and-coming technologies like machine learning in transforming TBM diagnostics and management. Advanced diagnostic technologies like targeted gene sequencing, real-time polymerase chain reaction (RT-PCR), miRNA assays, and metagenomic next-generation sequencing (mNGS) offer promising avenues for early TBM detection. The capabilities of these technologies are further augmented when paired with mass spectrometry, metabolomics, and proteomics, enriching the pool of disease-specific biomarkers. Machine learning algorithms, adept at sifting through voluminous datasets like medical imaging, genomic profiles, and patient histories, are increasingly revealing nuanced disease pathways, thereby elevating diagnostic accuracy and guiding treatment strategies. While these burgeoning technologies offer hope for more precise TBM diagnosis, hurdles remain in terms of their clinical implementation. Future endeavors should zero in on the validation of these tools through prospective studies, critically evaluating their limitations, and outlining protocols for seamless incorporation into established healthcare frameworks. Through this review, we aim to present an exhaustive snapshot of emerging diagnostic modalities in TBM, the current standing of machine learning in meningitis diagnostics, and the challenges and future prospects of converging these domains.

Clinical features of the course of tuberculous meningitis in HIV-infected patients

Background. Central nervous system tuberculosis is one of the most severe forms of extrapulmonary tuberculosis, which is due to an unfavorable clinical course, a high incidence of neurological complications and deaths. Despite this, the problem of early diagnosis is still not solved.&#x0D; Aim. To study the clinical and laboratory-instrumental features of the early diagnosis of tuberculous meningitis in HIV-infected patients.&#x0D; Materials and methods. A retrospective analysis of 31 case histories of patients with tuberculous lesions of the meninges and central nervous system in the late stages of HIV infection who were treated at the Clinical Tuberculosis Dispensary of Krasnodar Territory in 20202022 was carried out. The data of clinical manifestations of the disease, the results of laboratory and instrumental methods of examination were analyzed. Statistical data processing was performed by Microsoft Office Excel 2021 with the calculation of averages, standard deviation.&#x0D; Results. Tuberculous lesions of the meninges and the central nervous system among HIV-infected people were more common in men of working age who were not previously registered in a tuberculosis dispensary. All HIV-infected patients had late stages of HIV infection with severe immunodeficiency: the content of CD4+ lymphocytes less than 100 cells was detected in 45.46%; from 100 to 200 cells/l of CD4+ lymphocytes were recorded in 36.36%, more than 200 cells/l in 18.18%. Also, in all the studied patients, the primary focus was established in the form of tuberculosis of the respiratory organs, represented in 56.52% of cases by disseminated pulmonary tuberculosis. More than 70% had generalized tuberculosis with damage to the kidneys, spleen, and peripheral lymph nodes. A feature of the manifestation of tuberculous meningitis in HIV-infected people can be considered a high frequency of acute increase in neurological symptoms. Of the cerebral manifestations, the most common were: headache, dizziness, photophobia. 13.04% of HIV-infected patients complained of nausea and vomiting. 91.30% showed signs of damage to the substance of the brain, represented by mono-, hemiparesis and damage to the cranial nerves, mainly IIIIV, VI, VII pairs. The composition of CSF in HIV-positive patients revealed the presence of mild pleocytosis (up to 100 cells/l) in 56.52% of cases. The nature of the change in the concentration of proteins, chlorides and glucose is nonspecific.&#x0D; Conclusions. The study revealed the features of medical and social characteristics, clinical and laboratory and instrumental picture of tuberculous meningitis in HIV-infected patients and without HIV infection.

Relevance and challenges of neuroimaging for childhood tuberculous meningitis diagnosis in a resource-constraint country: A case report and literature review

Objective: Tuberculous meningitis (TBM) may be an undiagnosed cause of childhood mortality or neurologic sequelae. Cranial computed tomography (CT) scan remains a relevant diagnostic and prognostic tool amidst negative cerebrospinal fluid or sputum findings for tuberculous meningitis (TBM) diagnosis. Delays in diagnosis and treatment increase morbidity in resource-constraint countries.&#x0D; Case report: A seven-year-old boy was referred with three weeks history of fever, progressive body weakness, aphasia and unconsciousness (three days). He had right cranial nerve III palsy, generalized hypertonia, and hyperreflexia in right lower limbs. All tuberculosis tests were negative except the cranial CT findings of leptomeningeal enhancement with basilar involvement and evidence of obstructive hydrocephalus. He was managed with anti-tuberculous drugs, prednisolone, ventriculoperitoneal shunt, and physiotherapy, and made a significant recovery after a year of anti-tuberculosis  treatment.&#x0D; Conclusion: The cranial CT scan findings facilitate TBM diagnosis for which prompt treatment commencement is crucial for a good outcome.

A systematic review and meta-analysis of the diagnostic accuracy of metagenomic next-generation sequencing for diagnosing tuberculous meningitis.

The utility of metagenomic next-generation sequencing (mNGS) in the diagnosis of tuberculous meningitis (TBM) remains uncertain. We performed a meta-analysis to comprehensively evaluate its diagnostic accuracy for the early diagnosis of TBM. English (PubMed, Medline, Web of Science, Cochrane Library, and Embase) and Chinese (CNKI, Wanfang, and CBM) databases were searched for relevant studies assessing the diagnostic accuracy of mNGS for TBM. Review Manager was used to evaluate the quality of the included studies, and Stata was used to perform the statistical analysis. Of 495 relevant articles retrieved, eight studies involving 693 participants (348 with and 345 without TBM) met the inclusion criteria and were included in the meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the summary receiver-operating characteristic curve of mNGS for diagnosing TBM were 62% (95% confidence interval [CI]: 0.46-0.76), 99% (95% CI: 0.94-1.00), 139.08 (95% CI: 8.54-2266), 0.38 (95% CI: 0.25-0.58), 364.89 (95% CI: 18.39-7239), and 0.97 (95% CI: 0.95-0.98), respectively. mNGS showed good specificity but moderate sensitivity; therefore, a more sensitive test should be developed to assist in the diagnosis of TBM.

Diagnostic value of the cerebrospinal fluid lipoarabinomannan assay for tuberculous meningitis: a systematic review and meta-analysis.

This systematic review aims to evaluate the diagnostic accuracy of cerebrospinal fluid (CSF) lipoarabinomannan (LAM) assays in detecting tuberculous meningitis (TBM). A systematic review search was conducted in PubMed and five other databases up to April 2023. Studies that evaluated the diagnostic accuracy of CSF LAM assays were included with either definitive or composite reference standard used as the preferred reference standard. The quality of the included studies was assessed using the QUADAS-2 tool. We performed a bivariate random-effects meta-analysis and calculated the summary diagnostic statistics. A total of six studies, including a sample size of 999, were included in the final analysis. The pooled sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of CSF LAM for diagnosing TBM were determined to be 0.44 (95% CI: 0.31-0.58), 0.89 (95% CI: 0.81-0.93), and 0.76 (95% CI: 0.73-0.80), respectively. Significant heterogeneity was observed in both sensitivity (Q = 73.82, p < 0.01; I2 = 86.45, 95%CI: 79.64-93.27) and specificity (Q = 95.34, p < 0.01; I2 = 89.51, 95% CI: 84.61-94.42). Regression analysis indicated that the study design (retrospective vs. prospective) was associated with the heterogeneity of pooled sensitivity and specificity (all p < 0.05). Although more prospective studies are required to validate the role of the CSF LAM assay, current evidence supports that the performance of the CSF LAM assay is unsatisfactory for the TBM diagnosis. Additionally, the optimization of the CSF LAM assay (e.g., improvements in CSF collection and preparation methods) should be considered to improve its performance.

Tuberculostearic acid incorporated predictive model contributes to the clinical diagnosis of tuberculous meningitis

The conventional confirmation tests of tuberculous meningitis (TBM) are usually low in sensitivity, leading to high TBM mortality. Hence, sensitive methods for indicating the presence of bacilli are required. Tuberculostearic acid (TBSA), a constituent from Mycobacterium tuberculosis had been evaluated as a promising marker, but fails to demonstrate consistent results for definite TBM. This study retrospectively reviewed medical records of 113 TBM suspects, constructing a TBSA-combined scoring system based on multiple factors, which show sensitivity and specificity of 0.8148 and 0.8814, respectively, and the area under the receiver operating characteristic curve of 0.9010. Multivariate analyses revealed four co-predictive factors strongly associated with TBSA: extra-neural tuberculosis, basal meningeal enhancement, CSF glucose/Serum glucose <0.595, and coinfection in CNS (Total). The subsequent machine learning-based validation showed correspondent importance to factors in the TBSA model. This study demonstrates a simple scoring system to facilitate TBM prediction, yield reliable diagnoses and allow timely treatment initiation.

Tuberculous meningitis in Bhubaneswar, Odisha, during 2016 to 2022

BackgroundThe burden of tuberculous meningitis varies substantially by location, and is influenced by the overall burden of tuberculosis in that geographical area, and the age structure of the population. Conventional methods for diagnosis of tuberculous meningitis include acid fast bacilli (AFB) smear and culture. AFB smear has low sensitivity and culture techniques are time consuming. During the last few years, rapid and sensitive molecular methods such as cartridge based nucleic acid amplification technique (CBNAAT) is being used for the diagnosis of tuberculous meningitis. In this study, we evaluated the burden of tuberculosis and rifampicin resistance in suspected cases of tuberculous meningitis in Bhubaneswar, Odisha, during February 2016 to December 2022 using CBNAAT. MethodsUnder the National Strategic Plan 2012–2017, CBNAAT machines were rolled out in 2016, of which 1 was installed in the National Reference Laboratory (NRL) for Tuberculosis in Bhubaneswar. For this study, retrospective data on CBNAAT testing of cerebrospinal fluid (CSF) samples at the NRL was collected and analyzed from February 2016 to December 2022. All the demographic and laboratory data were entered in Excel 2010 (Microsoft office, USA) for data analysis. The age and sex distribution of the presumptive TB patients, proportion of samples referred from public and private health care facilities, proportion of M. tuberculosis positive CSF samples along with sensitivity to rifampicin was evaluated. The study was approved by the Institutional Human Ethics Committee. ResultsDuring February 2016 to December 2022, a total of 1627 CSF samples from presumptive TB meningitis patients were received in the NRL for CBNAAT testing. 60.7% (988/1627) of the presumptive TB patients were males. Of the 1627 patients, 3.1% (50/1627) were positive for M. Tuberculosis by CBNAAT. 56% (28/50) of the patients positive for tuberculous meningitis were males. The positivity for M. tuberculosis varied from 2.1% in 2017 to 5.1% in 2021. The CSF positivity for M. tuberculosis ranged from 0.7% in patients aged >60 years to 6.1% in 15–30 years age group. Of the 50 M. tuberculosis positive samples, 6% (3/50) were resistant for rifampicin. ConclusionOur study which included more than 1600 samples over a period of approximately 7 years found a 3.1% positivity for M. tuberculosis in CSF samples using CBNAAT. 6% of the M. tuberculosis positive samples were resistant to rifampicin. Future studies involving data from other districts of Odisha will help provide a more accurate information on the prevalence of tuberculous meningitis in Odisha state.

Recent advances in microbiological and molecular biological detection techniques of tuberculous meningitis.

Tuberculous meningitis (TBM) is the most common type of central nervous system tuberculosis (TB) and has the highest mortality and disability rate. Early diagnosis is key to improving the prognosis and survival rate of patients. However, laboratory diagnosis of TBM is often difficult due to its paucibacillary nature and sub optimal sensitivity of conventional microbiology and molecular tools which often fails to detect the pathogen. The gold standard for TBM diagnosis is the presence of MTB in the CSF. The recognised methods for the identification of MTB are acid-fast bacilli (AFB) detected under CSF smear microscopy, MTB cultured in CSF, and MTB detected by polymerase chain reaction (PCR). Currently, many studies consider that all diagnostic techniques for TBM are not perfect, and no single technique is considered simple, fast, cheap, and efficient. A definite diagnosis of TBM is still difficult in current clinical practice. In this review, we summarise the current state of microbiological and molecular biological diagnostics for TBM, the latest advances in research, and discuss the advantages of these techniques, as well as the issues and challenges faced in terms of diagnostic effectiveness, laboratory infrastructure, testing costs, and clinical expertise, for clinicians to select appropriate testing methods.

Development of clinical-based scoring system to diagnose tuberculous meningitis in children

ObjectiveDiagnosing tuberculous meningitis (TBM) in children is challenging due to the low sensitivity with time delay of bacterial culture techniques and the lack of brain imaging facilities in many low-...

Diagnosis and Management of Tuberculous Meningitis in Children- an Update

UPDATE ON THE DIAGNOSIS AND MANAGEMENT OF TUBERCULOUS MENINGITIS IN CHILDREN: Ronald van Toorn, Regan Solomons Seminars in Pediatric Neurology Volume 21, Issue 1, March 2014, Pages 12-18 Tuberculous meningitis (TBM), the most devastating manifestation of tuberculosis, is often missed or overlooked because of nonspecific symptoms and difficulties in diagnosis. It continues to be an important cause of neurologic handicap in resource-poor countries. Owing to the suboptimal performance of diagnostic tests of TBM, diagnosis relies on thorough history, clinical examination, and relevant investigations. The development of affordable, accurate diagnostic tests for TBM in resource-poor settings remains a priority. Short intensified treatment is safe and effective in both human immunodeficiency virus (HIV)-infected and HIV-uninfected children. Treatment of tuberculous hydrocephalus depends on the level of the cerebrospinal fluid obstruction. Corticosteroids reduce risk of neurodisability and death in HIV-uninfected children. Thalidomide should be considered in children compromised by tuberculosis abscesses and tuberculous-related optochiasmic arachnoiditis. In resource-poor countries, home-based TBM treatment after initial in-hospital stabilization is feasible in carefully selected patients. Early diagnosis and treatment of TBM is the single most important factor determining outcome.