Tuberculous meningitis is a major cause of mortality and morbidity in adults with central nervous system infections in Kota Kinabalu, Sabah, Malaysia: an observational study

Think TB! A rare case of influenza and rapid progressive neurotuberculosis coinfection

An Indian migrant presented with increasing neurological symptoms after an acute influenza B infection. We diagnosed progressive neurotuberculosis—a rare and difficult case of tuberculosis and influenza co-infection. It highlights the importance of broad-based diagnostics in people from low- and middle-income countries, taking into account unusual manifestations of tuberculosis.

Epidemiological and clinical characteristics of central nervous system infections in a tertiary center: A retrospective study

Background and Aims

Central nervous system (CNS) infection is one of the most common causes of morbidity, mortality, and hospital admission worldwide. The natural history of CNS infection is quite fatal. Early diagnosis and treatment have been proven to have a crucial role in patients' survival. The aim of this study was to identify the epidemiological and clinical patterns of patients diagnosed with CNS infections.

Methods

This study is a retrospective study conducted in a tertiary level hospital in Nepal in which patient diagnosed with CNS infections (September 2019 to 2021) were included. Data were collected and analyzed in SPSS.

Results

The mean age of the 95 patients included in the study was 45.18 ± 19.56. Meningoencephalitis (n = 44, 46.30%) was the most common infection diagnosed. Patients belonging to the age group 30-60 years had a higher frequency of focal neurological deficit, and other classical clinical features. All the patients who died during the treatment had associated comorbidities but no concurrent infections. Altered sensorium, fever, and headache were the common presenting symptoms in all the recovered patients.

Conclusion

To ensure optimum disease outcome, early diagnosis and prompt management are crucial. For this, recognizing the local disease patterns in terms of disease distribution, commonly implicated aetiologies, presenting symptoms, and prognostic factors is of utmost importance.

Clinical analysis of 103 cases of tuberculous meningitis complicated with hyponatremia in adults

OBJECTIVE

Tuberculous meningitis (TBM) is a common infection of the central nervous system. TBM with hyponatremia is very common. If hyponatremia is not treated properly, it might affect the outcome of TBM patients.

METHODS

We included 226 patients diagnosed with TBM who were admitted from August 2010 to August 2015 and retrospectively analyzed the clinical data of patients with and without hyponatremia.

RESULTS

In total, 45.6% (103/226) patients had hyponatremia and 54.4% (123/226) patients did not have hyponatremia. Serum sodium and severity of TBM were independent prediction factors of poor outcomes in TBM. The prognosis of patients with hyponatremia was worse than that of patients without hyponatremia. The mortality was 3.9% (4/103) in the hyponatremia group, while 0% (0/123) in the non-hyponatremia group. The degree of hyponatremia was related to imaging, cerebrospinal fluid (CSF) cell count and protein, severity of TBM, time to correct hyponatremia, and prognosis. We analyzed the causes of hyponatremia and found syndrome of inappropriate secretion of antidiuretic hormone (SIADH) was the most common cause (77.7%, 80/103), followed by cerebral salt wasting (CSW) (17.5%, 18/103). Comparing SIADH and CSW, there was a significant difference in mean blood pressure, albumin, and hematocrit, and no significant difference in demographic characteristics, imaging, CSF cell count and protein, severity, occurrence and correction time of hyponatremia, or prognosis.

CONCLUSION

TBM with hyponatremia was dominated by moderate hyponatremia, which often manifested as SIADH. The more severe hyponatremia was, the longer the correction time of hyponatremia, which will affect the prognosis of TBM patients.

Disentangling etiologies of CNS infections in Singapore using multiple correspondence analysis and random forest

Central nervous system (CNS) infections cause substantial morbidity and mortality worldwide, with mounting concern about new and emerging neurologic infections. Stratifying etiologies based on initial clinical and laboratory data would facilitate etiology-based treatment rather than relying on empirical treatment. Here, we report the epidemiology and clinical outcomes of patients with CNS infections from a prospective surveillance study that took place between 2013 and 2016 in Singapore. Using multiple correspondence analysis and random forest, we analyzed the link between clinical presentation, laboratory results, outcome and etiology. Of 199 patients, etiology was identified as infectious in 110 (55.3%, 95%-CI 48.3–62.0), immune-mediated in 10 (5.0%, 95%-CI 2.8–9.0), and unknown in 79 patients (39.7%, 95%-CI 33.2–46.6). The initial presenting clinical features were associated with the prognosis at 2 weeks, while laboratory-related parameters were related to the etiology of CNS disease. The parameters measured were helpful to stratify etiologies in broad categories, but were not able to discriminate completely between all the etiologies. Our results suggest that while prognosis of CNS is clearly related to the initial clinical presentation, pinpointing etiology remains challenging. Bio-computational methods which identify patterns in complex datasets may help to supplement CNS infection diagnostic and prognostic decisions.

The epidemiology and clinical spectrum of infections of the central nervous system in adults in north India

Infections of the central nervous system (CNS) are a leading cause of mortality in low- and middle-income countries. We studied the spectrum, aetiology and outcome of CNS infections in 401 consecutive patients aged ≥12 years admitted at the medical emergency centre of PGIMER, Chandigarh, India. An aetiological diagnosis was made in 365 (91.0%) patients, with 149 (40.8%) microbiologically confirmed cases. CNS tuberculosis was the most prevalent cause (51.5%), followed by viral meningoencephalitis (13.9%), community-acquired bacterial meningitis (9.7%), cryptococcal meningitis (6.2%), scrub typhus meningoencephalitis (1.7%), neurocysticercosis (1.7%) and fungal brain abscess (1.7%). Human immunodeficiency virus (11.0%) and diabetes mellitus (6.2%) remained the usual predisposing conditions. We found a mortality rate of 27.9%, highest in cases without an aetiology (64.5%). Tuberculosis remained the most common cause; however, an increasing number of scrub typhus, dengue, fungal infections and non-classical bacterial pathogens may indicate a change in the epidemiology of community-acquired CNS infections in India.

Inclusion of Mechanical Ventilation in Severity Staging of Tuberculous Meningitis Improves Outcome Prediction

Patients with tuberculous meningitis (TBM) in any stage of the British Medical Research Council (BMRC) scale, if requiring mechanical ventilation (MV), are likely to have a poor outcome. We report the usefulness of BMRC, BMRC-MV, and BMRC-hydrocephalus (BMRC-HC) staging, and Haydarpasa Meningitis Severity Index (HAMSI) scoring in predicting the outcome of TBM. One hundred ninety-seven TBM patients were analyzed from a prospectively maintained TBM registry. The severity of meningitis was categorized using BMRC (stages I-III), BMRC-MV (I-IV [MV patients were grouped as stage IV]), and BMRC-HC (I-IV [BMRC stage III patients with hydrocephalus were grouped as stage IV]). Haydarpasa Meningitis Severity Index scoring was categorized as < 6 and ≥ 6. The outcome was defined at 6 months using the modified Rankin Scale (mRS) as death, poor (mRS score > 2), or good (mRS score ≤ 2). Forty-nine (25%) patients died. BMRC-mechanical ventilation stage IV had the highest predictive value for defining death, with a sensitivity of 88% and a specificity of 86%. About 81.7% of surviving patients had a good outcome at 6 months. BMRC-mechanical ventilation stages I-III had the highest predictive value for defining good outcome, with a sensitivity of 93% and a specificity of 61%. In TBM, BMRC-MV staging has the best predictive value for defining death and disability.

Diabetic trends and associated mortality in tuberculosis patients in Texas, a large population-based analysis

BACKGROUND

Tuberculosis (TB) and diabetes mellitus (DM) comorbidity (TB-DM) is a major public health challenge worldwide. This analysis aimed to determine the risk factors and trends associated with TB-DM morbidity and mortality.

METHODS

Risk factors for TB-DM morbidity and mortality were identified by logistic regression using de-identified surveillance data of all TB patients from Texas, USA. reported between 01/2010-12/2016. Non-parametric testing was used for the morbidity and mortality trends.

RESULTS

From 2010 to 2016, 1400/9002 (15.6%) TB patients were diabetic with an annual prevalence increase from 12.5% to 18.7% (p = 0.005). Reported TB-DM patients had a higher mortality (10.3%) than non-DM patients (7.6%, p = 0.001) with nearly a 3-fold increase in the odds of death (overall and during treatment). Older age, being Hispanic, chronic kidney failure, pulmonary cavitation and positive TB culture or smear were associated with TB-DM. Age ≥45, US-birth, resident of long-term care facility, injecting-drug user, chronic kidney disease, TB meningitis, abnormal chest radiograph, non-conversion of culture, and HIV(+) were independently associated with a higher mortality.

CONCLUSIONS

TB-DM is an increasing public health problem in Texas with significantly high mortality. Risk factors for mortality determined by multivariate modeling will provide a foundation for the development of more effective strategies for TB-DM management.

Development and validation of a risk score to predict mortality during TB treatment in patients with TB-diabetes comorbidity

BACKGROUND

Making an accurate prognosis for mortality during tuberculosis (TB) treatment in TB-diabetes (TB-DM) comorbid patients remains a challenge for health professionals, especially in low TB prevalent populations, due to the lack of a standardized prognostic model.

METHODS

Using de-identified data from TB-DM patients from Texas, who received TB treatment had a treatment outcome of completed treatment or died before completion, reported to the National TB Surveillance System from January 2010-December 2016, we developed and internally validated a mortality scoring system, based on the regression coefficients.

RESULTS

Of 1227 included TB-DM patients, 112 (9.1%) died during treatment. The score used nine characteristics routinely collected by most TB programs. Patients were divided into three groups based on their score: low-risk (< 12 points), medium-risk (12-21 points) and high-risk (≥22 points). The model had good performance (with an area under the receiver operating characteristic (ROC) curve of 0.83 in development and 0.82 in validation), and good calibration. A practical mobile calculator app was also created ( https://oaa.app.link/Isqia5rN6K ).

CONCLUSION

Using demographic and clinical characteristics which are available from most TB programs at the patient's initial visits, our simple scoring system had good performance and may be a practical clinical tool for TB health professionals in identifying TB-DM comorbid patients with a high mortality risk.

A New Scoring System for the Differential Diagnosis between Tuberculous Meningitis and Viral Meningitis

BACKGROUND

Tuberculous meningitis (TBM) is associated with high mortality and morbidity despite administering anti-tuberculous chemotherapy to the patients. Differential diagnosis between TBM and viral meningitis (VM) is difficult in some clinical situations.

METHODS

We reviewed and analyzed records of adult patients who were admitted and diagnosed with TBM or VM at a tertiary hospital in Korea, between January 2006 and December 2015. Diagnostic criteria for TBM were categorized into three groups: definite, probable, and possible TBM. The VM group included patients with no evidence of other meningitis who achieved complete recovery with only conservative treatments. Clinical, laboratory and radiological findings, as well as outcomes, were compared between the TBM and VM groups.

RESULTS

Ninety-eight patients were enrolled. Among the study patients, 47 had TBM and 51 had VM. Based on univariate analysis and multivariate logistic regression, sodium < 135 mmol/L in serum (hyponatremia), lactate dehydrogenase > 70 (U/L) in cerebrospinal fluid (CSF), protein > 160 (mg/dL) in CSF, voiding difficulty, and symptoms of cranial nerve palsy were significant predictive factors for TBM in the final model. We constructed a weighted scoring system with predictive factors from multiple regression analyses. Receiver operating characteristic curve analyses and decision tree analyses were plotted to reveal an optimum cutoff point as 4 with this scoring system (range: 0-13).

CONCLUSION

For differential diagnosis between TBM and VM, we created a new weighted scoring system. This scoring system and decision tree analysis are simple and easy to apply in clinical practice to differentiate TBM from VM.

Prognostic score to predict mortality during TB treatment in TB/HIV co-infected patients

Background

Estimating mortality risk during TB treatment in HIV co-infected patients is challenging for health professionals, especially in a low TB prevalence population, due to the lack of a standardized prognostic system. The current study aimed to develop and validate a simple mortality prognostic scoring system for TB/HIV co-infected patients.

Methods

Using data from the CDC’s Tuberculosis Genotyping Information Management System of TB patients in Texas reported from 01/2010 through 12/2016, age ≥15 years, HIV(+), and outcome being “completed” or “died”, we developed and internally validated a mortality prognostic score using multiple logistic regression. Model discrimination was determined by the area under the receiver operating characteristic (ROC) curve (AUC). The model’s good calibration was determined by a non-significant Hosmer-Lemeshow’s goodness of fit test.

Results

Among the 450 patients included in the analysis, 57 (12.7%) died during TB treatment. The final prognostic score used six characteristics (age, residence in long-term care facility, meningeal TB, chest x-ray, culture positive, and culture not converted/unknown), which are routinely collected by TB programs. Prognostic scores were categorized into three groups that predicted mortality: low-risk (<20 points), medium-risk (20–25 points) and high-risk (>25 points). The model had good discrimination and calibration (AUC = 0.82; 0.80 in bootstrap validation), and a non-significant Hosmer-Lemeshow test p = 0.71.

Conclusion

Our simple validated mortality prognostic scoring system can be a practical tool for health professionals in identifying TB/HIV co-infected patients with high mortality risk.

Development and validation of a prognostic score to predict tuberculosis mortality

OBJECTIVE

To develop and validate a simple prognostic scoring system to predict the mortality risk during treatment in tuberculosis patients.

METHODS

Using data from the CDC's Tuberculosis Genotyping Information Management System of TB patients in Texas reported from 01/2010 to 12/2016, age ≥ 15 years and having an outcome as "completed" or "died", we developed and validated a prognostic mortality scoring system-based logistic regression beta-coefficients.

RESULTS

The developmental and validation cohorts consisted of 3378 and 3377 patients, respectively. The score used 9 demographic and clinical characteristics, which are usually available at the patient's initial visits to a healthcare facility. Prognostic scores were categorized into three groups that predicted mortality: low-risk (<15 points), medium-risk (15-18 points), and high-risk (>18 points). The model had excellent discrimination and calibration with an area under the receiver operating characteristic curve of 0.82 and 0.80, and a non-significant Hosmer-Lemeshow test P = 0.514 and P = 0.613 in the developmental and validation cohorts, respectively.

CONCLUSION

Our validated TB prognostic scoring system, which used demographic and clinical characteristics available at the patient's initial visits, can be a practical tool for health care providers to identify TB patients with high mortality risk so that appropriate treatment, medical supports and follow-up resources could be appropriately allocated.

Identification of potential metabolic biomarkers of cerebrospinal fluids that differentiate tuberculous meningitis from other types of meningitis by a metabolomics study

Tuberculous meningitis (TBM) is caused by tuberculosis infection of of the meninges, which are the membrane systems that encircle the brain, with a high morbidity and mortality rate. It is challenging to diagnose TBM among other types of meningitis, such as viral meningitis, bacterial meningitis and cryptococcal meningitis. We aimed to identify metabolites that are differentially expressed between TBM and the other types of meningitis by a global metabolomics analysis. The cerebrospinal fluids (CSF) from 50 patients with TBM, 17 with viral meningitis, 17 with bacterial meningitis, and 16 with cryptococcal meningitis were analyzed using ultra high performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS). A total of 1161 and 512 features were determined in positive and negative electrospray ionization mode, respectively. A clear separation between TBM and viral, bacterial or cryptococcal meningitis was achieved by orthogonal projections to latent structures-discriminate analysis (OPLS-DA) analysis. Potential metabolic markers and related pathways were identified, which were mainly involved in the metabolism of amino acid, lipids and nucleosides. In summary, differential metabolic profiles of the CSF exist between TBM and other types of meningitis, and potential metabolic biomarkers were identified to differentiate TBM from other types of meningitis.

Old age and hydrocephalus are associated with poor prognosis in patients with tuberculous meningitis: A retrospective study in a Chinese adult population

Tuberculous meningitis (TBM) is the most common form of central nervous system tuberculosis with a very poor prognosis. We aimed at assessing risk factors related to the prognosis of patients with TBM.Forty-five inpatients with TBM in our institution from January 2013 to December 2015 were enrolled retrospectively. The good or poor prognosis in the patients was defined, based on Glasgow Outcome Scale System at discharge. Patients with a GOS score less than 5 were defined as "poor prognosis." Univariate and multivariate logistic regression analyses were performed to assess the predictors for TBM outcome.Among 45 TBM patients, 35 (77.8%) and 10 (22.2%) were in good, poor prognoses, respectively. Old age, disturbance of consciousness, moderate to severe electroencephalogram abnormality, hydrocephalus, remarkable increase of protein (≥ 236 mg/dL) and white blood cell counts (≥ 243 /μL) in cerebral spinal fluid were associated with poor prognosis. Multivariate analysis indicated that old age (odds ratio (OR) = 18.395, P = .036) and hydrocephalus (OR = 32.995, P = .049) were independent factors for a poor outcome of TBM.In conclusion, old age and hydrocephalus are the predictors for poor prognosis of TBM. Patients with these risk factors should be treated promptly with a special care paid to improve their outcomes.

Comparison of clinical features and prognostic factors in HIV-negative adults with cryptococcal meningitis and tuberculous meningitis: a retrospective study

Background

The incidence of cryptococcal meningitis (CM) and tuberculous meningitis (TBM) have gradually increased in recent years. These two types of meningitis are easily misdiagnosed which leads to a poor prognosis. In this study we compared differences of clinical features and prognostic factors in non-HIV adults with CM and TBM.

Methods

We retrospectively reviewed the medical records of CM and TBM patients from January 2008 to December 2015 in our university hospital in China. The data included demographic characteristics, laboratory results, imaging findings, clinical outcomes.

Results

A total of 126 CM and 105 TBM patients were included. CM patients were more likely to present with headache, abnormal vision and hearing, and they might be less prone to fever and cough than TBM patients (P < 0.05). Higher percentage of CM patients presented with cerebral ischemia/infarction and demyelination in brain MRI than TBM patients (P < 0.05). CM patients had lower counts of WBC in CSF, lower total protein in CSF and serum CD4/CD8 ratio than TBM patients (P < 0.05). After three months of treatment, CM group have worse outcome than TBM group (P < 0.05). Multivariate analysis showed that age more than 60y (OR = 4.981, 95% CI: 1.955–12.692, P = 0.001), altered mentation (OR = 5.054, 95% CI: 1.592–16.046, P = 0.006), CD4/CD8 ratios < 1 (OR = 8.782, 95% CI: 2.436–31.661, P = 0.001) and CSF CrAg ≥ 1:1024 (OR = 4.853, 95% CI: 1.377–17.098, P = 0.014) were independent risk factors for poor prognosis for CM patients. For TBM patients, hydrocephalus (OR = 7.290, 95% CI: 1.630–32.606, P = 0.009) and no less than three underlying diseases (OR = 6.899, 95% CI: 1.766–26.949, P = 0.005) were independent risk factors, headache was a protective factor of prognosis.

Conclusions

Our study provided some helpful clues in the differential diagnosis of non-HIV patients with CM or TBM and identified some risk factors for the poor prognosis of these two meningitis which could help to improve the treatment outcome. Further studies are worth to be done.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-016-2126-6) contains supplementary material, which is available to authorized users.