Normocellular Community-Acquired Bacterial Meningitis in Adults: A Nationwide Population-Based Case Series

Progranulin Plays a Protective Role in Pneumococcal Meningitis by Inhibiting Pyroptosis

OBJECTIVE

Pneumococcal meningitis is a serious infectious disease with a high mortality rate and a global presence, and survivors have different degrees of neurological sequelae as a consequence of the host response to the infection. Progranulin (PGRN) is a multifunctional autocrine growth factor that is also a major immunoregulator. We want to investigate the role for PGRN in Pneumococcal meningitis in vivo and in vitro.

METHOD

Mouse and cell models were established to explore the protective effect and mechanism of PGRN against pneumococcal meningitis.

RESULTS

Progranulin plays a protective role in pneumococcal meningitis by inhibiting pyroptosis. Pyroptosis resulted from exposure of BV-2 cells to the bacterium and this was confirmed in the in vivo model. Administration of the NLRP3 inflammasome inhibitor MCC950 to mice prior to infection inhibited pyroptosis and protected PGRN -/- mice and BV-2 cell model from meningitis.

CONCLUSION

This study implicates a protective role for PGRN in pneumococcal meningitis by inhibiting pyroptosis, indicating that PGRN may have therapeutic potential.

Heparin-Binding Protein in Cerebrospinal Fluid as a Biomarker for Bacterial Meningitis: A Study of Diagnostic Accuracy

OBJECTIVE

We aimed to evaluate the diagnostic accuracy of heparin-binding protein (HBP) in cerebrospinal fluid for the diagnosis of bacterial meningitis in patients with a suspected central nervous system infection.

METHODS

This prospective multicenter cohort study determined the diagnostic accuracy of HBP in cerebrospinal fluid (CSF) for bacterial meningitis among a cohort of consecutive patients with a suspected central nervous infection. The final clinical diagnosis was considered the reference standard. The results were validated in a separate cohort.

RESULTS

A total of 631 Dutch patients were evaluated for the current study, of which 73 (12%) had a final diagnosis of bacterial meningitis. For the differentiation of bacterial meningitis from all other disorders, diagnostic accuracy was high with an area under the curve (AUC) of 0.98 (95% confidence interval [CI] 0.96-1.00). With the proposed cutoff of 5.2 ng/ml, sensitivity was 97% with a specificity of 96%. In the population of patients with a CSF leukocyte count of 5-1,000/mm3, the AUC was 0.96 (95% CI 0.87-1.00), outperforming CSF leukocytes (AUC 0.88 [95% CI 0.79-0.97]). Combining HBP with CSF C-reactive protein (CRP) significantly increased accuracy in this population and reached a 100% sensitivity (AUC 1.00 [95% CI 0.99-1.00], cutoff 0.07, sensitivity 100%, specificity 96%). These results remained robust in an external validation cohort of 120 Danish patients (AUC 0.97 [95% CI 0.93-1.00]).

INTERPRETATION

HBP can correctly distinguish bacterial meningitis from other disorders. It can be of additional value to current diagnostics in cases where CSF leukocyte count is relatively low, particularly when combined with CSF CRP. ANN NEUROL 2025.

Prognostic Factors for Japanese Adults With Acute Community-Acquired Bacterial Meningitis: A Retrospective Study

Background This study aimed to determine if the cerebrospinal fluid (CSF) cell count is useful for predicting the infection severity or prognosis in Japanese adults with community-acquired bacterial meningitis. Methodology This study retrospectively evaluated the prognosis of patients diagnosed with community-acquired bacterial meningitis at our hospital from January 2004 to December 2021 using the modified Rankin scale (mRs) (Showa General Hospital; N = 39). Patients were classified into the following two groups: (i) favorable (mRs: 0-3) and (ii) unfavorable (mRs: 4-6). Eight factors were selected and compared with outcomes, and then two factors were evaluated from those, and a multivariate logistic regression was used to determine the significant variables. Results CSF cell count was observed to be associated with poor prognoses (odds ratio (OR) = 0.86, 95% confidence interval (CI) = 0.99995-0.99999, p = 0.0012). Glasgow coma scale (GCS) score on admission was also observed to be associated with poor prognoses (OR = 0.93, 95% CI = 0.89145-0.97290, p = 0.0029). Conclusions Low CSF cell count and low GCS on admission were observed as risk factors for poor prognoses in patients with bacterial meningitis.

The clinical utility of metagenomic next-generation sequencing for the diagnosis of central nervous system infectious diseases

BACKGROUND

To evaluate the clinical utility of metagenomic next-generation sequencing (mNGS) for the diagnosis of central nervous system infections (CNSI).

METHODS

Cerebrospinal fluid (CSF) from 54 patients who were high-level clinical suspicion of CNSI was collected and sent for mNGS and conventional tests from January 2019 to March 2022.

RESULTS

Twenty out of 54 patients were diagnosed with CNSI and 34 non-CNSI. Among the 34 non-CNSI, one was false positive by mNGS. Among the 20 CNSI, 11 had presumed viral encephalitis and/or meningitis, 5 had presumed bacterial meningitis, 2 had presumed TMB, 1 had Crytococcus meningitis and 1 had neurosyphilis. The sensitivity of viral encephalitis and/or meningitis was 0.73 (8/11); 10 virus were detected; 9/10 was dsDNA; 1/10 was ssRNA. SSRN ranged from 1 to 13. The accuracy rate was 0.4, the accuracy rate was positively correlated with SSRN (r = 0.738, P = 0.015), SSRN ≥ 1, the accuracy rate was 0.4; SSRN ≥ 3, the accuracy rate was 0.66; SSRN ≥ 4, the accuracy rate was 0.75; SSRN ≥ 6, the accuracy rate was 1. The sensitivity of bacterial meningitis was 1. Seven kinds of bacteria were detected, among which 3/7 were gram positive, 3/7 were gram negative, and 1/7 was infected NTM (nontuberculous mycobacteria). The accuracy rate was 0.43 (3/7). The sensitivity of TBM was 0.66 (2/3), the accuracy rate was 1. The sensitivity of Crytococcus meningitis was 1, the accuracy rate was 0.5. PPV (positive predictive value) of mNGS was 0.94, NPV (negative predictive value) of mNGS was 0.89, specificity was 0.97 and sensitivity was 0.8. The AUG for CSF mNGS diagnosis of CNSI was 0.89 (95% CI = 0.78-0.99) Headache, meningeal irritation sign and image of meninges abnormal were correlated with the sensitivity of mNGS (r = 0.451, 0.313, 0.446; p = 0.001, 0.021, 0.001); CSF Glucose and CSF Chloride were negatively correlated with sensitivity of mNGS (r = -0.395, -0.462; p = 0.003, ＜ 0.001).

CONCLUSION

mNGS is a detection means with high sensitivity, wide coverage and strong timeliness, which can help clinicians to identify the pathogen diagnosis quickly, conduct targeted anti-infection treatment early and reduce antibiotic abuse. The pathogen which causing low CSF Glucose, low CSF Chloride or meninges infections was more likely to be detected by mNGS. It may be related to growth and structural characteristics of the pathogen and blood-brain barrier damage.

The management of acute meningitis: an update

Meningitis remains an important cause of mortality and morbidity. Clinicians should be alert to this diagnosis and have a low threshold for investigation and treatment of meningitis. This article provides an update of current evidence and existing guidelines for the management of suspected acute meningitis in adults in the UK.

BACTERIAL MENINGITIS PRESENTING WITH A NORMAL CEREBROSPINAL FLUID LEUKOCYTE COUNT

OBJECTIVES

We describe clinical characteristics and outcome of adults with bacterial meningitis presenting with a normal CSF leukocyte count.

METHODS

We studied community-acquired bacterial meningitis with a normal CSF leukocyte count (≤ 5 per mm³) in adults from a prospective nationwide cohort study.

RESULTS

From 2006 through 2020, 39 of 2,357 (2%) episodes presented with a normal CSF leukocyte count. Immunocompromising conditions were present in 19 of 39 patients (49%), compared to 690 of 2303 (30%) in patients with elevated leukocytes (P=0.02). The triad of fever, neck stiffness, and altered consciousness was present in 6 of 34 patients (18%). CSF protein was abnormal in 25 of 37 patients (68%). We identified 3 clinical subgroups: those with severe pneumococcal meningitis (20 patients [51%]), with mainly sepsis (8 [21%]), and a miscellaneous group (11 [28%]). All patients with severe pneumococcal meningitis presented with high CSF protein levels and 18 of 19 (95%) had bacteria in the CSF Gram stain. Outcome was unfavorable in 23 of 39 (59%) patients and 12 (31%) died.

CONCLUSION

Patients with bacterial meningitis may present with normal CSF leukocyte counts. In these patients, CSF protein levels and Gram staining are important diagnostic parameters.

Existing Data Sources for Clinical Epidemiology: The Danish Study Group of Infections of the Brain Database (DASGIB)

Central nervous system (CNS) infections are rare diseases that are associated with considerable morbidity and mortality. Increased knowledge based on contemporary data is a prerequisite for improved management and prevention of these serious conditions. Yet, population-based databases of patients hospitalized with CNS infections remain scarce. The Danish Study Group of Infections of the Brain (DASGIB) has prospectively registered information on all adults ≥18 years of age admitted with CNS infections at departments of infectious diseases in Denmark since 2015. The main variables collected are baseline demographics, blood and cerebrospinal fluid tests, imaging results, and outcome using the Glasgow Outcome Scale score. To investigate important aspects for each type of CNS infections, additional variables are included specifically for bacterial meningitis, viral meningitis, encephalitis, brain abscess, neurosyphilis, and Lyme neuroborreliosis. From 2015 to 2020, a total of 3579 cases of CNS infections have been recorded in the DASGIB database. Using the unique civil registration number assigned to all Danish residents, the database can be unambiguously linked with nationwide healthcare registries at the individual level. This enables researchers to conduct detailed population-based and longitudinal observational studies of risk and prognosis of CNS infections and to compare them with matched population cohorts. The database is well-suited for epidemiological research and the DASGIB network forms a solid infrastructure for future national and international collaborations.