Outcomes of acute meningitis according to immunosuppression status: 15-year retrospective cohort

Carla Marina Román-Montes; Valeria Alejandra Pérez-López; Nayeli Esmeralda Avalos-Celis; Aranza Castillejos-Gracia; Alfredo Ponce de León; Guillermo Arturo Guaracha-Basañez

doi:10.1371/journal.pone.0344150

Abstract

Acute meningitis remains a primary global health concern. Immunosuppressed patients have risks due to atypical clinical presentations and a broader range of causative pathogens. We aimed to describe the outcomes and clinical features of acute meningitis according to immunosuppression status. We performed a retrospective cohort study of adults with acute meningitis from January 2009 to December 2023. Patients with postsurgical meningitis were excluded. Outcomes and demographic, clinical, and laboratory features were compared using non-parametric statistical tests, and mortality was analyzed using multivariate logistic regression. Among 189 patients, 96 (51%) were immunosuppressed. The median age was lower in immunosuppressed patients (36 vs. 50 years, p < 0.01). There were no differences in symptoms; the classical triad was present in only 21% vs. 19%. Immunosuppressed patients had lower CSF glucose levels (59% vs. 39%, p = 0.004). Overall mortality was 20%, with no significant difference by immune status. Independent predictors of death included age over 50 years (OR 2.9), altered mental status (OR 4.7), and bacterial meningitis (OR 2.3). Acute meningitis in immunosuppressed hosts shows attenuated inflammatory CSF profiles and a broader etiologic spectrum. Immunosuppression was not independently associated with in-hospital mortality.

Citation: Román-Montes CM, Pérez-López VA, Avalos-Celis NE, Castillejos-Gracia A, Ponce de León A, Guaracha-Basañez GA (2026) Outcomes of acute meningitis according to immunosuppression status: 15-year retrospective cohort. PLoS One 21(3): e0344150. https://doi.org/10.1371/journal.pone.0344150

Editor: Karlo Toljan, Cleveland Clinic Abu Dhabi, UNITED ARAB EMIRATES

Received: January 1, 2026; Accepted: February 16, 2026; Published: March 24, 2026

Copyright: © 2026 Román-Montes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The datasets generated and analyzed during the current study are not publicly available but may be made available upon reasonable request. Although the dataset does not contain direct patient identifiers, access is restricted due to ethical and institutional requirements imposed by the Research and Ethics Committees of the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán to protect patient confidentiality. Data access requests may be directed to the President of the Institutional Research Ethics Committee at martha.guevarac@incmnsz.mx.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Acute meningitis remains a major global health problem, causing significant morbidity and mortality despite advances in prevention and treatment [1,2]. Globally, it accounts for an estimated 2.8 million cases and over 300,000 deaths each year, with the burden highest in low- and middle-income countries [3]. Bacterial meningitis is particularly severe, as it can rapidly progress to neurologic damage or death if not promptly treated [4].

In immunosuppressed populations, such as individuals with HIV/AIDS, solid-organ transplant recipients, patients on prolonged corticosteroids or immunosuppressive therapies for rheumatic disease, and those with hematologic malignancies, the risk of meningitis is markedly increased [5]. In these hosts, the etiologic spectrum expands beyond typical pathogens to include opportunistic organisms such as Listeria monocytogenes, Pseudomonas aeruginosa, Cryptococcus neoformans, and Mycobacterium tuberculosis [6,7].

Data from low- and middle-income countries, especially among patients with a high burden of rheumatic diseases and other non-HIV immunosuppression, remain scarce. In Latin America, most available studies on acute meningitis focus on HIV infection or community-acquired disease in the general population [8–10], with limited information on how immunosuppression influences clinical presentation, etiologic spectrum, and outcomes.

To address this gap, we conducted a 15-year retrospective analysis at a tertiary referral center in Latin America to compare the characteristics and outcomes of acute meningitis according to immunosuppression status and to identify independent predictors of in-hospital mortality.

Materials and methods

We conducted a retrospective cohort analysis of acute meningitis cases attended from January 2009 to December 2023 at a tertiary care center in Mexico City, examining outcomes according to immunosuppression status.

Population

Patients aged 18 years or older who met the definition of acute meningitis were included. Cases associated with neurosurgical procedures were excluded to avoid bias. Data were extracted from electronic medical records between August and November 2025. Demographic, clinical, and laboratory variables were collected from electronic files.

Definitions

Acute meningitis was defined as an acute central nervous system infectious syndrome characterized by headache [11,12] and/or fever plus at least one meningeal or neurological sign (neck stiffness, photophobia, seizures, or altered mental status [AMS]), together with cerebrospinal fluid (CSF) findings compatible with meningeal inflammation (CSF pleocytosis, elevated CSF protein, and low CSF glucose).

Low CSF glucose was defined as a CSF glucose level <45 mg/dL or a CSF-to-serum glucose ratio ≤0.5. Elevated CSF protein was defined as a CSF protein level >45 mg/dL, and CSF pleocytosis was defined as a CSF leukocyte count >5 cells/mm³.

Aseptic meningitis was defined as acute meningitis without microbiologic or etiologic evidence.

Tuberculous and cryptococcal meningitis were included when presenting within 14 days of symptom onset and with microbiological confirmation, to reflect the real-world diagnostic spectrum at our center. A sensitivity analysis excluding Mycobacterium tuberculosis and Cryptococcus spp. cases was performed [11,12].

Immunosuppression was defined a priori as the presence of at least one of the following at meningitis onset:

(1) receipt of systemic corticosteroids equivalent to ≥10 mg/day of prednisone for ≥4 consecutive weeks; (2) treatment within the previous 6 months with conventional synthetic or biologic disease-modifying antirheumatic drugs (DMARDs), calcineurin inhibitors, antimetabolites (e.g., azathioprine, mycophenolate mofetil), alkylating agents, tyrosine kinase inhibitors, or T- or B-cell–depleting agents (e.g., rituximab, cyclophosphamide); (3) recent cytotoxic chemotherapy for solid or hematologic malignancy; (4) solid organ or hematopoietic stem cell transplantation; (5) advanced HIV infection (CD4 cell count <200 cells/L or any AIDS-defining condition); (6) documented inborn error of immunity; (7) severe neutropenia <0.5 × 10⁹ neutrophils/L lasting >10 days temporally related to meningitis onset.

Comorbidities such as type 2 diabetes mellitus, obesity, chronic liver disease, chronic kidney disease, and chronic lung disease were recorded but did not meet the immunosuppression definition unless one of the above criteria was present [13].

Statistical analysis

Categorical variables are presented as frequencies and percentages, and continuous variables as medians with interquartile ranges (IQR). Distribution was assessed using the Shapiro–Wilk test.

Comparisons between immunosuppressed and non-immunosuppressed patients were performed using the or Fisher’s exact test for categorical variables and the Mann–Whitney U or Kruskal–Wallis test for continuous variables.

The primary outcome was in-hospital mortality. Candidate predictors were first evaluated in bivariable analyses. Variables associated with mortality at p < 0.20 and/or considered clinically relevant were entered into a multivariable logistic regression model.

Model performance was assessed using discrimination (area under the receiver operating characteristic curve) and calibration (goodness-of-fit test). Sensitivity and specificity were not emphasized because the model was not developed for binary risk classification.

All analyses were conducted using Stata version 14.0 (StataCorp, College Station, TX, USA). A two-sided p < 0.05 was considered statistically significant.

Results

A total of 189 cases of acute meningitis were identified. Most patients were women (105/189, 55.5%), with a median age of 41 years (IQR 30–57). Immunosuppression was present in 96 (51%) patients. There were no sex differences between groups, and the median age was lower in the immunosuppressed group (36 [IQR 27–50.5] vs. 50 [IQR 33–64] years, p < 0.01).

Demographic characteristics and comorbidities according to immunosuppression status are summarized in Table 1.

Download:

Table 1. Demographic and comorbidities of patients with acute meningitis according to immunosuppression status.

https://doi.org/10.1371/journal.pone.0344150.t001

Among immunosuppressed patients, 70/96 (73%) had pharmacological immunosuppression. Of these, 60/70 (86%) received prednisone (median dose 20 mg, IQR 5–50). The most frequently used DMARDs were methotrexate (24%), azathioprine (21%), mycophenolate (19%), tacrolimus (10%), and cyclophosphamide (10%). Advanced HIV infection accounted for 20/96 (31%) cases; the median CD4 count was 25 cells/L (IQR 0–125).

Clinical characteristics

The median duration of symptoms prior to emergency department presentation was 3 days (IQR 1–7), with no significant difference between groups (p = 0.15).

There were no significant differences in clinical manifestations between immunosuppressed and non-immunosuppressed patients (Table 2). The most frequent symptoms were headache, fever, and altered mental status. The classical triad (fever, neck rigidity, and altered mental status) was present in 21% vs. 19% of patients (p = 0.80).

Download:

Table 2. Clinical and diagnostic features in patients with acute meningitis according to immunosuppression status.

https://doi.org/10.1371/journal.pone.0344150.t002

Laboratory and CSF findings

All patients underwent lumbar puncture. Immunosuppressed patients had significantly lower CSF glucose levels (median 40 vs. 52 mg/dL, p = 0.02). There was no statistically significant difference in CSF leukocyte count (median 35 vs. 96 cells/mm³, p = 0.06) nor in the proportion with pleocytosis or elevated CSF protein.

Etiologic diagnosis was more frequently established among immunosuppressed patients (76/96, 79% vs. 54/93, 58%; p = 0.002). The proportion of aseptic meningitis was lower in immunosuppressed patients (21% vs. 42%; p = 0.002).

The most common etiologic category in immunosuppressed patients was Mycobacterium tuberculosis complex, whereas Streptococcus pneumoniae predominated among non-immunosuppressed individuals. The distribution of etiologic agents is shown in Fig 1.

Download:

Fig 1. Etiology of acute meningitis according to immunosuppression status.

https://doi.org/10.1371/journal.pone.0344150.g001

CSF culture was positive in 92 (49%) patients, without differences by immunosuppression status (p = 0.34). Blood cultures were obtained in 152 (80%) patients and were positive in 42 (28%), with no significant differences between groups (p = 0.16).

Mortality analysis

Overall in-hospital mortality was 38/189 (20%), without significant differences according to immunosuppression status (18% vs. 23%; p = 0.40). In multivariable logistic regression analysis, independent predictors of mortality included:

Age ≥50 years (OR 2.9, 95% CI 1.31–6.37, p = 0.01)
Altered mental status (OR 4.7, 95% CI 1.70–12.98, p = 0.003)
Bacterial meningitis (OR 2.3, 95% CI 1.01–5.1, p = 0.04)

Immunosuppression was not independently associated with mortality (OR 0.73, 95% CI 0.36–2.6; p=0.40).

The final multivariable model demonstrated good discrimination (AUC = 0.75) and adequate calibration (Pearson goodness-of-fit p = 0.52). The forest plot of the regression model is shown in Fig 2.

Download:

Fig 2. Multivariable logistic regression model for in-hospital mortality.

https://doi.org/10.1371/journal.pone.0344150.g002

Discussion

This study analyzes 15 years of acute meningitis at a tertiary referral center, with more than half of cases occurring in immunosuppressed patients, underscoring the importance of infections in this vulnerable population. Despite demographic and laboratory differences, mortality rates were similar between immunosuppressed and non-immunosuppressed patients, suggesting that immunosuppression alone may not be the primary determinant of short-term mortality.

Consistent with previous reports, only 20% of patients presented with the classical triad of meningitis, particularly among immunosuppressed individuals [5]. Clinical manifestations such as headache and fever were similar regardless of immune status. Attenuated inflammatory responses likely explain the lower CSF leukocyte counts and glucose levels observed in immunosuppressed patients [14,15]. These findings highlight the importance of maintaining a high index of suspicion and performing early lumbar puncture in immunocompromised patients presenting with nonspecific neurological symptoms, even in the absence of classic meningeal signs.

An etiologic diagnosis was more frequently established in immunosuppressed patients. Opportunistic infections in this group may yield higher microbiological diagnostic rates due to routine use of antigen testing, PCR-based methods, and fungal cultures. Previous studies have reported delayed diagnosis and higher false-negative rates in non-immunosuppressed populations [16]. In adults with community-acquired meningitis, low CSF glucose has been associated with increased likelihood of microbiologic confirmation and treatable etiologies [17], findings that are consistent with our results.

The etiologic spectrum observed in our cohort reflects regional epidemiology. Mycobacterium tuberculosis represented a significant proportion of cases among immunosuppressed patients, consistent with the burden of tuberculosis in Mexico [16]. Opportunistic pathogens such as Cryptococcus neoformans and Listeria monocytogenes were also prominent in this group, as previously described in HIV and transplant populations [6]. In contrast, Streptococcus pneumoniae remained the leading pathogen among non-immunosuppressed individuals.

In multivariable analysis, age ≥50 years, altered mental status, and bacterial etiology were independently associated with mortality. These findings align with prior studies in adult bacterial meningitis [1,18–20]. Older age and decreased level of consciousness at presentation have consistently been identified as strong predictors of unfavorable outcomes across different meningitis etiologies, including cryptococcal meningitis [21].

The absence of an independent association between immunosuppression and mortality should be interpreted cautiously. Younger age among immunosuppressed patients, higher microbiologic diagnostic yield, and confounding by etiologic distribution may partially explain this finding. Residual confounding inherent to retrospective analyses cannot be excluded.

This study has limitations. Its retrospective, single-center design may limit generalizability. Long-term neurological outcomes beyond hospital discharge were not evaluated. Furthermore, the inclusion of microbiologically confirmed tuberculous and cryptococcal meningitis presenting within 14 days may affect comparability with cohorts of acute bacterial or viral meningitis, although a sensitivity analysis was performed. A major strength is the 15-year follow-up period.

Conclusions

In this 15-year retrospective cohort, immunosuppressed patients with acute meningitis exhibited attenuated cerebrospinal fluid inflammatory profiles and a broader etiologic spectrum compared with non-immunosuppressed individuals. However, immunosuppression was not independently associated with in-hospital mortality after adjustment for age, neurologic severity, and etiology.

Age ≥50 years, altered mental status at presentation, and bacterial etiology were independent predictors of death. These findings underscore the importance of early recognition, prompt diagnostic evaluation, and appropriate empiric antimicrobial therapy in all patients with suspected acute meningitis, particularly in those with impaired immune function.

Supporting information

S1 Fig. Sensitivity analysis excluding tuberculosis and fungal meningitis.

https://doi.org/10.1371/journal.pone.0344150.s001

(TIFF)

S1 Table. Additional multivariable model excluding fungal cases.

https://doi.org/10.1371/journal.pone.0344150.s002

(PDF)

Acknowledgments

We thank the Clinical Archive Department for facilitating access to medical records and Fernanda González-Lara, MD, MSc, Head of the Clinical Microbiology Laboratory, for her support in accessing microbiological data. We also acknowledge the work of the laboratory chemists and microbiologists whose efforts directly contributed to patient care and diagnostic accuracy.

We are grateful to the clinical staff of the Infectious Diseases Department for their dedication in the management of patients included in this study.

References

1. Wall EC, Chan JM, Gil E, Heyderman RS. Acute bacterial meningitis. Curr Opin Neurol. 2021;34(3):386–95. pmid:33767093
- View Article
- PubMed/NCBI
- Google Scholar
2. van de Beek D, Brouwer M, Hasbun R, Koedel U, Whitney CG, Wijdicks E. Community-acquired bacterial meningitis. Nat Rev Dis Primers. 2016;2:16074. pmid:27808261
- View Article
- PubMed/NCBI
- Google Scholar
3. GBD 2016 Meningitis Collaborators. Global, regional, and national burden of meningitis, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018;17(12):1061–82. pmid:30507391
- View Article
- PubMed/NCBI
- Google Scholar
4. Glimåker M, Sjölin J, Åkesson S, Naucler P. Lumbar Puncture Performed Promptly or After Neuroimaging in Acute Bacterial Meningitis in Adults: A Prospective National Cohort Study Evaluating Different Guidelines. Clin Infect Dis. 2018;66(3):321–8. pmid:29020334
- View Article
- PubMed/NCBI
- Google Scholar
5. van Veen KEB, Brouwer MC, van der Ende A, van de Beek D. Bacterial Meningitis in Patients using Immunosuppressive Medication: a Population-based Prospective Nationwide Study. J Neuroimmune Pharmacol. 2017;12(2):213–8. pmid:27613024
- View Article
- PubMed/NCBI
- Google Scholar
6. Rajasingham R, Smith RM, Park BJ, Jarvis JN, Govender NP, Chiller TM, et al. Global burden of disease of HIV-associated cryptococcal meningitis: an updated analysis. Lancet Infect Dis. 2017;17(8):873–81. pmid:28483415
- View Article
- PubMed/NCBI
- Google Scholar
7. Pruitt AA. Central Nervous System Infections in Immunocompromised Patients. Curr Neurol Neurosci Rep. 2021;21(7):37. pmid:34037866
- View Article
- PubMed/NCBI
- Google Scholar
8. Sáfadi MAP, Valenzuela MT, Carvalho AF, De Oliveira LH, Salisbury DM, Andrus JK. Knowing the scope of meningococcal disease in Latin America. Rev Panam Salud Publica. 2017;41:e118. pmid:31391828
- View Article
- PubMed/NCBI
- Google Scholar
9. Carnalla-Barajas MN, Soto-Noguerón A, Solórzano-Santos F, Macías-Parra M, Díaz-Jiménez V, Sánchez-González G, et al. Pneumococcal meningitis in Mexico. Serotype distribution and antimicrobial resistance before and after the introduction of pneumococcal conjugate vaccines in pediatric patients. Results from the GIVEBPVac group. J Infect Public Health. 2026;19(1):103030. pmid:41223711
- View Article
- PubMed/NCBI
- Google Scholar
10. Villalpando-Carrión S, Henao-Martínez AF, Franco-Paredes C. Epidemiology and Clinical Outcomes of Bacterial Meningitis in Children and Adults in Low- and Middle-Income Countries. Curr Trop Med Rep. 2024;11(2):60–7. pmid:39006487
- View Article
- PubMed/NCBI
- Google Scholar
11. van de Beek D, Brouwer MC, Thwaites GE, Tunkel AR. Advances in treatment of bacterial meningitis. Lancet. 2012;380(9854):1693–702. pmid:23141618
- View Article
- PubMed/NCBI
- Google Scholar
12. World Health Organization. WHO guidelines on meningitis diagnosis, treatment and care. 2025.
13. Rubin LG, Levin MJ, Ljungman P, Davies EG, Avery R, Tomblyn M, et al. 2013 IDSA clinical practice guideline for vaccination of the immunocompromised host. Clin Infect Dis. 2014;58(3):309–18. pmid:24421306
- View Article
- PubMed/NCBI
- Google Scholar
14. Kastenbauer S, Pfister H-W. Pneumococcal meningitis in adults: spectrum of complications and prognostic factors in a series of 87 cases. Brain. 2003;126(Pt 5):1015–25. pmid:12690042
- View Article
- PubMed/NCBI
- Google Scholar
15. van Soest TM, Chekrouni N, van Sorge NM, Brouwer MC, van de Beek D. Bacterial meningitis presenting with a normal cerebrospinal fluid leukocyte count. J Infect. 2022;84(5):615–20. pmid:35245581
- View Article
- PubMed/NCBI
- Google Scholar
16. Bello-López JM, León-García G, Rojas-Bernabé A, Fernández-Sánchez V, García-Hernández O, Mancilla Ramírez J, et al. Morbidity Trends and Risk of Tuberculosis: Mexico 2007–2017. Canadian Respiratory Journal. 2019. https://doi.org/10.1155/2019/8295261
17. Chang WN, Lu CH, Huang CR, Chuang YC. Mixed infection in adult bacterial meningitis. Infection. 2000;28(1):8–12. pmid:10697784
- View Article
- PubMed/NCBI
- Google Scholar
18. Flores-Cordero JM, Amaya-Villar R, Rincón-Ferrari MD, Leal-Noval SR, Garnacho-Montero J, Llanos-Rodríguez AC, et al. Acute community-acquired bacterial meningitis in adults admitted to the intensive care unit: clinical manifestations, management and prognostic factors. Intensive Care Med. 2003;29(11):1967–73. pmid:12904848
- View Article
- PubMed/NCBI
- Google Scholar
19. de Fátima Magalhães Acioly Mendizabal M, Bezerra PC, Guedes DL, Cabral DBC, de Barros Miranda-Filho D. Prognostic indicators in bacterial meningitis: a case-control study. Braz J Infect Dis. 2013;17(5):538–44. pmid:23835007
- View Article
- PubMed/NCBI
- Google Scholar
20. van de Beek D, de Gans J, Spanjaard L, Weisfelt M, Reitsma JB, Vermeulen M. Clinical features and prognostic factors in adults with bacterial meningitis. N Engl J Med. 2004;351(18):1849–59. pmid:15509818
- View Article
- PubMed/NCBI
- Google Scholar
21. Chen C-H, Sy H-N, Lin L-J, Yen H-C, Wang S-H, Chen W-L, et al. Epidemiological characterization and prognostic factors in patients with confirmed cerebral cryptococcosis in central Taiwan. J Venom Anim Toxins Incl Trop Dis. 2015;21:12. pmid:26136773
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Wall EC, Chan JM, Gil E, Heyderman RS. Acute bacterial meningitis. Curr Opin Neurol. 2021;34(3):386–95. pmid:33767093
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. van de Beek D, Brouwer M, Hasbun R, Koedel U, Whitney CG, Wijdicks E. Community-acquired bacterial meningitis. Nat Rev Dis Primers. 2016;2:16074. pmid:27808261
View Article
PubMed/NCBI
Google Scholar

[6] View Article

[7] PubMed/NCBI

[8] Google Scholar

[ref3] 3. GBD 2016 Meningitis Collaborators. Global, regional, and national burden of meningitis, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018;17(12):1061–82. pmid:30507391
View Article
PubMed/NCBI
Google Scholar

[10] View Article

[11] PubMed/NCBI

[12] Google Scholar

[ref4] 4. Glimåker M, Sjölin J, Åkesson S, Naucler P. Lumbar Puncture Performed Promptly or After Neuroimaging in Acute Bacterial Meningitis in Adults: A Prospective National Cohort Study Evaluating Different Guidelines. Clin Infect Dis. 2018;66(3):321–8. pmid:29020334
View Article
PubMed/NCBI
Google Scholar

[14] View Article

[15] PubMed/NCBI

[16] Google Scholar

[ref5] 5. van Veen KEB, Brouwer MC, van der Ende A, van de Beek D. Bacterial Meningitis in Patients using Immunosuppressive Medication: a Population-based Prospective Nationwide Study. J Neuroimmune Pharmacol. 2017;12(2):213–8. pmid:27613024
View Article
PubMed/NCBI
Google Scholar

[18] View Article

[19] PubMed/NCBI

[20] Google Scholar

[ref6] 6. Rajasingham R, Smith RM, Park BJ, Jarvis JN, Govender NP, Chiller TM, et al. Global burden of disease of HIV-associated cryptococcal meningitis: an updated analysis. Lancet Infect Dis. 2017;17(8):873–81. pmid:28483415
View Article
PubMed/NCBI
Google Scholar

[22] View Article

[23] PubMed/NCBI

[24] Google Scholar

[ref7] 7. Pruitt AA. Central Nervous System Infections in Immunocompromised Patients. Curr Neurol Neurosci Rep. 2021;21(7):37. pmid:34037866
View Article
PubMed/NCBI
Google Scholar

[26] View Article

[27] PubMed/NCBI

[28] Google Scholar

[ref8] 8. Sáfadi MAP, Valenzuela MT, Carvalho AF, De Oliveira LH, Salisbury DM, Andrus JK. Knowing the scope of meningococcal disease in Latin America. Rev Panam Salud Publica. 2017;41:e118. pmid:31391828
View Article
PubMed/NCBI
Google Scholar

[30] View Article

[31] PubMed/NCBI

[32] Google Scholar

[ref9] 9. Carnalla-Barajas MN, Soto-Noguerón A, Solórzano-Santos F, Macías-Parra M, Díaz-Jiménez V, Sánchez-González G, et al. Pneumococcal meningitis in Mexico. Serotype distribution and antimicrobial resistance before and after the introduction of pneumococcal conjugate vaccines in pediatric patients. Results from the GIVEBPVac group. J Infect Public Health. 2026;19(1):103030. pmid:41223711
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref10] 10. Villalpando-Carrión S, Henao-Martínez AF, Franco-Paredes C. Epidemiology and Clinical Outcomes of Bacterial Meningitis in Children and Adults in Low- and Middle-Income Countries. Curr Trop Med Rep. 2024;11(2):60–7. pmid:39006487
View Article
PubMed/NCBI
Google Scholar

[38] View Article

[39] PubMed/NCBI

[40] Google Scholar

[ref11] 11. van de Beek D, Brouwer MC, Thwaites GE, Tunkel AR. Advances in treatment of bacterial meningitis. Lancet. 2012;380(9854):1693–702. pmid:23141618
View Article
PubMed/NCBI
Google Scholar

[42] View Article

[43] PubMed/NCBI

[44] Google Scholar

[ref12] 12. World Health Organization. WHO guidelines on meningitis diagnosis, treatment and care. 2025.

[ref13] 13. Rubin LG, Levin MJ, Ljungman P, Davies EG, Avery R, Tomblyn M, et al. 2013 IDSA clinical practice guideline for vaccination of the immunocompromised host. Clin Infect Dis. 2014;58(3):309–18. pmid:24421306
View Article
PubMed/NCBI
Google Scholar

[47] View Article

[48] PubMed/NCBI

[49] Google Scholar

[ref14] 14. Kastenbauer S, Pfister H-W. Pneumococcal meningitis in adults: spectrum of complications and prognostic factors in a series of 87 cases. Brain. 2003;126(Pt 5):1015–25. pmid:12690042
View Article
PubMed/NCBI
Google Scholar

[51] View Article

[52] PubMed/NCBI

[53] Google Scholar

[ref15] 15. van Soest TM, Chekrouni N, van Sorge NM, Brouwer MC, van de Beek D. Bacterial meningitis presenting with a normal cerebrospinal fluid leukocyte count. J Infect. 2022;84(5):615–20. pmid:35245581
View Article
PubMed/NCBI
Google Scholar

[55] View Article

[56] PubMed/NCBI

[57] Google Scholar

[ref16] 16. Bello-López JM, León-García G, Rojas-Bernabé A, Fernández-Sánchez V, García-Hernández O, Mancilla Ramírez J, et al. Morbidity Trends and Risk of Tuberculosis: Mexico 2007–2017. Canadian Respiratory Journal. 2019. https://doi.org/10.1155/2019/8295261

[ref17] 17. Chang WN, Lu CH, Huang CR, Chuang YC. Mixed infection in adult bacterial meningitis. Infection. 2000;28(1):8–12. pmid:10697784
View Article
PubMed/NCBI
Google Scholar

[60] View Article

[61] PubMed/NCBI

[62] Google Scholar

[ref18] 18. Flores-Cordero JM, Amaya-Villar R, Rincón-Ferrari MD, Leal-Noval SR, Garnacho-Montero J, Llanos-Rodríguez AC, et al. Acute community-acquired bacterial meningitis in adults admitted to the intensive care unit: clinical manifestations, management and prognostic factors. Intensive Care Med. 2003;29(11):1967–73. pmid:12904848
View Article
PubMed/NCBI
Google Scholar

[64] View Article

[65] PubMed/NCBI

[66] Google Scholar

[ref19] 19. de Fátima Magalhães Acioly Mendizabal M, Bezerra PC, Guedes DL, Cabral DBC, de Barros Miranda-Filho D. Prognostic indicators in bacterial meningitis: a case-control study. Braz J Infect Dis. 2013;17(5):538–44. pmid:23835007
View Article
PubMed/NCBI
Google Scholar

[68] View Article

[69] PubMed/NCBI

[70] Google Scholar

[ref20] 20. van de Beek D, de Gans J, Spanjaard L, Weisfelt M, Reitsma JB, Vermeulen M. Clinical features and prognostic factors in adults with bacterial meningitis. N Engl J Med. 2004;351(18):1849–59. pmid:15509818
View Article
PubMed/NCBI
Google Scholar

[72] View Article

[73] PubMed/NCBI

[74] Google Scholar

[ref21] 21. Chen C-H, Sy H-N, Lin L-J, Yen H-C, Wang S-H, Chen W-L, et al. Epidemiological characterization and prognostic factors in patients with confirmed cerebral cryptococcosis in central Taiwan. J Venom Anim Toxins Incl Trop Dis. 2015;21:12. pmid:26136773
View Article
PubMed/NCBI
Google Scholar

[76] View Article

[77] PubMed/NCBI

[78] Google Scholar

Figures

Abstract

Introduction

Materials and methods

Population

Definitions

Statistical analysis

Results

Clinical characteristics

Laboratory and CSF findings

Mortality analysis

Discussion

Conclusions

Supporting information

S1 Fig. Sensitivity analysis excluding tuberculosis and fungal meningitis.

S1 Table. Additional multivariable model excluding fungal cases.

Acknowledgments

References