For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
5
views
91
references
 Top references
cited by
17
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
1 collections
    0
    shares
      141
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: not found

      Global morbidity and mortality of central nervous system tuberculosis: a systematic review and meta-analysis

      review-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Tuberculosis (TB) is the second most common cause of death due to a single infectious agent worldwide after COVID-19. Up to 15% of the cases are extrapulmonary, and if it is located in the central nervous system (CNS-TB), it presents high morbidity and mortality. Still, the global epidemiology of CNS-TB remains unknown.

          Aim

          To estimate the global prevalence and incidence of CNS-TB based on the available literature.

          Methods

          We systematically searched in MEDLINE, Cochrane Central, Scopus, and LILACS databases (April 2020) and included observational studies evaluating the epidemiology of CNS-TB. Two independent researchers selected and assessed the quality of the studies and extracted relevant data. We performed random-effects model meta-analysis of proportions to estimate the pooled prevalence. The protocol of this study was registered in PROSPERO (CRD 42018103946).

          Results

          We included 53 studies from 28 countries, representing 12,621 patients with CNS-TB. The prevalence of CNS-TB was 2 per 100,000 inhabitants. According to the clinical setting, the prevalence of CNS-TB represented the 13.91% of all cases of meningitis and 4.55% of all cases of TB. The mortality was calculated by tuberculous meningitis due to the lack of data of other presentation, and it rose up to 42.12% in hospitalized patients. The burden of countries’ TB, Human Development Index (HDI), and the prevalence of HIV were the most important prevalence moderators, especially in patients with TB. No data on incidence were found.

          Conclusion

          The prevalence and mortality of CNS-TB remain high, and TB meningitis is the most frequent presentation. The highest prevalence was reported in developing countries, and its main moderators were the countries’ HDI and HIV infection. Our study was limited by high heterogeneity, risk of bias, and potential data under registration from developing countries. The integration of CNS-TB early detection and management into national TB programs and population-based studies from developing countries are needed for better global estimation and response.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00415-022-11052-8.

          Related collections

          Most cited references91

          • Record: found
          • Abstract: found
          • Article: not found

          Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group.

          D F Stroup, J A Berlin, S C Morton … (2000)
          Because of the pressure for timely, informed decisions in public health and clinical practice and the explosion of information in the scientific literature, research results must be synthesized. Meta-analyses are increasingly used to address this problem, and they often evaluate observational studies. A workshop was held in Atlanta, Ga, in April 1997, to examine the reporting of meta-analyses of observational studies and to make recommendations to aid authors, reviewers, editors, and readers. Twenty-seven participants were selected by a steering committee, based on expertise in clinical practice, trials, statistics, epidemiology, social sciences, and biomedical editing. Deliberations of the workshop were open to other interested scientists. Funding for this activity was provided by the Centers for Disease Control and Prevention. We conducted a systematic review of the published literature on the conduct and reporting of meta-analyses in observational studies using MEDLINE, Educational Research Information Center (ERIC), PsycLIT, and the Current Index to Statistics. We also examined reference lists of the 32 studies retrieved and contacted experts in the field. Participants were assigned to small-group discussions on the subjects of bias, searching and abstracting, heterogeneity, study categorization, and statistical methods. From the material presented at the workshop, the authors developed a checklist summarizing recommendations for reporting meta-analyses of observational studies. The checklist and supporting evidence were circulated to all conference attendees and additional experts. All suggestions for revisions were addressed. The proposed checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion. Use of the checklist should improve the usefulness of meta-analyses for authors, reviewers, editors, readers, and decision makers. An evaluation plan is suggested and research areas are explored.
          Article 0 comments Cited 2221 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            GRADE guidelines: 3. Rating the quality of evidence.

            Howard Balshem, Mark Helfand, Holger Schünemann … (2011)
            This article introduces the approach of GRADE to rating quality of evidence. GRADE specifies four categories-high, moderate, low, and very low-that are applied to a body of evidence, not to individual studies. In the context of a systematic review, quality reflects our confidence that the estimates of the effect are correct. In the context of recommendations, quality reflects our confidence that the effect estimates are adequate to support a particular recommendation. Randomized trials begin as high-quality evidence, observational studies as low quality. "Quality" as used in GRADE means more than risk of bias and so may also be compromised by imprecision, inconsistency, indirectness of study results, and publication bias. In addition, several factors can increase our confidence in an estimate of effect. GRADE provides a systematic approach for considering and reporting each of these factors. GRADE separates the process of assessing quality of evidence from the process of making recommendations. Judgments about the strength of a recommendation depend on more than just the quality of evidence. Copyright © 2011 Elsevier Inc. All rights reserved.
            Article 0 comments Cited 1541 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Meta-analysis in clinical trials.

              R DerSimonian, N Laird (1986)
              This paper examines eight published reviews each reporting results from several related trials. Each review pools the results from the relevant trials in order to evaluate the efficacy of a certain treatment for a specified medical condition. These reviews lack consistent assessment of homogeneity of treatment effect before pooling. We discuss a random effects approach to combining evidence from a series of experiments comparing two treatments. This approach incorporates the heterogeneity of effects in the analysis of the overall treatment efficacy. The model can be extended to include relevant covariates which would reduce the heterogeneity and allow for more specific therapeutic recommendations. We suggest a simple noniterative procedure for characterizing the distribution of treatment effects in a series of studies.
              Article 0 comments Cited 1058 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Kevin Pacheco-Barrios:
                ORCID: http://orcid.org/0000-0002-7166-2816
                kevin.pacheco.barrios@gmail.com
                Journal
                Journal ID (nlm-ta): J Neurol
                Journal ID (iso-abbrev): J Neurol
                Title: Journal of Neurology
                Publisher: Springer Berlin Heidelberg (Berlin/Heidelberg )
                ISSN (Print): 0340-5354
                ISSN (Electronic): 1432-1459
                Publication date (Electronic): 15 March 2022
                Pages: 1-13
                Affiliations
                [1 ]GRID grid.7450.6, ISNI 0000 0001 2364 4210, International Max Planck Research School for Neurosciences, , Georg-August-University Göttingen, ; Göttingen, Germany
                [2 ]GRID grid.441816.e, ISNI 0000 0001 2182 6061, Facultad de Medicina Humana, , Universidad San Martín de Porres, ; Chiclayo, Peru
                [3 ]SYNAPSIS Mental Health and Neurology, Non-Profit Organization, Lima, Peru
                [4 ]Sociedad Científica de Estudiantes de Medicina Cayetano Heredia (SOCEMCH), Lima, Peru
                [5 ]GRID grid.441893.3, ISNI 0000 0004 0542 1648, Unidad de Investigación Clínica y Epidemiológica, , Escuela de Medicina, Universidad Peruana Unión, ; Lima, Peru
                [6 ]GRID grid.441908.0, ISNI 0000 0001 1969 0652, Unidad de Investigación Para La Generación y Síntesis de Evidencias en Salud, Universidad San Ignacio de Loyola, ; 550 La Fontana Avenue, La Molina 15024, Lima, Peru
                [7 ]GRID grid.38142.3c, ISNI 000000041936754X, Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, , Harvard Medical School, ; Boston, USA
                Author information
                http://orcid.org/0000-0002-7166-2816
                Article
                Publisher ID: 11052
                DOI: 10.1007/s00415-022-11052-8
                PMC ID: 8920747
                PubMed ID: 35288778
                SO-VID: 1c620bb1-4c3c-422e-b940-7c1ff52b305b
                Copyright © © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany 2022
                License:

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                Date received : 30 January 2022
                Date revision received : 24 February 2022
                Date accepted : 24 February 2022
                Categories
                Subject: Review

                ScienceOpen disciplines: Neurology
                Keywords: tuberculoma,tuberculosis,central nervous system,meningitis,prevalence (source: mesh-nlm)
                Data availability:
                ScienceOpen disciplines: Neurology
                Keywords: tuberculoma, tuberculosis, central nervous system, meningitis, prevalence (source: mesh-nlm)

                Comments

                Comment on this article

                scite_

                Similar content141

                See all similar

                Cited by17

                See all cited by

                Most referenced authors2,271

                See all reference authors