ArticleHealth science reports2023
Epidemiological and clinical characteristics of central nervous system infections in a tertiary center: A retrospective study.
Article in Health science reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effectiveness of prophylactic antibiotics for the prevention of intracranial infections following penetrating traumatic brain injury: a systematic review and meta-analysis.Neurosurgical review · 2026Pooled it
- Chitosan-Based Nanoparticles for Nose-to-Brain Drug Delivery: A Real Path toward Effective CNS Therapy?ACS biomaterials science & engineering · 2026Review
- Crossing the Barrier:Microorganisms · 2025Review
- Clinical Metagenomic Next-Generation Sequencing for Diagnosis of Central Nervous System Infections: Advances and Challenges.Molecular diagnosis & therapy · 2024Review
- Epidemiological and clinical characteristics of central nervous system infections in a tertiary center: A retrospective study.Health science reports · 2023Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 ( 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.
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