Disentangling etiologies of CNS infections in Singapore using multiple correspondence analysis and random forest.
Sci Rep
; 10(1): 18219, 2020 10 26.
Article
em En
| MEDLINE
| ID: mdl-33106525
ABSTRACT
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Infecções do Sistema Nervoso Central
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Doenças Transmissíveis
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Antígenos de Bactérias
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Antígenos de Fungos
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Antígenos Virais
Tipo de estudo:
Clinical_trials
/
Diagnostic_studies
/
Etiology_studies
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Observational_studies
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Prognostic_studies
/
Risk_factors_studies
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
País/Região como assunto:
Asia
Idioma:
En
Revista:
Sci Rep
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Singapura