Disentangling etiologies of CNS infections in Singapore using multiple correspondence analysis and random forest

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 empir...

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Bibliographic Details
Published in:Scientific reports 2020-10, Vol.10 (1), p.18219-18219, Article 18219
Main Authors: Zellweger, Raphaël M, Yacoub, Sophie, Chan, Yvonne F Z, Soon, Derek, Shafi, Humaira, Ooi, Say Tat, Chan, Monica, Jacobson, Leslie, Sessions, October M, Vincent, Angela, Low, Jenny Guek Hong, Ooi, Eng Eong, Wang, Linfa, Wijaya, Limin, Tan, Kevin
Format: Article
Language:English
Subjects:
Aged
Antigens, Bacterial - analysis
Antigens, Fungal - analysis
Antigens, Viral - analysis
Central nervous system
Central Nervous System Infections - complications
Central Nervous System Infections - microbiology
Communicable Diseases - classification
Communicable Diseases - diagnosis
Communicable Diseases - epidemiology
Communicable Diseases - etiology
Computational neuroscience
Data Interpretation, Statistical
Diagnosis, Differential
Epidemiology
Etiology
Female
Humans
Infections
Laboratories
Male
Middle Aged
Morbidity
Patients
Prognosis
Prospective Studies
Singapore - epidemiology
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Summary: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.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-75088-4