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.
Highlights
IntroductionIdentification of the etiologic agent is crucial to optimize clinical care, as disease outcome often depends on tailoring treatment for the infectious agent[18]
Categorizing patients into the types of central nervous system (CNS) infections and postulating stratified etiologies based on initial clinical presentation and laboratory results would help rationalize early investigations and target treatments for the most likely etiologies
The identification of CNS infection etiology remains a major challenge in all health systems throughout the world due to limited access to the infection site, delay in the timely collection of relevant clinical samples, as well as limitations of current diagnostic tests
Summary
Identification of the etiologic agent is crucial to optimize clinical care, as disease outcome often depends on tailoring treatment for the infectious agent[18]. This challenge is compounded by (1) the limited accessibility of the tissue where pathogen replication occurs, (2) the absence, in most clinical laboratories, of sensitive methods for molecular and serological detection of infection and (3) the lack of consensus on case definitions and standardized diagnostic a pproaches[19]. Categorizing patients into the types of CNS infections and postulating stratified etiologies based on initial clinical presentation and laboratory results would help rationalize early investigations and target treatments for the most likely etiologies
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