en
Privat-docent thesis
Open access
English

Diagnostic Challenges in Acute Central Nervous System Infections in the 2020s

ContributorsSchibler, Manuel
Defense date2021-11-01
Abstract

Acute central nervous system (CNS) infection can manifest as various distinct entities, according to the affected anatomic structures, hence the terms encephalitis, meningitis, meningoencephalitis, myelitis, encephalomyelitis, amongst others. Most of these syndromes are caused by viruses and bacteria, and less frequently by fungi and parasites. Some CNS diseases are caused by an aberrant immune response to microorganisms. Noninfectious CNS inflammation causes mimicking CNS infection include autoimmunity, as well as drug- related reactions. Given the numerous etiologies, which most often cannot be identified based on clinical manifestations, diagnosing CNS infections is challenging and requires broad knowledge in the field and sharp clinical sense, in order to appropriately tailor diagnostic and therapeutic strategies. This thesis comprises four original publications illustrating two aspects regarding the implication of routine and emerging diagnostic tools that can be used for viral CNS infection diagnosis. The first two deal with the use of high throughput sequencing (HTS) in cases of CNS inflammation of undetermined cause, and the last two exemplify how the judicious application of routine microbiological diagnostic means can help to decipher a complex CMV encephalitis case, as well as to extend the understanding of CNS disease caused by an emerging viral disease, such as COVID-19. This selected work is put into perspective with a more global approach aimed at improving and optimizing CNS infection diagnosis.

eng
Citation (ISO format)
SCHIBLER, Manuel. Diagnostic Challenges in Acute Central Nervous System Infections in the 2020s. 2021. doi: 10.13097/archive-ouverte/unige:155980
Main files (1)
Thesis
accessLevelPublic
Identifiers
225views
146downloads

Technical informations

Creation11/03/2021 9:04:00 AM
First validation11/03/2021 9:04:00 AM
Update time03/16/2023 1:42:18 AM
Status update03/16/2023 1:42:18 AM
Last indexation01/29/2024 10:53:17 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack