Acute infections of the central nervous system in children and adults: diagnosis and management
Bibliographic record
Abstract
Central nervous system infections are due to different microorganisms such as viruses, bacteria, mycobacteria, fungi, amoebas, and other parasites. The etiology depends on multiple risk factors, and it defines the infection location because some microorganisms prefer meninges, brain tissue, cerebellum, brain stem or spinal cord. The microorganisms induce diseases in the nervous system through direct invasion, neurotoxin production, and the triggered immune response. To determine the infection etiology, there are several diagnostic tests which may be conducted with cerebrospinal fluid, blood, respiratory and stool samples. These tests include but are not limited to direct microscopic examination of the sample, stains, cultures, antigenic tests, nucleic acid amplification tests, metagenomic next-generation sequencing, immunologic biomarker and neuroimaging, especially contrast-enhanced magnetic resonance imaging. The treatment may consist of specific antimicrobial treatment and supportive standard care. Since viruses have no specific antiviral treatment, antimicrobial treatment is mainly targeted at non-viral infections. This article will focus on diagnosis and treatment of acute acquired infections of the central nervous system beyond the neonatal period. The discussion defines the disease, provides the clinical presentation, explains the etiology and risk factors, and briefly mentions potential complications. This updated review aims to provide the reader with all the elements needed to adequately approach a patient with a central nervous system infection. Mycobacterium tuberculosis infection, Cryptococcus spp. infection and vaccines are not within the scope of this article.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".