Classification of neurological diseases using multi-dimensional CSF analysis.
Brain
; 144(9): 2625-2634, 2021 10 22.
Article
en En
| MEDLINE
| ID: mdl-33848319
ABSTRACT
Although CSF analysis routinely enables the diagnosis of neurological diseases, it is mainly used for the gross distinction between infectious, autoimmune inflammatory, and degenerative disorders of the CNS. To investigate, whether a multi-dimensional cellular blood and CSF characterization can support the diagnosis of clinically similar neurological diseases, we analysed 546 patients with autoimmune neuroinflammatory, degenerative, or vascular conditions in a cross-sectional retrospective study. By combining feature selection with dimensionality reduction and machine learning approaches we identified pan-disease parameters that were altered across all autoimmune neuroinflammatory CNS diseases and differentiated them from other neurological conditions and inter-autoimmunity classifiers that subdifferentiate variants of CNS-directed autoimmunity. Pan-disease as well as diseases-specific changes formed a continuum, reflecting clinical disease evolution. A validation cohort of 231 independent patients confirmed that combining multiple parameters into composite scores can assist the classification of neurological patients. Overall, we showed that the integrated analysis of blood and CSF parameters improves the differential diagnosis of neurological diseases, thereby facilitating early treatment decisions.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Mediadores de Inflamación
/
Enfermedades del Sistema Nervioso
Tipo de estudio:
Diagnostic_studies
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Etiology_studies
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Incidence_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Female
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Humans
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Male
Idioma:
En
Revista:
Brain
Año:
2021
Tipo del documento:
Article
País de afiliación:
Alemania