Functional Motor Disorders (FMDs) represent nosological entities with no clear phenotypic characterization, especially in patients with multiple (combined FMDs) motor manifestations. A data-driven approach using cluster analysis of clinical data has been proposed as an analytic method to obtain non-hierarchical unbiased classifications. The study aimed to identify clinical subtypes of combined FMDs using a data-driven approach to overcome possible limits related to "a priori" classifications and clinical overlapping.

Data-driven clustering of combined Functional Motor Disorders based on the Italian registry

Geroin, Christian
;
Marcuzzo, Enrico;Di Vico, Ilaria Antonella;Tinazzi, Michele
2022-01-01

Abstract

Functional Motor Disorders (FMDs) represent nosological entities with no clear phenotypic characterization, especially in patients with multiple (combined FMDs) motor manifestations. A data-driven approach using cluster analysis of clinical data has been proposed as an analytic method to obtain non-hierarchical unbiased classifications. The study aimed to identify clinical subtypes of combined FMDs using a data-driven approach to overcome possible limits related to "a priori" classifications and clinical overlapping.
Functional Motor Disorders
clinical phenotypes
cluster analysis
data-driven phenotyping
functional neurological disorder
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1080769
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