Data-driven clustering of combined functional motor disorders based on the italian registry

HIGHLIGHTS

SUMMARY

    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. From a study population of n=410 subjects with FMDs, the authors selected n=188 subjects presenting combined FMDs to be analyzed. Based . . .

     

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