Frontiers in Neurology (Nov 2022)

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

  • Giovanni Mostile,
  • Giovanni Mostile,
  • Christian Geroin,
  • Roberto Erro,
  • Antonina Luca,
  • Enrico Marcuzzo,
  • Paolo Barone,
  • Roberto Ceravolo,
  • Sonia Mazzucchi,
  • Andrea Pilotto,
  • Andrea Pilotto,
  • Alessandro Padovani,
  • Luigi Michele Romito,
  • Roberto Eleopra,
  • Carlo Dallocchio,
  • Carla Arbasino,
  • Francesco Bono,
  • Pietro Antonio Bruno,
  • Benedetta Demartini,
  • Orsola Gambini,
  • Nicola Modugno,
  • Enrica Olivola,
  • Laura Bonanni,
  • Laura Bonanni,
  • Alberto Albanese,
  • Gina Ferrazzano,
  • Rosa De Micco,
  • Maurizio Zibetti,
  • Giovanna Calandra-Buonaura,
  • Giovanna Calandra-Buonaura,
  • Martina Petracca,
  • Francesca Morgante,
  • Francesca Morgante,
  • Marcello Esposito,
  • Marcello Esposito,
  • Antonio Pisani,
  • Antonio Pisani,
  • Paolo Manganotti,
  • Fabrizio Stocchi,
  • Mario Coletti Moja,
  • Ilaria Antonella Di Vico,
  • Lucia Tesolin,
  • Francesco De Bertoldi,
  • Tommaso Ercoli,
  • Giovanni Defazio,
  • Mario Zappia,
  • Alessandra Nicoletti,
  • Michele Tinazzi

DOI
https://doi.org/10.3389/fneur.2022.987593
Journal volume & issue
Vol. 13

Abstract

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IntroductionFunctional 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.MethodsData were obtained by the Italian Registry of Functional Motor Disorders. Patients identified with multiple or “combined” FMDs by standardized clinical assessments were selected to be analyzed. Non-hierarchical cluster analysis was performed based on FMDs phenomenology. Multivariate analysis was then performed after adjustment for principal confounding variables.ResultsFrom a study population of n = 410 subjects with FMDs, we selected n = 188 subjects [women: 133 (70.7%); age: 47.9 ± 14.4 years; disease duration: 6.4 ± 7.7 years] presenting combined FMDs to be analyzed. Based on motor phenotype, two independent clusters were identified: Cluster C1 (n = 82; 43.6%) and Cluster C2 (n = 106; 56.4%). Cluster C1 was characterized by functional tremor plus parkinsonism as the main clinical phenotype. Cluster C2 mainly included subjects with functional weakness. Cluster C1 included older subjects suffering from anxiety who were more treated with botulinum toxin and antiepileptics. Cluster C2 included younger subjects referring to different associated symptoms, such as pain, headache, and visual disturbances, who were more treated with antidepressants.ConclusionUsing a data-driven approach of clinical data from the Italian registry, we differentiated clinical subtypes among combined FMDs to be validated by prospective studies.

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