Motor and psychiatric features in idiopathic blepharospasm: A data-driven cluster analysis

Giovanni Defazio, Angelo F. Gigante, Mark Hallett, Alfredo Berardelli, Joel S. Perlmutter, Brian D. Berman, Joseph Jankovic, Tobias Bäumer, Cynthia Comella, Tommaso Ercoli, Gina Ferrazzano, Susan H. Fox, Han Joon Kim, Emile Sami Moukheiber, Sarah Pirio Richardson, Anne Weissbach, Hyder A. Jinnah

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Introduction: Idiopathic blepharospasm is a clinically heterogeneous dystonia also characterized by non motor symptoms. Methods: We used a k-means cluster analysis to assess 188 patients with idiopathic blepharospasm in order to identify relatively homogeneous subpopulations of patients, using a set of motor and psychiatric variables to generate the cluster solution. Results: Blepharospasm patients reached higher scores on scales assessing depressive- and anxiety-related disorders than healthy/disease controls. Cluster analysis suggested the existence of three groups of patients that differed by type of spasms, overall motor severity, and presence/severity of psychiatric problems. The greater severity of motor symptoms was observed in Group 1, the least severity in Group 3, while the severity of blepharospasm in Group 2 was between that observed in Groups 1 and 3. The three motor subtypes also differed by psychiatric features: the lowest severity of psychiatric symptoms was observed in the group with least severe motor symptoms (group 3), while the highest psychiatric severity scores were observed in group 2 that carried intermediate motor severity rather than in the group with more severe motor symptoms (group 1). The three groups did not differ by disease duration, age of onset, sex or other clinical features. Conclusions: The present study suggests that blepharospasm patients may be classified in different subtypes according to the type of spasms, overall motor severity and presence/severity of depressive symptoms and anxiety.

Original languageEnglish
Pages (from-to)94-98
Number of pages5
JournalParkinsonism and Related Disorders
StatePublished - Nov 2022


  • Anxiety
  • Blepharospasm
  • Cluster analysis
  • Depression


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