Dario Arnaldi, Pietro Mattioli, Stefano Raffa, Matteo Pardini, Federico Massa, Alex Iranzo, Andres Perissinotti, Aida Niñerola-Baizán, Carles Gaig, Monica Serradell, Amaia Muñoz-Lopetegi, Gerard Mayà, Claudio Liguori, Mariana Fernandes, Fabio Placidi, Agostino Chiaravalloti, Karel Šonka, Petr Dušek, David Zogala, Jiri Trnka, Bradley F Boeve, Toji Miyagawa, Val J Lowe, Tomoyuki Miyamoto, Masayuki Miyamoto, Monica Puligheddu, Michela Figorilli, Alessandra Serra, Michele T Hu, Johannes C Klein, Frederik Bes, Dieter Kunz, Valérie Cochen De Cock, Delphine de Verbizier, Giuseppe Plazzi, Elena Antelmi, Michele Terzaghi, Irene Bossert, Kristína Kulcsárová, Alessio Martino, Alessandro Giuliani, Marco Pagani, Flavio Nobili, Silvia Morbelli
OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). METHODS: In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation...
March 11, 2024: Annals of Neurology