A data‐driven approach to neuropsychological features in isolated REM behaviour disorder: A latent class analysis. Issue 1 (3rd October 2022)

• Record Type: Journal Article
• Authors: Mombelli, Samantha; Leitner, Caterina; D'Este, Giada; Sforza, Marco; Marelli, Sara; Castelnuovo, Alessandra; Zucconi, Marco; Casoni, Francesca; Fantini, Maria Livia; Novellino, Fabiana; Salsone, Maria; Ferini‐Strambi, Luigi; Galbiati, Andrea
• Is Part Of: Journal of neuropsychology. Volume 17:Issue 1(2023)
• Page Start: 161
• Page End: 179
• Publication Date: 2022-10-03
• Subjects: iRBD -- latent class analysis -- neurodegeneration -- neuropsychological tests -- phenotypes; Neuropsychology -- Periodicals; Brain -- Diseases -- Psychological aspects -- Periodicals; 612.82305
• DOI: 10.1111/jnp.12292
• Languages: English
• ISSNs: 1748-6645

Abstract

Abstract: Recent evidence demonstrated that neuropsychological assessment may be considered a valid marker of neurodegeneration in idiopathic REM sleep behaviour disorder (iRBD). However, little is known about the possible neuropsychological heterogeneity within the iRBD population. This retrospective study aimed to identify and describe different neuropsychological phenotypes in iRBD patients by means of a data‐driven approach using latent class analysis. A total of 289 iRBD patients underwent a neuropsychological assessment evaluating cognitive domains: global cognition, language, short‐ and long‐term memory, executive functions and visuospatial abilities. The presence of mild cognitive impairment (MCI) was also assessed. Latent class analysis was carried out to identify iRBD subtypes according to neuropsychological scores. The most parsimonious model identified three latent classes. Groups were labelled as follows: Class 2 "severely impaired" ( n = 83/289): mean pathological scores in different tests, a high percentage of MCI multiple‐domain and impairment in all neuropsychological domains. Class 1 "moderately impaired" ( n = 44/289): mean neuropsychological score within the normal value, a high percentage of MCI (high risk to phenoconversion) and great impairment in the visuospatial domain. Class 3 "slightly impaired" ( n = 162/289): no deficit worthy of attention except for short‐ and long‐term memory. Our results suggest three different clinical phenotypes within the iRBD population. These findings may be relevant in the future for predicting the clinical trajectories of phenoconversion in iRBD.