Spoken language alterations can predict phenoconversion in isolated REM sleep behavior disorder: a multicentric study.

Šubert, Martin; Novotný, Michal; Tykalová, Tereza; Hlavnička, Jan; Dušek, Petr; Růžička, Evžen; Škrabal, Dominik; Pelletier, Amelie; Postuma, Ronald B; Montplaisir, Jacques; Gagnon, Jean-François; Galbiati, Andrea; Ferini-Strambi, Luigi; Marelli, Sara; St Louis, Erik K; Timm, Paul C; Teigen, Luke N; Janzen, Annette; Oertel, Wolfgang; Heim, Beatrice; ... (2024). Spoken language alterations can predict phenoconversion in isolated REM sleep behavior disorder: a multicentric study. Annals of neurology, 95(3), pp. 530-543. Wiley-Blackwell 10.1002/ana.26835

Text Annals_of_Neurology_-_2023_-_ubert_-_Spoken_language_alterations_can_predict_phenoconversion_in_isolated_REM_sleep_behavior.pdf - Accepted Version Restricted to registered users only until 23 November 2024. Available under License Publisher holds Copyright. Download (1MB)

OBJECTIVE

This study assessed the relationship between speech and language impairment and outcome in a multicenter cohort of isolated/idiopathic rapid eye movement sleep behavior disorder (iRBD).

METHODS

Patients with iRBD from 7 centers speaking Czech, English, German, French, and Italian languages underwent a detailed speech assessment at baseline. Story-tale narratives were transcribed and linguistically annotated using fully automated methods based on automatic speech recognition and natural language processing algorithms, leading to the 3 distinctive linguistic and 2 acoustic patterns of language deterioration and associated composite indexes of their overall severity. Patients were then prospectively followed and received assessments for parkinsonism or dementia during follow-up. The Cox proportional hazard was performed to evaluate the predictive value of language patterns for phenoconversion over a follow-up period of 5 years.

RESULTS

Of 180 patients free of parkinsonism or dementia, 156 provided follow-up information. After a mean follow-up of 2.7 years, 42 (26.9%) patients developed neurodegenerative disease. Patients with higher severity of linguistic abnormalities (hazard ratio [HR = 2.35]) and acoustic abnormalities (HR = 1.92) were more likely to develop a defined neurodegenerative disease, with converters having lower content richness (HR = 1.74), slower articulation rate (HR = 1.58), and prolonged pauses (HR = 1.46). Dementia-first (n = 16) and parkinsonism-first with mild cognitive impairment (n = 9) converters had higher severity of linguistic abnormalities than parkinsonism-first with normal cognition converters (n = 17).

INTERPRETATION

Automated language analysis might provide a predictor of phenoconversion from iRBD into synucleinopathy subtypes with cognitive impairment, and thus can be used to stratify patients for neuroprotective trials. This article is protected by copyright. All rights reserved.

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