| Autor: |
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 |
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| Zdroj: |
Annals of Neurology; Mar2024, Vol. 95 Issue 3, p530-543, 14p |
| Abstrakt: |
Objective: This study assessed the relationship between speech and language impairment and outcome in a multicenter cohort of isolated/idiopathic rapid eye movement (REM) 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. ANN NEUROL 2024;95:530–543 [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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